diff --git a/LICENSE b/LICENSE
index 6776670..0b9afcd 100644
--- a/LICENSE
+++ b/LICENSE
@@ -1,6 +1,6 @@
 The MIT License (MIT)
 
-Copyright (C) 2019 Ines Montani
+Copyright (C) 2019 Julia Silge
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal
diff --git a/README.md b/README.md
index 7bcf8c3..53a8d48 100644
--- a/README.md
+++ b/README.md
@@ -8,9 +8,8 @@ You can access [this course for free online](https://supervised-ml-course.netlif
 
 This course approaches supervised machine learning using:
 
-- [tidyverse](https://tidyverse.tidyverse.org/) tools
-- more mature parts of the [tidymodels](https://github.com/tidymodels) suite of packages
-- [caret](https://topepo.github.io/caret/)
+- the [tidyverse](https://www.tidyverse.org/)
+- the [tidymodels](https://www.tidymodels.org/) ecosystem
 
 The interactive course site is built on the amazing framework created by [Ines Montani](https://ines.io/), originally built for her [spaCy course](https://course.spacy.io).  The front-end is powered by
 [Gatsby](http://gatsbyjs.org/) and [Reveal.js](https://revealjs.com) and the
@@ -19,7 +18,7 @@ back-end code execution uses [Binder](https://mybinder.org). [Florencia D'Andrea
 [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/juliasilge/supervised-ML-case-studies-course/binder) 
 ![Netlify Status](https://api.netlify.com/api/v1/badges/3ba21376-9a18-4cf0-960e-2c65e6bc2bbd/deploy-status)
 
-To learn more about building a course on this framework, see Ines's starter repos for making courses in [Python](https://github.com/ines/course-starter-python) and [R](https://github.com/ines/course-starter-r), and her explanation of how the framework works at [the original course repo](https://github.com/ines/spacy-course#-faq).
+To learn more about building a course on this framework, see Ines's starter repos for making courses in [Python](https://github.com/ines/course-starter-python) and [R](https://github.com/ines/course-starter-r), and her explanation of how the framework works at [the original course repo](https://github.com/ines/spacy-course#-faq). The original version of this course based on the R package caret [is available here](https://caret-ml-course.netlify.app/).
 
 Please note that this project is released with a [Contributor Code of Conduct](CODE_OF_CONDUCT.md). By contributing to this project, you agree to abide by its terms.
 
diff --git a/binder/install.R b/binder/install.R
index 0f6879f..7b5a2a2 100644
--- a/binder/install.R
+++ b/binder/install.R
@@ -1,8 +1,5 @@
-install.packages("e1071")
-install.packages("gbm")
-install.packages("xgboost")
-install.packages("randomForest") 
-install.packages("caret")  
-install.packages("rsample")
-install.packages("yardstick")
+install.packages("randomForest")
+install.packages("rpart")
+install.packages("ranger")
+install.packages("tidymodels")
 install.packages("tidyverse")
diff --git a/binder/runtime.txt b/binder/runtime.txt
index d04315d..e8bb161 100644
--- a/binder/runtime.txt
+++ b/binder/runtime.txt
@@ -1 +1 @@
-r-2019-08-10
+r-3.6-2020-05-01
diff --git a/chapters/chapter1.md b/chapters/chapter1.md
index 3ad93b0..79b3795 100644
--- a/chapters/chapter1.md
+++ b/chapters/chapter1.md
@@ -8,14 +8,14 @@ type: chapter
 id: 1
 ---
 
-<exercise id="1" title="Making predictions using machine learning" type="slides">
+<exercise id="1" title="Make predictions using machine learning" type="slides">
 
 <slides source="chapter1_01">
 </slides>
 
 </exercise>
 
-<exercise id="2" title="Choosing an appropriate model">
+<exercise id="2" title="Choose an appropriate model">
 
 In this case study, you will predict the fuel efficiency ⛽  of modern cars from characteristics of these cars, like transmission and engine displacement. Fuel efficiency is a numeric value that ranges smoothly from about 15 to 40 miles per gallon. What kind of model will you build?
 
@@ -47,7 +47,7 @@ A classification model predicts a group membership or discrete class label, not
 
 </exercise>
 
-<exercise id="3" title="Visualizing the fuel efficiency distribution">
+<exercise id="3" title="Visualize the fuel efficiency distribution">
 
 The first step before you start modeling is to explore your data. In this course we'll practice using tidyverse functions for exploratory data analysis. Start off this case study by examining your data set and visualizing the distribution of fuel efficiency. The ggplot2 package, with functions like [`ggplot()`](https://ggplot2.tidyverse.org/reference/ggplot.html) and [`geom_histogram()`](https://ggplot2.tidyverse.org/reference/geom_histogram.html) are included in the tidyverse.
 
@@ -57,9 +57,9 @@ The first time you run a code exercise, it may take a little while for your Dock
 
 **Wherever you see `___` in a code exercise, replace it with the correct code as instructed. Run the code (via the button) to see if it will run, and submit it (via the other button) to check if it's correct.**
 
-`tidyverse` is loaded for you. 
+The `tidyverse` metapackage is loaded for you, so you can use readr and ggplot2. 
 
-- Print the `cars2018` object. Notice that some of the column names have spaces in them and are surrounded by backticks, like `` `Recommended Fuel` ``.
+- Take a look at the `cars2018` object using `glimpse()`. Notice that some of the column names have spaces in them and are surrounded by backticks, like `` `Recommended Fuel` ``.
 - Use the appropriate column from the data set in the call to `aes()` so you can plot a histogram of fuel efficiency (MPG).
 - Set the correct `x` and `y` labels.
 
@@ -72,7 +72,7 @@ The first time you run a code exercise, it may take a little while for your Dock
 
 </exercise>
 
-<exercise id="4" title="Building a simple linear model">
+<exercise id="4" title="Build a simple linear model">
 
 Before embarking on more complex machine learning models, it's a good idea to build the simplest possible model to get an idea of what is going on. In this case, that means fitting a simple linear model using base R's `lm()` function.
 
@@ -80,7 +80,7 @@ Before embarking on more complex machine learning models, it's a good idea to bu
 
 - Use [`select()`](https://dplyr.tidyverse.org/reference/select.html) to deselect the two columns `Model` and `Model Index` from the model; these columns tell us the individual identifiers for each car and it would *not* make sense to include them in modeling. 
 - Fit `MPG` as the predicted quantity, explained by all the predictors, i.e., `.` in the R formula input to `lm()`. (You may have noticed the log distribution of MPG in the last exercise, but don't worry about fitting the logarithm of fuel efficiency yet.) 
-- Print the summary of the model.
+- Print the `summary()` of the model.
 
 <codeblock id="01_04">
 
@@ -90,7 +90,7 @@ Before embarking on more complex machine learning models, it's a good idea to bu
 
 </exercise>
 
-<exercise id="5" title="Getting started with caret" type="slides">
+<exercise id="5" title="Getting started with tidymodels" type="slides">
 
 <slides source="chapter1_05">
 </slides>
@@ -99,13 +99,13 @@ Before embarking on more complex machine learning models, it's a good idea to bu
 
 <exercise id="6" title="Training and testing data">
 
-Training models based on all of your data at once is typically not the best choice. 🚫 Instead, you can create subsets of your data that you use for different purposes, such as *training* your model and then *testing* your model. 
+Training models based on all of your data at once is typically not a good choice. 🚫 Instead, you can create subsets of your data that you use for different purposes, such as *training* your model and then *testing* your model. 
 
 Creating training/testing splits reduces overfitting. When you evaluate your model on data that it was not trained on, you get a better estimate of how it will perform on new data.
 
 **Instructions**
 
-- Load the `rsample` package. 
+- Load the `tidymodels` metapackage, which also includes dplyr for data manipulation. 
 - Create a data split that divides the original data into 80%/20% sections and (roughly) evenly divides the partitions between the different types of `Transmission`.
 - Assign the 80% partition to `car_train` and the 20% partition to `car_test`.
 
@@ -119,57 +119,61 @@ Creating training/testing splits reduces overfitting. When you evaluate your mod
 
 </exercise>
 
-<exercise id="7" title="Training models with caret">
+<exercise id="7" title="Train models with tidymodels">
 
-Now that your `car_train` data is ready, you can fit a set of models with caret. The [`train()`](https://topepo.github.io/caret/model-training-and-tuning.html#model-training-and-parameter-tuning) function from caret is flexible and powerful. It allows you to try out many different kinds of models and fitting procedures. To start off, train one linear regression model and one random forest model, without any resampling. (This is what `trainControl(method = "none")` does; it turns off all resampling.)
+Now that your `car_train` data is ready, you can fit a set of models with tidymodels. When we model data, we deal with model **type** (such as linear regression or random forest), **mode** (regression or classification), and model **engine** (how the models are actually fit). In tidymodels, we capture that modeling information in a model specification, so setting up your model specification can be a good place to start. In these exercises, fit one linear regression model and one random forest model, without any resampling of your data.
 
 **Instructions**
 
-- Load the caret package. 
-- Train a basic linear regression model on your `car_train` data. 
+- Load the tidymodels metapackage. 
+- Fit a basic linear regression model to your `car_train` data. 
 
 (Notice that we are fitting to `log(MPG)` since the fuel efficiency had a log normal distribution.)
 
 <codeblock id="01_07_1">
 
-For linear regression, use `method = "lm"`.
+For linear regression, use the function `linear_reg()`.
 
 </codeblock>
 
 **Instructions**
 
-- Train a random forest model on your `car_train` data.
+- Fit a random forest model to your `car_train` data.
 
 <codeblock id="01_07_2">
 
-For random forest, use `method = "rf"`.
+For a random forest model, use the function `rand_forest()`.
 
 </codeblock>
 
 </exercise>
 
-<exercise id="8" title="Evaluating your models">
+<exercise id="8" title="Evaluate model performance">
 
-The `fit_lm` and `fit_rf` models you just trained are in your environment. It's time to evaluate them! 🤩 For regression models, we will focus on evaluating using the **root mean squared error**. This quantity is measured in the same units as the original data (log of miles per gallon, in our case). Lower values indicate a better fit to the data. It's not too hard to calculate root mean squared error manually, but the [yardstick](https://tidymodels.github.io/yardstick/) package offers convenient functions for this and other model performance metrics.
+The `fit_lm` and `fit_rf` models you just trained are in your environment. It's time to see how they did! 🤩 How are we doing do this, though?! 🤔 There are several things to consider, including both what _metrics_ and what _data_ to use.
+
+For regression models, we will focus on evaluating using the **root mean squared error** metric. This quantity is measured in the same units as the original data (log of miles per gallon, in our case). Lower values indicate a better fit to the data. It's not too hard to calculate root mean squared error manually, but the [yardstick](https://tidymodels.github.io/yardstick/) package offers convenient functions for this and many other model performance metrics.
 
 **Instructions**
 
-- Load the yardstick package. 
+- Load the tidymodels metapackage, to access yardstick functions. 
 - Create new columns for model predictions from each of the models you have trained, first linear regression and then random forest.
-- Evaluate the performance of these models using [`metrics()`](https://tidymodels.github.io/yardstick/reference/metrics.html) by specifying the column in the original data that contains the real fuel efficiency.
+- Evaluate the performance of these models using [`metrics()`](https://tidymodels.github.io/yardstick/reference/metrics.html) by specifying the column that contains the real fuel efficiency.
 
 <codeblock id="01_08">
 
 - Use `fit_lm` to predict the values for linear regression and `fit_rf` to predict values for random forest.
-- The "truth" column in the original data is the column that holds fuel efficiency, `MPG`.
+- The "truth" column in `results` is the column that holds fuel efficiency, `MPG`.
 
 </codeblock>
 
 </exercise>
 
-<exercise id="9" title="Using the testing data">
+<exercise id="9" title="Use the testing data">
+
+"But wait!" you say, because you have been paying attention. 🤔 "That is how these models perform on the *training* data, the data that we used to build these models in the first place." This is _not_ a good idea because when you evaluate on the same data you used to train a model, the performance you estimate is too optimistic.
 
-"But wait!" you say, because you have been paying attention. 🤔 "That is how these models perform on the *training* data, the data that we used to build these models in the first place." Let's evaluate how these simple models perform on the testing data.
+Let's evaluate how these simple models perform on the testing data instead.
 
 **Instructions**
 
@@ -192,39 +196,40 @@ Where you had `car_train` before, switch out to `car_test`.
 
 <exercise id="11" title="Bootstrap resampling">
 
-In the last set of exercises, you trained linear regression and random forest models without any resampling. Resampling can improve the accuracy of machine learning models, and reduce overfitting.
+In the last set of exercises, you trained linear regression and random forest models without any resampling. Resampling can help us evaluate our machine learning models more accurately.
 
-Let's try bootstrap resampling, which means creating data sets the same size as the original one by randomly drawing with replacement from the original. In caret, the default behavior for bootstrapping is 25 resamplings, but you can change this using [`trainControl()`](https://topepo.github.io/caret/model-training-and-tuning.html#tune) if desired.
+Let's try bootstrap resampling, which means creating data sets the same size as the original one by randomly drawing with replacement from the original. In tidymodels, the default behavior for bootstrapping is 25 resamplings, but you can change this using the `times` argument in [`bootstraps()`](https://tidymodels.github.io/rsample/reference/bootstraps.html) if desired.
 
 **Instructions**
 
-The data sets available in your environment are 10% of their original size, to allow the code in this exercise to evaluate quickly. (This means you may see some warnings, such as about rank-deficient fits.)
+The data set available in your environment is 10% of its original size, to allow the code in this exercise to evaluate quickly. (This means you will see some warnings, such as about rank-deficient fits.)
 
-- Which data set should you train these models with, `car_train` or `car_test`?
-- Train these models using bootstrap resampling. The method for this is `"boot"`.
+- Create bootstrap resamples to evaluate these models. The function to create this kind of resample is `bootstraps()`.
+- Evaluate both kinds of models, the linear regression model and the random forest model.
+- Use the bootstrap resamples you created `car_boot` for evaluating both models.
 
 <codeblock id="01_11">
 
-You should still use the training data, `car_train`, for training these models.
+First evaluate `lm_mod`, and then evaluate `rf_mod`.
 
 </codeblock>
 
 </exercise>
 
-<exercise id="12" title="Plotting modeling results">
+<exercise id="12" title="Plot modeling results">
 
-You just trained models using bootstrap resampling, `cars_lm_bt` and `cars_rf_bt`. These models are available in your environment, trained on the entire training set instead of 10% only. Now let's evaluate how those models performed and compare them. We will again use `metrics()` from the yardstick package, but also we will plot the model predictions to inspect them visually.
+You just trained models on bootstrap resamples of the training set and now have the results in `lm_res` and `rf_res`. These results are available in your environment, trained using the entire training set instead of 10% only. Now let's compare them. 
 
-Notice in this code how we use [`gather()`](https://tidyr.tidyverse.org/reference/gather.html) from tidyr (another tidyverse package) to tidy the data frame and prepare it for plotting with ggplot2.
+Notice in this code how we use [`bind_rows()`](https://dplyr.tidyverse.org/reference/bind.html) from dplyr to combine the results from both models, along with [`collect_predictions()`](https://tune.tidymodels.org/reference/collect_predictions.html) to obtain and format predictions from each resample.
 
 **Instructions**
 
-- Use [`mutate()`](https://dplyr.tidyverse.org/reference/mutate.html) to create the new columns with the predictions from the two models you trained.
-- Choose which columns should be specified as `truth` and which should be `estimate` when calling `metrics()`.
+- First `collect_predictions()` for the linear model.
+- Then `collect_predictions()` for the random forest model.
 
 <codeblock id="01_12_1">
 
-Specify the `MPG` column as `truth` and the column created from the prediction (either `Linear regression` or `Random forest`) as `estimate`.
+The two sets of results are available in `lm_res` and `rf_res`.
 
 </codeblock>
 
diff --git a/chapters/chapter2.md b/chapters/chapter2.md
index 6d1366a..8ef4485 100644
--- a/chapters/chapter2.md
+++ b/chapters/chapter2.md
@@ -15,7 +15,7 @@ id: 2
 
 </exercise>
 
-<exercise id="2" title="Choosing an appropriate model">
+<exercise id="2" title="Choose an appropriate model">
 
 In this case study, you will predict whether a developer works remotely or not (i.e., in their company offices) from characteristics of these developers, like experience and size of the company. In this analysis, we will assume that a software developer can either work remotely, or not. What kind of model will you build?
 
@@ -47,18 +47,18 @@ A regression model predicts a numeric/continuous value or response, not a group
 
 </exercise>
 
-<exercise id="3" title="Exploring the Stack Overflow survey">
+<exercise id="3" title="Explore the Stack Overflow survey">
 
 Anytime you are planning to implement modeling, it is always a good idea to explore your dataset. Start off this modeling analysis by checking out how many remote and non-remote developers you have to work with, where they live, and how much experience they have.
 
 **Instructions**
 
-- Print the `stackoverflow` object.
+- Take a look at the `stack_overflow` object.
 - In the calls to [`count()`](https://dplyr.tidyverse.org/reference/tally.html), check out the distributions for remote status first, and then country.
 
 <codeblock id="02_03_1">
 
-To see how many developers work remotely and do *not* work remotely, use `count(Remote, sort = TRUE)`.
+To see how many developers work remotely and do *not* work remotely, use `count(remote, sort = TRUE)`.
 
 </codeblock>
 
@@ -68,33 +68,36 @@ Use the appropriate column from the data set so you can plot a boxplot with remo
 
 <codeblock id="02_03_2">
 
-The column `Remote` contains the remote status of each developer while the `YearsCodedJob` column contains how many years of experience each developer has.
+The column `remote` contains the remote status of each developer while the `years_coded_job` column contains how many years of experience each developer has.
 
 </codeblock>
 
 </exercise>
 
-<exercise id="4" title="Start with a simple model">
+<exercise id="4" title="Training and testing data">
 
-Before starting the process of building machine learning models, let's start by building an extremely simple model to get our bearings. This is not a model you would probably want to use to make predictions on new data, but it can give you an idea about how successful you may eventually be and which predictors are most important.
-
-Recall that when you use the pipe operator `%>%` with a function like [`glm()`](https://stat.ethz.ch/R-manual/R-devel/library/stats/html/glm.html) (whose first argument is not `data`), you must specify `data = .` to indicate that you are piping in the modeling data set.
+Before you deal with the imbalance in the remote/not remote classes, first split your data into training and testing sets. You create subsets of your data for *training* and *testing* your model for the same reasons you did before: to reduce overfitting and obtain a more accurate estimate for how your model will perform on new data.
 
 **Instructions**
 
-Build a simple logistic regression model predicting remote status.
+Create a data split that divides the original data into 80%/20% sections and about evenly divides the sections between the different classes of `remote`.
 
-- Use `select()` to deselect the column `Respondent` from the data set before using it in modeling.
-- Fit `Remote` as the predicted quantity, explained by all the predictors, i.e., `.` in the R formula input to `glm()`. Don't get confused with the two instances of `.`!
+- Load the `tidymodels` metapackage.
+- Create `stack_split`:
+    - For the first argument to [`initial_split()`](https://tidymodels.github.io/rsample/reference/initial_split.html), use a value for `p` of 0.8.
+    - For the second argument to `initial_split()`, stratify the split by remote status.
+- Use `training()` to assign the 80% partition to `stack_train` and use `testing()` to assign the 20% partition to `stack_test`.
 
 <codeblock id="02_04">
 
-To fit a logistic regression model using the pipe operator `%>%`, specify your model as `glm(Remote ~ ., family = "binomial", data = .)`. The first `.` here means that we want to predict `Remote` based on *all* the other columns in the data set, while the second `.` means that we have piped in the data set to the call to `glm()`.
+Use the output of `initial_split()` as the input of `training()` and `testing()`.
 
 </codeblock>
 
 </exercise>
 
+</exercise>
+
 <exercise id="5" title="Dealing with imbalanced data" type="slides">
 
 <slides source="chapter2_05">
@@ -102,70 +105,64 @@ To fit a logistic regression model using the pipe operator `%>%`, specify your m
 
 </exercise>
 
-<exercise id="6" title="Training and testing data">
+<exercise id="6" title="Preprocess with a recipe">
 
-Before you deal with the imbalance in the remote/not remote classes, first split your data into training and testing sets. You create subsets of your data for *training* and *testing* your model for the same reasons you did before: to reduce overfitting and obtain a more accurate estimate for how your model will perform on new data.
+There are multiple possible approaches to dealing with class imbalance. ⚖️ Here, you will implement downsampling using the [`step_downsample()`](https://tidymodels.github.io/recipes/reference/step_downsample.html) function.
 
 **Instructions**
 
-Create a data split that divides the original data into 80%/20% sections and about evenly divides the sections between the different classes of `Remote`.
-
-- Load the `rsample` package.
-- Create `stack_split`:
-    - For the first argument to [`initial_split()`](https://tidymodels.github.io/rsample/reference/initial_split.html), use a value for `p` of 0.8.
-    - For the second argument to `initial_split()`, pass the name of the variable that contains remote status as a string.
-- Assign the 80% partition to `stack_train` and the 20% partition to `stack_test`.
-
+- Use a `recipe()` to preprocess your training data. 
+- Downsample this data with respect to the remote status of the developers.
+	
 <codeblock id="02_06">
 
-Use the output of `initial_split()` as the input of `training()` and `testing()`.
+When you use `step_downsample(remote)`, you are saying "downsample my data so that the remote class is balanced".
 
 </codeblock>
 
 </exercise>
 
-<exercise id="7" title="Upsampling">
+<exercise id="7" title="Downsampling">
 
-There are multiple possible approaches to dealing with class imbalance. ⚖️ Here, you will implement upsampling using caret's [`upSample()`](https://topepo.github.io/caret/subsampling-for-class-imbalances.html#subsampling-techniques) function.
+Once your recipe is defined, you can estimate the parameters required to actually preprocess the data, and then extract the processed data. This typically isn't necessary is you use a `workflow()` for modeling, but it can be helpful to diagnose problems or explore your preprocessing results.
 
 **Instructions**
 
-- Use the `stack_train` data set for upsampling: 
-    - `x` should use `select()` to grab only the predictors from the data.
-    - `y` should be the class memberships in `stack_train` as a vector (use `$` notation).
-    - The label for the class column goes in `yname`; remember that it is `"Remote"`.
+- First, `prep()` the recipe.
+- Then, `juice()` the prepped recipe.	
+	
+Check out the results of counting remote status after downsampling! You likely will not need to `juice()` when building a model but you can use this for exploration.	
 	
 <codeblock id="02_07">
 
-- The class memberships that must be assigned to `y` are `training$Remote`.
-- This function needs to also know the label for the class column, as `yname = "Remote"`.
+When you `juice()` the prepped recipe `stack_prep`, you extract the processed (i.e. balanced) data.
 
 </codeblock>
 
 </exercise>
 
-<exercise id="8" title="Understanding upsampling">
+<exercise id="8" title="Understand downsampling">
 
-Consider the original data set `stackoverflow`, the training set that you created `stack_train`, and the upsampled set you created `up_train`. Both `stackoverflow` and `stack_train` have almost 10 times as many non-remote developers as remote developers. 
+Consider the original data set `stack_overflow`, the training set that you created `stack_train`, and the downsampled set you created `stack_down`. Both `stack_overflow` and `stack_train` have almost 10 times as many non-remote developers as remote developers. 
 
-How do the remote and non-remote developers in `up_train` compare?
+How do the remote and non-remote developers in `stack_down` compare?
 
 <choice>
 <opt text="There are more remote developers.">
 
-Upsampling changes the proportion of remote and non-remote developers, but *not* so that there are more non-remote developers.
+Downsampling changes the proportion of remote and non-remote developers, but *not* so that there are more non-remote developers.
 
 </opt>
 
 <opt text="There are more non-remote developers.">
 
-Although there were more non-remote developers in the original dataset, upsampling changes this ratio so that the classes are balanced.
+Although there were more non-remote developers in the original dataset, downsampling changes this ratio so that the classes are balanced.
 
 </opt>
 
 <opt text="There are the same number of remote and non-remote developers." correct="true">
 
-Upsampling samples with replacement until the class distributions are equal, so there are the same number of remote and non-remote developers after upsampling.
+Downsampling removes from the majority class until the class distributions are equal, so there are the same number of remote and non-remote developers after downsampling.
 
 </opt>
 
@@ -173,14 +170,14 @@ Upsampling samples with replacement until the class distributions are equal, so
 
 </exercise>
 
-<exercise id="9" title="Upsampling in your workflow">
+<exercise id="9" title="Downsampling in your workflow">
 
-We are starting to add more steps into the machine learning workflow. Think about when we implemented upsampling to deal with class imbalance. Which data set did we upsample?
+We are starting to add more steps into the machine learning workflow. Think about when we implemented downsampling to deal with class imbalance. Which data set did we upsample?
 
 <choice>
 <opt text="The original data.">
 
-We used upsampling only on a subset of the data, because its purpose is only applicable for part of the predictive modeling workflow. Does upsampling help you do a better job of training your model or testing your model?
+We used downsampling only on a subset of the data, because its purpose is only applicable for part of the predictive modeling workflow. Does downsampling help you do a better job of training your model or testing your model?
 
 </opt>
 
@@ -194,9 +191,9 @@ We used upsampling only on a subset of the data, because its purpose is only app
 
 We do not want to artificially balance the test set; the test set needs to be close to what we will see when applying our model on new data.
 
-<opt text="It doesn't matter! We'll upsample it all eventually anyway.">
+<opt text="It doesn't matter! We'll downsample it all eventually anyway.">
 
-We do not upsample all subsets of our data, because we do not want to artificially balance the test set.
+We do not downsample all subsets of our data, because we do not want to artificially balance the test set.
 
 </opt>
 
@@ -211,29 +208,33 @@ We do not upsample all subsets of our data, because we do not want to artificial
 
 </exercise>
 
-<exercise id="11" title="Training models">
-
-Finally! 😁 It's time to train predictive models for this data set of Stack Overflow Developer Survey responses. We will continue to use the powerful, flexible [`train()`](https://topepo.github.io/caret/model-training-and-tuning.html#model-training-and-parameter-tuning) function from caret to specify our machine learning models.
+<exercise id="11" title="Train models">
 
-To keep the code in this exercise evaluating quickly, the data sets in your environment are 1% of their original size. (This means you may see some warnings due to the subsampling.)
+Finally! 😁 It's time to train predictive models for this data set of Stack Overflow Developer Survey responses. We will specify our machine learning models with parsnip, and use [workflows](https://tidymodels.github.io/workflows/) for convenience.
 
 **Instructions**
 
-Build a logistic regression model using `method = "glm"` and `family = "binomial"` while implementing upsampling to address class imbalance.
+- Specify a logistic regression model using `logistic_reg()`.
+- Build a `workflow()` to hold your modeling components.
+- Add your model specification to your `workflow()` before fitting.
 
 <codeblock id="02_11_1">
 
-To upsample the training set within the call to `train()`, use `sampling = "up"` inside of `trainControl()`.
+You can add your model specification to your `workflow()` by piping `stack_wf %>% add_model(glm_spec)`.
 
 </codeblock>
 
 **Instructions**
 
-Build a random forest model while implementing upsampling to address class imbalance.
+Build a decision tree model with downsampling.
+
+- Specify a decision tree regression model using `decision_tree()`.
+- Add your recipe `stack_recipe` to your `workflow()`.
+- Fit your workflow, after you have added your model to it.
 
 <codeblock id="02_11_2">
 
-Use `method = "rf"` to build a random forest model.
+A workflow needs both a preprocessor (such as a recipe or formula) and a model to be fit.
 
 </codeblock>
 
@@ -243,21 +244,23 @@ Use `method = "rf"` to build a random forest model.
 
 A confusion matrix describes how well a classification model (like the ones you just trained!) performs. A confusion matrix tabulates how many examples in each class were correctly classified by a model. In your case, it will show you how many remote developers were classified as remote and how many non-remote developers were classified as non-remote; the confusion matrix also shows you how many were classified into the **wrong** categories.
 
-Here you will use the [`conf_mat()`](https://tidymodels.github.io/yardstick/reference/conf_mat.html) function from yardstick to evaluate the performance of the two models you trained, `stack_glm` and `stack_rf`. The models available in your environment were trained on all the training data, not only 1%.
+Here you will use the [`conf_mat()`](https://tidymodels.github.io/yardstick/reference/conf_mat.html) function from yardstick to evaluate the performance of the two models you trained, `stack_glm` and `stack_tree`. The models available in your environment were trained on the training data.
 
 **Instructions**
 
-Print the confusion matrix for the `stack_glm` model on the `stack_test` data. Note that the first argument to `conf_mat()` is `truth` and the second is `estimate`.
+Print the confusion matrix for the `stack_glm` model on the `stack_test` data. If we wanted to compare more than two modeling options, we should definitely create some resampled data sets like we did in the first case study. This case study is already getting long, so let's stick with the testing data.
+
+Note that the first argument to `conf_mat()` is `truth` and the second is `estimate`.
 
 <codeblock id="02_12_1">
 
-You are evaluating your models, so you should use the testing data set for all the possible arguments here.
+Use the arguments `truth = remote` and `estimate = .pred_glm`.
 
 </codeblock>
 
 **Instructions**
 
-Print the confusion matrix for the `stack_rf` model on the `stack_test` data.
+Print the confusion matrix for the `stack_tree` model on the `stack_test` data.
 
 <codeblock id="02_12_2">
 
@@ -271,12 +274,11 @@ Use the `conf_mat()` function to build a confusion matrix.
 
 The `conf_mat()` function is helpful but often you also want to store specific performance estimates for later, perhaps in a dataframe-friendly form. The yardstick package is built to handle such needs. For this kind of classification model, you might look at the [positive or negative predictive value](https://tidymodels.github.io/yardstick/reference/ppv.html) or perhaps overall [accuracy](https://tidymodels.github.io/yardstick/reference/accuracy.html).
 
-The models available in your environment, `stack_glm` and `stack_rf` were trained on all the training data, not only 1%.
+The models available in your environment, `stack_glm` and `stack_tree` were trained on the training data.
 
 **Instructions**
 
-- Load the yardstick package. 
-- Predict values for logistic regression (`stack_glm`) and random forest (`stack_rf`).  
+- Predict values for logistic regression (`stack_glm`) and decision tree (`stack_tree`).  
 - Calculate both accuracy and positive predictive value for these two models.
 	
 <codeblock id="02_13">
diff --git a/chapters/chapter3.md b/chapters/chapter3.md
index 2a58bec..542b7a5 100644
--- a/chapters/chapter3.md
+++ b/chapters/chapter3.md
@@ -15,7 +15,7 @@ id: 3
 
 </exercise>
 
-<exercise id="2" title="Choosing an appropriate model">
+<exercise id="2" title="Choose an appropriate model">
 
 In this case study, you will predict whether a person voted or not in the United States 2016 presidential election from responses that person gave on a survey. The survey focuses on opinions about political and economic topics. What kind of model will you build?
 
@@ -47,14 +47,14 @@ A regression model predicts a numeric/continuous value or response, not a group
 
 </exercise>
 
-<exercise id="3" title="Exploring the VOTER data">
+<exercise id="3" title="Explore the VOTER data">
 
 To do a good job with predictive modeling, you need to explore your dataset to understand it first. Start off this modeling analysis by checking out how many people voted or did not vote, and the answers to a few questions. The answers to the questions on this survey have been coded as integers, and the corresponding text has been provided for you here.
  
 **Instructions**
 
 - Load [tidyverse](https://tidyverse.tidyverse.org/).
-- Print `voters` to check out the data.
+- Take a look at `voters` to check out the data.
 - In the call to `count()`, use the appropriate variable (`turnout16_2016`) to see how many examples you have of those who voted and did not vote.
 
 <codeblock id="03_03_1">
@@ -120,19 +120,19 @@ We can tell whether our data is imbalanced by examining the data set and noticin
 
 </exercise>
 
-<exercise id="6" title="Fit a simple model">
+<exercise id="6" title="Training and testing data">
 
-Start off a predictive modeling project by building the simplest possible model, to learn about the data and questions you are dealing with. Here, you will fit a simple logistic regression model on the whole data set to get an idea of what is going on.
+It's time to split your data into training and testing sets, in the same way that you created these subsets in the previous case studies. You want to split your data about evenly on the class `turnout16_2016`.
 
 **Instructions**
 
-- Use [`select()`](https://dplyr.tidyverse.org/reference/select.html) to remove the column `case_identifier` from `voters` and assign it to `voters_select`. 
-- Fit a logistic regression model to predict `turnout16_2016` explained by all the other variables in `voters_select`.
+- Load the tidymodels metapackage, for using the functions to split your data.
+- Use the correct function to create a data split that divides `voters_select` into 80%/20% sections.
+- Assign the 80% partition to `vote_train` and the 20% partition to `vote_test`.
 
 <codeblock id="03_06">
 
-- The formula for your model should be `turnout16_2016 ~ .` . 
-- To fit a logistic regression model, use `family = "binomial"`.
+The `initial_split()` function sets up the data partitioning, and then you can use that as input to call `training()` and `testing()`.
 
 </codeblock>
 
@@ -145,35 +145,35 @@ Start off a predictive modeling project by building the simplest possible model,
 
 </exercise>
 
-<exercise id="8" title="Training and testing data">
+<exercise id="8" title="Preprocess with a recipe">
 
-It's time to split your data into training and testing sets, in the same way that you created these subsets in the previous case studies. You want to split your data about evenly on the class `turnout16_2016`.
+This dataset needs to prepared for modeling.
 
 **Instructions**
 
-- Load the rsample package, for using the functions to split your data.
-- Use the correct function to create a data split that divides `voters_select` into 80%/20% sections.
-- Assign the 80% partition to `vote_train` and the 20% partition to `vote_test`.
+- Use a `recipe()` to preprocess your training data, `vote_train`.
+- Upsample this training data with the function `step_upsample()`.
 
 <codeblock id="03_08">
 
-The `initial_split()` function sets up the data partitioning, and then you can use that as input to call `training()` and `testing()`.
+When you set up a recipe with `recipe(turnout16_2016 ~ ., data = vote_train)`, you are specifying that the following steps should be applied to your data to get it ready for data analysis.
 
 </codeblock>
 
 </exercise>
 
-<exercise id="9" title="Upsampling for imbalanced data">
+<exercise id="9" title="Create a modeling workflow">
 
-It's time to start training your predictive models using caret's [train()](https://topepo.github.io/caret/model-training-and-tuning.html#model-training-and-parameter-tuning) function. This survey data set is imbalanced, with many more examples of people who said they voted than people who did not. To build a model that performs better, you should deal with this class imbalance. In this exercise, use upsampling, the same approach we used in the last case study.
+In this case study, we'll experiment with a new engine for the random forest model, the ranger package. You can combine the model with your preprocessing steps (your recipe) in a [workflow()](https://tidymodels.github.io/workflows/) for convenience.
 
 **Instructions**
 
-Build a logistic regression model with no resampling of data, but add the specification for upsampling. If you can't remember, learn more about [`trainControl()`](https://topepo.github.io/caret/model-training-and-tuning.html#control).
+- Use `rand_forest()` to specify a random forest model. Notice that we are using a different engine than in the first case study.
+- Add the recipe and the model specification to the workflow.
 
 <codeblock id="03_09">
 
-To upsample the training set within the call to `train()`, use `sampling = "up"` inside `trainControl()`.
+You add a recipe with `add_recipe()` and you add a model specification with `add_model()`.
 
 </codeblock>
 
@@ -191,19 +191,19 @@ To upsample the training set within the call to `train()`, use `sampling = "up"`
 When you implement 10-fold cross-validation repeated 5 times, you...
 
 <choice>
-<opt text="randomly divide your training data into 50 subsets and train on 49 at a time (validating on the other subset), iterating through all 50 subsets for validation.">
+<opt text="randomly divide your training data into 50 subsets and train on 49 at a time (assessing on the other subset), iterating through all 50 subsets for assessment.">
 
 If you divide your data into 50 subsets, that would be called 50-fold cross-validation. For most practical situations, 50 folds is overkill.
 
 </opt>
 
-<opt text="randomly divide your training data into 10 subsets and train on 9 at a time (validating on the other subset), iterating through all 10 subsets for validation. Then you repeat that process 5 times." correct="true">
+<opt text="randomly divide your training data into 10 subsets and train on 9 at a time (assessing on the other subset), iterating through all 10 subsets for assessment. Then you repeat that process 5 times." correct="true">
 
-⚡️ Simulations and practical experience show that 10-fold cross-validation repeated 5 times is a great resampling approach for many situations. This approach involves randomly dividing your training data into 10 folds, or subsets or groups, and training on only 9 while using the other fold for validation. You iterate through all 10 folds being used for validation; this is one round of cross-validation. You can then repeat the whole process multiple, perhaps 5, times.
+⚡️ Simulations and practical experience show that 10-fold cross-validation repeated 5 times is a great resampling approach for many situations. This approach involves randomly dividing your training data into 10 folds, or subsets or groups, and training on only 9 while using the other fold for assessment. You iterate through all 10 folds being used for assessment; this is one round of cross-validation. You can then repeat the whole process multiple, perhaps 5, times.
 
 </opt>
 
-<opt text="randomly divide your training data into 5 subsets and train on 4 at a time (validating on the other subset), iterating through all 5 subsets. Then you repeat that process 10 times.">
+<opt text="randomly divide your training data into 5 subsets and train on 4 at a time (assessing on the other subset), iterating through all 5 subsets. Then you repeat that process 10 times.">
 
 If you divide your data into 5 subsets, that would be called 5-fold cross-validation. In many practical situations, 5 folds is not enough to get the maximum performance improvement possible.
 
@@ -212,98 +212,70 @@ If you divide your data into 5 subsets, that would be called 5-fold cross-valida
 
 </exercise>
 
-<exercise id="12" title="Training models with cross-validation">
+<exercise id="12" title="Create cross-validation folds">
 
-You can build models both with the upsampling you implemented before, *and* the cross-validation we just discussed. Here, try 10-fold cross-validation repeated 2 times.
-
-To allow the code in this exercise to evaluate in a short time, the training set in your environment is 2% of the real training set. Expect to see some warnings because of this.
+You can use tidymodels functions to create the kind of cross-validation folds appropriate for your use case. Here, try 10-fold cross-validation repeated 5 times.
 
 **Instructions**
 
-- Use `method = "repeatedcv"` to implement 10-fold cross-validation (10 folds or subsets is the default, but this can be changed) for the logistic regression model.
-- Specify `repeats = 2` to repeat the 10-fold cross-validation 2 times.
+- The argument `v` specifies the number of folds for cross-validation.
+- The argument `repeats` specifies the number of repeats.
 
-<codeblock id="03_12_1">
+<codeblock id="03_12">
 
-Your call to `trainControl()` should look like `trainControl(method = "repeatedcv", repeats = 2, sampling = "up")`.
-
-</codeblock>
-
-**Instructions**
-
-Now, train a random forest model by implementing 10-fold cross validation 2 times.
-
-<codeblock id="03_12_2">
-
-Similar to the logistic regression model, you need to use the `method` and `repeats` arguments inside `trainControl()`.
+Use argument `v = 10` and `repeats = 5` to implement 10-fold cross-validation repeated 5 times.
 
 </codeblock>
 
 </exercise>
 
-<exercise id="13" title="Comparing model performance" type="slides">
+<exercise id="13" title="Evaluate model performance" type="slides">
 
 <slides source="chapter3_13">
 </slides>
 
 </exercise>
 
-<exercise id="14" title="Confusion matrix for your training data">
+<exercise id="14" title="Resampling two models">
 
-Let's start by seeing how these two models perform on your training data by looking at some confusion matrices. A confusion matrix tabulates how many examples in each class were correctly classified by a model. In this case study, it will show you how many voters were classified as voters and how many non-voters were classified as non-voters; the confusion matrix also shows you how many were classified into the wrong categories. 
+Let's use cross-validation resampling to evaluate performance for two kinds of models with this vote data. You've already learned how to create resamples, preprocess data for modeling, build a model specification, and combine this in a workflow; now it's time to put this all together and evaluate this model's performance. 
 
-Here we want to see how your model performed on the **training** data, the data the model used when it was trained. The models available in your environment were trained on all the training data, not just a subset, with 10-fold cross-validation repeated 5 times.
+The training data available in your environment is 10% of its original size, to allow the code in this exercise to evaluate quickly. (This means you may see some warnings.)
 
 **Instructions**
 
-Print the confusion matrix for the logistic regression model on the training data.
+Use `fit_resamples()` to evaluate how this logistic regression model performs on the cross-validation resamples.
 
 <codeblock id="03_14_1">
 
-- Use the `conf_mat()` function to build a confusion matrix. 
-- We aren't evaluating your models on the testing data yet, so use the `vote_train` data for all the arguments here.
+The workflow `vote_wf` contains both the recipe and the model specification, and can be fit to the resamples `vote_folds`.
 
 </codeblock>
 
 **Instructions**
 
-Print the confusion matrix for the random forest model (`vote_rf`) on the training data.
+- Now fit the resamples `vote_folds` to the random forest model.
+- Compute the metrics `roc_auc`, `sens`, and `spec`.
 
 <codeblock id="03_14_2">
 
-Use `mutate()` to make a new column of `predict`ed values.
+The function `metric_set()` takes as its arguments the metrics you want to compute.
 
 </codeblock>
 
 </exercise>
 
-<exercise id="15" title="Confusion matrix for your testing data">
-
-Now, let's evaluate how the models perform on the testing data. This is what you use to estimate how your model will perform on new data.
-
-**Instructions**
-
-Print the confusion matrix for the logistic regression model on the training data.
-
-- Generate a confusion matrix for the logistic regression model (`vote_glm`). 
-- Instead of the `vote_train` data, now use the `vote_test` data.
-
-<codeblock id="03_15_1">
+<exercise id="15" title="Performance metrics from resampling">
 
-- Find the predictions using `predict(vote_glm, vote_test)`.
-- Choose the real voting status for the `truth` argument to `conf_mat()`, and the predicted voting status for `estimate`. 
-
-</codeblock>
+Now, let's evaluate these results from resampling.
 
 **Instructions**
 
-- Generate a confusion matrix for the random forest model (`vote_rf`). 
-- Instead of the `vote_train` data, now use the `vote_test` data.
+Use the function `collect_metrics()` to obtain the metrics we specified from the resampling results.
 
-<codeblock id="03_15_2">
+<codeblock id="03_15">
 
-- Use `mutate()` to make the new column with predicted values.
-- Remember that `conf_mat()` is the function to find a confusion matrix.
+You can obtain the metrics from the random forest results with `collect_metrics(rf_res)`.
 
 </codeblock>
 
@@ -311,22 +283,40 @@ Print the confusion matrix for the logistic regression model on the training dat
 
 <exercise id="16" title="Which model is best?">
 
-You have just spent a whole chapter of this course exploring how to predict voter turnout based on survey responses. Of the two types of models you tried, which is the better choice? Which do you expect to perform better on new data?
-
-Which model performed better on the **testing** data?
+You have just spent most of this chapter exploring how to predict voter turnout based on survey responses. Of the two types of models you tried, which is the better choice? Which do you expect to perform better on new data?
 
 <choice>
 <opt text="Random forest">
 
-Random forest models are very powerful and the random forest model had higher accuracy than the logistic regression model on the training data, but on the testing data, the random forest model could not identify any of the people who voted.
+Random forest models are very powerful, but the random forest model could not identify any of the people who did _not_ vote.
 
 </opt>
 
 <opt text="Logistic regression" correct="true">
 
-Logistic regression is a simpler model, but in this case, it performed better on the testing data and you can expect it to do a better job predicting on new data.
+Logistic regression is a simpler model, but in this case, it performed better and you can expect it to do a better job predicting on new data.
 
 </opt>
 </choice>
 
 </exercise>
+
+<exercise id="17" title="Back to the testing data">
+
+When we used resampling to evaluate model performance with the **training set**, the logistic regression model performed better. Now, let's put this model to the test! 😎 
+
+Let's use the `last_fit()` function to fit to the entire training set one time and evaluate one time on the **testing set**, with everything we've learned during this case study. Our model has not yet seen the testing data, so this last step is the best way to estimate how well the model will perform when predicting with new data.
+
+**Instructions**
+
+- Fit to the training set and evaluate on the testing set using `last_fit()`. 
+- Create a confusion matrix for the results from the testing set.
+
+<codeblock id="03_17">
+
+Remember that `conf_mat()` is the function to find a confusion matrix.
+
+</codeblock>
+
+</exercise>
+
diff --git a/chapters/chapter4.md b/chapters/chapter4.md
index f66373b..bf917c0 100644
--- a/chapters/chapter4.md
+++ b/chapters/chapter4.md
@@ -15,7 +15,7 @@ id: 4
 
 </exercise>
 
-<exercise id="2" title="Choosing an appropriate model">
+<exercise id="2" title="Choose an appropriate model">
 
 In this case study, you will predict the age of Catholic nuns from their answers on a survey fielded in 1967 focusing on questions about social and religious issues. What kind of model will you build?
 
@@ -47,7 +47,7 @@ To predict a continuous, numeric quantity like age, use regression models.
 
 </exercise>
 
-<exercise id="3" title="Visualizing the age distribution">
+<exercise id="3" title="Visualize the age distribution">
 
 The first step before you start modeling is to explore your data, and we are going to spend a little more time on this step in this last case study. To start with, check out the distribution of ages for the respondents in this survey. 📊 (Keep in mind throughout this case study that the data you have in your environment is one quarter of the real survey data.)
 
@@ -64,7 +64,7 @@ You can build a histogram using [`geom_histogram()`](https://ggplot2.tidyverse.o
 
 </exercise>
 
-<exercise id="4" title="Tidying the survey data">
+<exercise id="4" title="Tidy the survey data">
 
 Embracing [tidy data principles](https://tidyverse.tidyverse.org/articles/manifesto.html) is a powerful option for exploratory data analysis. When your data is tidy, you can quickly iterate in getting to know your data better and making exploratory plots. Let's transform this wide data set into a tidy data frame with one observation per row, and then check out some characteristics of this subset of the original survey.
 
@@ -72,12 +72,12 @@ Note: There is a column called `sister` in this dataset that is an identifier fo
 
 **Instructions**
 
-- Use the [`gather()`](https://tidyr.tidyverse.org/reference/gather.html) function to transform the wide data set with each survey question in a separate column to a narrow, tidy data set with each survey question in a separate row.
+- Use the [`pivot_longer()`](https://tidyr.tidyverse.org/reference/pivot_longer.html) function to transform the wide data set with each survey question in a separate column to a narrow, tidy data set with each survey question in a separate row.
 - View the structure of this tidy data set using `glimpse()`.
 
 <codeblock id="04_04_1">
 
-When you implement `... %>% gather(key, value, -age)`, you transform the data set from wide (non-tidy) to narrow (tidy). The argument `-age` specifies that we want to keep the `age` column for each row.
+When you implement `... %>% pivot_longer(-age, names_to = "key", values_to = "value")`, you transform the data set from wide (non-tidy) to narrow (tidy). The argument `-age` specifies that we want to keep the `age` column for each row.
 
 </codeblock>
 
@@ -104,7 +104,7 @@ Next look at question agreement overall.
 
 </exercise>
 
-<exercise id="6" title="Visualizing agreement with age">
+<exercise id="6" title="Visualize agreement with age">
 
 The tidied version of the survey data that you constructed is available in your environment. You have many options at your fingertips with this tidy data now. Make a plot that shows how agreement on a subset of the questions changes with age.
  📉
@@ -125,47 +125,25 @@ In this exercise, we are using [`filter()`](https://dplyr.tidyverse.org/referenc
 
 </exercise>
 
-<exercise id="7" title="Building a simple linear model">
+<exercise id="7" title="Training, validation, and testing data">
 
-You have gotten to know this data a bit through exploratory data analysis, and now it's time to build the simplest possible model, in preparation for more complex predictive modeling. For this data set where we want to predict age from the survey responses (coded as integers), we can build a simple linear model for all our data using only the [`lm()`](https://stat.ethz.ch/R-manual/R-devel/library/stats/html/lm.html) function.
-
-**Instructions**
-
-- Remove the identifier column `sister` from the dataset to create `sisters_select`. 
-- Use the correct variable on the left-hand side of the equation so that you build a model predicting age as a function of all other columns. 
-- Call `summary()` for the simple model you've built to see the results.
-
-<codeblock id="04_07">
-
-- We want to predict age using all other variables, so the first argument to `lm()` should be `age ~ .`.
-- Remove the `sister` identifier from the data set with `select(sisters67, -sister)`.
-- You can examine the results of this simple modeling with `summary(simple_lm)`.
-
-</codeblock>
-
-</exercise>
-
-<exercise id="8" title="Training, validation, and testing data">
-
-It's time to split your data into different sets now. You've done this three times already in this course, but in this last case study we are also going to create a validation set. Using a validation set is important anytime you will compare multiple models and choose between them, or adjust hyperparameters in a model. 
-
-We are going to split the data into 60% training, 20% validation, 20% testing.
+It's time to split your data into different sets now. You've done this three times already in this course, but in this last case study we are also going to create a validation set. Using a validation set is a good option when you have enough data (otherwise, you can use resampling). 
 
 **Instructions**
 
 - Create two data partitions: 
-    - Specify one to split between training (60%) and validation/testing (40%).
-    - Specify another one to split between validation and testing (50% each).
+    - Specify one to split between testing and everything else.
+    - Specify another one to split between validation and training.
 
-<codeblock id="04_08">
+<codeblock id="04_07">
 
-The [`initial_split()`](https://tidymodels.github.io/rsample/reference/initial_split.html) function creates a vector that specifies which examples belong in the training set, or the test set.
+The [`initial_split()`](https://tidymodels.github.io/rsample/reference/initial_split.html) function splits off the testing set, and then [`validation_split()`](https://tidymodels.github.io/rsample/reference/validation_split.html) creates a single resample to be used for validation.
 
 </codeblock>
 
 </exercise>
 
-<exercise id="9" title="Using your validation set">
+<exercise id="8" title="Using your validation set">
 
 This new validation set you just created will be used to...
 
@@ -191,87 +169,152 @@ The final evaluation is done with the testing set. It is important to do this fi
 
 </exercise>
 
-<exercise id="10" title="Predicting age with supervised machine learning" type="slides">
+<exercise id="9" title="Tune model hyperparameters" type="slides">
 
-<slides source="chapter4_10">
+<slides source="chapter4_09">
 </slides>
 
 </exercise>
 
-<exercise id="11" title="Training, validation, and testing data">
+<exercise id="10" title="Identify tuning parameters">
 
-In this chapter, you will explore a few new kinds of models. Fun! 💃The `"gbm"` gradient boosting and `"xbgLinear"` extreme gradient boosting models take a very long time to train, so we'll upload trained models for you to evaluate in the next exercises. In this exercise, train a CART model with `"rpart"` to predict age with all the other columns.
+It's time to build a modeling `workflow()` for this last dataset. We aren't going to fit this dataset just once, but instead _many_ times! We are going to use this `workflow()` to tune hyperparameters both in our model specification and our preprocessing recipe.
 
-To allow the code in this exercise to evaluate quickly, the training set in your environment only contains 500 rows. (You'll see a warning because the training set here is so small.)
+**Instructions**
+
+Let's start with our preprocessing tuning.
+
+- Add two preprocessing steps to this recipe, first to normalize and them to implement PCA.
+- Specify that we want to `tune()` the number of principal components.
+
+<codeblock id="04_10_1">
+
+- To normalize, use `step_normalize()`. 
+- To implement PCA, use `step_pca()`.
+
+</codeblock>
+
+Next let's build our model specification with tuning.
 
 **Instructions**
 
-- Using caret, train a CART model to predict `age` based on all other variables on `sisters_train` data. 
+- Start by specifying that we want to train a `decision_tree()` model.
+- Add the two parameters we want to tune, cost complexity and tree depth.
+
+<codeblock id="04_10_2">
+
+The variables for these parameters are `cost_complexity` and `tree_depth`.
 
-When you don't give any specific [`trainControl()`](https://topepo.github.io/caret/model-training-and-tuning.html#basic-parameter-tuning) argument to `train()`, the model training is implemented with a default resampling strategy, 25 bootstrap resamplings.
+</codeblock>
+
+Finally, let's put our recipe and model specification together in a `workflow()`, for ease of use.
+
+**Instructions**
+
+- First set up a `workflow()` object.
+- Add the recipe to the `workflow()`.
+- Add the model to the `workflow()`
+
+<codeblock id="04_10_3">
+
+You start off any workflow with the `workflow()` function.
+
+</codeblock>
+
+</exercise>
+
+
+<exercise id="11" title="Create a tuning grid">
+
+Let's create a grid! 💃To tune our hyperparameters, we need a set of possible values for each parameter to try. In this case study, we'll work through a regular grid of hyperparameter values.
+
+**Instructions**
+
+- Use the function `grid_regular()` to create a grid of tuning parameters.
+- Add the function for the tree depth tuning parameter, after the cost complexity tuning parameter function.
 
 <codeblock id="04_11">
 
-- To train a model use the `train()` function. 
-- The `method` argument to `train()` should be `"rpart"`.
+Use the function `tree_depth()` for the third tuning parameter in the grid.
 
 </codeblock>
 
 </exercise>
 
-<exercise id="12" title="Making predictions">
+<exercise id="12" title="Time to tune">
 
-Three models are available in your environment (trained on the data set in its entirety), the CART model you just trained along with two kinds of gradient boosting models. Your next task is to decide which of these models to use for prediction on new data. If you use the training data to evaluate the models, you will underestimate your error for new data and might make the wrong choice altogether. That leaves the validation data and the testing data.
+It's time to finally tune! The recipe, model, workflow, and grid are built here for you, and now you can put them together to find out which combination of parameters results in the best performance. (There is a smaller grid created here so the tuning will evaluate faster.)
 
 **Instructions**
 
-- Which data set should you use to choose between these three models, `sisters_validate` or `sisters_test`? Use that option to create a data frame for comparing the models.
+- Use the function `tune_grid()` to tune your model.
+- For the first argument, add your tuneable workflow.
+- For the third argument, add the grid of possible parameters.
 
 <codeblock id="04_12">
 
-The validation data set is the appropriate option for choosing between models.
+Your function should be `tune_grid(tree_wf, sisters_val, tree_grid)`.
 
 </codeblock>
 
 </exercise>
 
-<exercise id="13" title="Choosing between models">
+<exercise id="13" title="Visualize tuning results">
+
+Now that you have trained models for many possible tuning parameters, let's explore the results.
 
-Now that you have created a data frame that contains all three models' predictions, let's compare their performance.
+(The results available in your environment were trained over a larger grid of tuning parameters.)
 
 **Instructions**
 
-- Load `yardstick`. 
-- Use the [`metrics()`](https://tidymodels.github.io/yardstick/reference/metrics.html) function from the yardstick package to see how each model performed. There are two important arguments that you need to supply to `metrics()`, `truth` (the true age of each nun) and `estimate` (the predicted age of each nun). Which column in the data frame you created corresponds to each?
+- As a first step, use the function `collect_metrics()` to extract the performance metrics from the tuning results.
+- In the call to `aes()`, put `cost_complexity` on the x-axis and assign `tree_depth` to the color aesthetic.
 
 <codeblock id="04_13">
 
-The `truth` argument should always be `age`, while the `estimate` column changes with each model.
+Set up your aesthetic call as `aes(cost_complexity, mean, color = tree_depth)`.
 
 </codeblock>
 
 </exercise>
 
-<exercise id="14" title="Estimating uncertainty for new data">
+<exercise id="14" title="Find the best parameters">
 
-You just compared the three models you trained, and the XGBoost model performed best on the validation data set. Gradient boosting models are very effective and are a powerful tool in your machine learning arsenal. Before you take a trained model like this and use it to make predictions on new data, you must estimate how your final chosen model will perform. Specifically, let's estimate the [`rmse()`](https://tidymodels.github.io/yardstick/reference/rmse.html) for this model.
+You just visualized the tuning results, but you can also select the best set of tuning parameters and update your `workflow()` with these values.
 
 **Instructions**
 
-- Which data set would you use to estimate how your model will perform on new data? You have `sisters_train`, `sisters_validate`, and `sisters_test` data sets available in your environment. Use the correct one *both* at the beginning of the pipe and within the call to `predict()`.
-- Calculate the RMSE (root mean squared error) using the appropriate function from [yardstick](https://tidymodels.github.io/yardstick/).
+- Use the function `select_best()` to extract the hyperparameters with the lowest RMSE from the tuning results.
+- Pipe the original workflow object to `finalize_workflow()` with that best decision tree as an argument, to update it.
 
 <codeblock id="04_14">
 
-You want to use the `sisters_test` data along with the `rmse()` function.
+After you execute `tree_wf %>% finalize_workflow(best_tree)`, the output can be used to predict on new data.
+
+</codeblock>
+
+</exercise>
+
+<exercise id="15" title="Use the testing data">
+
+We haven't touched the testing data throughout this analysis, but here at the very end, we can come back to it and estimate how well our model will perform on new data. If all has gone well, our performance metrics such as RMSE will be about the same as from the validation set, indicating that we did not overfit during our tuning procedure. Let's use the `last_fit()` function to fit to the entire training set and evaluate on the testing set.
+
+**Instructions**
+
+- Fit to the training set and evaluate on the testing set using `last_fit()`. 
+- Access the performance metrics for the testing set using `collect_metrics()`.
+
+<codeblock id="04_15">
+
+You don't need to specify anything to get the testing set metrics; you only need to use the `collect_metrics()` function.
 
 </codeblock>
 
 </exercise>
 
-<exercise id="15" title="Wrapping up" type="slides">
+<exercise id="16" title="Wrapping up" type="slides">
 
-<slides source="chapter4_15">
+<slides source="chapter4_16">
 </slides>
 
 </exercise>
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diff --git a/data/sisters.csv b/data/sisters.csv
index 0905cec..006f528 100644
--- a/data/sisters.csv
+++ b/data/sisters.csv
@@ -1,19279 +1,19279 @@
 age,sister,v116,v117,v118,v119,v120,v121,v122,v123,v124,v125,v126,v127,v128,v129,v130,v131,v132,v133,v134,v135,v136,v137,v138,v139,v140,v141,v142,v143,v144,v145,v146,v147,v148,v149,v150,v151,v152,v153,v154,v155,v156,v157,v158,v159,v160,v161,v162,v163,v164,v165,v166,v167,v168,v169,v170,v171,v172,v173,v174,v175,v176,v177,v178,v179,v180
-40,11545,5,2,2,2,4,4,4,5,1,4,2,1,2,4,2,1,5,2,2,5,1,1,2,3,1,5,1,2,1,4,4,2,1,4,2,4,2,5,1,5,1,4,4,1,2,2,5,2,4,2,2,2,5,1,5,5,2,2,2,1,4,4,4,4,4
-30,16953,4,1,4,4,1,1,1,5,1,2,1,4,1,4,4,2,5,4,4,5,4,1,1,1,2,5,1,1,2,4,4,2,1,2,1,1,1,5,1,4,1,1,4,4,5,4,4,1,1,1,4,4,5,1,1,5,1,2,4,1,4,4,1,4,2
-40,73323,2,2,5,5,3,4,2,3,5,5,1,5,4,5,4,2,5,5,4,4,4,1,3,3,1,4,2,5,1,5,5,1,4,4,2,5,1,5,4,4,2,4,5,4,5,3,5,2,5,3,5,5,5,1,4,5,5,4,2,4,4,5,4,4,5
-30,75339,4,3,3,4,3,4,2,4,2,3,3,2,3,4,3,3,4,3,3,3,2,1,1,3,2,3,2,4,2,3,4,2,1,2,3,4,3,5,2,3,2,3,2,1,4,3,4,3,2,2,2,3,4,2,3,4,5,2,3,2,3,3,2,3,3
-40,36303,4,2,3,5,1,4,4,4,3,4,1,2,4,5,3,5,5,5,4,5,4,1,3,1,4,3,2,4,1,4,5,3,1,1,1,4,1,5,1,5,1,1,5,2,4,1,4,1,4,1,1,4,5,1,2,1,2,2,4,2,1,4,1,4,3
-30,95318,2,4,5,5,1,5,1,3,1,2,1,1,4,4,1,5,2,1,4,4,4,1,1,1,4,3,1,5,1,1,5,1,4,1,4,1,1,5,3,5,1,1,5,1,4,1,4,1,1,1,1,4,5,1,4,2,2,1,1,1,4,2,1,2,1
-70,22474,4,5,5,5,5,4,1,1,5,5,5,1,5,5,5,2,2,4,1,1,1,2,4,4,5,4,2,4,3,5,4,2,4,2,2,5,2,5,5,4,5,2,2,4,5,4,5,2,5,1,5,2,5,5,4,5,5,4,5,2,4,4,2,4,1
-30,114526,4,1,4,5,1,1,2,5,3,2,1,1,2,5,1,3,5,2,4,5,4,1,1,1,2,5,1,5,1,2,5,1,1,1,1,1,1,5,1,5,1,1,5,1,5,1,5,1,1,1,2,4,5,1,1,5,1,1,5,1,3,4,1,4,1
-60,20707,4,5,5,4,5,5,2,2,5,5,5,4,5,4,5,3,4,4,4,5,4,2,2,5,5,4,4,4,4,5,2,2,5,5,5,4,4,5,4,4,5,3,5,4,5,2,5,4,5,2,5,5,4,4,2,5,5,1,4,5,3,4,4,5,1
-80,91062,5,1,2,1,2,5,1,5,4,5,2,1,3,1,4,2,5,4,2,2,2,4,1,4,2,4,3,1,2,4,4,2,1,4,2,3,4,2,2,4,2,4,4,2,4,4,4,1,4,2,4,2,5,4,4,5,3,4,2,4,2,4,4,4,2
-90,66916,2,3,4,4,3,4,4,3,4,5,4,4,2,5,5,3,4,5,3,4,4,5,3,4,2,5,4,4,2,4,4,3,4,4,5,4,4,3,5,3,5,2,4,4,5,5,4,4,4,5,5,4,5,5,3,5,5,4,4,3,5,5,4,5,4
-40,32420,5,2,4,5,1,1,5,4,1,5,1,1,5,1,5,4,5,1,5,5,4,1,2,1,1,5,2,5,1,1,4,1,1,2,2,1,1,2,1,4,1,1,5,1,2,1,5,1,1,2,1,4,4,1,3,1,1,1,5,1,5,2,1,2,2
-60,39139,4,5,4,3,5,3,1,3,3,5,5,3,5,5,1,3,5,1,2,3,4,3,1,2,5,5,2,5,1,4,4,2,3,5,2,2,4,5,5,3,1,2,4,3,5,4,5,1,1,1,2,2,5,1,3,5,5,2,3,2,3,5,2,5,2
-80,116704,4,4,5,4,4,4,2,4,2,5,1,5,4,5,4,4,5,1,4,5,4,1,3,4,2,5,3,2,1,5,4,1,1,1,2,5,3,5,5,5,4,3,2,2,5,5,5,1,5,5,4,5,5,1,5,5,5,5,4,4,5,5,4,5,5
-40,120990,3,1,2,5,4,3,4,5,1,1,3,2,1,5,1,2,4,2,4,2,2,1,2,1,1,5,2,5,1,2,2,2,1,1,3,2,4,4,1,2,1,3,5,1,5,1,3,1,1,2,2,2,3,1,4,3,2,4,2,1,3,3,1,3,1
-30,90410,4,1,4,5,1,2,2,5,1,1,1,1,1,1,1,4,5,4,4,5,2,1,1,1,4,4,2,5,1,2,5,2,1,2,1,4,1,5,1,5,1,2,4,1,4,1,4,2,4,3,4,4,4,1,3,4,2,4,4,4,1,2,2,1,1
-60,33165,5,1,4,5,1,5,1,4,3,5,5,1,4,5,4,3,3,3,3,3,4,1,4,2,1,4,1,3,1,1,3,3,2,5,5,5,1,5,4,5,3,3,4,2,5,3,5,3,3,3,5,3,3,1,5,5,3,3,3,3,3,5,3,5,3
-30,46564,3,1,4,5,1,3,4,5,2,1,1,2,1,5,3,4,5,1,3,5,2,1,3,1,2,3,3,3,1,2,5,2,1,2,1,1,1,5,1,5,1,1,3,1,2,1,5,3,1,2,3,2,4,1,3,4,5,1,3,1,3,4,1,3,3
-40,776,4,2,2,4,2,3,2,4,2,2,2,2,1,5,2,4,5,2,4,5,2,1,1,1,2,5,1,5,1,2,4,4,1,1,1,4,2,4,1,1,1,1,4,1,4,1,5,1,4,4,4,4,5,1,4,5,2,4,4,1,2,4,2,4,2
-50,40297,2,2,3,4,2,4,3,5,1,2,1,3,1,5,2,2,5,2,5,5,4,2,2,1,4,3,3,2,1,4,5,3,3,4,2,4,2,4,3,5,4,2,5,1,5,1,5,1,2,1,4,5,5,1,5,5,4,4,3,1,4,4,4,2,3
-30,100157,5,1,5,2,1,1,1,5,4,5,1,1,4,5,1,4,5,1,4,5,4,1,1,1,4,5,1,5,1,1,4,1,1,1,1,2,1,5,5,4,1,1,4,1,4,4,5,1,1,1,4,5,5,1,4,5,1,1,5,1,5,5,1,4,2
-70,102688,3,1,4,4,4,5,1,3,4,5,5,5,5,4,5,3,5,5,4,5,5,5,4,5,5,5,5,5,5,5,5,4,5,5,5,5,5,5,5,5,5,5,5,4,5,5,5,5,5,3,5,3,5,5,5,5,5,5,5,5,5,5,5,5,5
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+70,101097,1,3,1,1,1,1,2,3,3,1,1,3,2,2,1,3,1,2,2,2,3,2,1,4,5,5,5,5,1,3,2,1,5,4,3,5,5,5,5,5,5,5,5,5,5,4,5,3,4,5,5,5,5,5,3,5,5,5,5,5,3,5,5,5,5
+40,110254,4,5,5,4,5,3,2,3,4,5,3,2,1,5,2,3,5,2,3,5,2,2,2,4,4,4,2,3,2,4,1,2,1,4,4,5,2,5,3,4,2,3,2,4,5,1,5,3,2,4,5,3,4,2,5,2,5,2,3,4,2,4,4,4,2
diff --git a/data/sisters_select.csv b/data/sisters_select.csv
index e67d414..f03bb98 100644
--- a/data/sisters_select.csv
+++ b/data/sisters_select.csv
@@ -1,1929 +1,1929 @@
 age,sister,v116,v117,v118,v119,v120,v121,v122,v123,v124,v125,v126,v127,v128,v129,v130,v131,v132,v133,v134,v135,v136,v137,v138,v139,v140,v141,v142,v143,v144,v145,v146,v147,v148,v149,v150,v151,v152,v153,v154,v155,v156,v157,v158,v159,v160,v161,v162,v163,v164,v165,v166,v167,v168,v169,v170,v171,v172,v173,v174,v175,v176,v177,v178,v179,v180
-30,13737,5,3,5,3,3,2,1,3,4,2,2,5,5,4,2,3,3,2,3,4,2,1,1,1,3,5,1,5,1,3,4,1,1,3,2,3,1,5,1,5,3,2,2,1,5,2,3,1,2,2,3,1,5,1,4,4,5,1,1,1,1,2,2,2,1
-60,81619,5,1,5,4,1,1,3,1,1,4,1,1,4,1,4,2,4,4,4,2,4,4,3,4,1,3,1,5,1,4,5,1,2,4,1,4,4,5,2,5,4,4,2,4,5,4,3,4,5,3,5,1,5,5,4,5,5,5,3,4,4,5,4,4,4
-50,80234,4,2,1,4,2,1,1,4,2,1,1,1,1,1,1,2,4,2,4,4,2,1,1,1,1,5,1,4,1,1,2,1,1,2,1,1,1,5,1,2,1,1,5,1,2,1,5,1,1,1,1,2,5,1,3,1,1,1,3,2,2,1,1,4,1
-40,81746,5,2,5,4,4,5,3,2,4,2,2,4,5,5,3,5,4,2,4,5,4,1,1,1,2,5,3,5,1,5,5,2,1,2,3,4,1,5,3,5,1,1,2,4,5,1,3,2,1,2,2,2,5,1,3,3,1,1,3,2,2,4,1,2,4
-30,113074,4,4,5,4,2,5,1,2,3,4,3,1,4,1,4,3,4,4,2,4,5,2,1,4,4,4,4,4,1,4,4,2,1,4,5,3,2,2,3,4,1,4,4,3,5,3,5,4,2,3,4,4,5,1,3,5,5,1,4,2,3,5,5,5,4
-50,83873,4,1,5,4,1,1,3,5,1,2,1,4,2,5,1,2,4,1,4,5,1,1,1,1,2,5,1,4,1,1,5,1,1,2,1,2,1,5,1,5,1,1,5,1,4,1,4,1,1,1,1,4,4,4,4,1,1,4,5,1,1,5,1,1,4
-30,1126,5,2,4,4,4,4,2,4,2,2,1,4,2,2,1,4,4,2,4,5,2,2,1,1,1,5,2,4,2,2,2,2,1,2,1,2,2,5,1,5,1,1,5,2,4,1,5,1,2,2,2,2,4,1,2,4,4,1,2,2,3,2,1,2,1
-50,28376,5,1,2,4,1,1,2,5,1,5,4,1,4,5,4,4,5,4,4,5,1,1,1,2,4,5,1,5,2,5,5,1,1,2,5,5,5,5,5,5,1,1,3,2,5,1,5,2,1,1,2,4,5,4,1,5,2,2,1,1,4,4,1,4,1
-30,87187,2,2,4,2,2,3,2,3,3,1,2,2,2,3,4,4,4,3,2,3,3,2,1,2,4,3,4,3,1,2,4,3,1,2,2,3,1,5,1,3,1,3,3,4,5,3,3,1,3,2,4,3,4,2,2,4,3,2,3,4,3,4,3,4,3
-50,67908,4,4,5,5,5,3,1,3,4,2,4,2,3,3,1,3,1,4,3,3,2,2,1,1,4,5,3,5,1,3,5,1,1,2,3,4,3,5,2,5,1,4,5,4,5,1,5,2,2,3,5,2,5,4,2,3,4,1,3,4,1,2,5,2,1
-70,90680,4,4,5,4,5,3,1,4,5,5,3,5,3,3,4,3,5,2,3,4,5,2,3,4,4,3,4,3,2,5,2,4,2,4,4,5,3,4,3,5,4,3,3,4,4,2,5,1,1,3,5,3,4,2,4,5,4,1,3,4,3,5,4,3,3
-40,72156,3,2,4,5,2,2,4,3,2,5,5,1,2,3,2,2,3,3,1,3,1,2,2,3,4,4,3,2,2,4,2,1,2,3,2,4,4,5,3,4,2,3,2,5,5,2,3,1,3,3,1,3,4,2,2,3,4,2,3,4,2,5,4,4,4
-60,35124,4,1,4,5,1,4,3,5,3,5,2,4,1,5,2,4,5,1,5,5,1,1,1,1,1,5,3,5,1,4,5,1,2,4,1,5,1,5,5,5,1,1,4,1,5,1,5,1,5,1,5,5,5,1,5,5,2,5,5,2,4,4,3,5,1
-40,121419,5,3,4,5,4,3,1,3,3,5,3,3,2,3,2,3,3,1,2,3,3,3,1,1,4,3,3,4,3,4,4,4,2,3,2,3,5,5,4,5,3,3,4,3,5,3,3,3,3,3,4,1,5,5,3,4,5,3,3,4,3,3,3,3,4
-40,36457,4,1,3,4,1,3,4,4,2,1,1,1,4,5,4,4,3,3,4,3,4,1,1,1,1,5,4,5,2,5,1,2,5,4,1,4,1,5,1,5,1,1,4,1,5,1,4,1,1,2,3,4,3,1,4,1,5,3,4,2,2,1,3,2,1
-30,109594,2,1,2,1,2,4,3,5,3,4,1,1,1,5,4,5,5,4,5,5,4,2,1,1,4,5,1,5,1,2,5,1,1,4,1,2,1,5,2,1,1,1,5,3,5,3,5,1,1,3,2,4,2,2,5,3,1,5,5,1,2,1,2,1,1
-60,35590,5,3,4,4,1,1,2,3,4,5,3,5,5,5,3,4,3,3,5,4,2,2,3,1,5,4,1,5,2,2,5,3,2,4,2,3,3,5,3,5,5,5,3,2,4,1,3,1,1,1,1,5,5,1,4,5,2,3,3,5,4,4,4,4,2
-50,32807,5,1,4,5,1,1,1,5,5,2,1,1,4,5,4,2,5,1,4,1,5,5,1,1,4,5,5,5,1,4,5,1,1,4,1,4,1,5,1,5,1,4,4,5,5,1,5,1,4,1,2,5,5,1,4,4,1,1,1,1,1,5,5,4,1
-50,22572,4,4,4,5,4,2,3,3,4,4,2,4,2,5,4,3,1,5,3,5,4,1,2,2,3,3,2,2,1,3,5,1,1,3,4,4,4,4,4,3,1,4,5,3,5,3,5,5,2,2,4,4,5,2,4,5,3,2,3,4,2,3,5,4,3
-20,28329,4,2,1,4,4,4,2,3,1,5,1,1,1,4,1,2,2,1,4,4,1,2,1,1,4,5,1,4,1,2,4,1,1,2,1,4,2,5,1,2,1,1,1,1,5,1,4,1,2,1,2,4,3,2,1,2,1,1,4,2,3,2,1,4,4
-70,39944,4,1,5,2,2,2,1,5,4,4,2,2,4,2,4,2,1,4,3,1,1,2,1,2,4,5,1,1,1,5,4,1,2,5,5,5,2,1,4,4,4,2,2,1,5,5,4,2,5,1,5,1,5,1,2,5,5,4,1,5,2,5,5,5,3
-80,37744,5,3,5,3,5,5,2,3,5,5,5,5,4,5,5,1,4,3,3,4,4,5,3,5,4,5,3,5,3,4,5,4,5,5,3,5,5,5,3,5,3,5,5,5,5,5,5,3,3,1,5,3,5,5,5,5,5,5,3,5,3,4,5,5,5
-50,19248,4,1,3,1,4,1,2,1,3,5,3,2,4,5,4,3,5,2,3,5,4,2,2,1,3,3,4,5,1,4,4,3,2,2,2,2,2,3,2,1,2,1,2,1,1,2,3,2,1,2,3,4,4,1,3,2,2,1,3,2,5,5,2,3,2
-50,4766,2,5,5,5,5,3,1,2,1,2,3,1,3,5,4,3,5,3,5,5,1,1,1,1,3,5,1,4,1,4,2,2,1,1,2,3,3,5,1,3,1,3,5,4,5,3,5,1,1,1,4,4,5,1,4,5,2,4,3,2,3,5,4,4,4
-30,26602,2,2,4,4,1,3,3,5,4,1,1,3,1,4,4,2,4,4,4,4,5,1,1,1,1,5,3,1,2,2,4,2,1,1,2,5,1,5,3,2,1,1,5,1,4,2,4,2,2,1,4,3,3,5,4,4,2,2,4,1,2,4,2,3,1
-50,105890,5,4,5,4,5,1,1,3,3,4,4,5,4,4,2,1,5,5,3,2,4,2,1,3,4,5,1,5,2,4,4,2,2,1,4,4,4,5,3,5,1,2,1,4,5,3,4,3,4,1,4,1,2,1,1,5,4,3,3,3,4,5,3,5,5
-40,69418,3,3,3,2,5,1,1,1,2,5,1,1,1,5,1,1,2,5,5,1,1,5,3,5,1,3,1,5,5,4,4,3,3,4,4,5,4,1,5,4,4,5,4,5,5,4,4,4,5,4,5,4,5,4,4,5,4,4,4,4,3,5,5,4,4
-70,120351,4,2,3,4,5,5,2,5,4,2,4,1,4,5,2,2,5,2,3,5,1,1,2,2,2,4,1,5,1,5,5,1,3,4,1,3,1,5,5,5,3,2,4,4,5,2,5,1,2,1,3,5,5,1,4,5,2,2,4,1,5,4,5,5,2
-40,108826,5,4,4,4,2,1,4,5,1,4,1,4,5,5,1,4,5,1,4,4,1,1,1,1,4,5,2,5,1,1,5,2,1,4,1,4,1,4,1,4,1,1,4,1,4,1,4,1,1,1,4,4,4,1,4,5,5,1,4,4,4,4,1,2,2
-40,5485,1,3,4,5,1,4,4,5,1,5,1,3,2,1,2,3,5,4,1,5,1,1,1,1,4,5,3,4,2,2,5,3,1,2,2,3,1,2,1,5,3,3,5,1,5,3,5,1,4,3,2,2,5,2,3,3,5,3,4,1,1,2,5,3,3
-70,59433,2,1,3,3,3,3,3,5,3,5,1,3,3,1,1,3,5,4,4,4,3,2,3,2,1,3,2,4,2,3,4,2,3,3,3,4,1,5,3,4,3,4,3,3,5,3,4,2,1,1,4,3,5,3,3,4,4,4,3,3,3,4,2,4,4
-60,32616,5,1,5,5,1,5,1,4,4,5,5,4,3,5,3,3,4,2,3,2,2,2,3,5,3,4,4,4,2,4,3,2,2,4,2,5,5,5,4,4,3,4,4,5,5,5,5,5,5,3,5,3,4,5,4,5,4,5,3,4,5,4,5,5,4
-70,37999,3,2,1,5,3,1,3,1,2,1,1,3,2,1,4,3,2,3,3,3,4,4,1,4,3,4,3,3,1,5,3,1,3,3,3,5,3,3,4,3,3,3,3,1,5,3,3,3,4,1,5,3,3,5,4,5,5,5,5,4,1,5,5,5,1
-70,67000,4,4,4,4,4,4,4,2,4,4,4,4,4,4,4,4,4,2,3,2,3,2,4,4,4,4,2,4,2,4,4,4,2,3,2,4,4,4,2,4,3,2,3,4,4,4,4,1,4,1,4,1,4,1,4,4,5,3,4,2,3,3,4,2,3
-30,21961,2,1,4,4,2,1,2,5,1,4,1,1,1,1,1,4,2,1,1,4,4,2,1,1,3,5,1,5,1,5,2,2,1,2,2,4,4,5,4,5,2,1,1,4,5,4,4,3,5,3,5,1,4,5,5,5,2,3,2,5,4,5,2,3,3
-70,99326,5,5,5,5,5,5,4,3,4,5,5,4,5,5,5,4,5,5,4,4,1,4,3,5,4,5,2,5,2,5,5,4,4,4,5,4,3,5,3,5,4,3,5,5,5,4,3,3,5,1,5,5,5,5,4,5,5,4,3,2,4,5,5,5,3
-30,24294,4,1,2,5,1,2,2,5,2,4,2,4,2,1,1,4,5,1,4,5,4,1,2,1,2,4,4,1,1,4,4,2,1,2,2,2,1,5,1,5,1,1,4,1,4,2,5,1,4,4,5,2,4,1,4,2,2,4,4,2,2,4,2,2,4
-60,31769,4,2,5,5,1,3,1,4,3,5,4,4,3,3,2,3,5,5,3,2,4,2,3,2,5,4,4,5,1,2,4,3,4,4,2,3,2,4,5,4,1,3,4,3,4,2,3,2,1,1,3,3,1,1,3,5,5,1,1,1,5,5,2,5,2
-30,129488,2,1,3,4,2,4,3,4,2,5,4,2,2,3,2,2,3,1,3,3,1,3,3,3,3,3,1,4,1,2,3,2,1,5,3,3,4,5,1,1,1,3,3,3,5,3,4,4,2,1,4,4,5,1,3,3,3,3,3,4,3,5,4,3,3
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-40,81508,5,4,5,5,3,4,1,3,3,5,2,4,2,4,4,3,5,4,3,4,4,1,1,2,5,5,3,5,1,4,5,1,1,3,5,4,1,1,1,5,4,2,4,1,2,2,5,2,4,1,5,2,3,1,4,5,2,3,3,2,4,1,4,1,3
-40,41760,2,2,3,5,1,1,4,5,1,1,1,1,1,5,1,4,5,1,5,5,4,1,1,1,1,5,4,1,1,1,4,5,1,2,1,2,1,5,1,5,1,1,4,2,4,3,1,1,1,4,3,3,2,1,5,2,2,4,5,1,4,4,2,4,4
-40,66106,2,1,4,4,4,3,4,5,2,4,2,1,2,5,4,2,4,2,2,4,3,1,1,2,4,5,3,5,1,2,5,2,1,2,4,4,4,4,2,2,2,1,5,3,5,1,4,1,4,1,4,1,4,2,4,5,4,2,3,4,2,4,4,1,1
-30,88542,5,1,4,3,3,3,2,5,4,5,1,3,5,5,3,3,3,4,5,5,4,3,1,1,4,3,4,3,3,3,3,2,1,4,3,4,4,4,3,5,1,1,4,4,5,3,1,1,4,1,5,5,5,1,5,5,4,4,5,2,4,3,3,4,4
-40,63351,2,1,4,4,1,1,1,5,2,3,1,4,2,1,1,4,2,2,3,4,1,1,1,1,4,5,4,2,1,1,5,1,1,4,4,1,1,5,1,5,1,1,5,1,3,3,1,1,4,1,1,2,3,2,4,5,1,3,1,1,4,3,1,5,1
-30,29820,4,1,4,4,1,3,1,5,4,2,1,1,1,5,1,3,5,2,2,5,1,1,1,1,4,5,4,4,1,1,5,2,1,1,4,4,1,5,4,5,1,1,3,2,5,1,5,2,1,1,3,4,3,1,4,3,1,1,4,1,3,4,2,3,1
-70,100038,5,5,5,4,4,5,2,2,5,5,5,4,5,3,5,2,5,5,4,4,1,3,2,5,5,4,4,5,2,5,5,1,2,5,2,2,5,5,5,5,4,5,4,5,5,5,1,2,5,1,5,5,5,4,3,4,5,4,4,2,5,5,5,5,5
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+40,57369,1,2,2,4,5,4,1,5,1,5,1,1,1,1,1,2,5,1,1,4,1,1,1,1,1,5,1,4,1,2,5,1,1,2,1,2,1,5,1,5,1,1,1,1,5,1,4,1,1,1,1,4,5,1,1,5,5,1,1,1,4,4,4,4,2
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+60,75849,5,1,5,5,1,3,1,5,2,1,1,2,2,5,1,5,5,2,5,5,1,1,4,1,4,2,1,5,1,5,5,4,1,2,3,5,1,5,1,5,1,5,5,1,4,1,5,1,1,1,5,5,5,2,1,5,5,1,5,5,5,5,5,5,1
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+80,101865,5,1,5,5,1,5,1,5,4,5,5,5,5,5,2,4,5,2,5,4,2,2,3,4,5,5,2,5,1,5,4,2,1,5,5,4,2,5,5,5,2,4,5,2,5,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,4
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+50,52662,5,2,4,5,1,1,1,5,4,2,1,2,4,5,5,2,5,4,2,4,2,2,3,1,1,5,1,2,1,2,2,3,2,2,1,4,1,5,1,5,2,1,4,1,2,1,4,1,1,1,4,4,4,1,4,5,1,4,4,1,5,5,1,5,5
+50,76092,5,1,3,5,1,1,2,5,1,5,1,1,5,5,1,2,5,2,5,5,1,1,1,1,1,5,1,5,1,4,5,1,1,2,3,2,1,4,2,2,2,1,4,1,2,2,5,1,1,1,2,4,5,2,4,5,5,1,2,2,1,2,1,5,1
+70,5970,5,2,4,2,5,4,1,4,4,2,2,3,4,5,4,1,1,4,1,5,4,3,3,2,2,4,2,5,2,5,1,2,2,4,2,5,3,5,5,5,1,4,3,4,5,4,5,1,1,1,4,4,5,2,4,5,5,4,4,2,5,5,4,5,5
+60,117958,5,5,4,2,5,5,1,2,5,5,4,4,5,2,5,2,1,4,2,1,3,5,5,4,2,2,3,4,2,5,2,3,1,4,4,5,4,4,5,4,2,2,3,5,5,5,4,2,2,1,5,4,2,5,3,5,1,2,1,2,5,5,4,5,5
+60,45817,5,3,5,4,4,5,3,2,4,5,4,4,2,4,5,3,3,5,3,3,4,2,4,5,4,3,1,3,1,5,2,2,4,4,5,4,4,2,5,3,5,3,4,3,5,4,3,4,2,3,4,3,3,4,3,1,4,3,5,5,4,5,1,5,3
+30,70894,4,1,1,4,1,4,4,5,4,5,1,1,1,5,4,4,5,3,5,5,3,2,1,1,1,5,1,4,1,4,4,3,1,4,1,4,5,5,1,4,1,3,4,1,5,4,5,1,4,1,4,3,3,2,4,3,4,3,5,2,1,4,4,3,1
+30,535,3,1,4,5,1,2,2,5,2,4,2,4,3,5,2,4,5,2,4,4,3,1,2,2,4,4,3,4,1,2,5,2,3,4,3,2,4,4,2,3,3,3,4,2,5,4,5,2,2,1,4,3,5,3,5,5,3,4,2,1,3,5,2,5,3
+40,851,1,4,3,4,3,3,2,2,2,4,3,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,1,3,3,4,2,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,3,1,4,4,3,4,4,4
+30,7918,5,1,3,5,1,2,4,5,1,1,1,4,4,5,1,2,5,4,5,5,1,1,1,1,4,5,1,5,1,4,5,1,1,1,1,2,1,5,1,4,1,1,5,1,3,1,4,1,4,5,1,4,4,1,5,4,1,1,4,1,1,1,1,2,1
+30,75804,5,2,5,4,4,1,1,5,4,5,4,4,5,4,5,4,5,4,4,2,1,3,1,4,5,2,1,4,1,5,3,2,4,5,4,5,1,5,1,5,4,2,2,5,5,4,2,5,1,1,5,2,4,1,3,5,5,1,5,5,5,5,5,5,2
+40,48529,5,2,3,4,2,2,3,3,2,4,1,1,2,5,2,4,5,3,5,5,2,1,1,2,2,4,1,2,2,2,5,2,1,1,1,1,1,5,2,4,2,1,4,1,5,1,5,1,2,1,2,5,5,1,5,5,5,4,3,2,1,4,2,1,2
+30,52125,4,1,4,5,3,1,3,5,1,1,1,1,5,5,1,5,5,1,5,5,1,1,1,1,1,5,3,1,1,4,2,1,1,1,2,2,1,5,1,5,1,1,3,1,5,1,5,1,1,1,1,5,5,1,5,5,1,1,5,1,3,4,1,3,3
+50,35809,5,3,4,4,1,2,2,3,1,4,1,2,2,5,2,4,3,2,2,3,1,1,3,2,4,3,1,4,2,2,3,3,5,2,2,4,3,4,2,4,2,2,2,3,5,1,4,2,3,1,4,2,3,2,3,3,4,1,3,2,2,2,3,2,1
+30,49862,4,3,3,4,4,1,2,4,1,4,1,2,2,4,2,4,5,4,1,2,1,1,1,1,2,4,3,4,1,2,5,2,1,2,2,5,5,5,1,5,2,1,4,2,4,4,4,2,4,2,1,4,5,1,4,4,4,1,1,1,4,4,2,2,2
+30,35002,4,2,5,5,1,3,4,5,4,2,1,4,3,5,3,4,4,2,4,5,1,1,1,1,2,5,1,2,1,1,5,1,1,1,2,1,1,5,1,5,1,1,4,1,4,1,4,1,2,2,2,3,4,1,4,1,1,1,4,1,2,3,2,3,2
+40,77661,4,1,3,5,2,3,2,5,2,2,1,1,4,5,3,4,5,3,3,5,2,1,3,1,4,3,3,4,3,2,4,3,1,2,1,2,1,5,1,5,1,1,3,3,3,2,4,1,1,1,3,5,4,1,4,1,3,3,4,2,1,2,2,3,1
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+40,19297,5,2,4,4,3,3,1,5,2,2,1,4,5,5,4,2,4,2,1,5,2,5,1,1,4,5,4,5,1,4,4,2,4,5,1,2,4,5,2,4,2,1,2,2,5,4,4,1,1,1,4,4,4,2,1,2,4,1,2,4,5,4,3,4,4
+70,61000,4,4,5,5,4,5,4,2,4,4,4,5,5,4,5,4,4,4,5,2,4,5,5,4,4,4,4,5,2,5,4,4,2,2,4,5,4,4,5,4,4,5,5,4,4,5,5,2,2,2,5,4,5,5,5,5,4,4,5,5,4,5,5,5,4
+50,29106,4,1,1,4,1,1,2,5,1,2,1,1,1,5,2,2,5,1,4,5,2,1,1,1,1,4,1,5,1,2,5,2,1,1,1,1,1,5,1,2,1,1,4,1,5,1,5,1,1,1,4,4,4,1,4,4,1,4,4,1,4,4,4,4,4
+40,70018,3,1,5,4,2,1,3,4,5,5,5,2,1,2,1,3,2,3,5,3,1,1,1,3,3,5,3,1,1,4,2,3,1,3,3,5,5,5,3,5,1,1,1,3,3,2,5,3,1,3,5,4,4,2,3,5,5,3,4,1,1,5,5,5,3
diff --git a/data/stack_glm.rds b/data/stack_glm.rds
index 171c4c5..5a14b26 100644
Binary files a/data/stack_glm.rds and b/data/stack_glm.rds differ
diff --git a/data/stackoverflow.csv b/data/stack_overflow.csv
similarity index 58%
rename from data/stackoverflow.csv
rename to data/stack_overflow.csv
index bfcf452..7203aa4 100644
--- a/data/stackoverflow.csv
+++ b/data/stack_overflow.csv
@@ -1,648 +1,648 @@
-Respondent,Country,Salary,YearsCodedJob,OpenSource,Hobby,CompanySizeNumber,Remote,CareerSatisfaction,Data scientist,Database administrator,Desktop applications developer,Developer with stats/math background,DevOps,Embedded developer,Graphic designer,Graphics programming,Machine learning specialist,Mobile developer,Quality assurance engineer,Systems administrator,Web developer
-3,United Kingdom,113750,20,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-15,United Kingdom,1e5,20,FALSE,TRUE,5e3,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-18,United States,13e4,20,TRUE,TRUE,1e3,Remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-19,United States,82500,3,FALSE,TRUE,1e4,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-26,United States,175e3,16,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-55,Germany,64516.1290322581,4,FALSE,FALSE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-62,India,6636.32359418588,1,FALSE,TRUE,5e3,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-71,United States,65e3,1,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-73,United States,12e4,20,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-77,United States,96283,20,TRUE,TRUE,1e3,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-82,United States,11e4,13,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-96,Germany,53763.4408602151,4,TRUE,FALSE,5e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+respondent,country,salary,years_coded_job,open_source,hobby,company_size_number,remote,career_satisfaction,data_scientist,database_administrator,desktop_applications_developer,developer_with_stats_math_background,dev_ops,embedded_developer,graphic_designer,graphics_programming,machine_learning_specialist,mobile_developer,quality_assurance_engineer,systems_administrator,web_developer
+3,United Kingdom,113750,20,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+15,United Kingdom,100000,20,FALSE,TRUE,5000,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+18,United States,130000,20,TRUE,TRUE,1000,Remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+19,United States,82500,3,FALSE,TRUE,10000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+26,United States,175000,16,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+55,Germany,64516.1290322581,4,FALSE,FALSE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+62,India,6636.32359418588,1,FALSE,TRUE,5000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+71,United States,65000,1,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+73,United States,120000,20,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+77,United States,96283,20,TRUE,TRUE,1000,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+82,United States,110000,13,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+96,Germany,53763.4408602151,4,TRUE,FALSE,5000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 100,United States,109400,7,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 103,Germany,83870.9677419355,17,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-104,United States,51e3,1,FALSE,FALSE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+104,United States,51000,1,FALSE,FALSE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 111,United Kingdom,32500,1,TRUE,FALSE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-114,United Kingdom,3e4,1,FALSE,TRUE,20,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-116,United States,9e4,10,TRUE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-124,United States,115e3,4,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-126,United States,93e3,9,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+114,United Kingdom,30000,1,FALSE,TRUE,20,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+116,United States,90000,10,TRUE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+124,United States,115000,4,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+126,United States,93000,9,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
 135,United States,92500,14,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 136,United Kingdom,32500,2,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 144,United Kingdom,43750,1,TRUE,TRUE,1,Not remote,5,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
 150,United Kingdom,113750,20,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-157,United States,8e4,5,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+157,United States,80000,5,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 158,United States,100297,15,FALSE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-170,United States,1e5,14,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-178,United States,12e4,4,FALSE,TRUE,20,Not remote,10,FALSE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+170,United States,100000,14,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+178,United States,120000,4,FALSE,TRUE,20,Not remote,10,FALSE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
 183,United Kingdom,131250,14,FALSE,FALSE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
-184,India,6606.95933049479,1,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+184,India,6606.95933049479,1,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 192,Germany,10752.688172043,1,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 193,Canada,87121.2121212121,10,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-196,United States,66e3,7,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-199,United States,146e3,15,TRUE,TRUE,1e4,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE
+196,United States,66000,7,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+199,United States,146000,15,TRUE,TRUE,10000,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE
 207,Canada,62121.2121212121,9,FALSE,FALSE,20,Not remote,6,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-210,Canada,54545.4545454545,8,FALSE,FALSE,1e3,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-215,Germany,51612.9032258064,4,TRUE,FALSE,5e3,Not remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-217,United States,5e4,15,TRUE,TRUE,1,Remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-220,United States,5e4,2,TRUE,TRUE,10,Not remote,4,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-221,United States,185e3,20,TRUE,FALSE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-224,United States,16e4,11,TRUE,TRUE,500,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-235,United States,63e3,6,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-236,United States,67e3,6,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-238,United States,8e4,5,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-239,United States,103e3,15,TRUE,TRUE,500,Remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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 1215,United Kingdom,51250,20,FALSE,FALSE,20,Not remote,6,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 1216,Canada,54545.4545454545,7,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-1412,Canada,5e4,10,FALSE,TRUE,20,Not remote,6,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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 1506,United Kingdom,56250,7,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-1511,United States,8e4,2,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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+1652,United Kingdom,65312.5,14,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-1811,United Kingdom,6e4,20,TRUE,FALSE,100,Not remote,4,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-1817,United States,89e3,12,FALSE,FALSE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-1828,United States,108e3,5,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-1833,United States,136e3,17,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-1838,United States,71e3,16,FALSE,TRUE,100,Not remote,6,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-1840,United States,115e3,8,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-1855,United States,12e4,9,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-1863,United Kingdom,5e4,7,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-1865,United Kingdom,112500,20,TRUE,FALSE,1e4,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-1879,United States,86e3,14,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-1884,United States,129e3,1,FALSE,FALSE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-1887,United States,62e3,5,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-1890,United States,14e4,6,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+1879,United States,86000,14,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+1884,United States,129000,1,FALSE,FALSE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+1887,United States,62000,5,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+1890,United States,140000,6,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-1899,United States,6e4,5,FALSE,FALSE,1,Not remote,6,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
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+1910,United States,128000,16,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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-1940,United States,45e3,1,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-1954,United States,5e4,5,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-1969,United States,75e3,1,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 2188,Canada,87121.2121212121,8,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 2200,Canada,73484.8484848485,10,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 2203,Canada,46212.1212121212,3,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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 2286,Canada,68181.8181818182,12,FALSE,FALSE,10,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 2293,Canada,78030.303030303,9,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-2296,United States,66e3,3,FALSE,TRUE,5e3,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 2306,Germany,64516.1290322581,9,FALSE,FALSE,100,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-2319,United States,12e4,4,FALSE,FALSE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-2324,United States,85e3,3,FALSE,FALSE,1e3,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-2365,United States,156e3,4,TRUE,TRUE,1e4,Not remote,7,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-2371,United States,192e3,14,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+2349,United States,163000,9,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-2383,United States,1e5,6,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 2406,United States,45600,1,TRUE,TRUE,10,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 2466,United Kingdom,32500,4,TRUE,TRUE,100,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 2468,Canada,53030.303030303,5,FALSE,TRUE,10,Not remote,8,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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 2473,Canada,39772.7272727273,1,FALSE,TRUE,20,Not remote,10,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-2500,United States,12e4,3,FALSE,FALSE,100,Not remote,8,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-2504,United States,73e3,4,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-2514,United States,105e3,2,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-2518,United States,7e4,3,FALSE,TRUE,1e4,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-2520,United States,75e3,8,TRUE,TRUE,100,Not remote,7,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-2525,United States,82e3,2,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-2529,United States,93500,5,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-2530,United States,7e4,1,TRUE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-2531,United States,104e3,4,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-2538,United States,115e3,7,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-2595,United States,8e4,4,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-2605,United States,18e4,20,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE
-2608,United States,125e3,9,TRUE,TRUE,500,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-2611,United States,129e3,16,TRUE,TRUE,5e3,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-2623,United States,8e4,6,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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+2608,United States,125000,9,TRUE,TRUE,500,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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+2613,United States,125000,1,FALSE,TRUE,1000,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+2616,United States,100000,16,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 2631,United States,87500,2,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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@@ -651,1235 +651,1235 @@ Respondent,Country,Salary,YearsCodedJob,OpenSource,Hobby,CompanySizeNumber,Remot
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+4465,United Kingdom,50000,4,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
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-4494,United States,12e4,19,TRUE,TRUE,5e3,Not remote,9,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-4497,United Kingdom,45e3,19,FALSE,FALSE,1,Remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-4500,United Kingdom,41250,14,FALSE,FALSE,1e3,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-4520,Germany,26881.7204301075,6,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-4527,India,5872.85273821759,1,FALSE,FALSE,1e4,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-4533,United States,78e3,6,TRUE,TRUE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+4494,United States,120000,19,TRUE,TRUE,5000,Not remote,9,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+4497,United Kingdom,45000,19,FALSE,FALSE,1,Remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+4500,United Kingdom,41250,14,FALSE,FALSE,1000,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+4520,Germany,26881.7204301075,6,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+4527,India,5872.85273821759,1,FALSE,FALSE,10000,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+4533,United States,78000,6,TRUE,TRUE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 4550,India,4404.63955366319,2,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-4551,United Kingdom,7e4,11,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-4553,United Kingdom,72500,6,FALSE,FALSE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+4551,United Kingdom,70000,11,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+4553,United Kingdom,72500,6,FALSE,FALSE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 4554,United Kingdom,47500,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-4557,United States,95e3,18,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+4557,United States,95000,18,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-4568,Germany,68817.2043010753,15,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+4568,Germany,68817.2043010753,15,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 4579,India,3156.65834679195,3,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 4588,Germany,45161.2903225806,3,FALSE,TRUE,100,Not remote,7,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-4592,United States,1e5,7,FALSE,FALSE,1,Not remote,10,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+4592,United States,100000,7,FALSE,FALSE,1,Not remote,10,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
 4600,United States,97500,5,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE
 4609,India,9161.65027161944,3,TRUE,FALSE,500,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-4622,Germany,28817.2043010753,4,FALSE,FALSE,1e3,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-4627,United States,7e4,2,TRUE,TRUE,20,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-4641,United States,104e3,11,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-4645,United States,72e3,4,FALSE,TRUE,5e3,Remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+4622,Germany,28817.2043010753,4,FALSE,FALSE,1000,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+4627,United States,70000,2,TRUE,TRUE,20,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+4641,United States,104000,11,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+4645,United States,72000,4,FALSE,TRUE,5000,Remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 4649,Germany,21505.376344086,3,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-4662,United Kingdom,6e4,10,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+4662,United Kingdom,60000,10,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 4687,Canada,48484.8484848485,2,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 4688,United States,112500,17,FALSE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-4707,United Kingdom,1e5,20,FALSE,TRUE,100,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+4707,United Kingdom,100000,20,FALSE,TRUE,100,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 4709,United Kingdom,37500,2,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE
-4717,United States,9e4,2,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-4721,United States,65e3,4,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-4741,United States,125e3,14,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-4747,United States,14e4,10,FALSE,FALSE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+4717,United States,90000,2,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+4721,United States,65000,4,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+4741,United States,125000,14,TRUE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+4747,United States,140000,10,FALSE,FALSE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 4777,Canada,47348.4848484848,1,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 4788,United Kingdom,62500,7,TRUE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-4794,United States,48e3,2,TRUE,TRUE,5e3,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+4794,United States,48000,2,TRUE,TRUE,5000,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 4801,United States,90750,6,FALSE,TRUE,10,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-4802,United States,14e4,20,TRUE,TRUE,20,Remote,10,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
-4807,United States,74574,5,FALSE,TRUE,1e3,Not remote,5,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-4815,United Kingdom,31875,10,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+4802,United States,140000,20,TRUE,TRUE,20,Remote,10,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
+4807,United States,74574,5,FALSE,TRUE,1000,Not remote,5,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+4815,United Kingdom,31875,10,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 4826,United States,113300,7,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-4836,United States,109e3,20,FALSE,FALSE,5e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+4836,United States,109000,20,FALSE,FALSE,5000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 4840,Germany,64516.1290322581,13,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 4857,United States,81600,7,FALSE,FALSE,20,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-4859,United States,65e3,3,FALSE,FALSE,1e4,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
-4860,United States,133e3,10,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-4863,United States,111e3,16,FALSE,FALSE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+4859,United States,65000,3,FALSE,FALSE,10000,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
+4860,United States,133000,10,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+4863,United States,111000,16,FALSE,FALSE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 4866,United Kingdom,47500,1,TRUE,TRUE,1,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-4871,United States,9e4,2,FALSE,FALSE,1e4,Not remote,9,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
+4871,United States,90000,2,FALSE,FALSE,10000,Not remote,9,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
 4874,United Kingdom,76250,10,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 4877,India,8809.27910732638,3,FALSE,TRUE,20,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 4879,United Kingdom,52500,4,TRUE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 4887,Germany,5806.45161290323,1,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-4889,United States,155e3,20,FALSE,TRUE,500,Not remote,8,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-4893,United States,115e3,10,TRUE,TRUE,500,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-4896,United States,85e3,4,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+4889,United States,155000,20,FALSE,TRUE,500,Not remote,8,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+4893,United States,115000,10,TRUE,TRUE,500,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+4896,United States,85000,4,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 4898,India,8211.40638996715,1,TRUE,FALSE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-4901,United States,61e3,1,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-4907,United States,153e3,10,FALSE,TRUE,100,Not remote,10,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+4901,United States,61000,1,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+4907,United States,153000,10,FALSE,TRUE,100,Not remote,10,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 4918,United Kingdom,47500,9,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 4919,Canada,36363.6363636364,1,FALSE,TRUE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 4930,Canada,60606.0606060606,11,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-4966,United States,12e4,15,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-4968,United States,85e3,4,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-4971,United States,95e3,14,FALSE,FALSE,1,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+4966,United States,120000,15,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+4968,United States,85000,4,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+4971,United States,95000,14,FALSE,FALSE,1,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-4985,United States,75e3,10,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-4989,Canada,83333.3333333333,12,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+4985,United States,75000,10,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+4989,Canada,83333.3333333333,12,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-4998,United States,155e3,18,FALSE,FALSE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5000,United States,75e3,2,FALSE,FALSE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+4998,United States,155000,18,FALSE,FALSE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5000,United States,75000,2,FALSE,FALSE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 5010,United Kingdom,57500,5,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5015,Canada,45454.5454545455,7,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-5026,United States,1e5,3,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5032,United States,135e3,18,FALSE,TRUE,5e3,Not remote,8,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5045,United States,7e4,8,FALSE,TRUE,100,Not remote,8,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+5015,Canada,45454.5454545455,7,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+5026,United States,100000,3,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5032,United States,135000,18,FALSE,TRUE,5000,Not remote,8,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5045,United States,70000,8,FALSE,TRUE,100,Not remote,8,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 5046,United Kingdom,56250,5,FALSE,FALSE,100,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5059,United States,104e3,8,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5059,United States,104000,8,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 5068,Canada,39393.9393939394,1,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-5090,United Kingdom,75e3,9,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5094,India,8809.27910732638,1,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-5098,United States,9e4,6,FALSE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5100,Germany,63978.4946236559,4,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
-5105,United States,6e4,3,FALSE,FALSE,1e3,Not remote,5,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-5111,United States,1e5,3,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-5128,United States,103e3,20,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-5136,United States,85e3,19,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5141,United States,101e3,8,TRUE,FALSE,500,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5143,United Kingdom,65e3,11,TRUE,TRUE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE
-5159,United Kingdom,58125,5,FALSE,TRUE,5e3,Remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+5090,United Kingdom,75000,9,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5094,India,8809.27910732638,1,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+5098,United States,90000,6,FALSE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5100,Germany,63978.4946236559,4,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+5105,United States,60000,3,FALSE,FALSE,1000,Not remote,5,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+5111,United States,100000,3,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+5128,United States,103000,20,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+5136,United States,85000,19,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5141,United States,101000,8,TRUE,FALSE,500,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5143,United Kingdom,65000,11,TRUE,TRUE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE
+5159,United Kingdom,58125,5,FALSE,TRUE,5000,Remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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-5169,United States,53e3,3,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5170,Germany,86021.5053763441,10,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+5169,United States,53000,3,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5170,Germany,86021.5053763441,10,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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 5227,United Kingdom,32500,3,TRUE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-5229,United Kingdom,77500,17,TRUE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5229,United Kingdom,77500,17,TRUE,FALSE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 5264,Canada,41666.6666666667,4,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 5284,United Kingdom,47500,5,FALSE,TRUE,1,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-5286,United States,73e3,18,FALSE,TRUE,5e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5287,United States,74e3,17,TRUE,TRUE,1e4,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5308,United States,7e4,3,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5322,United States,96e3,6,TRUE,FALSE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5324,United States,11e4,10,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5327,United States,1e5,16,FALSE,FALSE,1e4,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5332,United States,11e4,10,FALSE,TRUE,5e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5333,United States,78e3,9,FALSE,FALSE,1e4,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+5286,United States,73000,18,FALSE,TRUE,5000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5287,United States,74000,17,TRUE,TRUE,10000,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5308,United States,70000,3,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5322,United States,96000,6,TRUE,FALSE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5324,United States,110000,10,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5327,United States,100000,16,FALSE,FALSE,10000,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5332,United States,110000,10,FALSE,TRUE,5000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5333,United States,78000,9,FALSE,FALSE,10000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 5334,Germany,25806.4516129032,2,TRUE,FALSE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
 5337,United Kingdom,32877.5,3,FALSE,FALSE,20,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-5353,United States,72e3,2,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5356,United States,8e4,16,FALSE,TRUE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5353,United States,72000,2,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5356,United States,80000,16,FALSE,TRUE,1000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 5357,Germany,53763.4408602151,9,FALSE,TRUE,10,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 5358,Canada,75757.5757575758,9,FALSE,TRUE,100,Not remote,8,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 5360,Canada,37878.7878787879,3,TRUE,TRUE,1,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
-5362,Canada,45454.5454545455,10,FALSE,FALSE,1e4,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-5372,United States,65e3,1,FALSE,TRUE,1,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-5373,United Kingdom,55e3,10,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-5383,United States,72e3,9,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5386,United States,16e4,7,FALSE,TRUE,100,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+5362,Canada,45454.5454545455,10,FALSE,FALSE,10000,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+5372,United States,65000,1,FALSE,TRUE,1,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+5373,United Kingdom,55000,10,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+5383,United States,72000,9,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5386,United States,160000,7,FALSE,TRUE,100,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 5391,United Kingdom,46875,5,FALSE,TRUE,1,Remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-5399,United Kingdom,45e3,16,TRUE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5399,United Kingdom,45000,16,TRUE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 5400,United Kingdom,81250,10,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5413,United States,12e4,7,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5414,United States,4e4,1,FALSE,FALSE,500,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+5413,United States,120000,7,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5414,United States,40000,1,FALSE,FALSE,500,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
 5417,Canada,49242.4242424242,5,FALSE,FALSE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5422,United States,9e4,7,FALSE,FALSE,100,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5431,United States,111500,2,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5434,United States,44e3,9,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5422,United States,90000,7,FALSE,FALSE,100,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5431,United States,111500,2,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5434,United States,44000,9,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 5444,United Kingdom,62500,16,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-5445,United States,85e3,8,TRUE,TRUE,10,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5445,United States,85000,8,TRUE,TRUE,10,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 5446,Canada,45454.5454545455,4,TRUE,TRUE,100,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-5449,United States,105e3,20,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5456,United States,7e4,17,FALSE,FALSE,1e4,Not remote,6,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5463,United Kingdom,43750,8,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+5449,United States,105000,20,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5456,United States,70000,17,FALSE,FALSE,10000,Not remote,6,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5463,United Kingdom,43750,8,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 5465,Germany,38709.6774193548,2,TRUE,FALSE,1,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 5480,United Kingdom,32500,4,FALSE,FALSE,20,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-5492,United States,8e4,3,FALSE,FALSE,1e4,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-5504,United Kingdom,1e5,9,TRUE,TRUE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-5507,United States,9e4,20,FALSE,FALSE,100,Remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5492,United States,80000,3,FALSE,FALSE,10000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+5504,United Kingdom,100000,9,TRUE,TRUE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+5507,United States,90000,20,FALSE,FALSE,100,Remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 5513,Canada,58333.3333333333,3,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 5518,Canada,79545.4545454545,3,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-5521,United Kingdom,5e4,14,TRUE,FALSE,1e4,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5525,United States,15e4,20,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-5541,United States,64e3,3,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5521,United Kingdom,50000,14,TRUE,FALSE,10000,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5525,United States,150000,20,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+5541,United States,64000,3,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 5547,Canada,30303.0303030303,3,FALSE,FALSE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5551,United States,6e4,2,FALSE,FALSE,500,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+5551,United States,60000,2,FALSE,FALSE,500,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 5552,United States,82500,3,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5553,United States,75e3,1,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-5559,United States,15e4,20,FALSE,TRUE,1,Remote,4,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-5560,United States,57e3,1,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+5553,United States,75000,1,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+5559,United States,150000,20,FALSE,TRUE,1,Remote,4,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+5560,United States,57000,1,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 5561,Canada,56818.1818181818,6,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 5565,Canada,53030.303030303,5,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5574,Canada,65e3,5,FALSE,FALSE,10,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-5579,United States,105e3,14,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5581,United Kingdom,2e4,1,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5574,Canada,65000,5,FALSE,FALSE,10,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+5579,United States,105000,14,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5581,United Kingdom,20000,1,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-5608,United States,72e3,1,FALSE,TRUE,1,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5610,United States,7e4,2,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-5612,United States,98e3,9,FALSE,FALSE,1e3,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5608,United States,72000,1,FALSE,TRUE,1,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5610,United States,70000,2,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+5612,United States,98000,9,FALSE,FALSE,1000,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 5615,India,13948.0252532668,5,FALSE,TRUE,100,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-5620,United States,73e3,7,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-5635,United States,89e3,17,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5620,United States,73000,7,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+5635,United States,89000,17,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 5642,United States,87350,11,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 5652,Germany,38709.6774193548,5,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5656,United States,7e4,1,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-5658,United States,65e3,4,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+5656,United States,70000,1,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+5658,United States,65000,4,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 5663,Germany,55913.9784946237,20,FALSE,FALSE,10,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 5664,Germany,83870.9677419355,8,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-5674,United States,89e3,20,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+5674,United States,89000,20,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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 5681,Germany,86021.5053763441,16,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 5684,United Kingdom,31500,2,FALSE,TRUE,100,Not remote,3,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
-5692,United Kingdom,53125,6,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5700,United States,11e4,6,TRUE,TRUE,1e3,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5706,United States,12e4,20,FALSE,TRUE,5e3,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-5708,United Kingdom,66250,10,TRUE,FALSE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5710,United States,118e3,9,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
+5692,United Kingdom,53125,6,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5700,United States,110000,6,TRUE,TRUE,1000,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5706,United States,120000,20,FALSE,TRUE,5000,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+5708,United Kingdom,66250,10,TRUE,FALSE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5710,United States,118000,9,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
 5714,Germany,86021.5053763441,20,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-5723,United States,85e3,9,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-5724,United States,125e3,20,TRUE,TRUE,10,Remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-5727,Germany,43010.752688172,7,TRUE,TRUE,1e3,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
+5723,United States,85000,9,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+5724,United States,125000,20,TRUE,TRUE,10,Remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+5727,Germany,43010.752688172,7,TRUE,TRUE,1000,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
 5730,United Kingdom,48437.5,4,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 5735,United Kingdom,51250,4,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 5743,Germany,37634.4086021505,3,TRUE,FALSE,10,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-5746,United States,65e3,3,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5746,United States,65000,3,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 5751,Germany,64516.1290322581,10,FALSE,TRUE,100,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 5754,Canada,60606.0606060606,6,TRUE,FALSE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-5783,United States,132e3,3,FALSE,TRUE,1e4,Not remote,4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-5784,United States,119e3,12,TRUE,TRUE,1e4,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-5789,United States,8e4,3,TRUE,TRUE,10,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-5799,United States,148e3,20,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5783,United States,132000,3,FALSE,TRUE,10000,Not remote,4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+5784,United States,119000,12,TRUE,TRUE,10000,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+5789,United States,80000,3,TRUE,TRUE,10,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+5799,United States,148000,20,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 5810,United Kingdom,41250,6,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-5814,United States,1e5,20,TRUE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5820,United States,1e5,3,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5814,United States,100000,20,TRUE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5820,United States,100000,3,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-5837,United States,105e3,5,TRUE,FALSE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+5837,United States,105000,5,TRUE,FALSE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 5840,United Kingdom,41250,2,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 5849,United States,88500,4,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-5850,United States,6e4,1,TRUE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5854,United States,115e3,20,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-5858,United Kingdom,81250,20,TRUE,TRUE,1e3,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+5850,United States,60000,1,TRUE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5854,United States,115000,20,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+5858,United Kingdom,81250,20,TRUE,TRUE,1000,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 5864,Canada,75757.5757575758,16,TRUE,FALSE,20,Not remote,8,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
 5871,Canada,87121.2121212121,14,FALSE,TRUE,100,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 5874,Canada,64393.9393939394,16,FALSE,FALSE,1,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-5876,United States,12e4,10,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5882,United States,55e3,5,FALSE,TRUE,5e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5883,United States,131e3,14,FALSE,TRUE,1e3,Remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-5896,United States,52e3,3,FALSE,TRUE,5e3,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5901,United States,66e3,2,FALSE,TRUE,10,Not remote,7,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5905,United States,89e3,2,FALSE,TRUE,1e3,Not remote,0,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-5910,United Kingdom,50750,4,FALSE,FALSE,1e4,Not remote,6,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-5911,Canada,45454.5454545455,11,FALSE,TRUE,1e4,Not remote,2,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5913,United States,52e3,20,TRUE,TRUE,1,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
-5914,United States,75e3,6,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-5917,United States,81e3,3,FALSE,FALSE,100,Not remote,9,TRUE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5876,United States,120000,10,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5882,United States,55000,5,FALSE,TRUE,5000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5883,United States,131000,14,FALSE,TRUE,1000,Remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+5896,United States,52000,3,FALSE,TRUE,5000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5901,United States,66000,2,FALSE,TRUE,10,Not remote,7,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5905,United States,89000,2,FALSE,TRUE,1000,Not remote,0,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+5910,United Kingdom,50750,4,FALSE,FALSE,10000,Not remote,6,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+5911,Canada,45454.5454545455,11,FALSE,TRUE,10000,Not remote,2,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5913,United States,52000,20,TRUE,TRUE,1,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+5914,United States,75000,6,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+5917,United States,81000,3,FALSE,FALSE,100,Not remote,9,TRUE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-5926,United States,115e3,15,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5934,United States,125e3,7,TRUE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5939,United States,106e3,18,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5942,United States,13e4,10,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5956,Canada,75757.5757575758,20,FALSE,FALSE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5957,United States,9e4,7,FALSE,TRUE,1,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-5962,United States,135e3,20,FALSE,FALSE,10,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-5965,United States,11e4,20,FALSE,TRUE,100,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE
+5926,United States,115000,15,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5934,United States,125000,7,TRUE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5939,United States,106000,18,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5942,United States,130000,10,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5956,Canada,75757.5757575758,20,FALSE,FALSE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5957,United States,90000,7,FALSE,TRUE,1,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+5962,United States,135000,20,FALSE,FALSE,10,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+5965,United States,110000,20,FALSE,TRUE,100,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE
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-5985,United States,12e4,20,TRUE,TRUE,100,Remote,8,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE
-5986,United States,173e3,20,TRUE,FALSE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-5987,United States,36e3,5,FALSE,TRUE,10,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+5985,United States,120000,20,TRUE,TRUE,100,Remote,8,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE
+5986,United States,173000,20,TRUE,FALSE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+5987,United States,36000,5,FALSE,TRUE,10,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 5992,Canada,41666.6666666667,4,FALSE,TRUE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 5994,Canada,62121.2121212121,10,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 5999,United States,97500,20,TRUE,FALSE,500,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-6007,United Kingdom,4e4,2,FALSE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6025,United States,18e4,13,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6026,United States,135e3,20,FALSE,FALSE,1e4,Not remote,9,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-6035,United Kingdom,52500,4,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-6048,United Kingdom,52500,3,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6056,India,17618.5582146528,2,TRUE,TRUE,1e3,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6058,United States,11e4,8,FALSE,FALSE,10,Not remote,8,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-6059,United States,76e3,20,FALSE,FALSE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6070,Germany,59139.7849462366,2,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+6007,United Kingdom,40000,2,FALSE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6025,United States,180000,13,TRUE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6026,United States,135000,20,FALSE,FALSE,10000,Not remote,9,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+6035,United Kingdom,52500,4,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+6048,United Kingdom,52500,3,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6056,India,17618.5582146528,2,TRUE,TRUE,1000,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6058,United States,110000,8,FALSE,FALSE,10,Not remote,8,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+6059,United States,76000,20,FALSE,FALSE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6070,Germany,59139.7849462366,2,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
 6071,United Kingdom,17812.5,1,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6073,United States,68e3,2,FALSE,TRUE,10,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-6078,United States,4e4,1,FALSE,TRUE,100,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6084,United States,12e4,14,FALSE,FALSE,20,Remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+6073,United States,68000,2,FALSE,TRUE,10,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+6078,United States,40000,1,FALSE,TRUE,100,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6084,United States,120000,14,FALSE,FALSE,20,Remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 6095,Germany,59139.7849462366,6,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6103,United States,4e4,4,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6105,United States,75e3,8,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6110,United States,73e3,2,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+6103,United States,40000,4,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6105,United States,75000,8,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6110,United States,73000,2,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 6111,Canada,31818.1818181818,2,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6116,United States,45e3,2,FALSE,TRUE,1,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+6116,United States,45000,2,FALSE,TRUE,1,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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-6125,United States,12e4,19,TRUE,TRUE,1,Not remote,8,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE
-6128,United States,68e3,3,TRUE,FALSE,1,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+6125,United States,120000,19,TRUE,TRUE,1,Not remote,8,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE
+6128,United States,68000,3,TRUE,FALSE,1,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 6130,Canada,72727.2727272727,17,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-6141,United States,11e4,2,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-6146,United States,105600,4,FALSE,TRUE,1e4,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
-6152,United States,13e4,20,FALSE,FALSE,500,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+6141,United States,110000,2,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+6146,United States,105600,4,FALSE,TRUE,10000,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
+6152,United States,130000,20,FALSE,FALSE,500,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-6160,United States,143e3,5,FALSE,TRUE,20,Not remote,7,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-6167,United States,135e3,11,TRUE,FALSE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-6173,United States,65e3,2,FALSE,TRUE,20,Not remote,4,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-6179,United States,16e4,20,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-6183,United States,87e3,14,TRUE,TRUE,500,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6185,United States,121e3,20,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+6160,United States,143000,5,FALSE,TRUE,20,Not remote,7,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+6167,United States,135000,11,TRUE,FALSE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+6173,United States,65000,2,FALSE,TRUE,20,Not remote,4,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+6179,United States,160000,20,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+6183,United States,87000,14,TRUE,TRUE,500,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6185,United States,121000,20,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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-6198,United States,5e4,1,FALSE,FALSE,20,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-6201,United States,5e4,2,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6198,United States,50000,1,FALSE,FALSE,20,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+6201,United States,50000,2,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-6208,United States,75e3,4,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6209,United States,135e3,15,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+6208,United States,75000,4,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6209,United States,135000,15,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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-6213,United States,153e3,5,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-6216,United States,11e4,9,FALSE,TRUE,1e3,Remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+6213,United States,153000,5,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+6216,United States,110000,9,FALSE,TRUE,1000,Remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
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-6240,Canada,42424.2424242424,3,FALSE,TRUE,1e4,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-6242,United States,127e3,5,FALSE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-6243,United States,9e4,2,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-6248,United States,8e4,4,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+6240,Canada,42424.2424242424,3,FALSE,TRUE,10000,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+6242,United States,127000,5,FALSE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+6243,United States,90000,2,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+6248,United States,80000,4,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 6268,United States,65060,4,TRUE,TRUE,1,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6271,United States,11e4,4,FALSE,FALSE,5e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+6271,United States,110000,4,FALSE,FALSE,5000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
 6275,Germany,66129.0322580645,20,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-6277,United States,3e4,2,TRUE,TRUE,10,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
-6281,United States,145600,20,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-6286,Germany,75268.8172043011,9,FALSE,TRUE,1e3,Not remote,10,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+6277,United States,30000,2,TRUE,TRUE,10,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
+6281,United States,145600,20,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+6286,Germany,75268.8172043011,9,FALSE,TRUE,1000,Not remote,10,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
 6296,Canada,49242.4242424242,2,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6306,United States,99e3,6,TRUE,TRUE,5e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6311,United States,125e3,17,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-6313,United States,175e3,13,FALSE,TRUE,20,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-6315,United Kingdom,82500,9,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6321,United States,8e4,2,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6306,United States,99000,6,TRUE,TRUE,5000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6311,United States,125000,17,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+6313,United States,175000,13,FALSE,TRUE,20,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+6315,United Kingdom,82500,9,TRUE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6321,United States,80000,2,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 6326,Canada,56818.1818181818,3,FALSE,FALSE,100,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-6329,United States,145e3,18,TRUE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6332,United States,55e3,4,FALSE,TRUE,1e3,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-6341,United States,1e5,4,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6343,United States,14e4,20,TRUE,FALSE,1,Remote,8,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE
+6329,United States,145000,18,TRUE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6332,United States,55000,4,FALSE,TRUE,1000,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+6341,United States,100000,4,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6343,United States,140000,20,TRUE,FALSE,1,Remote,8,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE
 6348,Canada,37878.7878787879,1,FALSE,TRUE,10,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-6354,United States,125e3,8,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6362,United States,145e3,17,FALSE,TRUE,1e4,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-6363,United States,18e4,20,FALSE,FALSE,20,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-6366,United States,75e3,2,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6375,United States,126500,20,TRUE,TRUE,1e3,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-6376,United States,126e3,20,TRUE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6379,United States,85e3,5,TRUE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-6382,United States,11e4,13,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6390,United States,6e4,0,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6391,United States,93e3,9,FALSE,FALSE,100,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6354,United States,125000,8,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6362,United States,145000,17,FALSE,TRUE,10000,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+6363,United States,180000,20,FALSE,FALSE,20,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+6366,United States,75000,2,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6375,United States,126500,20,TRUE,TRUE,1000,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+6376,United States,126000,20,TRUE,FALSE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6379,United States,85000,5,TRUE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+6382,United States,110000,13,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6390,United States,60000,0,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6391,United States,93000,9,FALSE,FALSE,100,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 6394,Germany,48387.0967741935,5,TRUE,TRUE,20,Not remote,5,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-6408,United States,51e3,1,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6408,United States,51000,1,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 6412,United States,77250,2,TRUE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-6413,United States,103e3,20,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6421,United States,109e3,20,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
-6422,United States,79e3,4,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-6426,United States,17e3,1,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6413,United States,103000,20,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6421,United States,109000,20,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+6422,United States,79000,4,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+6426,United States,17000,1,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 6429,United States,122500,13,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6430,United States,17e4,20,TRUE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6430,United States,170000,20,TRUE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 6434,Canada,41666.6666666667,1,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6436,United States,65e3,3,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6438,United States,156e3,4,FALSE,FALSE,1e4,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-6453,United States,8e4,1,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6455,Canada,49242.4242424242,3,FALSE,TRUE,1e4,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+6436,United States,65000,3,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6438,United States,156000,4,FALSE,FALSE,10000,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+6453,United States,80000,1,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6455,Canada,49242.4242424242,3,FALSE,TRUE,10000,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
 6457,United States,47500,2,FALSE,TRUE,10,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 6459,Germany,53763.4408602151,7,TRUE,FALSE,20,Not remote,6,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-6461,United States,76e3,4,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-6465,United States,105e3,20,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6470,United States,65e3,3,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6474,United States,74880,20,FALSE,FALSE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6482,United States,108e3,7,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6486,United States,9e4,4,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6461,United States,76000,4,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+6465,United States,105000,20,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6470,United States,65000,3,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6474,United States,74880,20,FALSE,FALSE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6482,United States,108000,7,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6486,United States,90000,4,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 6490,Canada,34090.9090909091,8,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6495,United Kingdom,18125,3,TRUE,FALSE,1e3,Not remote,10,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+6495,United Kingdom,18125,3,TRUE,FALSE,1000,Not remote,10,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 6498,Germany,59139.7849462366,14,TRUE,TRUE,100,Not remote,3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-6501,United States,18e4,20,FALSE,TRUE,1e4,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
-6502,United States,11e4,2,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-6504,United States,175e3,17,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6508,United States,7e4,1,FALSE,FALSE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6511,United States,13e4,4,FALSE,TRUE,100,Not remote,6,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6515,United States,115668,1,FALSE,TRUE,1e4,Not remote,3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+6501,United States,180000,20,FALSE,TRUE,10000,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+6502,United States,110000,2,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+6504,United States,175000,17,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6508,United States,70000,1,FALSE,FALSE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6511,United States,130000,4,FALSE,TRUE,100,Not remote,6,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6515,United States,115668,1,FALSE,TRUE,10000,Not remote,3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 6520,Germany,64516.1290322581,13,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 6522,Canada,74242.4242424242,14,FALSE,TRUE,100,Not remote,9,TRUE,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
 6525,Canada,65909.0909090909,18,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6528,United States,73e3,4,FALSE,FALSE,1e4,Not remote,5,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6534,United States,7e4,8,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6548,United States,118e3,13,FALSE,TRUE,20,Remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-6551,United States,62e3,3,FALSE,TRUE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6554,United States,4e4,2,FALSE,TRUE,1,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6557,United States,1e5,13,FALSE,FALSE,20,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6559,United Kingdom,51250,14,FALSE,TRUE,1e4,Not remote,8,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6564,United States,141e3,4,TRUE,TRUE,1e4,Not remote,7,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,TRUE
+6528,United States,73000,4,FALSE,FALSE,10000,Not remote,5,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6534,United States,70000,8,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6548,United States,118000,13,FALSE,TRUE,20,Remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+6551,United States,62000,3,FALSE,TRUE,1000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6554,United States,40000,2,FALSE,TRUE,1,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6557,United States,100000,13,FALSE,FALSE,20,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6559,United Kingdom,51250,14,FALSE,TRUE,10000,Not remote,8,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6564,United States,141000,4,TRUE,TRUE,10000,Not remote,7,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,TRUE
 6566,Canada,75757.5757575758,10,FALSE,TRUE,20,Not remote,5,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 6567,India,24959.6241374248,9,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 6568,Germany,59139.7849462366,3,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-6569,United States,75e3,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-6570,United States,7e4,10,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-6571,United States,45e3,7,TRUE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6569,United States,75000,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+6570,United States,70000,10,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+6571,United States,45000,7,TRUE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 6575,Canada,34090.9090909091,2,FALSE,FALSE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-6616,United States,53e3,2,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6619,United States,101e3,16,FALSE,TRUE,100,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-6638,United States,72e3,1,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-6645,United States,5e4,1,FALSE,TRUE,100,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+6616,United States,53000,2,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6619,United States,101000,16,FALSE,TRUE,100,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+6638,United States,72000,1,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+6645,United States,50000,1,FALSE,TRUE,100,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 6646,United States,122400,20,FALSE,FALSE,100,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-6654,United States,54e3,2,FALSE,FALSE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-6657,United States,143e3,11,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-6660,United States,17e4,6,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6654,United States,54000,2,FALSE,FALSE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+6657,United States,143000,11,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+6660,United States,170000,6,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 6676,United Kingdom,18750,1,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6678,United States,9e4,0,FALSE,TRUE,1e3,Not remote,7,TRUE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE
-6695,United States,115e3,4,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6696,United States,77e3,1,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-6698,United States,125e3,17,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-6699,United States,16e4,9,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+6678,United States,90000,0,FALSE,TRUE,1000,Not remote,7,TRUE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE
+6695,United States,115000,4,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6696,United States,77000,1,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+6698,United States,125000,17,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+6699,United States,160000,9,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 6700,United States,91500,7,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 6702,United States,123456,8,FALSE,FALSE,20,Not remote,10,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-6712,United States,36e3,2,FALSE,TRUE,10,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6712,United States,36000,2,FALSE,TRUE,10,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 6714,Canada,45454.5454545455,8,TRUE,FALSE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE
-6716,United States,56e3,4,FALSE,FALSE,100,Remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6718,United Kingdom,193750,17,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-6719,Germany,41935.4838709677,4,FALSE,TRUE,1e4,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6722,United Kingdom,127500,7,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6716,United States,56000,4,FALSE,FALSE,100,Remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6718,United Kingdom,193750,17,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+6719,Germany,41935.4838709677,4,FALSE,TRUE,10000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6722,United Kingdom,127500,7,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 6725,Canada,68181.8181818182,15,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 6737,Canada,83333.3333333333,11,TRUE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-6744,United States,195e3,20,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6744,United States,195000,20,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 6745,Canada,45454.5454545455,1,FALSE,TRUE,100,Not remote,10,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-6749,United States,64e3,1,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6770,United States,88e3,18,FALSE,FALSE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6749,United States,64000,1,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6770,United States,88000,18,FALSE,FALSE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 6771,Canada,80681.8181818182,4,FALSE,FALSE,20,Remote,6,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6773,United States,14e4,20,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6779,United States,87e3,3,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
-6781,United States,6e4,10,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6784,United States,7e4,6,FALSE,TRUE,10,Not remote,8,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6793,United States,71e3,3,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+6773,United States,140000,20,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6779,United States,87000,3,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+6781,United States,60000,10,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6784,United States,70000,6,FALSE,TRUE,10,Not remote,8,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6793,United States,71000,3,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
 6795,Canada,49242.4242424242,3,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE
-6803,United States,13e4,7,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6803,United States,130000,7,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 6813,United Kingdom,91750,17,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 6816,United Kingdom,31250,2,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6823,United States,67200,3,FALSE,TRUE,1e4,Not remote,8,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-6826,United States,95900,20,TRUE,TRUE,5e3,Not remote,8,FALSE,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE
+6823,United States,67200,3,FALSE,TRUE,10000,Not remote,8,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+6826,United States,95900,20,TRUE,TRUE,5000,Not remote,8,FALSE,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE
 6830,United Kingdom,28750,2,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 6832,United Kingdom,52500,10,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6836,United States,66e3,2,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6847,United States,82500,3,TRUE,TRUE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+6836,United States,66000,2,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6847,United States,82500,3,TRUE,TRUE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 6872,United Kingdom,74967.5,7,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 6877,United Kingdom,62500,5,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-6879,United States,115e3,20,TRUE,TRUE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6885,United States,1e5,16,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6898,United States,82e3,6,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6900,United States,18e4,20,TRUE,TRUE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6905,United States,9e4,3,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6923,United States,135e3,19,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6879,United States,115000,20,TRUE,TRUE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6885,United States,100000,16,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6898,United States,82000,6,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6900,United States,180000,20,TRUE,TRUE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6905,United States,90000,3,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6923,United States,135000,19,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 6927,Canada,47727.2727272727,3,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6947,United States,14e4,20,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-6953,United States,91e3,11,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6955,Germany,79569.8924731183,4,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6947,United States,140000,20,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+6953,United States,91000,11,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6955,Germany,79569.8924731183,4,TRUE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 6959,United Kingdom,42500,4,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 6968,United States,89500,2,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 6971,Canada,45454.5454545455,3,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6973,United States,65e3,1,FALSE,FALSE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6974,United States,113e3,9,FALSE,TRUE,1e4,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6973,United States,65000,1,FALSE,FALSE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6974,United States,113000,9,FALSE,TRUE,10000,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 6986,Canada,53030.303030303,2,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6989,United States,75e3,1,FALSE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6989,United States,75000,1,FALSE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 6990,Canada,143181.818181818,4,FALSE,TRUE,100,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-6993,United States,68e3,1,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-7005,United States,1e5,16,TRUE,TRUE,1,Not remote,10,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-7012,United States,123e3,12,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-7017,United States,115e3,20,FALSE,TRUE,500,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-7020,United States,15e4,20,TRUE,TRUE,5e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-7056,United States,135e3,11,TRUE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-7059,India,8956.10042578182,4,TRUE,TRUE,5e3,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-7063,United States,106e3,20,FALSE,TRUE,100,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-7076,United States,105e3,5,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-7086,United States,4e4,6,TRUE,TRUE,1,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE
-7090,United States,83e3,1,TRUE,TRUE,1e3,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-7094,United States,175e3,6,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+6993,United States,68000,1,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+7005,United States,100000,16,TRUE,TRUE,1,Not remote,10,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+7012,United States,123000,12,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+7017,United States,115000,20,FALSE,TRUE,500,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7020,United States,150000,20,TRUE,TRUE,5000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7056,United States,135000,11,TRUE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+7059,India,8956.10042578182,4,TRUE,TRUE,5000,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7063,United States,106000,20,FALSE,TRUE,100,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7076,United States,105000,5,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+7086,United States,40000,6,TRUE,TRUE,1,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE
+7090,United States,83000,1,TRUE,TRUE,1000,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+7094,United States,175000,6,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 7110,Canada,51515.1515151515,1,FALSE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-7115,United States,121e3,10,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+7115,United States,121000,10,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 7125,United Kingdom,87500,8,TRUE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 7126,India,1761.85582146528,3,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-7127,United States,5e4,2,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7127,United States,50000,2,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 7158,India,13948.0252532668,4,FALSE,TRUE,10,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-7160,India,22023.197768316,4,FALSE,TRUE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-7163,United States,15e4,8,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+7160,India,22023.197768316,4,FALSE,TRUE,1000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7163,United States,150000,8,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
 7167,Germany,113978.494623656,17,TRUE,TRUE,500,Not remote,6,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 7172,United States,142500,10,TRUE,TRUE,20,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-7175,United States,125e3,16,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-7177,United States,11e4,14,FALSE,TRUE,1,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-7178,United States,9e4,20,FALSE,FALSE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-7207,United States,11e4,3,FALSE,TRUE,1e4,Not remote,7,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+7175,United States,125000,16,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+7177,United States,110000,14,FALSE,TRUE,1,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+7178,United States,90000,20,FALSE,FALSE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7207,United States,110000,3,FALSE,TRUE,10000,Not remote,7,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 7219,Canada,106060.606060606,7,TRUE,TRUE,20,Remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 7227,United Kingdom,38580,13,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-7232,United States,9e4,3,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7232,United States,90000,3,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-7264,India,22023.197768316,8,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-7269,India,4404.63955366319,1,TRUE,FALSE,1e4,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7264,India,22023.197768316,8,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+7269,India,4404.63955366319,1,TRUE,FALSE,10000,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-7280,United States,117e3,2,FALSE,TRUE,5e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-7283,United Kingdom,56250,3,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-7295,United States,81e3,2,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-7337,United Kingdom,75e3,7,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7280,United States,117000,2,FALSE,TRUE,5000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7283,United Kingdom,56250,3,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7295,United States,81000,2,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+7337,United Kingdom,75000,7,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 7375,Germany,55913.9784946237,6,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-7400,United States,175e3,9,FALSE,TRUE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+7400,United States,175000,9,FALSE,TRUE,1000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
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-7433,United Kingdom,35e3,9,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-7483,Germany,58064.5161290323,5,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-7507,United States,75e3,2,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-7583,United States,119e3,20,FALSE,FALSE,1e3,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7433,United Kingdom,35000,9,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7483,Germany,58064.5161290323,5,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7507,United States,75000,2,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+7583,United States,119000,20,FALSE,FALSE,1000,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 7596,United Kingdom,41250,7,TRUE,TRUE,1,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
-7602,Germany,91397.8494623656,15,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-7617,United States,12e4,20,TRUE,TRUE,500,Not remote,10,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7602,Germany,91397.8494623656,15,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7617,United States,120000,20,TRUE,TRUE,500,Not remote,10,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 7621,India,10277.4922918808,3,FALSE,TRUE,20,Not remote,6,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-7645,United States,32e3,2,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE
-7650,United States,149e3,20,TRUE,TRUE,5e3,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-7656,India,11745.7054764352,10,FALSE,TRUE,1e4,Remote,7,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-7664,United States,167e3,20,TRUE,TRUE,1,Not remote,10,FALSE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-7679,United States,85e3,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7645,United States,32000,2,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE
+7650,United States,149000,20,TRUE,TRUE,5000,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+7656,India,11745.7054764352,10,FALSE,TRUE,10000,Remote,7,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+7664,United States,167000,20,TRUE,TRUE,1,Not remote,10,FALSE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+7679,United States,85000,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 7680,United States,100400,11,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-7682,United Kingdom,3e4,1,FALSE,FALSE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-7685,United Kingdom,47500,16,TRUE,FALSE,1e3,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-7725,United Kingdom,112500,7,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-7747,United States,75e3,17,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7682,United Kingdom,30000,1,FALSE,FALSE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7685,United Kingdom,47500,16,TRUE,FALSE,1000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+7725,United Kingdom,112500,7,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7747,United States,75000,17,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 7754,United Kingdom,53750,5,TRUE,TRUE,100,Not remote,8,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-7761,Canada,90909.0909090909,14,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-7771,India,7047.42328586111,5,FALSE,TRUE,1e4,Not remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-7773,United States,115e3,20,FALSE,TRUE,100,Remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-7774,Germany,53763.4408602151,1,TRUE,TRUE,5e3,Not remote,6,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-7785,United States,11e4,9,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7761,Canada,90909.0909090909,14,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+7771,India,7047.42328586111,5,FALSE,TRUE,10000,Not remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+7773,United States,115000,20,FALSE,TRUE,100,Remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7774,Germany,53763.4408602151,1,TRUE,TRUE,5000,Not remote,6,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+7785,United States,110000,9,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 7798,United Kingdom,57500,6,TRUE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 7802,United Kingdom,37875,8,FALSE,FALSE,10,Not remote,5,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
 7818,Canada,49242.4242424242,3,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 7821,Germany,45161.2903225806,9,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-7829,United States,108e3,6,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-7840,United States,126e3,20,TRUE,TRUE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7829,United States,108000,6,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7840,United States,126000,20,TRUE,TRUE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 7849,United Kingdom,43750,2,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-7850,India,8192.62956981354,1,FALSE,TRUE,5e3,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-7851,United States,24e3,3,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-7864,United States,88750,11,TRUE,TRUE,5e3,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7850,India,8192.62956981354,1,FALSE,TRUE,5000,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7851,United States,24000,3,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+7864,United States,88750,11,TRUE,TRUE,5000,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 7882,Germany,12903.2258064516,1,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 7889,Germany,48387.0967741935,10,FALSE,TRUE,20,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-7893,United States,4e4,2,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-7901,United States,24e3,4,FALSE,TRUE,1e4,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-7911,India,15959.4773161063,6,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-7945,United States,15e4,9,FALSE,TRUE,100,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7893,United States,40000,2,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+7901,United States,24000,4,FALSE,TRUE,10000,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+7911,India,15959.4773161063,6,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+7945,United States,150000,9,FALSE,TRUE,100,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 7962,Germany,51612.9032258064,6,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-8022,United States,11e4,11,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-8029,Germany,64516.1290322581,5,FALSE,TRUE,1e3,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+8022,United States,110000,11,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+8029,Germany,64516.1290322581,5,FALSE,TRUE,1000,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 8035,Germany,75268.8172043011,14,TRUE,FALSE,100,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-8040,United States,92e3,5,FALSE,FALSE,100,Not remote,5,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+8040,United States,92000,5,FALSE,FALSE,100,Not remote,5,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
 8044,Canada,90909.0909090909,16,TRUE,TRUE,500,Remote,10,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE
-8048,Germany,64516.1290322581,20,FALSE,TRUE,1e4,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+8048,Germany,64516.1290322581,20,FALSE,TRUE,10000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 8068,Germany,19354.8387096774,9,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 8073,Germany,17204.3010752688,2,FALSE,TRUE,1,Remote,2,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 8086,United Kingdom,29375,2,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-8099,United Kingdom,45e3,3,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-8145,United States,17e4,14,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+8099,United Kingdom,45000,3,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+8145,United States,170000,14,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 8159,United Kingdom,59375,14,FALSE,TRUE,20,Not remote,7,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
-8163,United States,45e3,2,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-8177,United States,8e4,3,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-8195,United States,88e3,15,FALSE,FALSE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+8163,United States,45000,2,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+8177,United States,80000,3,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+8195,United States,88000,15,FALSE,FALSE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 8197,Canada,68181.8181818182,11,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 8202,Canada,41666.6666666667,2,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-8214,United States,11e4,20,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-8222,United States,13e4,1,TRUE,TRUE,100,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-8226,United States,45e3,1,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-8239,United States,65e3,2,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+8214,United States,110000,20,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+8222,United States,130000,1,TRUE,TRUE,100,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+8226,United States,45000,1,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+8239,United States,65000,2,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 8251,Canada,84090.9090909091,5,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-8258,United States,72e3,2,TRUE,TRUE,500,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-8278,United States,15e4,17,FALSE,TRUE,1e4,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-8282,United States,7e4,1,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+8258,United States,72000,2,TRUE,TRUE,500,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+8278,United States,150000,17,FALSE,TRUE,10000,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+8282,United States,70000,1,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 8285,United States,42500,8,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 8286,United States,107250,9,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-8291,United States,8e4,4,FALSE,TRUE,1,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+8291,United States,80000,4,FALSE,TRUE,1,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 8303,Canada,72727.2727272727,5,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 8307,Germany,35483.8709677419,18,TRUE,TRUE,1,Remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
 8324,Canada,75757.5757575758,20,TRUE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 8334,India,10424.3136103362,3,FALSE,TRUE,500,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
-8346,United States,1e5,4,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-8349,United States,66e3,3,TRUE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-8361,United States,12e4,4,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+8346,United States,100000,4,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+8349,United States,66000,3,TRUE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+8361,United States,120000,4,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 8363,India,3523.71164293055,2,FALSE,TRUE,1,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 8374,Canada,109848.484848485,20,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-8390,India,11011.598884158,2,FALSE,FALSE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-8393,United States,12e4,15,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-8394,United States,6e4,5,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-8409,United Kingdom,4e4,9,FALSE,TRUE,500,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+8390,India,11011.598884158,2,FALSE,FALSE,1000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+8393,United States,120000,15,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+8394,United States,60000,5,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+8409,United Kingdom,40000,9,FALSE,TRUE,500,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-8427,United States,63500,3,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-8478,United Kingdom,75e3,16,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+8427,United States,63500,3,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+8478,United Kingdom,75000,16,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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 8538,United Kingdom,36250,10,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-8539,Germany,66666.6666666667,9,FALSE,FALSE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+8539,Germany,66666.6666666667,9,FALSE,FALSE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-8559,United Kingdom,105e3,6,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-8562,United States,62e3,1,TRUE,TRUE,1e3,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+8559,United Kingdom,105000,6,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+8562,United States,62000,1,TRUE,TRUE,1000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-8585,United States,135e3,4,FALSE,TRUE,1e4,Not remote,8,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-8587,United States,11e4,20,FALSE,TRUE,100,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+8585,United States,135000,4,FALSE,TRUE,10000,Not remote,8,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+8587,United States,110000,20,FALSE,TRUE,100,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-8616,Germany,64516.1290322581,10,FALSE,FALSE,5e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-8624,United Kingdom,75e3,18,TRUE,TRUE,1,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-8628,Canada,60606.0606060606,1,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+8616,Germany,64516.1290322581,10,FALSE,FALSE,5000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+8624,United Kingdom,75000,18,TRUE,TRUE,1,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+8628,Canada,60606.0606060606,1,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 8650,Canada,55303.0303030303,14,FALSE,FALSE,10,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 8676,United States,34800,2,FALSE,FALSE,1,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 8692,Canada,49242.4242424242,0,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-8700,India,5872.85273821759,1,FALSE,TRUE,1e4,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-8711,United States,85e3,15,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-8751,United Kingdom,35e3,4,FALSE,TRUE,500,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-8756,United States,14e4,6,FALSE,TRUE,100,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-8764,United Kingdom,1e5,4,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+8700,India,5872.85273821759,1,FALSE,TRUE,10000,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+8711,United States,85000,15,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+8751,United Kingdom,35000,4,FALSE,TRUE,500,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+8756,United States,140000,6,FALSE,TRUE,100,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+8764,United Kingdom,100000,4,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 8768,Germany,3763.44086021505,6,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 8771,Canada,68181.8181818182,10,TRUE,TRUE,20,Not remote,9,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-8776,United States,16e4,10,FALSE,FALSE,1e4,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-8783,United States,9e4,4,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-8790,United States,125e3,12,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-8825,United States,9e4,8,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-8868,United States,71e3,6,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-8894,United Kingdom,25e3,4,FALSE,TRUE,10,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-8904,United States,96e3,5,FALSE,TRUE,5e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-8932,United States,165e3,20,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-8938,United States,11e4,7,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-8943,United States,12e4,4,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
-8951,India,19086.7713992072,10,TRUE,TRUE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-8968,United States,55e3,1,FALSE,TRUE,1e3,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-8978,India,39641.7559829687,12,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+8776,United States,160000,10,FALSE,FALSE,10000,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+8783,United States,90000,4,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+8790,United States,125000,12,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+8825,United States,90000,8,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+8868,United States,71000,6,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+8894,United Kingdom,25000,4,FALSE,TRUE,10,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+8904,United States,96000,5,FALSE,TRUE,5000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+8932,United States,165000,20,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+8938,United States,110000,7,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+8943,United States,120000,4,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
+8951,India,19086.7713992072,10,TRUE,TRUE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+8968,United States,55000,1,FALSE,TRUE,1000,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+8978,India,39641.7559829687,12,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 8984,United States,87200,8,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-8987,Germany,86021.5053763441,14,FALSE,FALSE,1e3,Not remote,6,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE
+8987,Germany,86021.5053763441,14,FALSE,FALSE,1000,Not remote,6,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE
 8994,Canada,87121.2121212121,3,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 9051,India,3876.08280722361,4,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 9098,Germany,34838.7096774194,4,FALSE,FALSE,1,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-9104,India,11099.6916752312,4,TRUE,TRUE,1e4,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-9130,Germany,43010.752688172,7,FALSE,FALSE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+9104,India,11099.6916752312,4,TRUE,TRUE,10000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9130,Germany,43010.752688172,7,FALSE,FALSE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
 9160,Germany,51612.9032258064,16,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-9176,United Kingdom,43750,6,FALSE,FALSE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9176,United Kingdom,43750,6,FALSE,FALSE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 9180,United Kingdom,44375,20,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-9200,United Kingdom,41875,4,FALSE,TRUE,5e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9200,United Kingdom,41875,4,FALSE,TRUE,5000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 9207,United Kingdom,63750,12,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 9236,Germany,50322.5806451613,5,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 9241,United Kingdom,56250,6,TRUE,TRUE,100,Not remote,7,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-9244,United Kingdom,5e4,5,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+9244,United Kingdom,50000,5,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
 9274,United Kingdom,59375,5,TRUE,TRUE,10,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 9280,United Kingdom,56250,6,TRUE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 9283,United Kingdom,31250,2,FALSE,TRUE,100,Not remote,8,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
-9297,India,8809.27910732638,2,TRUE,TRUE,5e3,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9297,India,8809.27910732638,2,TRUE,TRUE,5000,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 9302,Germany,34838.7096774194,6,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 9304,India,2642.78373219792,2,TRUE,TRUE,1,Not remote,3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 9320,Germany,86021.5053763441,17,TRUE,TRUE,100,Remote,2,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 9340,India,4551.46087211863,2,FALSE,FALSE,10,Not remote,3,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-9376,India,7047.42328586111,4,FALSE,TRUE,1e3,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9376,India,7047.42328586111,4,FALSE,TRUE,1000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 9378,United Kingdom,31250,3,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 9398,India,1468.2131845544,6,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-9399,United Kingdom,72500,5,FALSE,TRUE,1e4,Remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9399,United Kingdom,72500,5,FALSE,TRUE,10000,Remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 9409,United Kingdom,63750,20,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-9437,United States,84e3,20,FALSE,FALSE,100,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9437,United States,84000,20,FALSE,FALSE,100,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 9468,United Kingdom,27500,1,FALSE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-9473,United Kingdom,87500,9,FALSE,TRUE,1e4,Not remote,4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+9473,United Kingdom,87500,9,FALSE,TRUE,10000,Not remote,4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 9508,India,17618.5582146528,5,FALSE,FALSE,500,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 9515,India,10277.4922918808,4,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-9530,Germany,49462.3655913978,2,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-9542,United States,163e3,20,FALSE,TRUE,5e3,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-9548,United States,85e3,20,FALSE,TRUE,100,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+9530,Germany,49462.3655913978,2,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9542,United States,163000,20,FALSE,TRUE,5000,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+9548,United States,85000,20,FALSE,TRUE,100,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
 9561,United Kingdom,37500,5,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-9574,United Kingdom,4e4,6,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-9579,United States,75e3,4,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+9574,United Kingdom,40000,6,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+9579,United States,75000,4,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 9629,Germany,51612.9032258064,5,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-9642,United States,14e4,12,FALSE,FALSE,10,Remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9642,United States,140000,12,FALSE,FALSE,10,Remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 9658,Germany,41935.4838709677,2,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-9660,United States,62e3,3,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9660,United States,62000,3,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 9666,India,5138.74614594039,2,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-9670,United Kingdom,55e3,16,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+9670,United Kingdom,55000,16,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
 9695,United States,47500,2,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-9698,United Kingdom,1e5,9,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9698,United Kingdom,100000,9,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 9699,United Kingdom,29250,3,FALSE,TRUE,500,Not remote,8,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-9720,United Kingdom,1e5,20,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-9725,Canada,75757.5757575758,11,FALSE,FALSE,1e4,Not remote,8,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-9729,United Kingdom,75e3,4,FALSE,FALSE,20,Not remote,5,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-9731,United States,75e3,11,FALSE,FALSE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9720,United Kingdom,100000,20,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+9725,Canada,75757.5757575758,11,FALSE,FALSE,10000,Not remote,8,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+9729,United Kingdom,75000,4,FALSE,FALSE,20,Not remote,5,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+9731,United States,75000,11,FALSE,FALSE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 9734,Germany,45161.2903225806,5,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 9740,United Kingdom,52500,19,FALSE,TRUE,10,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-9741,United States,93e3,20,FALSE,TRUE,5e3,Not remote,9,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+9741,United States,93000,20,FALSE,TRUE,5000,Not remote,9,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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 9752,Germany,67741.935483871,8,FALSE,TRUE,10,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-9754,Germany,53593.5483870968,7,TRUE,TRUE,1e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9754,Germany,53593.5483870968,7,TRUE,TRUE,1000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 9756,Germany,42473.1182795699,5,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-9758,United Kingdom,5e4,5,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-9766,United Kingdom,4e4,2,FALSE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-9773,United States,11e4,7,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-9783,United States,86500,20,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-9795,United States,12e4,20,TRUE,TRUE,1,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9758,United Kingdom,50000,5,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9766,United Kingdom,40000,2,FALSE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9773,United States,110000,7,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9783,United States,86500,20,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+9795,United States,120000,20,TRUE,TRUE,1,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-9805,United States,135e3,19,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-9806,United States,9e4,13,FALSE,TRUE,500,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+9805,United States,135000,19,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9806,United States,90000,13,FALSE,TRUE,500,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-9820,Germany,51612.9032258064,5,FALSE,FALSE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-9822,Germany,1989.24731182796,3,FALSE,TRUE,1e3,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-9827,United States,77e3,4,TRUE,FALSE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-9829,United States,115e3,10,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-9830,United States,133e3,20,FALSE,TRUE,5e3,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE
-9832,United States,14e4,20,TRUE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-9866,United States,66e3,4,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-9883,Germany,55483.8709677419,11,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-9895,United States,12e4,20,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-9896,United States,102e3,9,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-9902,United States,115e3,9,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-9914,United States,57e3,2,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9820,Germany,51612.9032258064,5,FALSE,FALSE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9822,Germany,1989.24731182796,3,FALSE,TRUE,1000,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9827,United States,77000,4,TRUE,FALSE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+9829,United States,115000,10,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9830,United States,133000,20,FALSE,TRUE,5000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE
+9832,United States,140000,20,TRUE,FALSE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9866,United States,66000,4,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9883,Germany,55483.8709677419,11,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9895,United States,120000,20,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+9896,United States,102000,9,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+9902,United States,115000,9,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-10103,United States,103e3,12,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-10107,United States,8e4,14,FALSE,TRUE,1e3,Not remote,7,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
-10109,United States,82e3,6,FALSE,TRUE,1,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-10173,United States,8e4,15,FALSE,TRUE,100,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-10198,United States,63e3,4,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+10198,United States,63000,4,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-10202,United States,175e3,20,FALSE,TRUE,500,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-10209,United States,63e3,3,TRUE,TRUE,1e3,Not remote,7,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-10211,United States,9e4,20,FALSE,FALSE,1e4,Not remote,9,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-10219,United States,18e4,12,FALSE,TRUE,1,Remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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-10251,United States,75e3,20,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-10263,Canada,49242.4242424242,15,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-10265,Germany,55913.9784946237,7,TRUE,TRUE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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+10319,Canada,49242.4242424242,2,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
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-10346,United States,113e3,8,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+10340,India,18352.66480693,4,FALSE,TRUE,10000,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+10346,United States,113000,8,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
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+10368,India,11745.7054764352,5,TRUE,TRUE,1000,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE
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+10386,United States,153000,9,FALSE,FALSE,1000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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+10417,Germany,59139.7849462366,9,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-10485,United Kingdom,58750,13,FALSE,TRUE,5e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+10485,United Kingdom,58750,13,FALSE,TRUE,5000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-10503,United Kingdom,38750,1,FALSE,FALSE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+10503,United Kingdom,38750,1,FALSE,FALSE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-10540,United Kingdom,65e3,13,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+10540,United Kingdom,65000,13,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 10781,India,4404.63955366319,0,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
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 10861,India,24959.6241374248,8,FALSE,TRUE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 10872,Germany,48387.0967741935,5,FALSE,TRUE,1,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE
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+11373,United States,78000,4,TRUE,TRUE,10000,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+11379,United States,95000,20,FALSE,FALSE,100,Remote,6,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+11385,United States,130000,17,FALSE,TRUE,1000,Remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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+11416,United States,100000,20,FALSE,FALSE,500,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
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-11440,United States,7e4,1,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-11452,United States,12e4,4,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11454,United States,145e3,4,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11469,United States,12e4,20,TRUE,TRUE,100,Remote,10,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-11474,United States,114e3,20,FALSE,TRUE,1e3,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-11476,United States,5e4,2,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11437,United States,100000,18,FALSE,FALSE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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+11474,United States,114000,20,FALSE,TRUE,1000,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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 11477,United States,42500,5,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-11478,United States,112e3,20,TRUE,TRUE,1e3,Remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-11488,Canada,112878.787878788,20,FALSE,TRUE,1e4,Remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-11491,United Kingdom,106250,13,FALSE,TRUE,5e3,Not remote,8,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-11503,United States,55e3,1,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11478,United States,112000,20,TRUE,TRUE,1000,Remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+11488,Canada,112878.787878788,20,FALSE,TRUE,10000,Remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+11491,United Kingdom,106250,13,FALSE,TRUE,5000,Not remote,8,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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 11508,Canada,70454.5454545455,13,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11512,United States,9e4,8,TRUE,FALSE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11513,United States,9e4,4,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
-11519,United States,13e4,12,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11521,United States,57e3,1,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-11522,United States,7e4,2,TRUE,TRUE,100,Not remote,6,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-11524,United Kingdom,75e3,6,FALSE,TRUE,100,Not remote,9,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11526,United States,125e3,12,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-11540,United States,67e3,4,TRUE,TRUE,1,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-11542,United States,58e3,5,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11512,United States,90000,8,TRUE,FALSE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11513,United States,90000,4,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
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+11524,United Kingdom,75000,6,FALSE,TRUE,100,Not remote,9,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11526,United States,125000,12,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+11540,United States,67000,4,TRUE,TRUE,1,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+11542,United States,58000,5,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-11564,India,5505.79944207899,1,FALSE,FALSE,1e4,Not remote,3,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-11581,United States,95e3,15,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11582,United States,12e4,15,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+11564,India,5505.79944207899,1,FALSE,FALSE,10000,Not remote,3,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+11581,United States,95000,15,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11582,United States,120000,15,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
 11585,Canada,69696.9696969697,20,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-11588,United States,106e3,3,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11592,United States,65e3,13,FALSE,TRUE,100,Not remote,3,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-11596,United States,95e3,2,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11604,United States,67500,3,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11606,United States,8e4,4,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11588,United States,106000,3,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11592,United States,65000,13,FALSE,TRUE,100,Not remote,3,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+11596,United States,95000,2,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11604,United States,67500,3,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11606,United States,80000,4,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 11613,United Kingdom,47625,9,FALSE,FALSE,10,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11616,United States,13e4,4,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+11616,United States,130000,4,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 11618,United States,117832,20,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-11626,United States,5e4,1,FALSE,TRUE,1,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11626,United States,50000,1,FALSE,TRUE,1,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 11629,United States,91500,10,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11637,United States,109e3,15,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-11644,United States,77e3,3,TRUE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-11652,United States,83e3,8,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-11653,United States,134e3,2,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+11637,United States,109000,15,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+11644,United States,77000,3,TRUE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+11652,United States,83000,8,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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 11654,Canada,56818.1818181818,1,FALSE,TRUE,1,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE
-11655,United States,15e4,12,FALSE,TRUE,100,Not remote,5,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11659,United States,83e3,3,FALSE,FALSE,1e3,Remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11661,United States,104e3,12,TRUE,FALSE,5e3,Remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11664,United States,125e3,7,TRUE,TRUE,10,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11667,United States,135e3,15,FALSE,TRUE,10,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+11655,United States,150000,12,FALSE,TRUE,100,Not remote,5,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11659,United States,83000,3,FALSE,FALSE,1000,Remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11661,United States,104000,12,TRUE,FALSE,5000,Remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11664,United States,125000,7,TRUE,TRUE,10,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11667,United States,135000,15,FALSE,TRUE,10,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
 11668,Canada,69696.9696969697,10,TRUE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 11680,United States,63750,4,FALSE,TRUE,20,Remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-11683,United States,135e3,9,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-11686,United States,15e4,15,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-11693,United States,1e5,9,TRUE,TRUE,20,Not remote,3,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11696,United States,63e3,2,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11697,United States,78e3,10,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-11709,United States,14e4,8,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11683,United States,135000,9,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+11686,United States,150000,15,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+11693,United States,100000,9,TRUE,TRUE,20,Not remote,3,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11696,United States,63000,2,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11697,United States,78000,10,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+11709,United States,140000,8,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 11712,United States,68040,2,TRUE,FALSE,100,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-11713,India,35971.2230215827,10,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11714,United States,12e4,5,FALSE,TRUE,5e3,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11717,United States,65e3,3,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11722,United States,116e3,12,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11728,United States,175e3,17,TRUE,TRUE,500,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+11713,India,35971.2230215827,10,TRUE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11714,United States,120000,5,FALSE,TRUE,5000,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11717,United States,65000,3,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11722,United States,116000,12,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11728,United States,175000,17,TRUE,TRUE,500,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 11729,Canada,30303.0303030303,6,FALSE,TRUE,1,Remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE
-11731,United States,11e4,20,TRUE,TRUE,5e3,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11733,United States,95e3,1,TRUE,TRUE,100,Not remote,7,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-11736,United States,12e4,5,TRUE,TRUE,20,Remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11739,United States,6e4,8,TRUE,FALSE,20,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11740,United States,123e3,4,TRUE,TRUE,1e4,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-11743,United States,95e3,20,FALSE,FALSE,10,Remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-11751,United States,73400,9,FALSE,TRUE,1e3,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+11731,United States,110000,20,TRUE,TRUE,5000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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+11740,United States,123000,4,TRUE,TRUE,10000,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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+11751,United States,73400,9,FALSE,TRUE,1000,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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 11780,Canada,151515.151515152,20,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11782,United States,75e3,20,FALSE,TRUE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11782,United States,75000,20,FALSE,TRUE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-11798,India,6166.49537512847,2,TRUE,FALSE,1e4,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11799,India,13213.9186609896,6,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-11800,Canada,98484.8484848485,16,TRUE,TRUE,5e3,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
-11817,United States,1e5,3,FALSE,TRUE,20,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+11798,India,6166.49537512847,2,TRUE,FALSE,10000,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11799,India,13213.9186609896,6,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+11800,Canada,98484.8484848485,16,TRUE,TRUE,5000,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
+11817,United States,100000,3,FALSE,TRUE,20,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-11826,United States,135e3,17,FALSE,FALSE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11835,United States,108e3,6,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-11839,United States,32e3,2,FALSE,TRUE,10,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11858,United States,142e3,3,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
-11862,United States,92e3,3,FALSE,TRUE,100,Remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11864,United States,11e4,5,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11826,United States,135000,17,FALSE,FALSE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11835,United States,108000,6,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+11839,United States,32000,2,FALSE,TRUE,10,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11858,United States,142000,3,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+11862,United States,92000,3,FALSE,TRUE,100,Remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11864,United States,110000,5,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 11866,Germany,55913.9784946237,7,TRUE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11870,United States,115e3,10,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+11870,United States,115000,10,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-11890,United States,13e4,9,TRUE,TRUE,1e4,Remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
+11890,United States,130000,9,TRUE,TRUE,10000,Remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
 11932,Germany,65591.3978494624,17,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-11940,United States,13e4,20,FALSE,TRUE,100,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+11940,United States,130000,20,FALSE,TRUE,100,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 11999,Germany,46236.5591397849,10,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 12022,Germany,50322.5806451613,8,FALSE,TRUE,100,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 12040,Germany,32258.064516129,1,FALSE,FALSE,1,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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 12069,United Kingdom,40600,3,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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 12078,Germany,48924.7311827957,8,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 12083,India,17618.5582146528,2,TRUE,TRUE,20,Not remote,10,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE
 12101,United Kingdom,43750,4,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 12102,Germany,34408.6021505376,1,FALSE,TRUE,1,Not remote,1,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 12166,India,10729,5,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 12200,United Kingdom,62500,6,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
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-12243,Germany,5161.29032258064,2,FALSE,TRUE,5e3,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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 12328,Germany,45161.2903225806,9,TRUE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
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-12417,United States,12e4,10,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12426,Germany,2e4,4,FALSE,FALSE,10,Remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+12417,United States,120000,10,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 12485,United Kingdom,43750,1,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 12495,Germany,91397.8494623656,20,FALSE,TRUE,500,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 12498,India,11745.7054764352,5,TRUE,TRUE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 12506,India,14682.131845544,5,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12516,Canada,50504.5454545454,4,TRUE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+12516,Canada,50504.5454545454,4,TRUE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 12534,Germany,43010.752688172,7,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
 12543,India,17618.5582146528,8,TRUE,TRUE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 12547,India,19086.7713992072,6,TRUE,TRUE,500,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 12557,Germany,59139.7849462366,10,FALSE,FALSE,100,Not remote,6,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12574,United States,125e3,13,TRUE,TRUE,1e4,Remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12586,United States,12e4,9,TRUE,TRUE,100,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12590,United States,63e3,1,FALSE,TRUE,100,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12608,United States,86e3,9,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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+12586,United States,120000,9,TRUE,TRUE,100,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+12590,United States,63000,1,FALSE,TRUE,100,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+12608,United States,86000,9,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 12631,Canada,61818.1818181818,9,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12638,Germany,64516.1290322581,10,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+12638,Germany,64516.1290322581,10,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-12640,United States,9e4,4,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12644,United States,85e3,2,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12645,United States,117e3,3,TRUE,TRUE,1e3,Not remote,8,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-12646,Germany,69892.4731182796,5,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12648,United States,1e5,8,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-12651,United States,111e3,6,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12652,United States,13e4,15,TRUE,TRUE,10,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-12654,United States,65e3,1,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE
-12658,United States,12e4,10,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12661,United States,8e4,5,TRUE,TRUE,10,Remote,10,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-12663,United States,12e4,11,TRUE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12670,United States,92e3,15,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-12683,United States,43e3,4,TRUE,TRUE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12686,United States,137500,18,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12689,United States,16e4,12,TRUE,TRUE,500,Not remote,8,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-12699,United States,100780,16,FALSE,TRUE,1e3,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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-12707,India,10277.4922918808,4,TRUE,TRUE,5e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-12725,United States,85e3,8,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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+12707,India,10277.4922918808,4,TRUE,TRUE,5000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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+12725,United States,85000,8,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-12741,United States,8e4,20,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12748,United Kingdom,7e4,2,FALSE,TRUE,1e4,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-12749,United States,13e4,12,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
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-12757,United States,185e3,11,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12765,United States,98500,3,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-12783,United States,59e3,1,FALSE,TRUE,5e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-12794,United States,115e3,3,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-12806,United States,56e3,4,TRUE,TRUE,100,Remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+12783,United States,59000,1,FALSE,TRUE,5000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+12794,United States,115000,3,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+12798,United States,113000,14,TRUE,TRUE,100,Remote,6,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+12803,United States,120000,11,FALSE,TRUE,1000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
+12806,United States,56000,4,TRUE,TRUE,100,Remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
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-12825,United States,6e4,3,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-12828,United States,1e5,6,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-12829,United States,116e3,20,FALSE,FALSE,20,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12833,United States,6e4,1,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-12839,Germany,62365.5913978495,1,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-12843,United States,8e4,1,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-12847,United States,6e4,3,FALSE,TRUE,100,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-12849,United States,5e4,1,FALSE,TRUE,20,Not remote,6,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12852,United States,8e4,7,FALSE,FALSE,20,Not remote,0,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-12854,United States,4e4,1,FALSE,FALSE,20,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12858,United Kingdom,33747.5,3,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-12859,United States,98e3,20,FALSE,FALSE,1e4,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-12864,United States,11e4,11,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+12825,United States,60000,3,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+12828,United States,100000,6,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+12829,United States,116000,20,FALSE,FALSE,20,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+12833,United States,60000,1,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+12839,Germany,62365.5913978495,1,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+12843,United States,80000,1,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+12847,United States,60000,3,FALSE,TRUE,100,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+12849,United States,50000,1,FALSE,TRUE,20,Not remote,6,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+12852,United States,80000,7,FALSE,FALSE,20,Not remote,0,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+12854,United States,40000,1,FALSE,FALSE,20,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+12858,United Kingdom,33747.5,3,TRUE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+12859,United States,98000,20,FALSE,FALSE,10000,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+12864,United States,110000,11,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 12865,Germany,47311.8279569892,4,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12869,Canada,64393.9393939394,15,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+12869,Canada,64393.9393939394,15,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 12878,Canada,69696.9696969697,18,TRUE,TRUE,20,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 12879,Germany,12903.2258064516,4,FALSE,TRUE,1,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-12881,United Kingdom,35e3,15,TRUE,TRUE,20,Not remote,6,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
-12883,United States,7e4,10,FALSE,TRUE,100,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12890,United States,85e3,15,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+12881,United Kingdom,35000,15,TRUE,TRUE,20,Not remote,6,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
+12883,United States,70000,10,FALSE,TRUE,100,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+12890,United States,85000,15,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 12896,India,7341.06592277199,1,FALSE,TRUE,10,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-12901,India,36705.3296138599,6,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+12901,India,36705.3296138599,6,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 12906,Canada,41666.6666666667,2,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12912,United States,6e4,2,FALSE,FALSE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12923,United States,16e4,20,TRUE,FALSE,5e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+12912,United States,60000,2,FALSE,FALSE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+12923,United States,160000,20,TRUE,FALSE,5000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 12926,India,2128.90911760388,1,FALSE,TRUE,10,Remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12927,United States,75e3,1,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+12927,United States,75000,1,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 12928,Germany,139784.946236559,17,FALSE,TRUE,500,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 12939,Canada,69696.9696969697,6,TRUE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12940,United States,42e3,4,TRUE,TRUE,10,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+12940,United States,42000,4,TRUE,TRUE,10,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
 12945,United Kingdom,58750,3,FALSE,TRUE,100,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
 12946,United States,92500,10,FALSE,TRUE,20,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 12966,Canada,71969.696969697,2,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-12971,United States,92e3,13,FALSE,TRUE,1e4,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+12971,United States,92000,13,FALSE,TRUE,10000,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 12978,United States,51312,1,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12979,United States,9e4,19,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+12979,United States,90000,19,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 12981,United States,52500,1,FALSE,TRUE,1,Not remote,1,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE
-12983,United States,118e3,9,TRUE,FALSE,1,Remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12987,Canada,98484.8484848485,2,TRUE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-12988,United States,75e3,2,TRUE,TRUE,500,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12990,United States,6e4,16,FALSE,FALSE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-12991,United States,111e3,17,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12992,United States,66e3,5,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-12993,United States,95e3,20,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+12983,United States,118000,9,TRUE,FALSE,1,Remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+12987,Canada,98484.8484848485,2,TRUE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+12988,United States,75000,2,TRUE,TRUE,500,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+12990,United States,60000,16,FALSE,FALSE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+12991,United States,111000,17,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+12992,United States,66000,5,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+12993,United States,95000,20,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 12995,United States,146600,20,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
 13007,Germany,35483.8709677419,1,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 13008,United Kingdom,56250,11,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-13010,United States,95e3,2,FALSE,TRUE,20,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13021,United States,72e3,20,FALSE,FALSE,1e3,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13022,United States,99e3,6,TRUE,TRUE,1e4,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE
-13029,United States,85e3,1,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13030,United Kingdom,55e3,5,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13010,United States,95000,2,FALSE,TRUE,20,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13021,United States,72000,20,FALSE,FALSE,1000,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13022,United States,99000,6,TRUE,TRUE,10000,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE
+13029,United States,85000,1,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13030,United Kingdom,55000,5,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 13042,Canada,56060.6060606061,7,TRUE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13056,United States,115e3,20,FALSE,FALSE,20,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-13060,United States,106e3,12,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13063,United States,7e4,6,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+13056,United States,115000,20,FALSE,FALSE,20,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+13060,United States,106000,12,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13063,United States,70000,6,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 13066,Canada,37878.7878787879,4,FALSE,TRUE,1,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 13067,United States,62500,2,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-13069,United States,8e4,1,FALSE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-13082,Germany,86021.5053763441,14,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE,TRUE,TRUE
-13089,United States,112200,12,FALSE,TRUE,1e4,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13091,United States,75e3,6,FALSE,TRUE,20,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+13069,United States,80000,1,FALSE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+13082,Germany,86021.5053763441,14,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE,TRUE,TRUE
+13089,United States,112200,12,FALSE,TRUE,10000,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13091,United States,75000,6,FALSE,TRUE,20,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 13094,Germany,48387.0967741935,4,TRUE,FALSE,1,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
-13095,United States,61e3,2,FALSE,FALSE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13096,United States,34e3,1,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-13103,United States,9e4,7,FALSE,FALSE,100,Remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13095,United States,61000,2,FALSE,FALSE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13096,United States,34000,1,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+13103,United States,90000,7,FALSE,FALSE,100,Remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 13105,United States,106500,2,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13115,United States,11e4,7,FALSE,TRUE,20,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-13118,United States,12e4,13,TRUE,TRUE,20,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13115,United States,110000,7,FALSE,TRUE,20,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+13118,United States,120000,13,TRUE,TRUE,20,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 13131,Germany,64516.1290322581,9,FALSE,TRUE,10,Not remote,10,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-13135,United States,45e3,13,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13136,United States,125e3,18,FALSE,FALSE,5e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13147,United States,6e4,4,FALSE,TRUE,1,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13148,United States,9e4,1,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13149,United States,107e3,4,FALSE,TRUE,100,Not remote,8,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13154,United States,78e3,3,FALSE,FALSE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-13165,United States,105e3,5,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-13175,United States,145e3,6,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13180,United States,127e3,20,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13182,United States,82e3,9,FALSE,TRUE,100,Not remote,3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13184,United States,55e3,2,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13185,United States,52e3,1,FALSE,TRUE,1,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+13135,United States,45000,13,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13136,United States,125000,18,FALSE,FALSE,5000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13147,United States,60000,4,FALSE,TRUE,1,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13148,United States,90000,1,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13149,United States,107000,4,FALSE,TRUE,100,Not remote,8,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13154,United States,78000,3,FALSE,FALSE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+13165,United States,105000,5,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+13175,United States,145000,6,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13180,United States,127000,20,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13182,United States,82000,9,FALSE,TRUE,100,Not remote,3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13184,United States,55000,2,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13185,United States,52000,1,FALSE,TRUE,1,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 13196,Canada,42424.2424242424,1,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13201,United States,16e4,16,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13203,United States,109e3,3,FALSE,TRUE,1,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-13209,United States,13e4,9,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13213,United States,13e4,16,TRUE,TRUE,20,Remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+13201,United States,160000,16,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13203,United States,109000,3,FALSE,TRUE,1,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+13209,United States,130000,9,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13213,United States,130000,16,TRUE,TRUE,20,Remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 13217,United States,114792,20,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 13221,Canada,56818.1818181818,5,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-13225,United States,11e4,3,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13236,United States,17e4,14,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13247,United States,52e3,0,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13250,United States,12e4,3,TRUE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13272,Canada,54545.4545454545,3,FALSE,FALSE,5e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-13280,United Kingdom,6e4,2,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-13289,United States,5e4,4,FALSE,FALSE,1,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-13300,United States,9e4,4,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-13302,United States,111e3,9,FALSE,FALSE,1e4,Not remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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+13236,United States,170000,14,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13247,United States,52000,0,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13250,United States,120000,3,TRUE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13272,Canada,54545.4545454545,3,FALSE,FALSE,5000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+13280,United Kingdom,60000,2,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+13289,United States,50000,4,FALSE,FALSE,1,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+13300,United States,90000,4,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+13302,United States,111000,9,FALSE,FALSE,10000,Not remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 13319,Canada,45454.5454545455,2,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13320,United States,13e4,9,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13322,United States,31e3,2,TRUE,TRUE,1,Not remote,4,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13328,United States,125e3,20,TRUE,TRUE,1e4,Remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-13333,United States,14e4,3,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-13337,United States,108e3,3,TRUE,TRUE,100,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-13339,United States,75e3,1,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-13345,United States,141e3,9,TRUE,TRUE,20,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-13350,United States,12e4,1,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13357,United States,16e4,14,FALSE,TRUE,10,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
-13359,United States,105e3,2,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13361,United States,85e3,3,TRUE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13363,United States,1e5,5,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13371,United States,112e3,15,TRUE,FALSE,10,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13373,United States,75e3,5,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+13320,United States,130000,9,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13322,United States,31000,2,TRUE,TRUE,1,Not remote,4,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13328,United States,125000,20,TRUE,TRUE,10000,Remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+13333,United States,140000,3,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+13337,United States,108000,3,TRUE,TRUE,100,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+13339,United States,75000,1,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+13345,United States,141000,9,TRUE,TRUE,20,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+13350,United States,120000,1,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13357,United States,160000,14,FALSE,TRUE,10,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
+13359,United States,105000,2,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13361,United States,85000,3,TRUE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13363,United States,100000,5,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13371,United States,112000,15,TRUE,FALSE,10,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13373,United States,75000,5,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 13375,United States,117500,4,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13377,United States,9e4,2,FALSE,TRUE,20,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13379,United States,8e4,1,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+13377,United States,90000,2,FALSE,TRUE,20,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13379,United States,80000,1,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
 13400,India,8809.27910732638,4,TRUE,TRUE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-13404,United States,3e4,2,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13419,United States,149e3,13,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13424,United States,13e4,3,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13404,United States,30000,2,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13419,United States,149000,13,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13424,United States,130000,3,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 13425,Canada,42424.2424242424,6,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-13433,United States,8e4,17,TRUE,TRUE,20,Remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-13434,United States,135e3,2,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-13437,United States,76e3,2,TRUE,TRUE,100,Not remote,4,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-13438,United States,104e3,2,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13449,United States,13e4,3,FALSE,FALSE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13459,United States,14e4,4,TRUE,TRUE,1,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-13465,United States,87500,2,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13433,United States,80000,17,TRUE,TRUE,20,Remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+13434,United States,135000,2,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+13437,United States,76000,2,TRUE,TRUE,100,Not remote,4,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+13438,United States,104000,2,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13449,United States,130000,3,FALSE,FALSE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13459,United States,140000,4,TRUE,TRUE,1,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+13465,United States,87500,2,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 13466,India,23491.4109528704,4,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 13477,United States,31500,2,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13479,United States,16e4,20,TRUE,FALSE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+13479,United States,160000,20,TRUE,FALSE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
 13490,India,8809.27910732638,2,TRUE,TRUE,100,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE
-13493,United States,12e4,14,FALSE,FALSE,10,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13495,Germany,53763.4408602151,5,TRUE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13493,United States,120000,14,FALSE,FALSE,10,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13495,Germany,53763.4408602151,5,TRUE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 13497,India,37878.7878787879,2,FALSE,TRUE,10,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
-13500,United States,104e3,2,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13508,Germany,68817.2043010753,3,FALSE,FALSE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13516,United States,111800,4,TRUE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+13500,United States,104000,2,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13508,Germany,68817.2043010753,3,FALSE,FALSE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13516,United States,111800,4,TRUE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 13520,Canada,90500,10,FALSE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 13522,India,19820.8779914844,4,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 13526,India,11011.598884158,5,FALSE,TRUE,100,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
@@ -1887,8 +1887,8 @@ Respondent,Country,Salary,YearsCodedJob,OpenSource,Hobby,CompanySizeNumber,Remot
 13553,Germany,37500,3,FALSE,FALSE,10,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 13555,United Kingdom,52500,20,FALSE,TRUE,1,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 13556,India,2114.22698575833,1,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13574,United States,33e3,5,FALSE,TRUE,20,Not remote,9,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-13623,Germany,39139.7849462366,3,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+13574,United States,33000,5,FALSE,TRUE,20,Not remote,9,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+13623,Germany,39139.7849462366,3,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 13627,India,7047.42328586111,1,TRUE,TRUE,20,Not remote,10,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 13633,United Kingdom,46875,2,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 13636,United Kingdom,33750,4,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
@@ -1901,510 +1901,510 @@ Respondent,Country,Salary,YearsCodedJob,OpenSource,Hobby,CompanySizeNumber,Remot
 13759,Germany,55483.8709677419,20,FALSE,TRUE,10,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE
 13782,Canada,37878.7878787879,12,FALSE,TRUE,1,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
 13799,Germany,29677.4193548387,4,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13807,United Kingdom,75e3,20,TRUE,TRUE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13807,United Kingdom,75000,20,TRUE,TRUE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 13809,India,6695.05212156805,3,TRUE,FALSE,10,Not remote,3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 13811,United Kingdom,56250,9,FALSE,FALSE,10,Not remote,5,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13834,United States,106e3,2,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13842,United Kingdom,25e3,1,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+13834,United States,106000,2,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13842,United Kingdom,25000,1,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 13857,United States,113500,5,TRUE,TRUE,20,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 13871,United Kingdom,65625,3,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 13883,Germany,64516.1290322581,6,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13885,United States,45e3,1,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13893,United States,1e5,9,FALSE,TRUE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+13885,United States,45000,1,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13893,United States,100000,9,FALSE,TRUE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 13901,United States,88400,14,FALSE,TRUE,20,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-13907,United Kingdom,75e3,20,TRUE,TRUE,1e4,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-13909,United States,91707,13,FALSE,FALSE,1e3,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13927,United States,54e3,7,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13907,United Kingdom,75000,20,TRUE,TRUE,10000,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+13909,United States,91707,13,FALSE,FALSE,1000,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13927,United States,54000,7,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 13928,India,10277.4922918808,2,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 13930,Germany,41290.3225806452,5,FALSE,TRUE,20,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
-13933,United States,46e3,3,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13936,United States,101e3,1,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-13938,United States,1e5,4,TRUE,TRUE,10,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13933,United States,46000,3,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13936,United States,101000,1,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+13938,United States,100000,4,TRUE,TRUE,10,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 13941,India,19086.7713992072,1,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-13944,United States,89e3,13,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13944,United States,89000,13,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-13962,Canada,62878.7878787879,4,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-13972,United States,35e3,2,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-13975,United Kingdom,68750,17,FALSE,FALSE,1e3,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+13962,Canada,62878.7878787879,4,TRUE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+13972,United States,35000,2,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+13975,United Kingdom,68750,17,FALSE,FALSE,1000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 13980,Canada,56060.6060606061,20,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-13983,Canada,79545.4545454545,20,TRUE,TRUE,5e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
+13983,Canada,79545.4545454545,20,TRUE,TRUE,5000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
 13993,Germany,37419.3548387097,1,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-13995,United States,62e3,6,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
+13995,United States,62000,6,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
 13996,Germany,44086.0215053763,2,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14001,United States,55e3,2,FALSE,FALSE,1e4,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-14002,United States,95e3,14,FALSE,FALSE,20,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14001,United States,55000,2,FALSE,FALSE,10000,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+14002,United States,95000,14,FALSE,FALSE,20,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14014,Germany,67204.3010752688,7,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14018,United States,15e4,14,FALSE,FALSE,20,Not remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14020,United States,64e3,1,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14018,United States,150000,14,FALSE,FALSE,20,Not remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14020,United States,64000,1,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14036,Canada,37878.7878787879,5,FALSE,TRUE,20,Not remote,7,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14039,United States,75e3,1,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14052,United States,128e3,20,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+14039,United States,75000,1,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14052,United States,128000,20,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 14054,United States,76500,1,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14058,United Kingdom,42500,10,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14060,United Kingdom,81250,3,FALSE,TRUE,100,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14063,United States,6e4,1,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14069,United States,65e3,0,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14085,United States,66e3,2,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+14063,United States,60000,1,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14069,United States,65000,0,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14085,United States,66000,2,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
 14091,Canada,45454.5454545455,1,FALSE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14093,United States,75e3,3,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-14099,United States,116500,13,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14107,United States,12e4,6,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14093,United States,75000,3,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+14099,United States,116500,13,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14107,United States,120000,6,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14114,Canada,42424.2424242424,1,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14115,India,1908.67713992072,1,FALSE,TRUE,1e3,Not remote,6,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14121,United States,15e4,20,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14124,United States,78e3,3,TRUE,TRUE,1,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14130,United States,45e3,3,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14115,India,1908.67713992072,1,FALSE,TRUE,1000,Not remote,6,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14121,United States,150000,20,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14124,United States,78000,3,TRUE,TRUE,1,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14130,United States,45000,3,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14132,Canada,83333.3333333333,20,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14162,Canada,47727.2727272727,4,FALSE,TRUE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 14163,United States,173300,6,TRUE,TRUE,100,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14168,United States,75e3,4,TRUE,FALSE,1e4,Not remote,3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14170,United Kingdom,58750,13,TRUE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14173,United States,12e4,20,FALSE,FALSE,10,Not remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-14176,United States,8e4,10,FALSE,TRUE,100,Not remote,8,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14190,United States,135e3,7,TRUE,TRUE,100,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14191,United States,114e3,8,FALSE,TRUE,100,Remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+14168,United States,75000,4,TRUE,FALSE,10000,Not remote,3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14170,United Kingdom,58750,13,TRUE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14173,United States,120000,20,FALSE,FALSE,10,Not remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+14176,United States,80000,10,FALSE,TRUE,100,Not remote,8,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14190,United States,135000,7,TRUE,TRUE,100,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14191,United States,114000,8,FALSE,TRUE,100,Remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 14192,United States,84500,3,FALSE,TRUE,20,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14197,United States,13e4,17,FALSE,FALSE,100,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14201,United States,86e3,2,FALSE,TRUE,1e4,Not remote,2,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14202,United States,12e4,20,TRUE,FALSE,1e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-14203,Germany,55913.9784946237,3,FALSE,TRUE,1e4,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14205,United States,75e3,1,FALSE,TRUE,5e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-14207,United States,11e4,12,TRUE,TRUE,1,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+14197,United States,130000,17,FALSE,FALSE,100,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14201,United States,86000,2,FALSE,TRUE,10000,Not remote,2,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14202,United States,120000,20,TRUE,FALSE,1000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+14203,Germany,55913.9784946237,3,FALSE,TRUE,10000,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14205,United States,75000,1,FALSE,TRUE,5000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+14207,United States,110000,12,TRUE,TRUE,1,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 14213,United States,57500,9,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14217,United States,13e4,10,TRUE,TRUE,20,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14219,United States,145e3,11,FALSE,FALSE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14217,United States,130000,10,TRUE,TRUE,20,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14219,United States,145000,11,FALSE,FALSE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 14220,Germany,48387.0967741935,2,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14221,United States,9e4,5,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14222,United States,18e4,9,FALSE,TRUE,20,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14221,United States,90000,5,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14222,United States,180000,9,FALSE,TRUE,20,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 14225,Canada,81818.1818181818,4,TRUE,TRUE,100,Remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14226,United Kingdom,75e3,13,FALSE,FALSE,1,Not remote,8,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14226,United Kingdom,75000,13,FALSE,FALSE,1,Not remote,8,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14228,United Kingdom,31250,3,TRUE,TRUE,1,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14231,Germany,49032.2580645161,6,FALSE,TRUE,1e3,Not remote,7,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-14238,United States,85e3,9,TRUE,TRUE,1,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14239,United States,85e3,6,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14247,United States,6e4,2,TRUE,FALSE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14231,Germany,49032.2580645161,6,FALSE,TRUE,1000,Not remote,7,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+14238,United States,85000,9,TRUE,TRUE,1,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14239,United States,85000,6,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14247,United States,60000,2,TRUE,FALSE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14248,Germany,80645.1612903226,17,TRUE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14252,United States,72480,6,TRUE,TRUE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14253,Canada,54545.4545454545,10,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14255,United States,95e3,12,TRUE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14261,United States,95e3,7,FALSE,FALSE,20,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-14263,United States,124e3,1,FALSE,TRUE,100,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14266,United States,165e3,12,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
-14267,United States,147e3,6,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14253,Canada,54545.4545454545,10,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14255,United States,95000,12,TRUE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14261,United States,95000,7,FALSE,FALSE,20,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+14263,United States,124000,1,FALSE,TRUE,100,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14266,United States,165000,12,TRUE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
+14267,United States,147000,6,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14271,United States,72500,1,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14279,Canada,121212.121212121,14,TRUE,TRUE,1,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14284,United States,15e4,9,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14284,United States,150000,9,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14288,Germany,87204.3010752688,17,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14297,United States,12e4,17,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-14301,United States,142e3,13,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14297,United States,120000,17,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+14301,United States,142000,13,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14310,United States,67500,14,TRUE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14312,United States,11e4,10,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE
-14316,United States,113e3,16,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-14323,United States,8e4,8,TRUE,TRUE,1,Remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+14312,United States,110000,10,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE
+14316,United States,113000,16,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+14323,United States,80000,8,TRUE,TRUE,1,Remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 14326,Canada,60606.0606060606,15,FALSE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14328,United States,117e3,13,TRUE,TRUE,100,Not remote,9,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-14329,United States,125e3,10,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14336,United States,115e3,13,TRUE,TRUE,1,Remote,10,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE
+14328,United States,117000,13,TRUE,TRUE,100,Not remote,9,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+14329,United States,125000,10,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14336,United States,115000,13,TRUE,TRUE,1,Remote,10,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE
 14337,Canada,50757.5757575758,10,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 14341,Germany,48387.0967741935,1,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
 14342,United Kingdom,62500,5,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14349,United States,92e3,4,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-14356,United States,1e5,20,FALSE,FALSE,1,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14357,United States,125e3,5,FALSE,TRUE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+14349,United States,92000,4,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+14356,United States,100000,20,FALSE,FALSE,1,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14357,United States,125000,5,FALSE,TRUE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 14358,United States,42262,3,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14360,United States,121e3,5,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14364,United States,192e3,20,TRUE,TRUE,1e3,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-14369,United States,105e3,6,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14360,United States,121000,5,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14364,United States,192000,20,TRUE,TRUE,1000,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+14369,United States,105000,6,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 14372,United Kingdom,52500,5,FALSE,TRUE,10,Not remote,10,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-14380,United States,138e3,12,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-14383,United States,62e3,3,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14395,United States,16e4,20,FALSE,FALSE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-14396,United Kingdom,5e4,6,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14398,United States,126680,15,FALSE,FALSE,5e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14399,United States,12e4,8,FALSE,TRUE,20,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14400,United States,145e3,20,FALSE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-14405,United States,74e3,2,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14406,United States,153e3,10,TRUE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14407,United States,55e3,1,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14380,United States,138000,12,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+14383,United States,62000,3,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14395,United States,160000,20,FALSE,FALSE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+14396,United Kingdom,50000,6,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14398,United States,126680,15,FALSE,FALSE,5000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14399,United States,120000,8,FALSE,TRUE,20,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14400,United States,145000,20,FALSE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+14405,United States,74000,2,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14406,United States,153000,10,TRUE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14407,United States,55000,1,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14410,Germany,32258.064516129,2,FALSE,TRUE,1,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14423,United Kingdom,48620,1,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE
-14425,United States,105e3,2,TRUE,TRUE,1e4,Remote,10,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-14436,United Kingdom,21250,2,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+14423,United Kingdom,48620,1,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE
+14425,United States,105000,2,TRUE,TRUE,10000,Remote,10,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+14436,United Kingdom,21250,2,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 14442,Canada,56818.1818181818,2,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14453,United States,111e3,17,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14454,Canada,46969.696969697,16,FALSE,FALSE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14456,United States,87e3,5,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14462,United States,74e3,1,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-14463,Germany,56989.247311828,5,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14466,United States,84e3,6,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14453,United States,111000,17,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14454,Canada,46969.696969697,16,FALSE,FALSE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14456,United States,87000,5,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14462,United States,74000,1,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+14463,Germany,56989.247311828,5,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14466,United States,84000,6,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14470,Canada,26515.1515151515,2,TRUE,TRUE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-14473,United States,6e4,1,FALSE,TRUE,20,Not remote,9,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14479,United States,6e4,6,TRUE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14486,Canada,76515.1515151515,14,FALSE,TRUE,1e3,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14487,United States,6e4,2,FALSE,TRUE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14492,United States,172e3,12,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+14473,United States,60000,1,FALSE,TRUE,20,Not remote,9,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14479,United States,60000,6,TRUE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14486,Canada,76515.1515151515,14,FALSE,TRUE,1000,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14487,United States,60000,2,FALSE,TRUE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14492,United States,172000,12,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 14493,Canada,100378.787878788,13,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14495,United States,7e4,1,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE
+14495,United States,70000,1,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE
 14502,Canada,61328.7878787879,11,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 14515,Canada,56818.1818181818,11,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE
-14517,United States,95e3,7,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-14518,Germany,60215.0537634409,3,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14517,United States,95000,7,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+14518,Germany,60215.0537634409,3,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 14519,Canada,46969.696969697,4,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 14523,United Kingdom,46250,15,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 14525,Canada,45454.5454545455,9,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14527,United States,57e3,2,FALSE,FALSE,500,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE
-14530,United States,129e3,10,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14527,United States,57000,2,FALSE,FALSE,500,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE
+14530,United States,129000,10,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14534,Canada,41666.6666666667,2,TRUE,TRUE,500,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-14543,United States,71e3,5,FALSE,FALSE,20,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14547,United States,8e4,20,TRUE,TRUE,1,Remote,10,TRUE,TRUE,FALSE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-14548,United States,93e3,4,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+14543,United States,71000,5,FALSE,FALSE,20,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14547,United States,80000,20,TRUE,TRUE,1,Remote,10,TRUE,TRUE,FALSE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+14548,United States,93000,4,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 14552,Germany,64516.1290322581,7,TRUE,TRUE,100,Not remote,5,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-14554,Germany,14e4,8,TRUE,TRUE,20,Remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+14554,Germany,140000,8,TRUE,TRUE,20,Remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 14556,Canada,60606.0606060606,4,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-14562,United Kingdom,5e4,3,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14564,United States,117e3,16,FALSE,TRUE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-14566,Germany,10752.688172043,2,TRUE,FALSE,5e3,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-14568,United States,11e4,10,FALSE,FALSE,1e3,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14570,United States,14e4,20,TRUE,TRUE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14571,United States,150500,15,TRUE,FALSE,1e4,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14573,United States,8e4,3,TRUE,TRUE,1e3,Not remote,3,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-14582,United States,72e3,4,FALSE,TRUE,10,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-14584,United States,9e4,4,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-14592,United States,11e4,9,FALSE,FALSE,100,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14562,United Kingdom,50000,3,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14564,United States,117000,16,FALSE,TRUE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+14566,Germany,10752.688172043,2,TRUE,FALSE,5000,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+14568,United States,110000,10,FALSE,FALSE,1000,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14570,United States,140000,20,TRUE,TRUE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14571,United States,150500,15,TRUE,FALSE,10000,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14573,United States,80000,3,TRUE,TRUE,1000,Not remote,3,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+14582,United States,72000,4,FALSE,TRUE,10,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+14584,United States,90000,4,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+14592,United States,110000,9,FALSE,FALSE,100,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 14593,Canada,41666.6666666667,3,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14594,United States,166500,17,TRUE,TRUE,500,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-14595,United States,15e4,6,FALSE,FALSE,100,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14597,Germany,53763.4408602151,5,FALSE,TRUE,1e4,Not remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-14603,United States,115e3,10,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
-14604,United States,12e4,3,FALSE,FALSE,1e3,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14605,United States,5e4,2,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14595,United States,150000,6,FALSE,FALSE,100,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14597,Germany,53763.4408602151,5,FALSE,TRUE,10000,Not remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+14603,United States,115000,10,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+14604,United States,120000,3,FALSE,FALSE,1000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14605,United States,50000,2,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14617,United Kingdom,57500,7,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14618,Canada,49242.4242424242,2,FALSE,TRUE,500,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14621,United States,15e4,13,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14625,United States,56e3,1,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14621,United States,150000,13,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14625,United States,56000,1,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14627,Canada,60606.0606060606,11,FALSE,TRUE,1,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14628,Germany,50537.6344086021,8,FALSE,FALSE,1e3,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14629,United States,129e3,5,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14631,United Kingdom,7e4,9,TRUE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14636,United States,13e4,5,FALSE,TRUE,1e4,Not remote,5,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-14639,United States,72e3,4,FALSE,FALSE,10,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-14643,United States,65e3,20,TRUE,TRUE,1,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-14645,United States,9e4,5,FALSE,FALSE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14647,United States,113e3,1,TRUE,TRUE,1e4,Not remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14649,United Kingdom,37500,1,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14628,Germany,50537.6344086021,8,FALSE,FALSE,1000,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14629,United States,129000,5,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14631,United Kingdom,70000,9,TRUE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14636,United States,130000,5,FALSE,TRUE,10000,Not remote,5,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+14639,United States,72000,4,FALSE,FALSE,10,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+14643,United States,65000,20,TRUE,TRUE,1,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+14645,United States,90000,5,FALSE,FALSE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14647,United States,113000,1,TRUE,TRUE,10000,Not remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14649,United Kingdom,37500,1,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14652,Germany,92473.1182795699,14,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-14654,United States,115e3,9,FALSE,TRUE,20,Remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14654,United States,115000,9,FALSE,TRUE,20,Remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14658,Germany,41290.3225806452,4,FALSE,TRUE,20,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 14661,United Kingdom,62500,4,FALSE,FALSE,100,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14665,Canada,68181.8181818182,8,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14666,United States,11e4,5,TRUE,TRUE,1e4,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14666,United States,110000,5,TRUE,TRUE,10000,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14669,United States,46111,3,FALSE,TRUE,100,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14672,Germany,62365.5913978495,5,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-14677,United Kingdom,58750,3,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14681,United States,12e4,9,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-14685,United States,14e4,5,TRUE,TRUE,100,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-14686,United States,105e3,11,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14690,United States,155e3,13,FALSE,TRUE,100,Not remote,9,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+14677,United Kingdom,58750,3,TRUE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14681,United States,120000,9,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+14685,United States,140000,5,TRUE,TRUE,100,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+14686,United States,105000,11,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14690,United States,155000,13,FALSE,TRUE,100,Not remote,9,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
 14691,Germany,38709.6774193548,7,TRUE,FALSE,1,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 14694,United Kingdom,62500,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14695,Germany,77419.3548387097,15,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14699,Germany,33333.3333333333,2,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14702,United States,13e4,20,TRUE,TRUE,1e4,Remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-14714,United States,48e3,5,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-14726,United States,126e3,10,FALSE,TRUE,1,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
-14728,United States,102e3,15,FALSE,FALSE,100,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14729,United States,91e3,14,FALSE,FALSE,1e3,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14702,United States,130000,20,TRUE,TRUE,10000,Remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+14714,United States,48000,5,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+14726,United States,126000,10,FALSE,TRUE,1,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+14728,United States,102000,15,FALSE,FALSE,100,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14729,United States,91000,14,FALSE,FALSE,1000,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14731,Canada,65909.0909090909,7,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14732,United States,11e4,20,FALSE,TRUE,5e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14733,United States,11e4,7,FALSE,TRUE,100,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14738,United States,125e3,2,FALSE,TRUE,100,Not remote,4,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-14746,United States,11e4,2,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14747,United States,145e3,20,TRUE,FALSE,20,Not remote,9,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14748,United States,7e4,1,FALSE,FALSE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14750,United States,15e4,20,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+14732,United States,110000,20,FALSE,TRUE,5000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14733,United States,110000,7,FALSE,TRUE,100,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14738,United States,125000,2,FALSE,TRUE,100,Not remote,4,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+14746,United States,110000,2,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14747,United States,145000,20,TRUE,FALSE,20,Not remote,9,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14748,United States,70000,1,FALSE,FALSE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14750,United States,150000,20,TRUE,TRUE,10000,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 14753,United States,58420,9,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14755,Canada,75757.5757575758,10,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14757,United States,105e3,1,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
-14758,United States,115e3,3,TRUE,TRUE,500,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-14761,United States,12e4,3,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14763,United States,98e3,5,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14770,United Kingdom,62500,20,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14772,United States,115e3,20,FALSE,FALSE,20,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+14757,United States,105000,1,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+14758,United States,115000,3,TRUE,TRUE,500,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+14761,United States,120000,3,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14763,United States,98000,5,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14770,United Kingdom,62500,20,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14772,United States,115000,20,FALSE,FALSE,20,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
 14773,Germany,37634.4086021505,2,TRUE,TRUE,10,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-14775,United States,69200,2,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14775,United States,69200,2,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14777,Germany,55913.9784946237,2,FALSE,TRUE,20,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-14783,United States,188e3,20,TRUE,FALSE,1e4,Not remote,10,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14783,United States,188000,20,TRUE,FALSE,10000,Not remote,10,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 14789,United States,128500,15,TRUE,FALSE,10,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14791,Germany,77419.3548387097,16,FALSE,TRUE,100,Not remote,8,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14792,United States,11e4,1,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14797,United States,88e3,7,FALSE,TRUE,100,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14792,United States,110000,1,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14797,United States,88000,7,FALSE,TRUE,100,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 14799,United States,187500,6,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14805,United States,15e4,17,FALSE,TRUE,1e3,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14806,United States,17e4,12,TRUE,TRUE,100,Remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+14805,United States,150000,17,FALSE,TRUE,1000,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14806,United States,170000,12,TRUE,TRUE,100,Remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 14808,Canada,45454.5454545455,6,TRUE,TRUE,100,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-14810,United States,88e3,9,TRUE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14817,United States,1e5,3,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14819,United States,13e4,2,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14810,United States,88000,9,TRUE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14817,United States,100000,3,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14819,United States,130000,2,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 14821,Canada,56818.1818181818,7,FALSE,TRUE,10,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14839,United States,95e3,5,FALSE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14841,United States,85e3,2,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14839,United States,95000,5,FALSE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14841,United States,85000,2,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14846,Germany,45161.2903225806,15,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14847,Canada,45454.5454545455,2,FALSE,FALSE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-14861,United States,145e3,9,TRUE,TRUE,100,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-14864,United States,58e3,2,FALSE,TRUE,10,Not remote,7,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14866,United States,175e3,13,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14872,United States,77e3,1,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14861,United States,145000,9,TRUE,TRUE,100,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+14864,United States,58000,2,FALSE,TRUE,10,Not remote,7,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14866,United States,175000,13,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14872,United States,77000,1,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14878,United States,145600,19,FALSE,TRUE,20,Not remote,8,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-14890,United States,98e3,7,FALSE,TRUE,100,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14894,United States,9e4,7,TRUE,FALSE,20,Remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14890,United States,98000,7,FALSE,TRUE,100,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14894,United States,90000,7,TRUE,FALSE,20,Remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14898,Canada,45454.5454545455,2,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14906,United States,118e3,1,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14917,United States,81e3,7,FALSE,FALSE,1e3,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14906,United States,118000,1,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14917,United States,81000,7,FALSE,FALSE,1000,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14919,United Kingdom,48750,13,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
 14922,United Kingdom,41250,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 14932,Canada,59090.9090909091,5,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 14936,United States,97500,9,FALSE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-14938,United States,96e3,20,FALSE,TRUE,20,Remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14957,United States,63e3,1,TRUE,TRUE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
-14964,United States,8e4,3,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14938,United States,96000,20,FALSE,TRUE,20,Remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14957,United States,63000,1,TRUE,TRUE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+14964,United States,80000,3,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 14972,Canada,68181.8181818182,20,FALSE,TRUE,20,Remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-14973,United States,11e4,1,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14975,United States,4e4,13,FALSE,FALSE,1,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14977,United States,105e3,8,TRUE,TRUE,20,Remote,10,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14979,United States,45e3,9,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-14980,United States,93e3,6,TRUE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14981,United States,145e3,11,FALSE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
-14984,United States,119e3,17,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-14990,United States,7e4,1,FALSE,TRUE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-14994,United States,13e4,3,FALSE,TRUE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14973,United States,110000,1,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14975,United States,40000,13,FALSE,FALSE,1,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14977,United States,105000,8,TRUE,TRUE,20,Remote,10,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14979,United States,45000,9,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+14980,United States,93000,6,TRUE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14981,United States,145000,11,FALSE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+14984,United States,119000,17,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+14990,United States,70000,1,FALSE,TRUE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+14994,United States,130000,3,FALSE,TRUE,1000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15001,Canada,79545.4545454545,8,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
 15007,Germany,45161.2903225806,3,TRUE,FALSE,1,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15011,United States,92500,6,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-15016,United States,111e3,3,FALSE,FALSE,1e4,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-15021,United States,13e4,19,FALSE,TRUE,100,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15031,United States,175e3,20,TRUE,FALSE,5e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-15042,United States,138e3,14,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15043,United States,97e3,5,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-15044,United Kingdom,37500,14,FALSE,FALSE,1e4,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15054,United States,102e3,10,TRUE,FALSE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-15055,United States,9e4,2,FALSE,FALSE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15065,India,36705.3296138599,9,TRUE,TRUE,1e4,Remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+15016,United States,111000,3,FALSE,FALSE,10000,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+15021,United States,130000,19,FALSE,TRUE,100,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15031,United States,175000,20,TRUE,FALSE,5000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+15042,United States,138000,14,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15043,United States,97000,5,TRUE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+15044,United Kingdom,37500,14,FALSE,FALSE,10000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15054,United States,102000,10,TRUE,FALSE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+15055,United States,90000,2,FALSE,FALSE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15065,India,36705.3296138599,9,TRUE,TRUE,10000,Remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 15071,India,52855.6746439583,15,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15072,Germany,53763.4408602151,5,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15074,Canada,43939.3939393939,1,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15075,United States,166e3,10,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15075,United States,166000,10,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15079,Canada,53030.303030303,1,FALSE,TRUE,20,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-15080,United States,75e3,8,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+15080,United States,75000,8,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 15083,United States,50200,1,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15089,United States,175e3,12,FALSE,TRUE,1e4,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15103,United States,13e4,8,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+15089,United States,175000,12,FALSE,TRUE,10000,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15103,United States,130000,8,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 15113,India,2202.3197768316,1,FALSE,TRUE,20,Remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 15114,India,18323.3005432389,7,FALSE,FALSE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-15116,United States,135e3,8,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+15116,United States,135000,8,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 15119,India,7047.42328586111,2,TRUE,TRUE,10,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-15123,Germany,64516.1290322581,8,FALSE,FALSE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-15129,United States,155e3,14,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15123,Germany,64516.1290322581,8,FALSE,FALSE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+15129,United States,155000,14,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15133,India,10277.4922918808,1,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15136,India,20701.805902217,3,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15145,United States,8e4,2,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15145,United States,80000,2,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15165,India,13067.0973425341,1,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15173,United States,127e3,9,TRUE,TRUE,5e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-15178,India,12846.865364851,8,TRUE,FALSE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15173,United States,127000,9,TRUE,TRUE,5000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+15178,India,12846.865364851,8,TRUE,FALSE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15191,Germany,45161.2903225806,1,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15212,India,9543.38569960358,2,FALSE,TRUE,100,Not remote,9,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-15221,United States,134e3,3,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15221,United States,134000,3,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15255,United Kingdom,43750,2,FALSE,TRUE,100,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 15264,India,7341.06592277199,15,FALSE,FALSE,10,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE
-15267,United States,103e3,2,TRUE,TRUE,5e3,Not remote,4,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-15269,United Kingdom,41250,7,TRUE,TRUE,5e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+15267,United States,103000,2,TRUE,TRUE,5000,Not remote,4,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+15269,United Kingdom,41250,7,TRUE,TRUE,5000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 15270,India,14682.131845544,4,FALSE,TRUE,10,Not remote,9,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-15286,United Kingdom,47500,7,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15289,United Kingdom,25e3,1,FALSE,TRUE,1,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+15286,United Kingdom,47500,7,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15289,United Kingdom,25000,1,FALSE,TRUE,1,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 15299,Germany,75268.8172043011,15,TRUE,FALSE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 15326,Germany,61720.4301075269,10,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15336,India,8809.27910732638,4,TRUE,TRUE,1e4,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15358,United Kingdom,5e4,11,FALSE,FALSE,1e3,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-15360,India,30832.4768756423,3,FALSE,TRUE,1e3,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+15336,India,8809.27910732638,4,TRUE,TRUE,10000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15358,United Kingdom,50000,11,FALSE,FALSE,1000,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+15360,India,30832.4768756423,3,FALSE,TRUE,1000,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
 15368,Germany,54838.7096774193,7,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15375,Germany,48387.0967741935,4,FALSE,FALSE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 15382,United Kingdom,33750,2,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15411,United Kingdom,23750,2,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 15436,India,23491.4109528704,1,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15454,Germany,80645.1612903226,5,TRUE,TRUE,1e3,Not remote,5,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-15459,Germany,10322.5806451613,2,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15454,Germany,80645.1612903226,5,TRUE,TRUE,1000,Not remote,5,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+15459,Germany,10322.5806451613,2,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15465,India,2642.78373219792,2,TRUE,TRUE,1,Not remote,10,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15470,United Kingdom,42187.5,2,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+15470,United Kingdom,42187.5,2,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 15476,United Kingdom,47500,2,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 15485,India,14682.131845544,6,FALSE,TRUE,20,Remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15499,Germany,60215.0537634409,3,FALSE,TRUE,5e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15499,Germany,60215.0537634409,3,FALSE,TRUE,5000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15515,India,8809.27910732638,2,FALSE,TRUE,1,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 15519,United Kingdom,40625,2,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15540,Germany,43870.9677419355,16,FALSE,FALSE,1,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15541,United Kingdom,3e4,2,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15579,United States,12e4,9,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+15541,United Kingdom,30000,2,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15579,United States,120000,9,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 15585,United Kingdom,23750,1,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15588,Germany,68817.2043010753,8,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 15596,India,9543.38569960358,4,TRUE,TRUE,100,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15598,United States,115e3,15,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15598,United States,115000,15,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15634,India,3876.08280722361,2,FALSE,FALSE,20,Not remote,0,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15635,India,57260.3141976215,13,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 15643,United Kingdom,31250,2,FALSE,FALSE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-15649,India,8442.22581118779,2,FALSE,FALSE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15649,India,8442.22581118779,2,FALSE,FALSE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15668,India,7400,4,FALSE,FALSE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 15694,Germany,32258.064516129,3,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-15704,India,9102.92174423726,3,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15704,India,9102.92174423726,3,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15705,Germany,70967.7419354839,7,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 15708,India,3876.08280722361,3,FALSE,FALSE,20,Not remote,8,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15721,United Kingdom,77500,9,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15722,United States,85e3,20,FALSE,FALSE,1,Remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15722,United States,85000,20,FALSE,FALSE,1,Remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15723,United Kingdom,37500,2,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15736,Germany,32258.064516129,9,FALSE,TRUE,10,Not remote,5,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE
-15756,United Kingdom,41250,4,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15761,Germany,53763.4408602151,8,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-15774,United States,91e3,2,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15756,United Kingdom,41250,4,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15761,Germany,53763.4408602151,8,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+15774,United States,91000,2,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15777,Germany,64516.1290322581,6,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 15792,Germany,53763.4408602151,18,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15803,United States,68e3,6,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15806,United States,14e4,14,TRUE,FALSE,500,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+15803,United States,68000,6,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15806,United States,140000,14,TRUE,FALSE,500,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 15816,United Kingdom,88750,15,TRUE,TRUE,100,Remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-15817,United Kingdom,75e3,20,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE
+15817,United Kingdom,75000,20,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE
 15819,Germany,56989.247311828,4,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-15821,United Kingdom,35e3,2,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-15826,United States,5e4,3,TRUE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15828,United States,5e4,10,FALSE,TRUE,100,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-15853,United Kingdom,75e3,3,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15856,United States,65e3,11,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+15821,United Kingdom,35000,2,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+15826,United States,50000,3,TRUE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15828,United States,50000,10,FALSE,TRUE,100,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+15853,United Kingdom,75000,3,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15856,United States,65000,11,TRUE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 15860,Canada,56818.1818181818,10,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15861,Germany,134408.602150538,20,TRUE,FALSE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+15861,Germany,134408.602150538,20,TRUE,FALSE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 15868,Germany,125806.451612903,16,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15872,United Kingdom,56250,2,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 15876,United States,89600,6,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
-15878,United Kingdom,1e5,11,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15879,United States,12e4,4,FALSE,FALSE,1e3,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-15881,United States,46e3,1,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15895,India,6606.95933049479,2,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-15901,India,26427.8373219792,3,FALSE,FALSE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15902,United States,12e4,11,FALSE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15878,United Kingdom,100000,11,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15879,United States,120000,4,FALSE,FALSE,1000,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+15881,United States,46000,1,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15895,India,6606.95933049479,2,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+15901,India,26427.8373219792,3,FALSE,FALSE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15902,United States,120000,11,FALSE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15911,United Kingdom,31250,5,TRUE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15913,United States,85e3,5,TRUE,TRUE,1e3,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-15926,United States,70200,2,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+15913,United States,85000,5,TRUE,TRUE,1000,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+15926,United States,70200,2,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 15931,Canada,35454.5454545455,12,FALSE,FALSE,1,Remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-15941,United States,54e3,2,FALSE,TRUE,100,Not remote,2,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15941,United States,54000,2,FALSE,TRUE,100,Not remote,2,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15954,United Kingdom,32500,3,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15964,United States,185e3,10,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15990,United States,146e3,10,FALSE,TRUE,1e3,Remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE
+15964,United States,185000,10,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15990,United States,146000,10,FALSE,TRUE,1000,Remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE
 15992,United Kingdom,37500,10,FALSE,TRUE,20,Not remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15994,United States,108e3,17,TRUE,TRUE,1e3,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-15995,United States,86e3,3,FALSE,TRUE,20,Remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15994,United States,108000,17,TRUE,TRUE,1000,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+15995,United States,86000,3,FALSE,TRUE,20,Remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 15999,United Kingdom,93750,17,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 16000,United Kingdom,96250,9,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-16010,United States,155e3,20,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-16015,United States,13e4,6,FALSE,FALSE,1e4,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-16022,United States,99e3,5,TRUE,TRUE,1e3,Not remote,0,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-16033,United States,84e3,2,FALSE,FALSE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-16046,United Kingdom,35e3,1,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-16048,United States,85e3,8,TRUE,TRUE,1,Not remote,8,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-16051,United Kingdom,41250,7,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-16054,United States,95e3,3,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-16063,United States,9e4,3,FALSE,FALSE,1e4,Not remote,10,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
+16010,United States,155000,20,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+16015,United States,130000,6,FALSE,FALSE,10000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+16022,United States,99000,5,TRUE,TRUE,1000,Not remote,0,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+16033,United States,84000,2,FALSE,FALSE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+16046,United Kingdom,35000,1,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+16048,United States,85000,8,TRUE,TRUE,1,Not remote,8,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+16051,United Kingdom,41250,7,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+16054,United States,95000,3,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+16063,United States,90000,3,FALSE,FALSE,10000,Not remote,10,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
 16067,United Kingdom,33750,2,FALSE,TRUE,100,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-16074,United States,12e4,20,TRUE,FALSE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-16084,United States,8e4,14,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-16085,United States,135e3,5,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-16087,United States,55e3,4,FALSE,TRUE,20,Not remote,5,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-16089,United States,12e4,2,FALSE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+16074,United States,120000,20,TRUE,FALSE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+16084,United States,80000,14,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+16085,United States,135000,5,TRUE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+16087,United States,55000,4,FALSE,TRUE,20,Not remote,5,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+16089,United States,120000,2,FALSE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 16093,India,6342.680957275,1,FALSE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-16095,United States,55e3,1,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-16109,United States,7e4,3,FALSE,TRUE,10,Remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+16095,United States,55000,1,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+16109,United States,70000,3,FALSE,TRUE,10,Remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 16110,Germany,50537.6344086021,8,FALSE,FALSE,10,Remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 16131,United Kingdom,37500,1,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-16144,United States,116900,1,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
-16145,United States,102e3,9,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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+16145,United States,102000,9,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-16150,United States,8e4,1,FALSE,FALSE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-16151,United States,153e3,20,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
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-16172,United States,12e4,16,FALSE,TRUE,1e3,Not remote,10,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-16177,United States,95e3,9,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-16180,United Kingdom,52500,16,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-16190,United States,63e3,6,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-16192,United States,12e4,16,FALSE,FALSE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-16208,United States,127e3,9,TRUE,TRUE,500,Not remote,6,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-16213,United States,82e3,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-16229,United States,125e3,15,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+16198,United States,120000,15,FALSE,FALSE,20,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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 16260,United Kingdom,45243.75,10,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-16264,United States,105e3,3,FALSE,FALSE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-16266,United Kingdom,5e4,2,FALSE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-16271,United States,5e4,1,FALSE,TRUE,1e4,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+16264,United States,105000,3,FALSE,FALSE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+16266,United Kingdom,50000,2,FALSE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+16271,United States,50000,1,FALSE,TRUE,10000,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
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-16306,United States,5e4,6,FALSE,TRUE,10,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-16309,United States,6e4,4,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-16328,United States,112e3,12,FALSE,FALSE,5e3,Remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-16330,Germany,54838.7096774193,2,FALSE,TRUE,1e3,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-16331,Canada,75757.5757575758,11,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-16333,United States,8e4,2,FALSE,TRUE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-16341,United States,11e4,15,FALSE,FALSE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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+16330,Germany,54838.7096774193,2,FALSE,TRUE,1000,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+16331,Canada,75757.5757575758,11,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+16333,United States,80000,2,FALSE,TRUE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-16356,Germany,75268.8172043011,5,TRUE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+16354,United States,60000,3,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+16356,Germany,75268.8172043011,5,TRUE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-16405,United States,85e3,4,TRUE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-16407,United States,125e3,15,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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+16407,United States,125000,15,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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+16437,Germany,68279.5698924731,5,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-16461,Germany,80645.1612903226,12,FALSE,FALSE,1e3,Not remote,9,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+16459,United States,110000,2,FALSE,TRUE,20,Remote,10,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+16461,Germany,80645.1612903226,12,FALSE,FALSE,1000,Not remote,9,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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+16472,United States,175000,16,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-16481,United States,12e4,9,FALSE,TRUE,20,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-16486,United States,95e3,5,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-16497,Germany,53763.4408602151,8,TRUE,TRUE,1e3,Not remote,7,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-16499,United States,6e4,3,FALSE,TRUE,1e4,Remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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+16497,Germany,53763.4408602151,8,TRUE,TRUE,1000,Not remote,7,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
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-16521,United States,65e3,2,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-16572,United States,75e3,12,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-16598,United States,95e3,3,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-16669,United States,112e3,9,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-16708,India,7341.06592277199,3,TRUE,TRUE,1e4,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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+16768,United Kingdom,65000,10,FALSE,FALSE,20,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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@@ -2414,151 +2414,151 @@ Respondent,Country,Salary,YearsCodedJob,OpenSource,Hobby,CompanySizeNumber,Remot
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+16834,India,5138.74614594039,2,TRUE,TRUE,10000,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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-16917,India,25693.730729702,9,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-16919,United Kingdom,16049.3827160494,10,TRUE,TRUE,5e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+16917,India,25693.730729702,9,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+16919,United Kingdom,16049.3827160494,10,TRUE,TRUE,5000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 16931,Germany,48387.0967741935,5,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-16932,United Kingdom,65e3,18,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+16932,United Kingdom,65000,18,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 16943,India,2239.47446999104,2,FALSE,FALSE,10,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-16984,United States,12e4,4,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-17010,United Kingdom,55e3,15,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+16984,United States,120000,4,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17010,United Kingdom,55000,15,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-17040,United States,118e3,17,FALSE,TRUE,5e3,Remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+17040,United States,118000,17,FALSE,TRUE,5000,Remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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-17067,India,17618.5582146528,4,FALSE,FALSE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-17081,Germany,53763.4408602151,9,FALSE,FALSE,5e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17067,India,17618.5582146528,4,FALSE,FALSE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17081,Germany,53763.4408602151,9,FALSE,FALSE,5000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 17083,Germany,53763.4408602151,2,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-17084,United Kingdom,87500,20,FALSE,TRUE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-17090,Germany,53763.4408602151,16,FALSE,TRUE,1e3,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+17084,United Kingdom,87500,20,FALSE,TRUE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+17090,Germany,53763.4408602151,16,FALSE,TRUE,1000,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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-17112,United Kingdom,52500,4,TRUE,FALSE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17112,United Kingdom,52500,4,TRUE,FALSE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 17170,Canada,49242.4242424242,3,FALSE,TRUE,10,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-17178,United States,65e3,3,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17178,United States,65000,3,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 17180,Germany,59139.7849462366,5,FALSE,FALSE,1,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-17203,United States,85e3,8,FALSE,FALSE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-17210,United States,108e3,20,FALSE,TRUE,500,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-17214,India,5652.62076053443,2,FALSE,TRUE,1e4,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-17216,United Kingdom,35e3,1,TRUE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-17220,India,8075.17251504918,2,FALSE,TRUE,1e4,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17203,United States,85000,8,FALSE,FALSE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17210,United States,108000,20,FALSE,TRUE,500,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+17214,India,5652.62076053443,2,FALSE,TRUE,10000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17216,United Kingdom,35000,1,TRUE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+17220,India,8075.17251504918,2,FALSE,TRUE,10000,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 17222,United Kingdom,62500,4,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 17247,Germany,45161.2903225806,2,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 17249,United Kingdom,83750,15,TRUE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 17253,United Kingdom,68750,20,FALSE,TRUE,20,Not remote,6,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-17272,United States,7e4,2,FALSE,TRUE,1e4,Not remote,2,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-17277,United States,128e3,19,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17272,United States,70000,2,FALSE,TRUE,10000,Not remote,2,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+17277,United States,128000,19,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 17282,Germany,59139.7849462366,5,TRUE,TRUE,10,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
 17284,India,32300.6900601967,5,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-17285,United Kingdom,1e5,8,TRUE,TRUE,10,Remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17285,United Kingdom,100000,8,TRUE,TRUE,10,Remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 17287,Germany,48387.0967741935,2,TRUE,TRUE,10,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 17290,Canada,34090.9090909091,3,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-17291,United States,14e4,6,FALSE,TRUE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17291,United States,140000,6,FALSE,TRUE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 17297,United Kingdom,32500,20,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 17298,Canada,41666.6666666667,2,FALSE,FALSE,1,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 17301,Canada,71969.696969697,7,FALSE,FALSE,500,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
 17316,United Kingdom,33125,1,TRUE,FALSE,1,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-17323,United Kingdom,5e4,4,FALSE,TRUE,10,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-17342,United States,13e4,18,FALSE,TRUE,1,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-17343,United States,11e4,6,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-17344,United States,12e4,1,FALSE,TRUE,10,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+17323,United Kingdom,50000,4,FALSE,TRUE,10,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17342,United States,130000,18,FALSE,TRUE,1,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17343,United States,110000,6,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+17344,United States,120000,1,FALSE,TRUE,10,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 17346,Germany,29032.2580645161,10,TRUE,TRUE,1,Not remote,3,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-17348,United States,15e4,20,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17348,United States,150000,20,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 17368,Germany,45161.2903225806,17,FALSE,FALSE,20,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-17381,United States,105e3,4,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-17383,Germany,49e3,2,FALSE,TRUE,100,Not remote,4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-17398,United Kingdom,75e3,12,FALSE,FALSE,10,Not remote,9,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+17381,United States,105000,4,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+17383,Germany,49000,2,FALSE,TRUE,100,Not remote,4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+17398,United Kingdom,75000,12,FALSE,FALSE,10,Not remote,9,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 17425,United Kingdom,32500,2,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-17437,United States,55e3,2,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17437,United States,55000,2,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 17448,Canada,41666.6666666667,8,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 17462,Germany,41600,3,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-17466,United States,125e3,5,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-17471,United States,12e4,4,FALSE,FALSE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17466,United States,125000,5,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17471,United States,120000,4,FALSE,FALSE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 17492,United Kingdom,43750,5,FALSE,TRUE,20,Not remote,9,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-17503,Canada,31818.1818181818,3,FALSE,TRUE,1e3,Not remote,10,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE
-17505,United Kingdom,4e4,8,TRUE,TRUE,20,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17503,Canada,31818.1818181818,3,FALSE,TRUE,1000,Not remote,10,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE
+17505,United Kingdom,40000,8,TRUE,TRUE,20,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 17544,Canada,34090.9090909091,4,TRUE,TRUE,10,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 17556,Canada,34090.9090909091,1,TRUE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-17558,India,17618.5582146528,5,FALSE,TRUE,1e3,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-17561,United States,11e4,14,TRUE,TRUE,1e3,Remote,5,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-17565,United States,8e4,3,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17558,India,17618.5582146528,5,FALSE,TRUE,1000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+17561,United States,110000,14,TRUE,TRUE,1000,Remote,5,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+17565,United States,80000,3,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-17573,United States,19e4,20,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-17582,United States,41e3,5,FALSE,TRUE,20,Not remote,5,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-17591,Germany,51612.9032258064,1,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+17573,United States,190000,20,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+17582,United States,41000,5,FALSE,TRUE,20,Not remote,5,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17591,Germany,51612.9032258064,1,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 17609,Germany,22580.6451612903,5,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 17625,Canada,79545.4545454545,14,FALSE,TRUE,20,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE
 17646,Germany,8817.20430107527,3,FALSE,TRUE,20,Not remote,2,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 17652,Germany,33548.3870967742,5,FALSE,TRUE,1,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-17684,Germany,51612.9032258064,7,FALSE,FALSE,1e3,Remote,4,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17684,Germany,51612.9032258064,7,FALSE,FALSE,1000,Remote,4,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 17706,Germany,69892.4731182796,7,FALSE,FALSE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-17722,United Kingdom,87500,9,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-17725,Germany,51612.9032258064,9,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+17722,United Kingdom,87500,9,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17725,Germany,51612.9032258064,9,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 17732,Germany,76344.0860215054,8,TRUE,TRUE,100,Not remote,9,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 17742,Germany,62903.2258064516,7,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 17751,Germany,41935.4838709677,2,TRUE,TRUE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
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-17774,United Kingdom,4e4,2,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17774,United Kingdom,40000,2,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-17802,United States,65e3,9,FALSE,TRUE,100,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-17828,United Kingdom,37500,2,FALSE,FALSE,1e4,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17802,United States,65000,9,FALSE,TRUE,100,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+17828,United Kingdom,37500,2,FALSE,FALSE,10000,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 17857,Canada,41666.6666666667,4,FALSE,TRUE,1,Not remote,10,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
 17861,Germany,45161.2903225806,7,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-17870,Canada,39393.9393939394,5,FALSE,TRUE,1e4,Not remote,2,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-17873,United States,124e3,1,FALSE,FALSE,10,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-17895,United States,107700,4,TRUE,FALSE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+17870,Canada,39393.9393939394,5,FALSE,TRUE,10000,Not remote,2,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+17873,United States,124000,1,FALSE,FALSE,10,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17895,United States,107700,4,TRUE,FALSE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
 17896,Canada,38863.6363636364,1,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 17898,Canada,46575.7575757576,1,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-17920,India,35237.1164293055,11,FALSE,FALSE,1e4,Not remote,4,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17920,India,35237.1164293055,11,FALSE,FALSE,10000,Not remote,4,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 17959,Germany,64516.1290322581,8,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-17971,United States,12e4,6,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-17985,United States,16e4,20,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17971,United States,120000,6,TRUE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+17985,United States,160000,20,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 17991,Canada,37878.7878787879,2,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
 17995,Germany,75268.8172043011,8,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-18008,United Kingdom,88750,11,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-18027,United Kingdom,56250,8,FALSE,TRUE,1e4,Not remote,8,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-18031,United States,79e3,5,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-18055,United States,12e4,5,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-18059,United States,17e4,16,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-18070,United States,115e3,1,FALSE,TRUE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18008,United Kingdom,88750,11,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18027,United Kingdom,56250,8,FALSE,TRUE,10000,Not remote,8,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+18031,United States,79000,5,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18055,United States,120000,5,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18059,United States,170000,16,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18070,United States,115000,1,FALSE,TRUE,1000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 18079,Canada,49242.4242424242,1,TRUE,TRUE,100,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-18088,United States,118e3,2,FALSE,TRUE,5e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-18094,United States,1e5,1,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-18095,United Kingdom,133125,15,FALSE,TRUE,5e3,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-18096,India,8809.27910732638,7,FALSE,TRUE,1e4,Not remote,8,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-18100,United States,91500,5,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+18088,United States,118000,2,FALSE,TRUE,5000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18094,United States,100000,1,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18095,United Kingdom,133125,15,FALSE,TRUE,5000,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+18096,India,8809.27910732638,7,FALSE,TRUE,10000,Not remote,8,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+18100,United States,91500,5,TRUE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
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 18122,Canada,41666.6666666667,3,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-18125,United States,103e3,10,FALSE,TRUE,1e4,Remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-18138,United States,1e5,1,TRUE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-18141,United States,11e4,11,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-18142,United States,9e4,3,TRUE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-18144,United States,1e5,1,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18125,United States,103000,10,FALSE,TRUE,10000,Remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+18138,United States,100000,1,TRUE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18141,United States,110000,11,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18142,United States,90000,3,TRUE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18144,United States,100000,1,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-18146,United States,95e3,2,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-18151,United States,1e5,14,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE
-18181,United States,14e4,7,TRUE,TRUE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-18189,United States,135e3,20,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-18201,India,3523.71164293055,1,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-18214,United States,14e4,20,FALSE,FALSE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18146,United States,95000,2,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+18151,United States,100000,14,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE
+18181,United States,140000,7,TRUE,TRUE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18189,United States,135000,20,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+18201,India,3523.71164293055,1,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+18214,United States,140000,20,FALSE,FALSE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 18218,India,1211.27587725738,1,FALSE,FALSE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-18238,United States,195e3,10,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18238,United States,195000,10,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 18250,Canada,60606.0606060606,2,FALSE,TRUE,1,Remote,7,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 18258,India,5872.85273821759,3,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 18300,Germany,61505.376344086,9,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-18308,United States,147e3,3,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18308,United States,147000,3,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 18309,Germany,64516.1290322581,4,FALSE,FALSE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-18315,Germany,55913.9784946237,7,TRUE,TRUE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18315,Germany,55913.9784946237,7,TRUE,TRUE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 18343,Canada,60606.0606060606,6,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 18346,India,1761.85582146528,1,FALSE,FALSE,10,Not remote,2,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 18349,India,3670.53296138599,1,TRUE,TRUE,10,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
@@ -2570,186 +2570,186 @@ Respondent,Country,Salary,YearsCodedJob,OpenSource,Hobby,CompanySizeNumber,Remot
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 18481,India,4404.63955366319,1,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 18498,India,17618.5582146528,6,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-18502,United Kingdom,25e3,2,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-18504,Germany,27956.9892473118,5,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
-18530,United Kingdom,43750,3,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18502,United Kingdom,25000,2,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18504,Germany,27956.9892473118,5,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
+18530,United Kingdom,43750,3,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 18538,India,10277.4922918808,3,TRUE,TRUE,500,Not remote,8,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-18546,United Kingdom,5e4,9,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-18557,United Kingdom,63750,20,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+18546,United Kingdom,50000,9,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18557,United Kingdom,63750,20,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 18561,United Kingdom,56250,12,TRUE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 18567,India,8809.27910732638,2,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-18572,India,13213.9186609896,4,FALSE,FALSE,1e3,Not remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+18572,India,13213.9186609896,4,FALSE,FALSE,1000,Not remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-18604,United Kingdom,28750,2,FALSE,TRUE,1e4,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-18613,United Kingdom,35e3,1,FALSE,TRUE,1e4,Not remote,4,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+18604,United Kingdom,28750,2,FALSE,TRUE,10000,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+18613,United Kingdom,35000,1,FALSE,TRUE,10000,Not remote,4,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
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-18667,Germany,59139.7849462366,6,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-18696,United States,12e4,20,FALSE,FALSE,1e4,Remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18667,Germany,59139.7849462366,6,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+18696,United States,120000,20,FALSE,FALSE,10000,Remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-18707,United Kingdom,144086.021505376,9,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18707,United Kingdom,144086.021505376,9,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-18751,United States,87e3,10,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-18774,United Kingdom,45e3,6,TRUE,TRUE,5e3,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-18775,Germany,64516.1290322581,4,FALSE,FALSE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-18783,United Kingdom,87500,17,FALSE,TRUE,1e4,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+18751,United States,87000,10,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+18774,United Kingdom,45000,6,TRUE,TRUE,5000,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18775,Germany,64516.1290322581,4,FALSE,FALSE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+18783,United Kingdom,87500,17,FALSE,TRUE,10000,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
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-18805,India,13213.9186609896,5,TRUE,TRUE,5e3,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-18823,United States,84e3,10,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18805,India,13213.9186609896,5,TRUE,TRUE,5000,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18823,United States,84000,10,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-18906,United States,105e3,6,FALSE,TRUE,10,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-18930,United States,9e4,7,FALSE,FALSE,1e4,Remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+18906,United States,105000,6,FALSE,TRUE,10,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18930,United States,90000,7,FALSE,FALSE,10000,Remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-18945,Canada,90909.0909090909,12,TRUE,TRUE,1e3,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+18945,Canada,90909.0909090909,12,TRUE,TRUE,1000,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-18986,United States,15e4,9,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-18990,United States,155e3,16,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-18991,United Kingdom,62500,6,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+18986,United States,150000,9,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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+18991,United Kingdom,62500,6,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
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-19006,United States,65e3,14,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19007,United States,65e3,1,FALSE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19015,United States,7e4,2,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19006,United States,65000,14,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19007,United States,65000,1,FALSE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19015,United States,70000,2,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-19047,United Kingdom,43750,8,TRUE,TRUE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19056,United States,14e4,3,TRUE,TRUE,1e4,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+19047,United Kingdom,43750,8,TRUE,TRUE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19056,United States,140000,3,TRUE,TRUE,10000,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 19074,United Kingdom,87500,8,FALSE,TRUE,1,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19080,United States,65e3,5,FALSE,TRUE,1,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19080,United States,65000,5,FALSE,TRUE,1,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 19087,Germany,80645.1612903226,7,FALSE,FALSE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 19089,United Kingdom,41250,3,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19101,United States,11e4,20,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+19101,United States,110000,20,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 19103,Germany,55913.9784946237,6,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19105,United States,91e3,2,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19113,United States,139e3,10,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19122,United Kingdom,25e3,2,TRUE,TRUE,10,Not remote,8,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19127,United Kingdom,35e3,1,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19140,Germany,53763.4408602151,2,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19146,United States,85e3,3,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19150,United States,1e5,15,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-19159,United States,1e5,2,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19189,United States,68400,2,FALSE,TRUE,1e3,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-19200,United States,6e4,2,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
+19105,United States,91000,2,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19113,United States,139000,10,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19122,United Kingdom,25000,2,TRUE,TRUE,10,Not remote,8,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19127,United Kingdom,35000,1,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19140,Germany,53763.4408602151,2,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19146,United States,85000,3,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19150,United States,100000,15,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+19159,United States,100000,2,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19189,United States,68400,2,FALSE,TRUE,1000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+19200,United States,60000,2,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
 19208,United Kingdom,36875,4,TRUE,TRUE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19210,United States,4e4,2,FALSE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19225,United States,95e3,4,TRUE,FALSE,10,Remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19235,United Kingdom,125e3,8,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+19210,United States,40000,2,FALSE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19225,United States,95000,4,TRUE,FALSE,10,Remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19235,United Kingdom,125000,8,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-19237,Canada,45454.5454545455,1,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-19239,United States,12e4,20,FALSE,TRUE,20,Remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-19243,United States,102e3,10,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19249,United States,147e3,3,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19252,United States,75e3,2,FALSE,TRUE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19237,Canada,45454.5454545455,1,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+19239,United States,120000,20,FALSE,TRUE,20,Remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+19243,United States,102000,10,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19249,United States,147000,3,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19252,United States,75000,2,FALSE,TRUE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 19257,United Kingdom,37500,3,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 19263,Germany,52903.2258064516,3,TRUE,TRUE,20,Not remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19266,Germany,47096.7741935484,2,TRUE,TRUE,1e3,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+19266,Germany,47096.7741935484,2,TRUE,TRUE,1000,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 19282,United Kingdom,28750,3,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19288,United States,8e4,14,TRUE,FALSE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19288,United States,80000,14,TRUE,FALSE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 19294,Germany,51612.9032258064,3,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19310,United States,108552,20,FALSE,FALSE,1e4,Remote,8,FALSE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
-19328,United Kingdom,55e3,5,TRUE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-19339,United States,133e3,20,FALSE,FALSE,1e4,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-19346,United States,65e3,1,FALSE,TRUE,1e3,Not remote,6,FALSE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,TRUE
-19355,United Kingdom,5e4,3,FALSE,TRUE,100,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-19362,United States,1e5,8,FALSE,TRUE,20,Not remote,6,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-19363,United States,14e4,9,FALSE,TRUE,100,Remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19365,United States,145e3,4,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+19310,United States,108552,20,FALSE,FALSE,10000,Remote,8,FALSE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+19328,United Kingdom,55000,5,TRUE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+19339,United States,133000,20,FALSE,FALSE,10000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+19346,United States,65000,1,FALSE,TRUE,1000,Not remote,6,FALSE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,TRUE
+19355,United Kingdom,50000,3,FALSE,TRUE,100,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+19362,United States,100000,8,FALSE,TRUE,20,Not remote,6,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+19363,United States,140000,9,FALSE,TRUE,100,Remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19365,United States,145000,4,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 19368,United Kingdom,62500,5,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-19391,United States,115e3,6,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-19394,United States,122e3,5,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19391,United States,115000,6,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+19394,United States,122000,5,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 19408,Germany,43010.752688172,5,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19427,United States,9e4,2,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-19428,United States,125e3,4,TRUE,TRUE,20,Not remote,8,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-19435,United States,63e3,4,FALSE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19437,Germany,60215.0537634409,3,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-19440,United Kingdom,45e3,5,FALSE,TRUE,5e3,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19467,United States,35e3,3,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19427,United States,90000,2,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+19428,United States,125000,4,TRUE,TRUE,20,Not remote,8,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+19435,United States,63000,4,FALSE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19437,Germany,60215.0537634409,3,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+19440,United Kingdom,45000,5,FALSE,TRUE,5000,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19467,United States,35000,3,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 19473,Canada,34090.9090909091,2,FALSE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19474,United States,9e4,6,TRUE,TRUE,20,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-19484,United Kingdom,1e5,12,FALSE,TRUE,10,Not remote,9,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+19474,United States,90000,6,TRUE,TRUE,20,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+19484,United Kingdom,100000,12,FALSE,TRUE,10,Not remote,9,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 19506,Canada,41666.6666666667,2,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-19514,United States,4e4,1,TRUE,TRUE,10,Not remote,7,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,TRUE,TRUE,TRUE
-19523,United States,175e3,17,FALSE,TRUE,100,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-19535,United Kingdom,68750,20,FALSE,TRUE,1e3,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+19514,United States,40000,1,TRUE,TRUE,10,Not remote,7,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,TRUE,TRUE,TRUE
+19523,United States,175000,17,FALSE,TRUE,100,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+19535,United Kingdom,68750,20,FALSE,TRUE,1000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-19545,United States,11e4,7,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19547,United States,1e5,10,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19564,United States,75e3,3,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19545,United States,110000,7,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19547,United States,100000,10,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19564,United States,75000,3,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-19571,United States,8e4,2,FALSE,TRUE,1e4,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-19572,Canada,45454.5454545455,1,TRUE,TRUE,1e4,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19573,United States,11e4,6,FALSE,TRUE,5e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-19575,United States,8e4,4,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19584,United States,18e4,20,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19594,United States,105e3,20,TRUE,TRUE,5e3,Not remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
+19571,United States,80000,2,FALSE,TRUE,10000,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+19572,Canada,45454.5454545455,1,TRUE,TRUE,10000,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19573,United States,110000,6,FALSE,TRUE,5000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+19575,United States,80000,4,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19584,United States,180000,20,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19594,United States,105000,20,TRUE,TRUE,5000,Not remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
 19600,Germany,75268.8172043011,7,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 19604,United States,88200,7,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-19606,United States,11e4,17,FALSE,TRUE,500,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19607,United States,72e3,3,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19611,United States,11e4,9,FALSE,TRUE,20,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,TRUE
+19606,United States,110000,17,FALSE,TRUE,500,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19607,United States,72000,3,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19611,United States,110000,9,FALSE,TRUE,20,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,TRUE
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-19633,United States,6e4,2,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19634,United States,145e3,7,FALSE,FALSE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19638,United States,155e3,12,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19641,United States,11e4,1,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+19633,United States,60000,2,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19634,United States,145000,7,FALSE,FALSE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19638,United States,155000,12,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19641,United States,110000,1,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
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-19651,United States,15e4,20,TRUE,FALSE,500,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19651,United States,150000,20,TRUE,FALSE,500,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-19662,United States,9e4,5,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19678,United States,75e3,14,FALSE,FALSE,1e3,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19691,United States,11e4,9,FALSE,TRUE,10,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-19703,United States,85e3,6,FALSE,FALSE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19705,United States,18e4,20,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
-19707,United States,145e3,9,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19726,United States,127e3,20,TRUE,TRUE,500,Not remote,5,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19739,United States,6e4,9,FALSE,TRUE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19750,United States,105e3,5,FALSE,TRUE,1e3,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19662,United States,90000,5,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19678,United States,75000,14,FALSE,FALSE,1000,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19691,United States,110000,9,FALSE,TRUE,10,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+19703,United States,85000,6,FALSE,FALSE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19705,United States,180000,20,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
+19707,United States,145000,9,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19726,United States,127000,20,TRUE,TRUE,500,Not remote,5,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19739,United States,60000,9,FALSE,TRUE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19750,United States,105000,5,FALSE,TRUE,1000,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-19770,United States,13e4,8,TRUE,TRUE,1e3,Remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE
-19778,United States,13e4,10,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19791,United States,84e3,2,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-19792,United States,16e4,6,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-19794,United States,75e3,2,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19796,United States,69806.0606060606,1,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE
-19803,United States,98e3,8,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-19816,United States,76e3,1,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+19770,United States,130000,8,TRUE,TRUE,1000,Remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE
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 21652,Canada,68181.8181818182,15,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-21661,United States,8e4,9,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-21662,United States,115e3,5,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-21692,Germany,64516.1290322581,3,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+21661,United States,80000,9,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+21662,United States,115000,5,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+21692,Germany,64516.1290322581,3,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 21702,United States,71500,3,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-21705,United States,75e3,3,FALSE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+21705,United States,75000,3,FALSE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 21710,Canada,64393.9393939394,5,FALSE,FALSE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-21716,United States,105e3,9,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-21728,United States,134e3,1,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-21729,United States,49e3,2,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-21762,India,25693.730729702,14,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+21716,United States,105000,9,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+21728,United States,134000,1,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+21729,United States,49000,2,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+21762,India,25693.730729702,14,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 21764,India,4698.28219057407,2,FALSE,FALSE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 21777,India,7047.42328586111,0,TRUE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 21794,India,2114.22698575833,0,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE
@@ -2933,22 +2933,22 @@ Respondent,Country,Salary,YearsCodedJob,OpenSource,Hobby,CompanySizeNumber,Remot
 21850,India,10277.4922918808,3,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 21857,India,22023.197768316,1,FALSE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 21860,India,1761.85582146528,2,FALSE,TRUE,10,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-21875,United States,15e4,4,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+21875,United States,150000,4,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 21889,Germany,42030.1075268817,1,FALSE,FALSE,100,Not remote,10,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-21897,United Kingdom,3e4,2,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+21897,United Kingdom,30000,2,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
 21907,Germany,3225.8064516129,2,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 21917,India,7341.06592277199,3,FALSE,TRUE,10,Remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 21920,Germany,64516.1290322581,9,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 21926,Germany,51612.9032258064,4,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
 21935,India,8809.27910732638,3,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-21999,United Kingdom,15e3,1,FALSE,FALSE,1,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-22000,India,14682.131845544,5,FALSE,FALSE,1e3,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+21999,United Kingdom,15000,1,FALSE,FALSE,1,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+22000,India,14682.131845544,5,FALSE,FALSE,1000,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 22008,India,2657.46586404346,1,TRUE,TRUE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 22009,United Kingdom,72500,16,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-22047,United Kingdom,48625,1,FALSE,FALSE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-22060,Germany,75268.8172043011,12,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+22047,United Kingdom,48625,1,FALSE,FALSE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+22060,Germany,75268.8172043011,12,TRUE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 22062,India,5138.74614594039,3,TRUE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-22072,United Kingdom,5e4,4,FALSE,FALSE,10,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+22072,United Kingdom,50000,4,FALSE,FALSE,10,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 22073,United Kingdom,41875,4,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 22089,Germany,62365.5913978495,5,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 22091,Germany,69892.4731182796,4,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
@@ -2956,339 +2956,339 @@ Respondent,Country,Salary,YearsCodedJob,OpenSource,Hobby,CompanySizeNumber,Remot
 22122,Germany,52903.2258064516,4,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 22146,Canada,85416.6666666667,20,FALSE,TRUE,20,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 22178,United Kingdom,56250,4,FALSE,FALSE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-22222,Canada,42651.5151515152,2,FALSE,FALSE,5e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+22222,Canada,42651.5151515152,2,FALSE,FALSE,5000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
 22224,India,8075.17251504918,4,FALSE,FALSE,20,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-22227,Germany,69892.4731182796,9,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-22231,Germany,56989.247311828,3,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+22227,Germany,69892.4731182796,9,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+22231,Germany,56989.247311828,3,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 22234,Germany,35483.8709677419,5,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-22245,United States,18e4,20,TRUE,TRUE,1,Not remote,10,FALSE,TRUE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+22245,United States,180000,20,TRUE,TRUE,1,Not remote,10,FALSE,TRUE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 22251,United Kingdom,62500,5,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
-22259,United Kingdom,26875,1,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+22259,United Kingdom,26875,1,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 22262,United Kingdom,26250,3,TRUE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 22275,Germany,43010.752688172,3,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-22284,United States,108e3,11,TRUE,TRUE,5e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-22298,United States,103e3,20,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+22284,United States,108000,11,TRUE,TRUE,5000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+22298,United States,103000,20,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 22301,Germany,64516.1290322581,14,FALSE,TRUE,500,Not remote,8,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 22302,Germany,3225.8064516129,2,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-22318,United States,19e4,16,FALSE,FALSE,5e3,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-22338,Germany,118279.569892473,9,TRUE,TRUE,1e4,Not remote,4,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+22318,United States,190000,16,FALSE,FALSE,5000,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+22338,Germany,118279.569892473,9,TRUE,TRUE,10000,Not remote,4,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
 22339,India,13213.9186609896,10,TRUE,TRUE,100,Not remote,6,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 22355,Germany,45161.2903225806,2,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE
 22372,Germany,38709.6774193548,3,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 22375,India,2114.22698575833,1,TRUE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-22399,United States,85e3,3,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+22399,United States,85000,3,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 22406,United Kingdom,51250,2,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 22412,Germany,69892.4731182796,10,FALSE,TRUE,1,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-22414,Germany,53763.4408602151,5,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-22419,Germany,48387.0967741935,6,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+22414,Germany,53763.4408602151,5,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+22419,Germany,48387.0967741935,6,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 22431,Germany,91397.8494623656,8,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-22435,United States,14e4,14,FALSE,TRUE,1e3,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-22438,United Kingdom,62500,9,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+22435,United States,140000,14,FALSE,TRUE,1000,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+22438,United Kingdom,62500,9,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 22447,United Kingdom,46875,2,FALSE,FALSE,100,Not remote,6,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-22455,United States,5e4,2,FALSE,FALSE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-22462,United States,11e4,17,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-22466,United States,53e3,9,FALSE,TRUE,500,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-22472,United States,12e4,14,FALSE,TRUE,10,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+22455,United States,50000,2,FALSE,FALSE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+22462,United States,110000,17,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+22466,United States,53000,9,FALSE,TRUE,500,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+22472,United States,120000,14,FALSE,TRUE,10,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 22474,Germany,62365.5913978495,4,FALSE,TRUE,10,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 22488,Germany,74193.5483870968,10,FALSE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-22489,United States,17e4,10,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-22510,Canada,71969.696969697,10,TRUE,FALSE,1e3,Not remote,8,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-22515,United States,6e4,2,TRUE,TRUE,100,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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-22530,United States,135e3,20,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+22489,United States,170000,10,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+22510,Canada,71969.696969697,10,TRUE,FALSE,1000,Not remote,8,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+22515,United States,60000,2,TRUE,TRUE,100,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+22528,United Kingdom,37500,0,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+22530,United States,135000,20,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 22545,United Kingdom,31250,1,FALSE,FALSE,20,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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 22581,Germany,3333.33333333333,14,TRUE,TRUE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 22585,Canada,45454.5454545455,1,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-22606,United States,7e4,5,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-22612,United Kingdom,4e4,5,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-22619,United States,9e4,3,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE
+22606,United States,70000,5,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+22612,United Kingdom,40000,5,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+22619,United States,90000,3,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE
 22622,United Kingdom,87500,12,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 22623,Germany,51612.9032258064,5,FALSE,FALSE,20,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 22627,United Kingdom,52500,2,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-22630,United States,65e3,14,TRUE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+22630,United States,65000,14,TRUE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 22635,Germany,46451.6129032258,5,FALSE,TRUE,10,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-22667,United Kingdom,40400,9,FALSE,TRUE,1e3,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE
-22668,United States,9e4,9,FALSE,FALSE,100,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-22694,United Kingdom,2e4,2,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+22667,United Kingdom,40400,9,FALSE,TRUE,1000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE
+22668,United States,90000,9,FALSE,FALSE,100,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+22694,United Kingdom,20000,2,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 22708,United Kingdom,42500,7,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 22716,Germany,64516.1290322581,15,FALSE,TRUE,20,Not remote,9,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
-22721,United States,6e4,2,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-22724,United States,65e3,3,TRUE,TRUE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-22733,United States,6e4,2,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-22737,United States,14e4,15,FALSE,TRUE,20,Remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-22753,Canada,83333.3333333333,10,FALSE,TRUE,1e3,Not remote,8,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+22721,United States,60000,2,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+22724,United States,65000,3,TRUE,TRUE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+22733,United States,60000,2,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+22737,United States,140000,15,FALSE,TRUE,20,Remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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 23559,Germany,59139.7849462366,14,FALSE,FALSE,20,Not remote,8,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 23619,United Kingdom,57937.5,20,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 23635,United Kingdom,66250,9,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 23657,Germany,69892.4731182796,11,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-23664,United States,83e3,20,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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 23710,Germany,12903.2258064516,2,FALSE,FALSE,10,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE
 23714,Germany,41935.4838709677,9,FALSE,FALSE,1,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
 23723,United Kingdom,18750,1,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 23736,United Kingdom,51250,5,TRUE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 23757,India,3964.17559829687,2,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 23771,Germany,75268.8172043011,4,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-23803,United Kingdom,25e3,2,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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 23805,Germany,45161.2903225806,1,TRUE,FALSE,20,Not remote,3,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
 23833,United Kingdom,31250,1,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 23835,United Kingdom,53750,20,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 23900,United Kingdom,42500,1,TRUE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 23907,United Kingdom,87500,10,FALSE,TRUE,1,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE
-23912,United Kingdom,46875,20,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+23912,United Kingdom,46875,20,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 23918,United Kingdom,22500,1,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-23956,India,12479.8120687124,2,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-23969,Canada,69696.9696969697,19,TRUE,FALSE,1e3,Not remote,8,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-23977,United Kingdom,63750,2,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-23984,United States,7e4,5,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-24024,United Kingdom,54062.5,20,FALSE,TRUE,1e4,Remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+23956,India,12479.8120687124,2,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+23969,Canada,69696.9696969697,19,TRUE,FALSE,1000,Not remote,8,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+23977,United Kingdom,63750,2,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+23984,United States,70000,5,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+24024,United Kingdom,54062.5,20,FALSE,TRUE,10000,Remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 24029,Germany,43010.752688172,3,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-24032,United Kingdom,32500,1,FALSE,TRUE,1e3,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
-24044,Canada,65909.0909090909,10,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+24032,United Kingdom,32500,1,FALSE,TRUE,1000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+24044,Canada,65909.0909090909,10,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 24046,Germany,37419.3548387097,7,FALSE,TRUE,1,Not remote,3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE
 24070,United Kingdom,31250,3,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-24079,United Kingdom,25e3,1,FALSE,TRUE,10,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-24081,United States,115e3,20,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-24088,United States,88e3,5,FALSE,TRUE,1e4,Not remote,8,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE
+24079,United Kingdom,25000,1,FALSE,TRUE,10,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+24081,United States,115000,20,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+24088,United States,88000,5,FALSE,TRUE,10000,Not remote,8,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE
 24096,United States,91200,10,TRUE,TRUE,1,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-24097,United Kingdom,75e3,5,TRUE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+24097,United Kingdom,75000,5,TRUE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 24107,Germany,51612.9032258064,7,FALSE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 24109,Germany,66666.6666666667,13,FALSE,FALSE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 24114,Canada,60606.0606060606,14,TRUE,TRUE,10,Remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 24122,United Kingdom,43250,3,FALSE,TRUE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-24136,United States,87e3,8,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+24136,United States,87000,8,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 24142,Germany,53763.4408602151,15,FALSE,FALSE,20,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-24178,United States,11e4,1,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+24178,United States,110000,1,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 24180,United Kingdom,62500,7,TRUE,FALSE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-24181,United States,135e3,5,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-24182,United States,11e4,13,FALSE,FALSE,20,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-24189,United States,95e3,7,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-24191,United States,75e3,3,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
-24195,Canada,60606.0606060606,20,FALSE,TRUE,5e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-24196,United States,1e5,15,TRUE,FALSE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+24181,United States,135000,5,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+24182,United States,110000,13,FALSE,FALSE,20,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+24189,United States,95000,7,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+24191,United States,75000,3,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
+24195,Canada,60606.0606060606,20,FALSE,TRUE,5000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+24196,United States,100000,15,TRUE,FALSE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 24199,Germany,2150.5376344086,5,TRUE,FALSE,10,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-24200,United States,115e3,3,FALSE,TRUE,1e3,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 24201,United Kingdom,62500,8,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 24209,United Kingdom,93750,13,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-24217,United Kingdom,42500,2,FALSE,TRUE,1e3,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+24217,United Kingdom,42500,2,FALSE,TRUE,1000,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 24228,United Kingdom,38125,2,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-24233,United Kingdom,35e3,4,FALSE,TRUE,10,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+24233,United Kingdom,35000,4,FALSE,TRUE,10,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 24238,United Kingdom,58750,6,FALSE,FALSE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-24260,United States,55e3,2,TRUE,TRUE,1,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-24262,United Kingdom,5e4,2,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-24273,United States,17e4,8,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-24286,United States,11e4,7,FALSE,FALSE,100,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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+24262,United Kingdom,50000,2,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+24273,United States,170000,8,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-24303,United States,94e3,14,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 24320,United States,49677,15,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-24328,United States,114e3,9,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-24334,United States,77e3,7,FALSE,TRUE,1e4,Remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-24335,United States,15e4,4,TRUE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-24336,United States,92e3,5,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-24351,United Kingdom,143750,5,FALSE,TRUE,1e4,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-24353,Germany,48387.0967741935,8,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-24355,United States,76e3,6,FALSE,FALSE,20,Not remote,6,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-24359,United States,54e3,13,FALSE,FALSE,10,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+24327,United States,80000,20,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+24328,United States,114000,9,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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+24336,United States,92000,5,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+24351,United Kingdom,143750,5,FALSE,TRUE,10000,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+24353,Germany,48387.0967741935,8,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+24355,United States,76000,6,FALSE,FALSE,20,Not remote,6,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+24359,United States,54000,13,FALSE,FALSE,10,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-24367,United States,126e3,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-24384,United States,5e4,0,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+24367,United States,126000,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 24392,Canada,54545.4545454545,7,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-24421,United Kingdom,22500,1,FALSE,TRUE,1e4,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-24449,United States,85e3,13,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-24460,Canada,5e4,3,FALSE,FALSE,20,Not remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+24421,United Kingdom,22500,1,FALSE,TRUE,10000,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+24449,United States,85000,13,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+24460,Canada,50000,3,FALSE,FALSE,20,Not remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-24464,United States,6e4,1,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+24464,United States,60000,1,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-24491,United States,73800,3,TRUE,TRUE,5e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
-24502,United States,133e3,20,FALSE,TRUE,1e3,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+24491,United States,73800,3,TRUE,TRUE,5000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+24502,United States,133000,20,FALSE,TRUE,1000,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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-24512,United Kingdom,41825,2,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-24591,United States,7e4,2,FALSE,TRUE,5e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-24682,United States,71e3,5,FALSE,TRUE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-24683,United States,105e3,3,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-24695,United States,105e3,12,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-24697,United States,115e3,19,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-24738,United Kingdom,4e4,3,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-24778,United States,85e3,19,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
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-24782,United Kingdom,75e3,12,TRUE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-24793,United States,12e4,10,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-24795,United States,8e4,6,FALSE,FALSE,1e3,Remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
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-24862,United States,95e3,17,FALSE,TRUE,500,Remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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-24887,United States,3e4,14,TRUE,TRUE,1e4,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE
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-24918,United States,15e4,8,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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@@ -3308,14 +3308,14 @@ Respondent,Country,Salary,YearsCodedJob,OpenSource,Hobby,CompanySizeNumber,Remot
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-25258,United Kingdom,3e4,20,FALSE,FALSE,1,Remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
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+25274,Germany,91397.8494623656,17,FALSE,FALSE,5000,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 25352,United Kingdom,56250,16,TRUE,TRUE,20,Not remote,7,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE
@@ -3325,414 +3325,414 @@ Respondent,Country,Salary,YearsCodedJob,OpenSource,Hobby,CompanySizeNumber,Remot
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-25452,United States,55e3,9,FALSE,FALSE,500,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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-25465,United Kingdom,5e4,1,FALSE,FALSE,1e4,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+25465,United Kingdom,50000,1,FALSE,FALSE,10000,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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 25541,Germany,91397.8494623656,10,FALSE,TRUE,1,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
-25545,United Kingdom,6e4,6,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+25545,United Kingdom,60000,6,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 25554,Canada,37878.7878787879,4,FALSE,TRUE,10,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 25559,Germany,69892.4731182796,6,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 25566,Germany,57526.8817204301,6,TRUE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-25575,United States,114e3,20,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-25580,United Kingdom,25e3,8,FALSE,FALSE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-25588,United States,7e4,4,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+25575,United States,114000,20,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+25580,United Kingdom,25000,8,FALSE,FALSE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 25604,Germany,43870.9677419355,1,FALSE,TRUE,10,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-25608,United States,42e3,2,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 25629,Germany,48387.0967741935,2,TRUE,TRUE,100,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 25630,United Kingdom,42500,1,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 25643,United Kingdom,43750,4,FALSE,TRUE,10,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE
 25658,Germany,53763.4408602151,2,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-25663,United Kingdom,1e5,20,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-25681,Germany,15053.7634408602,1,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+25663,United Kingdom,100000,20,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+25681,Germany,15053.7634408602,1,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 25694,Canada,113636.363636364,17,FALSE,FALSE,10,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 25695,United Kingdom,46250,10,FALSE,TRUE,10,Not remote,5,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-25697,United States,55e3,1,FALSE,TRUE,1,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-25718,United States,15e4,12,FALSE,TRUE,20,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+25697,United States,55000,1,FALSE,TRUE,1,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+25718,United States,150000,12,FALSE,TRUE,20,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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-25735,United Kingdom,46250,16,TRUE,TRUE,1e3,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-25736,United States,67e3,3,FALSE,TRUE,20,Not remote,10,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-25757,United States,87e3,1,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+25735,United Kingdom,46250,16,TRUE,TRUE,1000,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+25736,United States,67000,3,FALSE,TRUE,20,Not remote,10,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+25757,United States,87000,1,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-25761,United Kingdom,4e4,3,FALSE,TRUE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-25762,United Kingdom,46250,2,FALSE,TRUE,1e4,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-25778,United States,96e3,9,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-25783,United States,65e3,3,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-25792,United States,7e4,6,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-25804,United States,77322,4,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE
-25812,United States,11e4,8,TRUE,TRUE,100,Remote,5,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+25761,United Kingdom,40000,3,FALSE,TRUE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+25762,United Kingdom,46250,2,FALSE,TRUE,10000,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
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+25839,United States,110000,8,FALSE,TRUE,100,Remote,7,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 25846,Germany,51612.9032258064,4,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 25853,Germany,56989.247311828,6,FALSE,TRUE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
 25859,Canada,32954.5454545455,3,FALSE,FALSE,10,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-25864,United States,12e4,10,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-25867,United States,9e4,20,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-25869,United States,75e3,14,TRUE,TRUE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-25875,United States,92e3,6,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
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+25869,United States,75000,14,TRUE,TRUE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+25875,United States,92000,6,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
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-25893,United Kingdom,57500,16,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-25900,United States,9e4,4,FALSE,TRUE,10,Remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-25914,United States,62100,7,TRUE,TRUE,1e3,Not remote,6,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+25893,United Kingdom,57500,16,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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+25914,United States,62100,7,TRUE,TRUE,1000,Not remote,6,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-25933,United Kingdom,97500,20,FALSE,FALSE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-25935,United States,87e3,5,FALSE,TRUE,1e4,Remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-25939,United States,7e4,5,FALSE,TRUE,20,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+25933,United Kingdom,97500,20,FALSE,FALSE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+25935,United States,87000,5,FALSE,TRUE,10000,Remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+25939,United States,70000,5,FALSE,TRUE,20,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 25960,United Kingdom,37500,3,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
-25970,United States,135e3,4,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-25973,United States,125e3,5,TRUE,FALSE,10,Not remote,5,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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+25973,United States,125000,5,TRUE,FALSE,10,Not remote,5,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-25986,United States,95306,19,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+25986,United States,95306,19,TRUE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-25991,United States,138e3,14,TRUE,FALSE,1e4,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+25991,United States,138000,14,TRUE,FALSE,10000,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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-26013,United States,7e4,2,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+26013,United States,70000,2,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-26032,United States,125e3,20,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-26034,United States,106e3,8,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+26032,United States,125000,20,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+26034,United States,106000,8,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-26047,United Kingdom,23750,2,FALSE,TRUE,1e4,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-26055,United States,12e4,13,FALSE,TRUE,20,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-26061,United States,133e3,6,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-26069,United States,124800,15,FALSE,FALSE,5e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+26047,United Kingdom,23750,2,FALSE,TRUE,10000,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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+26061,United States,133000,6,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+26069,United States,124800,15,FALSE,FALSE,5000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
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-26074,United States,107e3,12,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-26080,United States,75e3,3,FALSE,FALSE,20,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-26099,United States,111e3,15,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-26103,United States,11e4,11,TRUE,TRUE,1,Remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-26124,United States,93e3,6,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-26126,Germany,67741.935483871,7,FALSE,FALSE,1e4,Not remote,6,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-26151,United States,75e3,7,FALSE,TRUE,500,Remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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+26161,India,5880.19380414036,1,FALSE,FALSE,10000,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-26167,United States,6e4,3,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-26168,United States,68e3,1,FALSE,TRUE,10,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-26195,United States,126e3,20,FALSE,TRUE,1e3,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
+26195,United States,126000,20,FALSE,TRUE,1000,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
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-26207,United Kingdom,58750,5,FALSE,TRUE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-26210,United States,71e3,1,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-26227,United States,175e3,14,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-26230,United States,9e4,3,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-26233,United States,93e3,9,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+26207,United Kingdom,58750,5,FALSE,TRUE,1000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-26944,United States,9e4,8,TRUE,TRUE,20,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-26957,United Kingdom,53125,4,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-26961,United States,116e3,20,FALSE,FALSE,1e4,Not remote,5,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+26937,United Kingdom,58750,2,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+26944,United States,90000,8,TRUE,TRUE,20,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+26957,United Kingdom,53125,4,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+26961,United States,116000,20,FALSE,FALSE,10000,Not remote,5,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 26969,Germany,69892.4731182796,7,TRUE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-26974,India,25693.730729702,11,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-26984,United Kingdom,52500,3,FALSE,TRUE,1e4,Not remote,6,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+26974,India,25693.730729702,11,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+26984,United Kingdom,52500,3,FALSE,TRUE,10000,Not remote,6,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 26986,United Kingdom,31250,2,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27006,United Kingdom,45e3,3,TRUE,FALSE,1,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27006,United Kingdom,45000,3,TRUE,FALSE,1,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 27014,Germany,66666.6666666667,7,FALSE,TRUE,1,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
 27017,Canada,20681.8181818182,1,FALSE,TRUE,10,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 27019,United Kingdom,28750,1,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27022,United States,127e3,20,TRUE,TRUE,20,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+27022,United States,127000,20,TRUE,TRUE,20,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 27027,Germany,59139.7849462366,7,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 27028,Canada,41666.6666666667,5,FALSE,TRUE,1,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
 27031,United Kingdom,56250,4,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27038,United States,36e3,1,FALSE,TRUE,1,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-27041,United States,134e3,14,FALSE,TRUE,1e3,Not remote,9,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-27055,United Kingdom,3e4,2,TRUE,TRUE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27058,United States,6e4,6,TRUE,TRUE,10,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27038,United States,36000,1,FALSE,TRUE,1,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+27041,United States,134000,14,FALSE,TRUE,1000,Not remote,9,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+27055,United Kingdom,30000,2,TRUE,TRUE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27058,United States,60000,6,TRUE,TRUE,10,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 27063,United States,62500,3,FALSE,TRUE,100,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 27067,India,5285.56746439583,2,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-27073,United States,101e3,1,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27073,United States,101000,1,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 27074,Canada,53030.303030303,1,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-27078,Germany,55913.9784946237,3,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27079,United States,92e3,7,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+27078,Germany,55913.9784946237,3,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27079,United States,92000,7,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 27081,Germany,78279.5698924731,10,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 27110,United Kingdom,47500,2,TRUE,TRUE,500,Not remote,7,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE
-27118,United States,97e3,9,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27118,United States,97000,9,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 27128,Germany,83870.9677419355,6,FALSE,FALSE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 27129,India,14682.131845544,6,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27134,United States,168e3,16,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27134,United States,168000,16,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 27139,Canada,53030.303030303,7,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 27144,Canada,70075.7575757576,7,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 27146,Canada,66666.6666666667,20,FALSE,FALSE,10,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 27149,Germany,48387.0967741935,2,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 27158,Germany,29677.4193548387,3,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-27166,United Kingdom,45e3,12,TRUE,TRUE,10,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+27166,United Kingdom,45000,12,TRUE,TRUE,10,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 27171,Germany,43548.3870967742,5,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 27175,Germany,58064.5161290323,8,TRUE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 27183,United Kingdom,61250,20,FALSE,TRUE,100,Remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27195,United States,12e4,5,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-27215,United States,13e4,8,FALSE,TRUE,5e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-27229,India,27896.0505065335,6,TRUE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-27232,United States,15e4,5,TRUE,FALSE,1e4,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-27238,United States,145e3,6,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-27240,United Kingdom,64375,6,FALSE,FALSE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27195,United States,120000,5,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+27215,United States,130000,8,FALSE,TRUE,5000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+27229,India,27896.0505065335,6,TRUE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+27232,United States,150000,5,TRUE,FALSE,10000,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+27238,United States,145000,6,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+27240,United Kingdom,64375,6,FALSE,FALSE,1000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 27247,United States,136500,2,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27271,United States,82e3,9,FALSE,FALSE,1e4,Not remote,3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+27271,United States,82000,9,FALSE,FALSE,10000,Not remote,3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 27282,Germany,38709.6774193548,3,FALSE,TRUE,100,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 27286,Germany,81720.4301075269,20,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-27291,United Kingdom,51250,20,TRUE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+27291,United Kingdom,51250,20,TRUE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 27296,Germany,64516.1290322581,3,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 27300,United Kingdom,38750,2,FALSE,TRUE,20,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-27311,United States,71e3,3,FALSE,TRUE,500,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
+27311,United States,71000,3,FALSE,TRUE,500,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
 27312,Canada,53030.303030303,6,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 27316,United Kingdom,68750,6,FALSE,TRUE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27319,United States,99e3,1,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27319,United States,99000,1,TRUE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 27320,United Kingdom,51875,2,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27331,United States,12e4,6,FALSE,FALSE,1e4,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-27334,United States,117e3,2,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27342,United States,16e4,8,FALSE,TRUE,1e3,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27347,United Kingdom,35e3,2,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27331,United States,120000,6,FALSE,FALSE,10000,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+27334,United States,117000,2,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27342,United States,160000,8,FALSE,TRUE,1000,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27347,United Kingdom,35000,2,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 27349,Germany,54193.5483870968,0,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27350,United States,9e4,2,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27352,United States,97e3,12,FALSE,FALSE,1e4,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27361,United States,115e3,18,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27372,United States,95e3,6,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27374,United States,95e3,20,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27350,United States,90000,2,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27352,United States,97000,12,FALSE,FALSE,10000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27361,United States,115000,18,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27372,United States,95000,6,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27374,United States,95000,20,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 27378,United Kingdom,26250,2,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27383,United States,100568,11,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-27390,United States,105e3,3,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27391,United States,12e4,20,FALSE,TRUE,1e4,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-27395,United States,125e3,14,TRUE,FALSE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-27400,United States,55e3,2,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27401,United States,15e4,10,TRUE,TRUE,1e4,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-27415,United States,135e3,6,FALSE,FALSE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27383,United States,100568,11,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+27390,United States,105000,3,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27391,United States,120000,20,FALSE,TRUE,10000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+27395,United States,125000,14,TRUE,FALSE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+27400,United States,55000,2,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27401,United States,150000,10,TRUE,TRUE,10000,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+27415,United States,135000,6,FALSE,FALSE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 27421,India,35237.1164293055,15,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-27426,United States,89e3,20,FALSE,FALSE,1e4,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27434,United States,105e3,5,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27426,United States,89000,20,FALSE,FALSE,10000,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27434,United States,105000,5,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 27435,Canada,51893.9393939394,9,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 27438,United States,122088,20,FALSE,FALSE,20,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 27440,India,35237.1164293055,15,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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-27450,United States,118e3,9,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27460,United States,119e3,4,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27450,United States,118000,9,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27460,United States,119000,4,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 27462,India,4052.26838937014,2,TRUE,FALSE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-27472,United States,112e3,5,FALSE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27472,United States,112000,5,FALSE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-27484,United States,57e3,2,FALSE,FALSE,100,Remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27491,United States,93e3,11,TRUE,TRUE,100,Remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27498,United States,12e4,3,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27499,United States,9e4,20,FALSE,TRUE,1,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+27484,United States,57000,2,FALSE,FALSE,100,Remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27491,United States,93000,11,TRUE,TRUE,100,Remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27498,United States,120000,3,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27499,United States,90000,20,FALSE,TRUE,1,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
 27512,India,12479.8120687124,5,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27555,India,19086.7713992072,5,TRUE,FALSE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27555,India,19086.7713992072,5,TRUE,FALSE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 27559,Germany,40860.2150537634,1,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 27562,India,10277.4922918808,4,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 27582,Germany,45161.2903225806,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 27593,United Kingdom,51250,10,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-27594,Germany,53763.4408602151,2,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-27596,India,6606.95933049479,2,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27601,United Kingdom,156250,7,TRUE,FALSE,1e4,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+27594,Germany,53763.4408602151,2,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+27596,India,6606.95933049479,2,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27601,United Kingdom,156250,7,TRUE,FALSE,10000,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
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-27654,United Kingdom,71875,15,FALSE,TRUE,1e4,Not remote,9,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27664,Canada,15e4,4,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE
+27654,United Kingdom,71875,15,FALSE,TRUE,10000,Not remote,9,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-27738,Germany,60215.0537634409,7,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-27740,Germany,53763.4408602151,20,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE
-27741,United States,108500,8,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27738,Germany,60215.0537634409,7,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+27740,Germany,53763.4408602151,20,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE
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 27768,Canada,41666.6666666667,9,FALSE,TRUE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27770,United Kingdom,42500,4,TRUE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27770,United Kingdom,42500,4,TRUE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 27771,Canada,32196.9696969697,2,TRUE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-27809,United Kingdom,43750,1,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27835,United Kingdom,41250,1,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+27809,United Kingdom,43750,1,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27835,United Kingdom,41250,1,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 27840,Canada,60606.0606060606,3,TRUE,TRUE,10,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
 27848,United States,86400,11,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 27850,Germany,38709.6774193548,2,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27865,United States,45e3,8,TRUE,TRUE,1e3,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+27865,United States,45000,8,TRUE,TRUE,1000,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
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-27883,Germany,51612.9032258064,2,TRUE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27883,Germany,51612.9032258064,2,TRUE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-27903,United Kingdom,6e4,5,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27915,United States,7e4,1,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27919,United States,65e3,6,TRUE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27920,United States,15e4,5,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27903,United Kingdom,60000,5,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27915,United States,70000,1,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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+27920,United States,150000,5,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-27943,United States,46e3,2,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27944,United States,195e3,12,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27946,Canada,49242.4242424242,6,FALSE,TRUE,5e3,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+27943,United States,46000,2,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27944,United States,195000,12,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27946,Canada,49242.4242424242,6,FALSE,TRUE,5000,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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 27950,Germany,75268.8172043011,20,TRUE,TRUE,100,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-27963,United States,97e3,10,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27971,United States,4e4,1,FALSE,FALSE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-27972,United Kingdom,5e4,2,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-27983,United States,11e4,15,FALSE,FALSE,1e4,Not remote,3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-27985,United Kingdom,22500,1,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27963,United States,97000,10,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27971,United States,40000,1,FALSE,FALSE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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+27985,United Kingdom,22500,1,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-27995,United States,95500,5,FALSE,FALSE,1e4,Remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-27999,United Kingdom,54375,2,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-28014,India,7179.562472471,3,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-28017,United Kingdom,75e3,9,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-28023,United Kingdom,37500,1,FALSE,FALSE,1e4,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-28033,United States,112750,5,TRUE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-28039,Germany,83870.9677419355,20,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-28044,United Kingdom,42e3,1,FALSE,FALSE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-28048,United States,135e3,3,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+27995,United States,95500,5,FALSE,FALSE,10000,Remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+27999,United Kingdom,54375,2,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+28014,India,7179.562472471,3,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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+28023,United Kingdom,37500,1,FALSE,FALSE,10000,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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+28044,United Kingdom,42000,1,FALSE,FALSE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-28063,United States,115e3,10,FALSE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-28066,United States,102e3,1,FALSE,TRUE,1e4,Remote,10,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+28063,United States,115000,10,FALSE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-28078,United Kingdom,3e4,1,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-28084,United States,13e4,20,TRUE,TRUE,20,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+28078,United Kingdom,30000,1,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+28084,United States,130000,20,TRUE,TRUE,20,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-28119,United States,73500,3,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+28119,United States,73500,3,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-28138,United States,1e5,4,FALSE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+28138,United States,100000,4,FALSE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-28166,United States,12e4,3,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+28166,United States,120000,3,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-28189,United States,155e3,11,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-28193,United States,127e3,3,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-28207,United States,11e4,14,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-28210,United States,125e3,20,TRUE,FALSE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-28212,United States,109e3,2,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-28215,United States,16e4,20,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-28219,United States,4e4,3,TRUE,TRUE,10,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE
+28189,United States,155000,11,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+28193,United States,127000,3,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+28207,United States,110000,14,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+28210,United States,125000,20,TRUE,FALSE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+28212,United States,109000,2,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+28215,United States,160000,20,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-28230,United States,135e3,20,FALSE,TRUE,1e3,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-28235,United States,83e3,1,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-28236,United States,1e5,2,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-28240,Canada,62121.2121212121,16,FALSE,FALSE,1e3,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-28244,Canada,45454.5454545455,3,TRUE,TRUE,5e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-28258,United States,154e3,12,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+28230,United States,135000,20,FALSE,TRUE,1000,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+28235,United States,83000,1,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+28236,United States,100000,2,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+28240,Canada,62121.2121212121,16,FALSE,FALSE,1000,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+28244,Canada,45454.5454545455,3,TRUE,TRUE,5000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+28258,United States,154000,12,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-28287,United States,11e4,20,TRUE,FALSE,1e3,Not remote,5,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-28289,United States,85e3,2,TRUE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-28296,United States,13e4,4,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+28287,United States,110000,20,TRUE,FALSE,1000,Not remote,5,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+28289,United States,85000,2,TRUE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+28296,United States,130000,4,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-28305,United States,85e3,3,FALSE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-28311,United States,65e3,6,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-28321,United States,121e3,20,FALSE,TRUE,1e3,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+28305,United States,85000,3,FALSE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+28311,United States,65000,6,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+28321,United States,121000,20,FALSE,TRUE,1000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-28345,United States,65e3,4,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-28361,United States,145e3,2,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+28345,United States,65000,4,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-28513,United States,115e3,4,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+28513,United States,115000,4,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 28527,Germany,38709.6774193548,1,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE
 28534,Germany,64516.1290322581,8,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 28548,United Kingdom,28750,3,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
@@ -3740,388 +3740,388 @@ Respondent,Country,Salary,YearsCodedJob,OpenSource,Hobby,CompanySizeNumber,Remot
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-28586,United States,55e3,1,FALSE,FALSE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+28586,United States,55000,1,FALSE,FALSE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 28591,Canada,45454.5454545455,3,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-28620,Germany,59139.7849462366,5,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-28621,India,4771.69284980179,1,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
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+28626,India,19380.414036118,3,FALSE,FALSE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE
 28635,India,11745.7054764352,3,TRUE,TRUE,100,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 28637,Germany,1505.37634408602,1,TRUE,TRUE,20,Not remote,2,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
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-28659,India,23491.4109528704,6,FALSE,FALSE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-28667,India,12039.3481133461,4,FALSE,FALSE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+28659,India,23491.4109528704,6,FALSE,FALSE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+28667,India,12039.3481133461,4,FALSE,FALSE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 28699,India,13948.0252532668,2,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-28732,Germany,46451.6129032258,5,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+28732,Germany,46451.6129032258,5,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-28768,India,22023.197768316,5,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 28794,India,5285.56746439583,3,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-28834,Canada,60606.0606060606,2,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-28853,United Kingdom,68750,9,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-28867,United States,108e3,20,TRUE,FALSE,10,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+28834,Canada,60606.0606060606,2,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+28853,United Kingdom,68750,9,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+28867,United States,108000,20,TRUE,FALSE,10,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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 28872,Germany,51612.9032258064,2,FALSE,TRUE,20,Not remote,3,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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-28926,United Kingdom,3e4,3,FALSE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-28928,India,11745.7054764352,3,TRUE,TRUE,1e4,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-28970,United Kingdom,40625,10,FALSE,TRUE,1e3,Not remote,6,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+28970,United Kingdom,40625,10,FALSE,TRUE,1000,Not remote,6,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-29001,United Kingdom,46250,1,TRUE,FALSE,1e4,Not remote,6,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+29001,United Kingdom,46250,1,TRUE,FALSE,10000,Not remote,6,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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 29014,United Kingdom,41250,5,FALSE,TRUE,1,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29016,United Kingdom,46140,9,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+29016,United Kingdom,46140,9,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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-29027,United Kingdom,43750,4,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+29027,United Kingdom,43750,4,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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 29041,Germany,77419.3548387097,19,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 29044,Germany,37634.4086021505,4,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-29046,India,22023.197768316,12,FALSE,FALSE,5e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+29046,India,22023.197768316,12,FALSE,FALSE,5000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 29051,Germany,45161.2903225806,1,FALSE,FALSE,10,Not remote,0,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
 29054,Germany,46666.6666666667,9,FALSE,TRUE,10,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 29066,Canada,68181.8181818182,7,FALSE,FALSE,10,Remote,10,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29067,United States,64e3,4,TRUE,TRUE,1e4,Not remote,3,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+29067,United States,64000,4,TRUE,TRUE,10000,Not remote,3,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
 29076,India,17618.5582146528,3,FALSE,TRUE,20,Not remote,5,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
-29077,India,27896.0505065335,1,FALSE,TRUE,1e4,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+29077,India,27896.0505065335,1,FALSE,TRUE,10000,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 29082,Germany,3279.56989247312,6,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-29091,United Kingdom,52500,1,FALSE,FALSE,1e4,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29091,United Kingdom,52500,1,FALSE,FALSE,10000,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-29161,United States,62e3,2,FALSE,TRUE,100,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29170,Germany,59626.8817204301,16,TRUE,TRUE,1e3,Not remote,5,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+29161,United States,62000,2,FALSE,TRUE,100,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29170,Germany,59626.8817204301,16,TRUE,TRUE,1000,Not remote,5,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-29213,United States,145e3,18,FALSE,FALSE,5e3,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29230,United Kingdom,35e3,2,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29240,United Kingdom,37500,3,FALSE,FALSE,1e3,Not remote,6,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-29246,United States,97e3,9,FALSE,FALSE,1,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-29247,United States,58e3,1,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-29268,United States,115e3,20,TRUE,FALSE,100,Not remote,5,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-29274,United States,8e4,1,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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-29314,United States,8e4,4,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-29368,United States,65e3,1,FALSE,FALSE,100,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-29369,United States,62e3,4,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29372,United Kingdom,6e4,8,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-29491,United States,46e3,1,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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-29513,United States,95e3,16,FALSE,FALSE,100,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29513,United States,95000,16,FALSE,FALSE,100,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 29517,United Kingdom,26250,1,FALSE,TRUE,10,Not remote,8,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
 29521,United Kingdom,46250,8,FALSE,TRUE,100,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 29525,United Kingdom,54687.5,16,TRUE,TRUE,100,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
 29565,Germany,46236.5591397849,3,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-29580,United States,98e3,6,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29583,United States,74e3,5,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29587,United States,7e4,2,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29580,United States,98000,6,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29583,United States,74000,5,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29587,United States,70000,2,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 29594,United Kingdom,49375,2,FALSE,FALSE,500,Not remote,8,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 29597,Canada,29545.4545454545,3,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29599,United States,1e5,1,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29604,Germany,64516.1290322581,6,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29607,Canada,43181.8181818182,2,FALSE,TRUE,5e3,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE
-29615,United States,65e3,5,TRUE,FALSE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+29599,United States,100000,1,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29604,Germany,64516.1290322581,6,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29607,Canada,43181.8181818182,2,FALSE,TRUE,5000,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE
+29615,United States,65000,5,TRUE,FALSE,1000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 29621,Germany,86021.5053763441,17,FALSE,FALSE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 29630,United Kingdom,32500,2,TRUE,FALSE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 29639,Germany,43870.9677419355,6,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-29647,United States,54e3,7,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29648,India,18352.66480693,5,FALSE,TRUE,5e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29649,United States,65e3,9,TRUE,TRUE,10,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-29651,United Kingdom,87500,12,TRUE,FALSE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-29653,Germany,45161.2903225806,2,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29661,United States,97e3,5,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29662,United States,105e3,11,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
-29663,United States,17e4,20,FALSE,TRUE,1e3,Not remote,8,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE
-29672,United States,82e3,5,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29674,United States,87500,3,TRUE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29676,Germany,48387.0967741935,9,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-29687,United States,13e4,20,FALSE,TRUE,10,Remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+29647,United States,54000,7,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29648,India,18352.66480693,5,FALSE,TRUE,5000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29649,United States,65000,9,TRUE,TRUE,10,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+29651,United Kingdom,87500,12,TRUE,FALSE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+29653,Germany,45161.2903225806,2,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29661,United States,97000,5,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29662,United States,105000,11,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+29663,United States,170000,20,FALSE,TRUE,1000,Not remote,8,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE
+29672,United States,82000,5,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29674,United States,87500,3,TRUE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29676,Germany,48387.0967741935,9,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+29687,United States,130000,20,FALSE,TRUE,10,Remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
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-29703,United States,128e3,9,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-29722,United States,1e5,2,FALSE,FALSE,1,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29703,United States,128000,9,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+29722,United States,100000,2,FALSE,FALSE,1,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 29728,Germany,56989.247311828,1,FALSE,TRUE,100,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29756,United States,4e4,1,FALSE,TRUE,1e3,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29756,United States,40000,1,FALSE,TRUE,1000,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 29764,United States,47500,4,FALSE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 29770,United States,52500,1,FALSE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29776,United States,72e3,3,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29776,United States,72000,3,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 29779,Canada,56818.1818181818,8,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29781,United States,105e3,10,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29782,Canada,53787.8787878788,4,FALSE,FALSE,1e3,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29794,United States,16e4,16,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29797,United States,95e3,4,TRUE,TRUE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-29803,United States,105e3,5,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+29781,United States,105000,10,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29782,Canada,53787.8787878788,4,FALSE,FALSE,1000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29794,United States,160000,16,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29797,United States,95000,4,TRUE,TRUE,1000,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+29803,United States,105000,5,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
 29805,Germany,40322.5806451613,5,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 29806,United States,66500,1,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29808,United States,11e4,7,TRUE,TRUE,1e4,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+29808,United States,110000,7,TRUE,TRUE,10000,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
 29809,Germany,24731.1827956989,3,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-29815,United States,106e3,6,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29815,United States,106000,6,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-29817,United States,55e3,2,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29819,United States,7e4,4,FALSE,TRUE,1e3,Not remote,6,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-29821,Canada,65909.0909090909,13,TRUE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29817,United States,55000,2,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29819,United States,70000,4,FALSE,TRUE,1000,Not remote,6,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+29821,Canada,65909.0909090909,13,TRUE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 29822,United States,76813,7,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29823,United States,14e4,16,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29832,United States,82e3,1,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
-29836,Canada,46212.1212121212,2,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29837,United States,97900,3,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29844,United States,85e3,11,FALSE,FALSE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29846,United States,1e5,14,FALSE,TRUE,100,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29847,United States,62745,2,TRUE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29848,United States,62e3,4,FALSE,FALSE,20,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
-29851,United States,12e3,3,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE
-29863,United States,72e3,7,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+29823,United States,140000,16,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29832,United States,82000,1,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+29836,Canada,46212.1212121212,2,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29837,United States,97900,3,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29844,United States,85000,11,FALSE,FALSE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29846,United States,100000,14,FALSE,TRUE,100,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29847,United States,62745,2,TRUE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29848,United States,62000,4,FALSE,FALSE,20,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
+29851,United States,12000,3,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE
+29863,United States,72000,7,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-29868,United States,145e3,5,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
-29872,United States,8e4,6,FALSE,TRUE,500,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29868,United States,145000,5,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+29872,United States,80000,6,FALSE,TRUE,500,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-29877,United States,72e3,3,TRUE,TRUE,100,Not remote,5,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-29878,United States,56e3,4,FALSE,TRUE,1e4,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29880,United States,15e4,12,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29882,United States,122e3,11,TRUE,TRUE,1e4,Remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-29890,United Kingdom,45e3,5,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29894,United States,59e3,2,FALSE,TRUE,20,Remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-29896,United States,63e3,4,FALSE,TRUE,100,Not remote,10,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-29900,United States,105e3,4,FALSE,TRUE,20,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29945,United States,85e3,10,FALSE,FALSE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29957,United States,12e4,9,TRUE,TRUE,10,Not remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-29958,United States,127e3,2,FALSE,TRUE,1e4,Not remote,2,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-29969,United States,75e3,1,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-29971,United States,65e3,5,FALSE,TRUE,500,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29972,United States,17e4,20,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-29973,United States,65e3,2,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29877,United States,72000,3,TRUE,TRUE,100,Not remote,5,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+29878,United States,56000,4,FALSE,TRUE,10000,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29880,United States,150000,12,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29882,United States,122000,11,TRUE,TRUE,10000,Remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+29890,United Kingdom,45000,5,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29894,United States,59000,2,FALSE,TRUE,20,Remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+29896,United States,63000,4,FALSE,TRUE,100,Not remote,10,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+29900,United States,105000,4,FALSE,TRUE,20,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29945,United States,85000,10,FALSE,FALSE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29957,United States,120000,9,TRUE,TRUE,10,Not remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+29958,United States,127000,2,FALSE,TRUE,10000,Not remote,2,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+29969,United States,75000,1,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+29971,United States,65000,5,FALSE,TRUE,500,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29972,United States,170000,20,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+29973,United States,65000,2,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 29976,Canada,39772.7272727273,4,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 29978,Canada,60606.0606060606,12,FALSE,TRUE,100,Not remote,3,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 29981,Canada,53030.303030303,5,FALSE,TRUE,20,Remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-29986,United States,115e3,8,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29987,United States,8e4,2,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-29990,United States,9e4,2,FALSE,TRUE,20,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-30009,United States,68e3,6,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-30011,United States,104e3,9,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+29986,United States,115000,8,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29987,United States,80000,2,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+29990,United States,90000,2,FALSE,TRUE,20,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+30009,United States,68000,6,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-31162,United Kingdom,95e3,20,TRUE,TRUE,5e3,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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+31158,United States,91000,10,FALSE,FALSE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+31162,United Kingdom,95000,20,TRUE,TRUE,5000,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-31973,India,8809.27910732638,3,TRUE,TRUE,1e4,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+31964,Germany,32258.064516129,3,TRUE,TRUE,1000,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+31973,India,8809.27910732638,3,TRUE,TRUE,10000,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 31974,Canada,37878.7878787879,5,FALSE,FALSE,20,Not remote,0,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 31982,United Kingdom,43750,9,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 31983,United Kingdom,43750,6,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
@@ -4129,26 +4129,26 @@ Respondent,Country,Salary,YearsCodedJob,OpenSource,Hobby,CompanySizeNumber,Remot
 32028,India,3230.06900601967,0,TRUE,FALSE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 32051,United Kingdom,62500,6,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 32065,India,3171.3404786375,2,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-32075,United Kingdom,6e4,6,FALSE,TRUE,500,Not remote,7,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+32075,United Kingdom,60000,6,FALSE,TRUE,500,Not remote,7,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 32086,Germany,25806.4516129032,5,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE
 32087,United Kingdom,51500,8,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 32090,India,3171.3404786375,1,FALSE,TRUE,20,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-32111,Germany,63440.8602150538,2,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-32178,United Kingdom,6e4,16,FALSE,TRUE,1e4,Remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+32111,Germany,63440.8602150538,2,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+32178,United Kingdom,60000,16,FALSE,TRUE,10000,Remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
 32184,United Kingdom,31250,1,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-32198,India,17618.5582146528,1,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-32235,India,5138.74614594039,2,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+32198,India,17618.5582146528,1,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+32235,India,5138.74614594039,2,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 32241,Germany,70967.7419354839,10,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 32252,United Kingdom,41250,2,TRUE,TRUE,20,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 32266,Germany,53763.4408602151,7,FALSE,TRUE,20,Not remote,4,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 32273,United Kingdom,43750,2,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 32276,United Kingdom,93750,20,TRUE,FALSE,20,Remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
 32298,Germany,45161.2903225806,3,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-32317,Germany,65591.3978494624,8,FALSE,FALSE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+32317,Germany,65591.3978494624,8,FALSE,FALSE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 32325,Germany,73118.2795698925,9,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-32333,Germany,48387.0967741935,4,FALSE,TRUE,5e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+32333,Germany,48387.0967741935,4,FALSE,TRUE,5000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 32341,Germany,38709.6774193548,5,TRUE,TRUE,1,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-32350,United Kingdom,15e3,1,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+32350,United Kingdom,15000,1,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 32358,India,3523.71164293055,0,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 32360,Germany,64516.1290322581,10,FALSE,FALSE,20,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 32372,United Kingdom,52500,7,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
@@ -4156,29 +4156,29 @@ Respondent,Country,Salary,YearsCodedJob,OpenSource,Hobby,CompanySizeNumber,Remot
 32411,Germany,73118.2795698925,12,TRUE,TRUE,100,Remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 32416,Germany,53763.4408602151,8,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 32417,Germany,48387.0967741935,3,FALSE,TRUE,100,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-32428,United Kingdom,51250,8,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-32491,United Kingdom,57500,9,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-32494,United States,105e3,11,FALSE,FALSE,1e3,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+32428,United Kingdom,51250,8,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+32491,United Kingdom,57500,9,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+32494,United States,105000,11,FALSE,FALSE,1000,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 32496,Germany,40860.2150537634,1,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 32517,Germany,53763.4408602151,6,FALSE,TRUE,100,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 32535,United Kingdom,40312.5,4,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-32544,United States,74e3,2,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-32546,United States,1e5,7,TRUE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-32549,United Kingdom,5e4,2,FALSE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+32544,United States,74000,2,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+32546,United States,100000,7,TRUE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+32549,United Kingdom,50000,2,FALSE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 32552,Germany,45161.2903225806,2,FALSE,TRUE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-32580,United States,1e5,4,FALSE,TRUE,1e4,Not remote,10,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-32589,United Kingdom,5e4,6,TRUE,FALSE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+32580,United States,100000,4,FALSE,TRUE,10000,Not remote,10,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+32589,United Kingdom,50000,6,TRUE,FALSE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 32592,United Kingdom,62500,10,TRUE,TRUE,100,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-32623,United States,194e3,20,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-32640,Germany,62365.5913978495,4,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+32623,United States,194000,20,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+32640,Germany,62365.5913978495,4,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 32654,United Kingdom,31250,6,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-32665,United States,139e3,20,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+32665,United States,139000,20,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 32674,United Kingdom,56250,14,FALSE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 32690,United Kingdom,43250,9,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-32691,United States,1e5,5,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+32691,United States,100000,5,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 32710,Germany,62204.3010752688,4,FALSE,TRUE,10,Not remote,6,TRUE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-32714,United Kingdom,5e4,4,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-32719,United States,83e3,5,FALSE,FALSE,1e4,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+32714,United Kingdom,50000,4,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+32719,United States,83000,5,FALSE,FALSE,10000,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 32726,United Kingdom,81250,3,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 32731,United Kingdom,62500,10,FALSE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 32758,United States,52500,1,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
@@ -4187,99 +4187,99 @@ Respondent,Country,Salary,YearsCodedJob,OpenSource,Hobby,CompanySizeNumber,Remot
 32801,Germany,66666.6666666667,7,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 32812,Germany,70967.7419354839,15,FALSE,TRUE,500,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 32821,Canada,98484.8484848485,18,TRUE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-32843,United States,14e4,8,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-32844,United States,85e3,6,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-32846,United States,16e4,7,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+32843,United States,140000,8,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+32844,United States,85000,6,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+32846,United States,160000,7,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
 32848,Canada,49242.4242424242,4,TRUE,TRUE,100,Not remote,6,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-32867,United States,69e3,8,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-32880,United Kingdom,5e4,4,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-32886,United States,42e3,3,FALSE,FALSE,1e4,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+32867,United States,69000,8,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+32880,United Kingdom,50000,4,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+32886,United States,42000,3,FALSE,FALSE,10000,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 32892,United Kingdom,87500,8,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-32895,United States,75e3,3,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+32895,United States,75000,3,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 32900,United States,123500,5,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-32913,United States,1e5,20,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE
+32913,United States,100000,20,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE
 32917,Germany,45161.2903225806,9,TRUE,FALSE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-32919,United States,93e3,4,FALSE,TRUE,1,Not remote,6,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
+32919,United States,93000,4,FALSE,TRUE,1,Not remote,6,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
 32924,Canada,68181.8181818182,5,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-32933,Canada,93181.8181818182,20,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-32955,United States,105e3,20,FALSE,FALSE,1e4,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-32959,United States,141e3,13,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-32964,United States,66e3,2,FALSE,TRUE,1e3,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
-32970,United States,13e4,20,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-32971,United States,6e4,2,FALSE,TRUE,5e3,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-32972,United States,97e3,11,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-32974,United States,102e3,20,FALSE,TRUE,100,Remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+32933,Canada,93181.8181818182,20,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+32955,United States,105000,20,FALSE,FALSE,10000,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+32959,United States,141000,13,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+32964,United States,66000,2,FALSE,TRUE,1000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
+32970,United States,130000,20,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+32971,United States,60000,2,FALSE,TRUE,5000,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+32972,United States,97000,11,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+32974,United States,102000,20,FALSE,TRUE,100,Remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 32983,United States,71200,1,FALSE,TRUE,500,Not remote,10,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-33003,United Kingdom,5e4,6,FALSE,FALSE,20,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-33016,United States,68500,4,TRUE,FALSE,1e4,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+33003,United Kingdom,50000,6,FALSE,FALSE,20,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+33016,United States,68500,4,TRUE,FALSE,10000,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 33044,United States,57600,4,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 33047,Canada,45454.5454545455,2,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-33053,United States,6e4,1,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+33053,United States,60000,1,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 33057,Canada,55681.8181818182,5,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-33074,United States,78e3,5,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+33074,United States,78000,5,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 33085,Germany,48387.0967741935,5,FALSE,TRUE,100,Not remote,1,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-33090,United States,105e3,5,FALSE,FALSE,10,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-33093,United States,115e3,2,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-33102,United States,133e3,7,TRUE,TRUE,1e4,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+33090,United States,105000,5,FALSE,FALSE,10,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+33093,United States,115000,2,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+33102,United States,133000,7,TRUE,TRUE,10000,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 33103,Germany,53763.4408602151,4,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-33106,United States,115e3,3,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-33112,United States,165e3,20,TRUE,FALSE,20,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-33126,United States,141e3,14,TRUE,TRUE,5e3,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-33127,United States,115e3,11,FALSE,FALSE,100,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-33130,United States,105e3,2,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-33136,United States,85e3,11,FALSE,TRUE,1e3,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-33137,United States,12e4,12,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-33138,United States,165e3,20,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+33106,United States,115000,3,TRUE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+33112,United States,165000,20,TRUE,FALSE,20,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+33126,United States,141000,14,TRUE,TRUE,5000,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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-33173,United States,117e3,13,TRUE,TRUE,500,Not remote,10,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE
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@@ -4289,172 +4289,172 @@ Respondent,Country,Salary,YearsCodedJob,OpenSource,Hobby,CompanySizeNumber,Remot
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-34205,Germany,53763.4408602151,3,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+34205,Germany,53763.4408602151,3,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 34237,United Kingdom,29493.75,3,FALSE,TRUE,100,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-34243,United Kingdom,85e3,19,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34244,United States,118e3,20,TRUE,TRUE,100,Remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+34243,United Kingdom,85000,19,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34244,United States,118000,20,TRUE,TRUE,100,Remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 34252,Germany,53763.4408602151,9,FALSE,TRUE,100,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 34261,Germany,64516.1290322581,18,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34283,United States,78e3,2,FALSE,FALSE,1e4,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34286,India,16150.3450300984,7,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-34290,Canada,49242.4242424242,9,FALSE,TRUE,5e3,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34296,United Kingdom,75e3,9,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-34335,United Kingdom,78750,4,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-34348,United States,11e4,5,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-34349,United Kingdom,3e4,0,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+34283,United States,78000,2,FALSE,FALSE,10000,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34286,India,16150.3450300984,7,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+34290,Canada,49242.4242424242,9,FALSE,TRUE,5000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34296,United Kingdom,75000,9,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+34335,United Kingdom,78750,4,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+34348,United States,110000,5,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+34349,United Kingdom,30000,0,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 34362,United Kingdom,26875,5,FALSE,TRUE,10,Not remote,6,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 34368,Germany,69892.4731182796,20,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-34373,United Kingdom,55e3,20,FALSE,TRUE,500,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
+34373,United Kingdom,55000,20,FALSE,TRUE,500,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
 34380,Germany,3387.09677419355,3,FALSE,TRUE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 34402,Germany,66666.6666666667,9,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 34412,United Kingdom,27500,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-34418,United States,107e3,17,TRUE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-34425,Canada,106060.606060606,8,TRUE,TRUE,1e3,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34429,United States,8e4,3,FALSE,TRUE,5e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34418,United States,107000,17,TRUE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+34425,Canada,106060.606060606,8,TRUE,TRUE,1000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34429,United States,80000,3,FALSE,TRUE,5000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 34435,United Kingdom,62500,2,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 34436,Germany,81720.4301075269,9,FALSE,FALSE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-34446,United States,9e4,1,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34459,Canada,53030.303030303,15,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34505,United Kingdom,5e4,3,TRUE,TRUE,1e3,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34512,United States,105e3,20,FALSE,FALSE,100,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34516,United Kingdom,25e3,2,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34527,United States,97e3,3,FALSE,TRUE,1e4,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34446,United States,90000,1,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34459,Canada,53030.303030303,15,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34505,United Kingdom,50000,3,TRUE,TRUE,1000,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34512,United States,105000,20,FALSE,FALSE,100,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34516,United Kingdom,25000,2,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34527,United States,97000,3,FALSE,TRUE,10000,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 34528,United Kingdom,46250,12,FALSE,TRUE,100,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-34537,United States,5e4,6,TRUE,FALSE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-34543,United States,62500,18,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34551,United States,5e4,2,FALSE,TRUE,20,Remote,10,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-34555,United States,7e4,1,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-34558,United States,65e3,2,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-34587,United States,115e3,4,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34592,United States,92e3,15,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34594,India,4110.99691675231,1,FALSE,TRUE,1e4,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE
+34537,United States,50000,6,TRUE,FALSE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+34543,United States,62500,18,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34551,United States,50000,2,FALSE,TRUE,20,Remote,10,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+34555,United States,70000,1,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+34558,United States,65000,2,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+34587,United States,115000,4,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34592,United States,92000,15,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34594,India,4110.99691675231,1,FALSE,TRUE,10000,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE
 34602,Germany,69892.4731182796,19,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 34604,Canada,22727.2727272727,0,FALSE,TRUE,1,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34632,United States,165e3,4,FALSE,TRUE,1,Not remote,10,FALSE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+34632,United States,165000,4,FALSE,TRUE,1,Not remote,10,FALSE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
 34643,India,10571.1349287917,4,FALSE,TRUE,100,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 34651,India,2936.42636910879,6,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34653,United States,71e3,9,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-34655,United States,71500,3,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-34659,United States,14e4,14,TRUE,TRUE,1e4,Remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-34669,United States,8e4,3,FALSE,FALSE,100,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34699,United States,15e4,20,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-34702,United States,144e3,18,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-34709,United States,96e3,4,FALSE,TRUE,100,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34720,United States,135e3,20,FALSE,FALSE,20,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-34740,United States,77e3,2,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-34751,United States,164e3,20,FALSE,FALSE,1e3,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34753,United States,68e3,3,TRUE,TRUE,1e3,Not remote,7,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34759,United States,1e5,1,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-34770,United States,60400,3,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34653,United States,71000,9,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+34655,United States,71500,3,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+34659,United States,140000,14,TRUE,TRUE,10000,Remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+34669,United States,80000,3,FALSE,FALSE,100,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34699,United States,150000,20,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+34702,United States,144000,18,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+34709,United States,96000,4,FALSE,TRUE,100,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34720,United States,135000,20,FALSE,FALSE,20,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+34740,United States,77000,2,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+34751,United States,164000,20,FALSE,FALSE,1000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34753,United States,68000,3,TRUE,TRUE,1000,Not remote,7,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34759,United States,100000,1,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+34770,United States,60400,3,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-34780,India,32300.6900601967,2,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34780,India,32300.6900601967,2,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 34793,Canada,55303.0303030303,3,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 34794,United States,87500,5,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34818,United States,1e5,11,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-34835,United States,15e4,20,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34836,United States,153e3,12,FALSE,TRUE,5e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-34844,United States,86400,10,TRUE,TRUE,1e3,Not remote,10,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-34859,United States,12e4,20,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+34818,United States,100000,11,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+34835,United States,150000,20,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34836,United States,153000,12,FALSE,TRUE,5000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+34844,United States,86400,10,TRUE,TRUE,1000,Not remote,10,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+34859,United States,120000,20,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-34873,United States,9e4,1,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-34874,United States,148e3,19,FALSE,FALSE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34902,United States,145e3,19,TRUE,TRUE,1,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-34904,United States,6e4,2,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34873,United States,90000,1,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+34874,United States,148000,19,FALSE,FALSE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34902,United States,145000,19,TRUE,TRUE,1,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+34904,United States,60000,2,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 34905,Canada,75757.5757575758,4,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-34915,United States,128e3,1,FALSE,TRUE,500,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-34920,United States,16e4,11,TRUE,FALSE,10,Not remote,9,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-34922,United States,66e3,4,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-34923,United States,135e3,20,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34935,United Kingdom,43750,4,FALSE,TRUE,5e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-34942,United States,84e3,11,FALSE,FALSE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34951,United States,126e3,9,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34956,United States,6e4,1,FALSE,FALSE,10,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34969,United States,68e3,6,FALSE,TRUE,100,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-34984,United States,87e3,7,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34915,United States,128000,1,FALSE,TRUE,500,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+34920,United States,160000,11,TRUE,FALSE,10,Not remote,9,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+34922,United States,66000,4,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+34923,United States,135000,20,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34935,United Kingdom,43750,4,FALSE,TRUE,5000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+34942,United States,84000,11,FALSE,FALSE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34951,United States,126000,9,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34956,United States,60000,1,FALSE,FALSE,10,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34969,United States,68000,6,FALSE,TRUE,100,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+34984,United States,87000,7,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 34985,United Kingdom,52500,1,TRUE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 34994,United States,63500,20,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 34998,United States,72051,9,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-35003,United States,62e3,2,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-35005,United States,72e3,20,FALSE,TRUE,1e3,Remote,7,TRUE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-35009,United States,11e4,17,FALSE,TRUE,5e3,Not remote,4,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-35010,United States,106e3,6,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-35019,United States,123e3,18,TRUE,TRUE,1e3,Remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-35022,United States,122e3,15,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
-35036,United States,12e4,9,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-35038,United States,115e3,3,TRUE,FALSE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-35047,United States,95e3,15,FALSE,TRUE,500,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+35003,United States,62000,2,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+35005,United States,72000,20,FALSE,TRUE,1000,Remote,7,TRUE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+35009,United States,110000,17,FALSE,TRUE,5000,Not remote,4,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+35010,United States,106000,6,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+35019,United States,123000,18,TRUE,TRUE,1000,Remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+35022,United States,122000,15,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
+35036,United States,120000,9,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+35038,United States,115000,3,TRUE,FALSE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+35047,United States,95000,15,FALSE,TRUE,500,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-35060,United States,135e3,18,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-35070,United States,122e3,5,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-35082,United States,96e3,3,FALSE,TRUE,5e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-35085,United States,13e4,11,TRUE,TRUE,1,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+35060,United States,135000,18,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+35070,United States,122000,5,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+35082,United States,96000,3,FALSE,TRUE,5000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+35085,United States,130000,11,TRUE,TRUE,1,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 35096,Canada,47727.2727272727,9,TRUE,TRUE,10,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-35102,United States,15e4,20,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-35121,United States,11e4,8,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-35127,United States,156e3,16,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-35130,United States,88e3,3,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+35102,United States,150000,20,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+35121,United States,110000,8,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+35127,United States,156000,16,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+35130,United States,88000,3,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 35138,Canada,30303.0303030303,10,TRUE,TRUE,20,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 35157,India,7047.42328586111,6,TRUE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-35178,United States,1e4,5,FALSE,TRUE,1e3,Not remote,5,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+35178,United States,10000,5,FALSE,TRUE,1000,Not remote,5,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 35189,Canada,55681.8181818182,7,TRUE,TRUE,100,Not remote,9,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
 35206,India,9117.60387608281,2,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 35226,India,3876.08280722361,2,TRUE,FALSE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 35238,India,4110.99691675231,1,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 35241,Germany,48387.0967741935,5,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
-35286,India,24959.6241374248,7,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+35286,India,24959.6241374248,7,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 35302,Germany,56451.6129032258,9,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-35306,United Kingdom,5e4,20,FALSE,FALSE,20,Not remote,6,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+35306,United Kingdom,50000,20,FALSE,FALSE,20,Not remote,6,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 35350,India,7341.06592277199,1,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-35352,United Kingdom,22500,1,FALSE,TRUE,5e3,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-35353,Germany,48086.0215053763,5,FALSE,TRUE,5e3,Not remote,9,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+35352,United Kingdom,22500,1,FALSE,TRUE,5000,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+35353,Germany,48086.0215053763,5,FALSE,TRUE,5000,Not remote,9,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
 35403,United Kingdom,62500,12,FALSE,TRUE,20,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-35412,United Kingdom,57500,13,FALSE,FALSE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+35412,United Kingdom,57500,13,FALSE,FALSE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 35435,India,7047.42328586111,2,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 35447,India,3523.71164293055,2,TRUE,TRUE,1,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 35451,India,31566.5834679195,16,FALSE,TRUE,100,Not remote,6,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
@@ -4462,793 +4462,793 @@ Respondent,Country,Salary,YearsCodedJob,OpenSource,Hobby,CompanySizeNumber,Remot
 35488,Germany,38709.6774193548,2,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 35490,Germany,8602.15053763441,3,FALSE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE
 35496,India,3523.71164293055,2,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-35507,India,19644.6924093378,6,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+35507,India,19644.6924093378,6,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 35512,Germany,4176.34408602151,8,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-35518,India,8104.53677874027,2,FALSE,FALSE,1e3,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+35518,India,8104.53677874027,2,FALSE,FALSE,1000,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 35526,India,18352.66480693,4,FALSE,FALSE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 35544,Germany,64516.1290322581,20,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-35545,United Kingdom,4e4,12,FALSE,TRUE,1,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-35546,Germany,48387.0967741935,2,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-35557,Germany,98924.7311827957,6,FALSE,FALSE,5e3,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-35561,India,8515.6364704155,6,FALSE,TRUE,1e4,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
-35575,India,27455.5865511672,3,FALSE,TRUE,1e3,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+35545,United Kingdom,40000,12,FALSE,TRUE,1,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+35546,Germany,48387.0967741935,2,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+35557,Germany,98924.7311827957,6,FALSE,FALSE,5000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+35561,India,8515.6364704155,6,FALSE,TRUE,10000,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+35575,India,27455.5865511672,3,FALSE,TRUE,1000,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 35598,United Kingdom,46575,5,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-35601,United Kingdom,5e4,2,FALSE,TRUE,100,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+35601,United Kingdom,50000,2,FALSE,TRUE,100,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 35610,United Kingdom,41843.75,5,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 35619,Germany,53763.4408602151,13,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-35638,United Kingdom,55e3,6,FALSE,TRUE,10,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-35639,United Kingdom,42500,20,FALSE,FALSE,1e3,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+35638,United Kingdom,55000,6,FALSE,TRUE,10,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+35639,United Kingdom,42500,20,FALSE,FALSE,1000,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 35646,India,36705.3296138599,9,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 35656,United Kingdom,61250,7,FALSE,TRUE,100,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 35677,United Kingdom,76250,20,FALSE,FALSE,20,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
 35690,India,5872.85273821759,3,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 35706,United Kingdom,58750,6,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-35707,United Kingdom,52187.5,11,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+35707,United Kingdom,52187.5,11,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 35718,United Kingdom,62500,7,FALSE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 35742,Germany,45161.2903225806,20,TRUE,TRUE,20,Not remote,8,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-35745,United Kingdom,62500,2,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+35745,United Kingdom,62500,2,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-35775,Germany,80645.1612903226,13,TRUE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+35775,Germany,80645.1612903226,13,TRUE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 35784,United Kingdom,22500,1,FALSE,TRUE,20,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-35793,United Kingdom,5e4,4,FALSE,FALSE,1,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+35793,United Kingdom,50000,4,FALSE,FALSE,1,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 35849,India,2202.3197768316,1,FALSE,TRUE,1,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-35867,United Kingdom,45e3,5,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-35877,Germany,59139.7849462366,14,TRUE,TRUE,1e4,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+35867,United Kingdom,45000,5,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+35877,Germany,59139.7849462366,14,TRUE,TRUE,10000,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-35898,United States,92e3,20,FALSE,FALSE,10,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+35898,United States,92000,20,FALSE,FALSE,10,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 35907,Germany,78494.623655914,20,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-35917,United Kingdom,168750,19,FALSE,FALSE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-35937,United States,7e4,2,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
-35939,United Kingdom,62500,15,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+35917,United Kingdom,168750,19,FALSE,FALSE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+35937,United States,70000,2,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
+35939,United Kingdom,62500,15,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 35975,United Kingdom,59375,7,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-36008,United States,85e3,8,FALSE,FALSE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36023,United States,115e3,4,FALSE,TRUE,500,Not remote,7,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-36024,United States,109e3,14,FALSE,TRUE,1e4,Remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+36008,United States,85000,8,FALSE,FALSE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36023,United States,115000,4,FALSE,TRUE,500,Not remote,7,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+36024,United States,109000,14,FALSE,TRUE,10000,Remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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 36053,United Kingdom,71375,16,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-36098,United States,98e3,10,FALSE,TRUE,1e4,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36104,United States,85e3,15,FALSE,TRUE,1e4,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+36098,United States,98000,10,FALSE,TRUE,10000,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36104,United States,85000,15,FALSE,TRUE,10000,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
 36116,Canada,45454.5454545455,7,FALSE,FALSE,100,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-36117,United States,16e4,6,TRUE,FALSE,1e4,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-36118,United States,1e5,20,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36117,United States,160000,6,TRUE,FALSE,10000,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+36118,United States,100000,20,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 36119,Germany,64516.1290322581,20,TRUE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-36120,United States,15e4,15,FALSE,TRUE,1e3,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36138,United States,29e3,4,FALSE,TRUE,10,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-36152,United States,8e4,2,FALSE,TRUE,5e3,Remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36120,United States,150000,15,FALSE,TRUE,1000,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36138,United States,29000,4,FALSE,TRUE,10,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+36152,United States,80000,2,FALSE,TRUE,5000,Remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 36164,Germany,59139.7849462366,5,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36165,United States,55e3,5,TRUE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36165,United States,55000,5,TRUE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 36180,Germany,48387.0967741935,14,FALSE,FALSE,100,Not remote,6,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36197,India,3523.71164293055,4,FALSE,TRUE,1e4,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36199,United States,5e4,1,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36197,India,3523.71164293055,4,FALSE,TRUE,10000,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36199,United States,50000,1,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 36211,Germany,9032.25806451613,1,FALSE,TRUE,1,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 36226,United Kingdom,56250,19,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 36230,India,5285.56746439583,0,TRUE,FALSE,100,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 36236,United Kingdom,63750,6,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-36241,United States,4e4,2,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36249,United States,75e3,7,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36255,United States,27e3,2,FALSE,TRUE,1,Not remote,6,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-36279,United States,13e4,11,TRUE,TRUE,500,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-36287,United States,51e3,4,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-36289,United States,56e3,4,TRUE,TRUE,1,Remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-36290,United States,12e4,15,FALSE,FALSE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36294,United States,9e4,15,TRUE,TRUE,1e3,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-36295,United States,6e4,1,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-36298,Germany,107526.88172043,20,FALSE,TRUE,5e3,Not remote,8,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-36309,United States,1e5,1,FALSE,TRUE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36241,United States,40000,2,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36249,United States,75000,7,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36255,United States,27000,2,FALSE,TRUE,1,Not remote,6,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+36279,United States,130000,11,TRUE,TRUE,500,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+36287,United States,51000,4,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+36289,United States,56000,4,TRUE,TRUE,1,Remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+36290,United States,120000,15,FALSE,FALSE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36294,United States,90000,15,TRUE,TRUE,1000,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+36295,United States,60000,1,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+36298,Germany,107526.88172043,20,FALSE,TRUE,5000,Not remote,8,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+36309,United States,100000,1,FALSE,TRUE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-36327,United States,12e4,20,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-36332,United States,69995,4,FALSE,FALSE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36336,United States,73e3,8,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-36355,United States,8e4,2,FALSE,FALSE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36327,United States,120000,20,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+36332,United States,69995,4,FALSE,FALSE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36336,United States,73000,8,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+36355,United States,80000,2,FALSE,FALSE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 36374,Canada,40909.0909090909,5,TRUE,FALSE,20,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-36389,United States,91e3,15,TRUE,TRUE,1e4,Not remote,10,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-36395,Canada,39393.9393939394,8,FALSE,FALSE,5e3,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36405,Germany,53763.4408602151,1,FALSE,FALSE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-36410,United States,85e3,20,FALSE,TRUE,100,Not remote,6,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36417,India,8075.17251504918,3,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-36422,United States,13e4,5,FALSE,FALSE,1e4,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36429,United States,55e3,1,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-36433,United Kingdom,67500,4,TRUE,TRUE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36435,United States,145e3,11,TRUE,FALSE,100,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36389,United States,91000,15,TRUE,TRUE,10000,Not remote,10,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+36395,Canada,39393.9393939394,8,FALSE,FALSE,5000,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36405,Germany,53763.4408602151,1,FALSE,FALSE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+36410,United States,85000,20,FALSE,TRUE,100,Not remote,6,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36417,India,8075.17251504918,3,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+36422,United States,130000,5,FALSE,FALSE,10000,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36429,United States,55000,1,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+36433,United Kingdom,67500,4,TRUE,TRUE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36435,United States,145000,11,TRUE,FALSE,100,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-36441,United States,75e3,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36442,United States,7e4,1,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36453,United States,84e3,4,FALSE,FALSE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36457,United States,14e4,20,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-36473,United States,55e3,2,TRUE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36491,United States,16e4,20,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-36503,United States,86e3,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36514,United States,55e3,10,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36515,United States,5e4,6,FALSE,TRUE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
-36535,United Kingdom,56250,13,TRUE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36536,United States,51e3,6,TRUE,TRUE,20,Not remote,8,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-36545,United States,12e4,5,FALSE,FALSE,1e4,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36548,United States,145e3,20,TRUE,FALSE,20,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-36560,United States,118e3,4,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36574,United States,74e3,1,FALSE,TRUE,20,Not remote,10,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36582,United States,65e3,2,FALSE,TRUE,1,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
-36583,United States,92e3,9,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+36441,United States,75000,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36442,United States,70000,1,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36453,United States,84000,4,FALSE,FALSE,1000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36457,United States,140000,20,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+36473,United States,55000,2,TRUE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36491,United States,160000,20,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+36503,United States,86000,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36514,United States,55000,10,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36515,United States,50000,6,FALSE,TRUE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
+36535,United Kingdom,56250,13,TRUE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36536,United States,51000,6,TRUE,TRUE,20,Not remote,8,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+36545,United States,120000,5,FALSE,FALSE,10000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36548,United States,145000,20,TRUE,FALSE,20,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+36560,United States,118000,4,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36574,United States,74000,1,FALSE,TRUE,20,Not remote,10,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36582,United States,65000,2,FALSE,TRUE,1,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+36583,United States,92000,9,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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-36620,United States,125e3,4,TRUE,FALSE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36621,United States,57e3,1,FALSE,TRUE,1e4,Not remote,3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-36629,Germany,64516.1290322581,9,TRUE,FALSE,1e4,Not remote,0,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36632,United States,3e4,20,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+36620,United States,125000,4,TRUE,FALSE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36621,United States,57000,1,FALSE,TRUE,10000,Not remote,3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+36629,Germany,64516.1290322581,9,TRUE,FALSE,10000,Not remote,0,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36632,United States,30000,20,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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-36694,United States,115e3,20,FALSE,TRUE,1,Not remote,8,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-36699,United States,118e3,2,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+36694,United States,115000,20,FALSE,TRUE,1,Not remote,8,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+36699,United States,118000,2,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
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-36736,United States,21e3,6,FALSE,TRUE,1,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+36736,United States,21000,6,FALSE,TRUE,1,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
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-36758,United States,8e4,16,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36761,India,14682.131845544,3,TRUE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36762,India,1761.85582146528,4,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36818,India,16150.3450300984,5,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-36830,United Kingdom,55e3,20,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36758,United States,80000,16,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36761,India,14682.131845544,3,TRUE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36762,India,1761.85582146528,4,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36818,India,16150.3450300984,5,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36830,United Kingdom,55000,20,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-36919,United Kingdom,5e4,10,TRUE,TRUE,5e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
-36934,United Kingdom,35e3,3,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+36919,United Kingdom,50000,10,TRUE,TRUE,5000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
+36934,United Kingdom,35000,3,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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-36938,Germany,86021.5053763441,20,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+36938,Germany,86021.5053763441,20,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-36997,United Kingdom,123456.790123457,5,TRUE,TRUE,1e3,Not remote,8,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-36998,United Kingdom,121250,7,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-37009,India,30245.1916018206,9,FALSE,TRUE,1e3,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+36997,United Kingdom,123456.790123457,5,TRUE,TRUE,1000,Not remote,8,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+36998,United Kingdom,121250,7,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+37009,India,30245.1916018206,9,FALSE,TRUE,1000,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-37025,United States,95e3,8,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-37039,United States,135e3,14,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+37025,United States,95000,8,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+37039,United States,135000,14,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 37047,India,16150.3450300984,6,TRUE,TRUE,100,Not remote,9,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-37052,United States,113e3,12,FALSE,TRUE,100,Not remote,2,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-37056,United Kingdom,35e3,2,FALSE,TRUE,5e3,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+37052,United States,113000,12,FALSE,TRUE,100,Not remote,2,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+37056,United Kingdom,35000,2,FALSE,TRUE,5000,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-37073,United States,115e3,13,FALSE,FALSE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-37106,United States,92e3,10,FALSE,TRUE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-37109,United States,14e4,19,TRUE,TRUE,10,Not remote,9,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-37135,India,16150.3450300984,5,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+37073,United States,115000,13,FALSE,FALSE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+37106,United States,92000,10,FALSE,TRUE,1000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+37109,United States,140000,19,TRUE,TRUE,10,Not remote,9,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+37135,India,16150.3450300984,5,TRUE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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 37176,United Kingdom,66250,2,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-37184,United States,1e5,12,FALSE,TRUE,5e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+37184,United States,100000,12,FALSE,TRUE,5000,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
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-37270,United States,91e3,8,TRUE,TRUE,1,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-37276,United States,8e4,1,TRUE,TRUE,1e4,Not remote,3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-37283,United States,67500,5,FALSE,TRUE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-37292,United States,17e4,10,FALSE,FALSE,10,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-37300,United States,107e3,20,FALSE,TRUE,500,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-37325,United States,118e3,9,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+37270,United States,91000,8,TRUE,TRUE,1,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+37276,United States,80000,1,TRUE,TRUE,10000,Not remote,3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+37283,United States,67500,5,FALSE,TRUE,1000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+37292,United States,170000,10,FALSE,FALSE,10,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+37300,United States,107000,20,FALSE,TRUE,500,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+37325,United States,118000,9,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 37390,India,51387.4614594039,13,FALSE,TRUE,20,Not remote,8,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 37416,India,6166.49537512847,1,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-37459,India,14682.131845544,1,TRUE,TRUE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-37471,Germany,53763.4408602151,2,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+37459,India,14682.131845544,1,TRUE,TRUE,1000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+37471,Germany,53763.4408602151,2,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 37483,Germany,32258.064516129,5,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-37490,United States,142e3,5,FALSE,FALSE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+37490,United States,142000,5,FALSE,FALSE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 37497,Germany,86021.5053763441,9,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 37507,Canada,113636.363636364,15,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 37520,Germany,43333.3333333333,3,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
-37541,United States,92e3,20,TRUE,TRUE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-37558,Canada,30303.0303030303,2,FALSE,FALSE,1e3,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-37569,United States,101e3,16,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-37575,United States,16e4,16,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-37612,United States,9e4,1,FALSE,TRUE,5e3,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+37541,United States,92000,20,TRUE,TRUE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+37558,Canada,30303.0303030303,2,FALSE,FALSE,1000,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+37569,United States,101000,16,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+37575,United States,160000,16,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+37612,United States,90000,1,FALSE,TRUE,5000,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 37640,India,6313.31669358391,2,TRUE,TRUE,100,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 37651,India,4845.10350902951,2,TRUE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
 37665,Germany,59139.7849462366,8,TRUE,TRUE,20,Remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-37669,Germany,61290.3225806452,1,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-37690,Germany,26881.7204301075,3,FALSE,FALSE,1e4,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-37705,United States,9e4,5,TRUE,TRUE,100,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-37718,United States,9e4,11,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+37669,Germany,61290.3225806452,1,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+37690,Germany,26881.7204301075,3,FALSE,FALSE,10000,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+37705,United States,90000,5,TRUE,TRUE,100,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+37718,United States,90000,11,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 37722,United Kingdom,87500,15,TRUE,FALSE,100,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-37733,United States,95e3,4,TRUE,TRUE,1e4,Remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-37748,United States,108e3,6,TRUE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+37733,United States,95000,4,TRUE,TRUE,10000,Remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+37748,United States,108000,6,TRUE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 37754,Germany,51612.9032258064,2,FALSE,TRUE,10,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 37755,Germany,69892.4731182796,3,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE
-37759,United States,119e3,12,FALSE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-37763,United States,104e3,20,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-37771,United States,126e3,10,TRUE,TRUE,100,Remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-37804,United States,156e3,2,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-37809,United States,6e4,1,FALSE,TRUE,20,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-37816,United States,78e3,5,FALSE,TRUE,1e4,Not remote,7,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-37840,United States,83500,1,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-37841,United States,95e3,6,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+37759,United States,119000,12,FALSE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+37763,United States,104000,20,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+37771,United States,126000,10,TRUE,TRUE,100,Remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+37804,United States,156000,2,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+37809,United States,60000,1,FALSE,TRUE,20,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+37816,United States,78000,5,FALSE,TRUE,10000,Not remote,7,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+37840,United States,83500,1,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+37841,United States,95000,6,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 37944,India,5872.85273821759,3,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 37980,India,6606.95933049479,3,FALSE,FALSE,20,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-37982,India,1174.57054764352,6,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+37982,India,1174.57054764352,6,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 38012,Germany,83870.9677419355,5,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 38018,India,4404.63955366319,2,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 38020,Germany,34408.6021505376,1,TRUE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 38075,India,20554.9845837616,6,TRUE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 38091,India,13948.0252532668,7,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 38120,India,35237.1164293055,0,TRUE,TRUE,1,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-38127,India,6900.60196740567,5,FALSE,TRUE,1e4,Not remote,7,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+38127,India,6900.60196740567,5,FALSE,TRUE,10000,Not remote,7,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 38142,Germany,60215.0537634409,10,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38148,United Kingdom,75e3,17,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38158,India,2660.40229041257,1,FALSE,TRUE,1e3,Not remote,0,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+38148,United Kingdom,75000,17,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38158,India,2660.40229041257,1,FALSE,TRUE,1000,Not remote,0,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 38163,United Kingdom,56250,20,FALSE,FALSE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-38176,United Kingdom,68750,3,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-38190,Germany,64516.1290322581,9,TRUE,TRUE,1e3,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38176,United Kingdom,68750,3,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+38190,Germany,64516.1290322581,9,TRUE,TRUE,1000,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 38211,Germany,59408.6021505376,9,FALSE,FALSE,500,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-38227,Germany,44946.2365591398,2,FALSE,TRUE,1e3,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-38231,United Kingdom,43750,5,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38227,Germany,44946.2365591398,2,FALSE,TRUE,1000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+38231,United Kingdom,43750,5,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 38264,India,22394.7446999104,8,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38270,United Kingdom,49500,2,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+38270,United Kingdom,49500,2,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 38283,Germany,69892.4731182796,13,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38297,United Kingdom,31250,1,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+38297,United Kingdom,31250,1,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
 38333,Germany,3440.86021505376,9,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 38335,India,4404.63955366319,2,FALSE,FALSE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
 38343,India,20554.9845837616,20,FALSE,TRUE,500,Remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-38346,United Kingdom,45e3,5,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+38346,United Kingdom,45000,5,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 38349,India,3523.71164293055,0,TRUE,TRUE,20,Remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 38357,India,4580.82513580972,3,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 38359,India,4052.26838937014,1,FALSE,FALSE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
 38372,United Kingdom,42500,4,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 38410,India,10864.7775657025,4,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38416,Germany,64516.1290322581,9,FALSE,TRUE,1e4,Not remote,5,TRUE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-38435,India,19086.7713992072,4,FALSE,TRUE,1e4,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38416,Germany,64516.1290322581,9,FALSE,TRUE,10000,Not remote,5,TRUE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+38435,India,19086.7713992072,4,FALSE,TRUE,10000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 38437,United Kingdom,31250,3,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38463,India,4698.28219057407,1,FALSE,TRUE,1e4,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-38486,India,5285.56746439583,0,TRUE,TRUE,1e3,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+38463,India,4698.28219057407,1,FALSE,TRUE,10000,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+38486,India,5285.56746439583,0,TRUE,TRUE,1000,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 38491,Germany,3225.8064516129,1,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-38492,India,5872.85273821759,2,FALSE,FALSE,1e4,Not remote,4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-38515,Germany,63440.8602150538,3,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+38492,India,5872.85273821759,2,FALSE,FALSE,10000,Not remote,4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+38515,Germany,63440.8602150538,3,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
 38518,India,4404.63955366319,5,TRUE,TRUE,10,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38540,United Kingdom,37500,2,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38543,United States,6e4,2,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+38540,United Kingdom,37500,2,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38543,United States,60000,2,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
 38551,United Kingdom,71250,13,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38555,United States,103e3,14,FALSE,FALSE,1e3,Not remote,2,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38555,United States,103000,14,FALSE,FALSE,1000,Not remote,2,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 38556,Germany,58064.5161290323,4,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 38559,United States,107500,6,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38562,Germany,51612.9032258064,7,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38570,Germany,80645.1612903226,16,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38562,Germany,51612.9032258064,7,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38570,Germany,80645.1612903226,16,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 38574,United States,41600,2,FALSE,FALSE,20,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-38598,United States,109e3,12,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38622,United States,41e3,2,FALSE,TRUE,1e3,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38598,United States,109000,12,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38622,United States,41000,2,FALSE,TRUE,1000,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 38623,India,11745.7054764352,4,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38631,Germany,75268.8172043011,17,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-38641,United States,75e3,5,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38653,United States,9e4,5,TRUE,TRUE,20,Remote,2,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38658,United States,6e4,7,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-38662,United States,13e4,9,TRUE,TRUE,100,Remote,9,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-38663,United States,12e4,7,FALSE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38667,United States,85e3,1,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38682,United States,89e3,8,FALSE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+38631,Germany,75268.8172043011,17,TRUE,TRUE,10000,Not remote,10,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+38641,United States,75000,5,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38653,United States,90000,5,TRUE,TRUE,20,Remote,2,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38658,United States,60000,7,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+38662,United States,130000,9,TRUE,TRUE,100,Remote,9,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+38663,United States,120000,7,FALSE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38667,United States,85000,1,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38682,United States,89000,8,FALSE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 38695,Germany,69892.4731182796,8,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-38710,United States,7e4,12,TRUE,TRUE,1e4,Remote,3,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38710,United States,70000,12,TRUE,TRUE,10000,Remote,3,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 38711,United Kingdom,32187.5,1,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-38716,United States,62e3,5,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38720,Germany,51612.9032258064,6,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-38721,United States,9e4,2,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38716,United States,62000,5,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38720,Germany,51612.9032258064,6,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+38721,United States,90000,2,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 38747,United States,87500,13,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-38750,United Kingdom,125e3,15,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-38759,United States,8e4,5,FALSE,TRUE,1,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-38772,United States,92e3,7,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38773,United States,78e3,13,FALSE,FALSE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-38777,United States,14e4,20,FALSE,FALSE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38781,United States,9e4,2,FALSE,FALSE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38750,United Kingdom,125000,15,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+38759,United States,80000,5,FALSE,TRUE,1,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+38772,United States,92000,7,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38773,United States,78000,13,FALSE,FALSE,1000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+38777,United States,140000,20,FALSE,FALSE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38781,United States,90000,2,FALSE,FALSE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 38795,Germany,66666.6666666667,12,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 38796,United States,92406,6,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
-38797,United States,95e3,16,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-38818,United Kingdom,51e3,4,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38819,Germany,80645.1612903226,7,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-38828,United States,63300,2,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-38832,United States,82e3,2,FALSE,TRUE,1e3,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38834,Germany,107526.88172043,9,TRUE,TRUE,1e4,Not remote,6,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+38797,United States,95000,16,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+38818,United Kingdom,51000,4,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38819,Germany,80645.1612903226,7,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+38828,United States,63300,2,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+38832,United States,82000,2,FALSE,TRUE,1000,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38834,Germany,107526.88172043,9,TRUE,TRUE,10000,Not remote,6,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
 38845,India,7399.79445015416,3,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38853,United Kingdom,73750,14,FALSE,FALSE,1e4,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38853,United Kingdom,73750,14,FALSE,FALSE,10000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 38868,Germany,88172.0430107527,13,TRUE,TRUE,20,Not remote,9,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-38869,United States,92e3,5,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38878,United States,96e3,5,FALSE,FALSE,1e4,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+38869,United States,92000,5,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38878,United States,96000,5,FALSE,FALSE,10000,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 38885,India,20554.9845837616,2,TRUE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 38886,United States,53500,2,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-38900,United States,12e4,17,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38962,United States,126e3,15,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-38986,United States,35e3,1,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-38993,United States,11e4,4,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39005,United States,65e3,1,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39010,United States,165e3,20,FALSE,FALSE,10,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39016,United States,65e3,5,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39019,United States,124e3,15,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39020,United States,65e3,4,FALSE,FALSE,100,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-39025,United Kingdom,86250,13,TRUE,FALSE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE
+38900,United States,120000,17,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38962,United States,126000,15,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+38986,United States,35000,1,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+38993,United States,110000,4,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39005,United States,65000,1,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39010,United States,165000,20,FALSE,FALSE,10,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39016,United States,65000,5,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39019,United States,124000,15,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39020,United States,65000,4,FALSE,FALSE,100,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+39025,United Kingdom,86250,13,TRUE,FALSE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE
 39028,Canada,41666.6666666667,6,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-39033,United States,83e3,10,FALSE,FALSE,20,Not remote,6,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-39041,Canada,50757.5757575758,19,FALSE,FALSE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39045,United States,45e3,10,FALSE,FALSE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39046,United States,83e3,4,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39048,United States,6e4,16,FALSE,FALSE,100,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39065,United States,19e4,20,FALSE,FALSE,20,Remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+39033,United States,83000,10,FALSE,FALSE,20,Not remote,6,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+39041,Canada,50757.5757575758,19,FALSE,FALSE,1000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39045,United States,45000,10,FALSE,FALSE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39046,United States,83000,4,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39048,United States,60000,16,FALSE,FALSE,100,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39065,United States,190000,20,FALSE,FALSE,20,Remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 39070,Canada,94696.9696969697,2,TRUE,TRUE,20,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-39075,United States,55e3,2,TRUE,TRUE,5e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39086,United States,6e4,16,FALSE,TRUE,1,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE
-39105,United States,12e4,20,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39075,United States,55000,2,TRUE,TRUE,5000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39086,United States,60000,16,FALSE,TRUE,1,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE
+39105,United States,120000,20,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 39108,Germany,137634.408602151,16,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 39123,United States,62500,1,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39135,United States,13e4,20,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39149,United States,125e3,20,FALSE,TRUE,1e4,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39154,United States,98e3,8,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+39135,United States,130000,20,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39149,United States,125000,20,FALSE,TRUE,10000,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39154,United States,98000,8,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 39162,United Kingdom,42500,2,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39170,United States,6e4,3,FALSE,TRUE,10,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+39170,United States,60000,3,FALSE,TRUE,10,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 39174,United Kingdom,37500,3,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-39176,United States,75e3,2,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39178,United States,11e4,4,TRUE,TRUE,20,Not remote,10,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39184,United States,1e5,19,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39191,United States,185e3,20,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+39176,United States,75000,2,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39178,United States,110000,4,TRUE,TRUE,20,Not remote,10,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39184,United States,100000,19,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39191,United States,185000,20,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 39196,Germany,56989.247311828,6,TRUE,TRUE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39197,United States,115e3,3,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39202,United States,105e3,10,FALSE,TRUE,5e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39205,United States,7e4,4,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39210,United States,8e4,7,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39223,United States,19e4,14,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39231,United States,11e4,14,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-39238,United States,17e4,14,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-39245,United States,77500,6,FALSE,TRUE,5e3,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39280,United States,98e3,20,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-39295,India,24959.6241374248,4,FALSE,FALSE,1e4,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-39300,United States,13e4,1,FALSE,FALSE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39306,India,4404.63955366319,1,FALSE,TRUE,1e3,Remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+39197,United States,115000,3,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39202,United States,105000,10,FALSE,TRUE,5000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39205,United States,70000,4,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39210,United States,80000,7,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39223,United States,190000,14,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39231,United States,110000,14,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+39238,United States,170000,14,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+39245,United States,77500,6,FALSE,TRUE,5000,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39280,United States,98000,20,TRUE,TRUE,10000,Not remote,10,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+39295,India,24959.6241374248,4,FALSE,FALSE,10000,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+39300,United States,130000,1,FALSE,FALSE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39306,India,4404.63955366319,1,FALSE,TRUE,1000,Remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 39311,United States,74800,4,TRUE,TRUE,20,Remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-39313,United States,105e3,2,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39342,India,16796.3588313023,5,FALSE,FALSE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+39313,United States,105000,2,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39342,India,16796.3588313023,5,FALSE,FALSE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 39347,India,3523.71164293055,2,TRUE,TRUE,10,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 39348,India,2936.42636910879,2,TRUE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 39355,India,6342.680957275,4,TRUE,TRUE,100,Not remote,2,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39359,United States,155e3,17,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39370,India,5872.85273821759,2,FALSE,FALSE,1e4,Not remote,2,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-39379,India,28630.1570988107,12,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-39391,United States,4e4,5,FALSE,FALSE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39359,United States,155000,17,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39370,India,5872.85273821759,2,FALSE,FALSE,10000,Not remote,2,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39379,India,28630.1570988107,12,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+39391,United States,40000,5,FALSE,FALSE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 39396,India,1761.85582146528,1,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
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 39463,India,17618.5582146528,5,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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 39610,India,2349.14109528704,1,FALSE,TRUE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-39616,United Kingdom,5e4,20,FALSE,FALSE,20,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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 39622,India,5138.74614594039,4,TRUE,TRUE,100,Not remote,3,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 39662,India,2642.78373219792,1,FALSE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-39676,United Kingdom,62500,3,TRUE,FALSE,1e4,Not remote,7,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-39737,United Kingdom,5e4,5,FALSE,TRUE,1e3,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 39771,India,10277.4922918808,7,FALSE,FALSE,20,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 39833,United Kingdom,28750,2,FALSE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 39867,Germany,69892.4731182796,9,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-39878,United States,1e5,19,FALSE,FALSE,5e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+39878,United States,100000,19,FALSE,FALSE,5000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 39893,Germany,43010.752688172,9,TRUE,TRUE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 39906,United Kingdom,58655,7,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-39923,United States,16e4,20,TRUE,TRUE,10,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+39923,United States,160000,20,TRUE,TRUE,10,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
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-39951,United States,97e3,4,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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 39961,India,4771.69284980179,0,TRUE,FALSE,1,Remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 40014,India,14645.4265159301,13,FALSE,TRUE,20,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 40030,Germany,2956.98924731183,3,FALSE,TRUE,20,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-40039,United Kingdom,35625,4,FALSE,FALSE,1e3,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40040,United States,129e3,16,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40039,United Kingdom,35625,4,FALSE,FALSE,1000,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 40085,United Kingdom,28750,3,FALSE,TRUE,1,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
 40092,United States,73500,4,FALSE,TRUE,500,Not remote,2,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40101,India,11011.598884158,5,FALSE,TRUE,1e4,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40110,United States,11e4,4,FALSE,TRUE,1e3,Not remote,7,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+40101,India,11011.598884158,5,FALSE,TRUE,10000,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40110,United States,110000,4,FALSE,TRUE,1000,Not remote,7,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
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-40175,United States,92e3,3,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-40189,United States,1e5,16,FALSE,FALSE,1e3,Not remote,9,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-40190,United States,98500,5,TRUE,FALSE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40195,United States,7e4,3,TRUE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40175,United States,92000,3,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+40189,United States,100000,16,FALSE,FALSE,1000,Not remote,9,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+40190,United States,98500,5,TRUE,FALSE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40195,United States,70000,3,TRUE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 40207,Germany,59139.7849462366,9,FALSE,TRUE,100,Not remote,6,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-40208,Canada,51893.9393939394,3,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+40208,Canada,51893.9393939394,3,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 40209,Germany,53763.4408602151,3,FALSE,TRUE,500,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 40211,Germany,69892.4731182796,11,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40242,United States,18e4,19,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40264,United States,6e4,8,FALSE,TRUE,100,Not remote,5,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40270,United States,65e3,3,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-40273,United States,13e4,15,FALSE,TRUE,20,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40280,United States,92e3,2,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40282,United States,95e3,3,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40303,United States,115e3,4,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-40305,United States,2e4,9,FALSE,FALSE,1,Remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-40306,United States,5e4,2,FALSE,TRUE,1e3,Not remote,4,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40312,United States,125e3,17,FALSE,FALSE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-40315,United States,4e4,2,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40242,United States,180000,19,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40264,United States,60000,8,FALSE,TRUE,100,Not remote,5,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40270,United States,65000,3,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+40273,United States,130000,15,FALSE,TRUE,20,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40280,United States,92000,2,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40282,United States,95000,3,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40303,United States,115000,4,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+40305,United States,20000,9,FALSE,FALSE,1,Remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+40306,United States,50000,2,FALSE,TRUE,1000,Not remote,4,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40312,United States,125000,17,FALSE,FALSE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+40315,United States,40000,2,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-40321,United States,72e3,2,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40324,United States,143820,11,TRUE,FALSE,1e3,Remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40326,United States,48e3,2,FALSE,TRUE,1e3,Not remote,3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40327,United States,52e3,9,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
-40336,United States,15e4,16,TRUE,TRUE,5e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40337,United States,112e3,12,TRUE,TRUE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40321,United States,72000,2,TRUE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40324,United States,143820,11,TRUE,FALSE,1000,Remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40326,United States,48000,2,FALSE,TRUE,1000,Not remote,3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40327,United States,52000,9,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
+40336,United States,150000,16,TRUE,TRUE,5000,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40337,United States,112000,12,TRUE,TRUE,1000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-40341,United States,12e4,12,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-40347,United States,8e4,10,FALSE,FALSE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40349,United States,9e4,4,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40353,United States,83e3,14,FALSE,TRUE,100,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40358,United States,65e3,4,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-40359,United States,148e3,17,FALSE,FALSE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-40361,United States,125e3,20,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40341,United States,120000,12,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+40347,United States,80000,10,FALSE,FALSE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40349,United States,90000,4,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40353,United States,83000,14,FALSE,TRUE,100,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40358,United States,65000,4,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+40359,United States,148000,17,FALSE,FALSE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+40361,United States,125000,20,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-40364,United States,8e4,8,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40366,United States,12e4,20,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40368,United States,16e4,8,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40369,United States,11e4,4,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40373,United States,66e3,16,FALSE,TRUE,1,Remote,6,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
-40381,United States,108e3,10,FALSE,FALSE,1e3,Not remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-40386,United States,75e3,1,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40390,United States,67e3,6,TRUE,TRUE,1,Not remote,7,FALSE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-40391,United States,88e3,15,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40392,Canada,64393.9393939394,3,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40398,United States,67e3,3,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-40401,United States,6e4,1,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40410,United States,87e3,13,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-40420,United States,78e3,1,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-40422,United States,91e3,20,FALSE,TRUE,1e4,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-40425,Canada,53030.303030303,9,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40431,United States,39e3,18,FALSE,TRUE,500,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40432,United States,119e3,12,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+40364,United States,80000,8,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40366,United States,120000,20,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40368,United States,160000,8,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40369,United States,110000,4,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40373,United States,66000,16,FALSE,TRUE,1,Remote,6,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
+40381,United States,108000,10,FALSE,FALSE,1000,Not remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+40386,United States,75000,1,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40390,United States,67000,6,TRUE,TRUE,1,Not remote,7,FALSE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+40391,United States,88000,15,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40392,Canada,64393.9393939394,3,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40398,United States,67000,3,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+40401,United States,60000,1,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40410,United States,87000,13,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+40420,United States,78000,1,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+40422,United States,91000,20,FALSE,TRUE,10000,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+40425,Canada,53030.303030303,9,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40431,United States,39000,18,FALSE,TRUE,500,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40432,United States,119000,12,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 40434,Canada,46212.1212121212,4,FALSE,TRUE,1,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-40437,United States,52e3,1,TRUE,TRUE,100,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40438,United States,8e4,6,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40440,United States,115e3,9,FALSE,FALSE,1e4,Remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-40441,United States,6e4,4,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40445,United States,87125,5,FALSE,TRUE,5e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40437,United States,52000,1,TRUE,TRUE,100,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40438,United States,80000,6,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40440,United States,115000,9,FALSE,FALSE,10000,Remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+40441,United States,60000,4,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40445,United States,87125,5,FALSE,TRUE,5000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 40446,United Kingdom,68750,7,FALSE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-40451,United States,104e3,20,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-40459,United States,6e4,5,FALSE,TRUE,500,Not remote,8,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40460,United States,2e4,5,FALSE,TRUE,1,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40465,United Kingdom,143750,17,TRUE,FALSE,1e4,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-40466,United Kingdom,95e3,9,TRUE,TRUE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-40481,United States,11e4,20,TRUE,FALSE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-40482,United States,133e3,7,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-40485,United States,18e4,4,TRUE,TRUE,1,Remote,5,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40490,United States,98e3,0,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-40495,United States,85e3,2,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40503,United States,17e4,20,TRUE,FALSE,10,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40506,United States,11e4,2,TRUE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-40507,United States,8e4,8,FALSE,FALSE,100,Not remote,10,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-40512,United States,55e3,8,FALSE,TRUE,100,Not remote,4,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-40513,United States,95e3,2,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40514,United States,66114,16,FALSE,FALSE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+40451,United States,104000,20,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+40459,United States,60000,5,FALSE,TRUE,500,Not remote,8,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40460,United States,20000,5,FALSE,TRUE,1,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40465,United Kingdom,143750,17,TRUE,FALSE,10000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+40466,United Kingdom,95000,9,TRUE,TRUE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+40481,United States,110000,20,TRUE,FALSE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+40482,United States,133000,7,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+40485,United States,180000,4,TRUE,TRUE,1,Remote,5,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40490,United States,98000,0,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+40495,United States,85000,2,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40503,United States,170000,20,TRUE,FALSE,10,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40506,United States,110000,2,TRUE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+40507,United States,80000,8,FALSE,FALSE,100,Not remote,10,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+40512,United States,55000,8,FALSE,TRUE,100,Not remote,4,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+40513,United States,95000,2,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40514,United States,66114,16,FALSE,FALSE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 40524,India,10864.7775657025,3,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-40527,United States,8e4,15,TRUE,TRUE,10,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
-40528,United States,112e3,6,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40529,United States,81e3,7,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40527,United States,80000,15,TRUE,TRUE,10,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+40528,United States,112000,6,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40529,United States,81000,7,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 40531,United States,17500,1,TRUE,TRUE,20,Remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-40535,India,6636.32359418588,2,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-40541,India,6606.95933049479,1,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-40545,United States,165e3,8,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-40549,United States,13e4,6,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-40557,United States,18e4,20,FALSE,TRUE,20,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-40561,United States,8e4,3,FALSE,TRUE,100,Not remote,7,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40535,India,6636.32359418588,2,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+40541,India,6606.95933049479,1,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+40545,United States,165000,8,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+40549,United States,130000,6,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+40557,United States,180000,20,FALSE,TRUE,20,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+40561,United States,80000,3,FALSE,TRUE,100,Not remote,7,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 40565,Canada,28787.8787878788,1,FALSE,FALSE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
 40602,United Kingdom,87500,8,FALSE,TRUE,1,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40603,India,12479.8120687124,8,TRUE,TRUE,1e4,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-40606,United Kingdom,53750,7,FALSE,TRUE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-40610,India,19086.7713992072,11,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40603,India,12479.8120687124,8,TRUE,TRUE,10000,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+40606,United Kingdom,53750,7,FALSE,TRUE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+40610,India,19086.7713992072,11,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 40612,India,18352.66480693,2,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-40617,United Kingdom,35625,2,FALSE,TRUE,5e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-40623,Germany,80645.1612903226,19,TRUE,TRUE,1e4,Not remote,10,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE,TRUE,TRUE
-40624,United Kingdom,47500,6,TRUE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40625,United Kingdom,75e3,8,TRUE,FALSE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40617,United Kingdom,35625,2,FALSE,TRUE,5000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+40623,Germany,80645.1612903226,19,TRUE,TRUE,10000,Not remote,10,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE,TRUE,TRUE
+40624,United Kingdom,47500,6,TRUE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40625,United Kingdom,75000,8,TRUE,FALSE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 40630,Germany,51612.9032258064,6,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-40638,India,13213.9186609896,3,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40646,India,16884.4516223756,6,FALSE,TRUE,1e4,Remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-40647,United Kingdom,78750,10,TRUE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40655,United Kingdom,48750,20,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40638,India,13213.9186609896,3,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40646,India,16884.4516223756,6,FALSE,TRUE,10000,Remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+40647,United Kingdom,78750,10,TRUE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40655,United Kingdom,48750,20,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 40660,United Kingdom,56250,5,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 40669,Germany,51612.9032258064,7,TRUE,TRUE,500,Not remote,3,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 40671,United Kingdom,29375,1,FALSE,FALSE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 40673,Germany,46236.5591397849,5,FALSE,FALSE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 40685,India,8075.17251504918,2,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-40687,United States,87e3,7,FALSE,TRUE,1e4,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+40687,United States,87000,7,FALSE,TRUE,10000,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 40692,Germany,69892.4731182796,12,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-40694,United States,7e4,6,FALSE,TRUE,100,Not remote,9,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
-40696,United States,1e5,20,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40694,United States,70000,6,FALSE,TRUE,100,Not remote,9,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
+40696,United States,100000,20,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 40705,Germany,53763.4408602151,3,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-40712,Germany,48924.7311827957,9,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40712,Germany,48924.7311827957,9,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 40713,United States,57500,6,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-40717,United States,6e4,2,FALSE,TRUE,100,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40717,United States,60000,2,FALSE,TRUE,100,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 40720,Canada,67575.7575757576,11,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 40721,United Kingdom,62500,6,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40728,United States,75e3,3,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40728,United States,75000,3,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 40734,United Kingdom,107500,6,TRUE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 40736,United Kingdom,52500,4,FALSE,TRUE,100,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-40737,United Kingdom,5e4,8,FALSE,TRUE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-40740,United States,8e4,4,TRUE,FALSE,1e4,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40737,United Kingdom,50000,8,FALSE,TRUE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+40740,United States,80000,4,TRUE,FALSE,10000,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 40744,United States,45700,1,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-40745,United States,75e3,5,FALSE,TRUE,20,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+40745,United States,75000,5,FALSE,TRUE,20,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 40749,Canada,48484.8484848485,12,FALSE,TRUE,10,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-40754,United States,58e3,3,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40754,United States,58000,3,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 40756,Germany,43010.752688172,3,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
-40757,United States,92e3,9,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
-40758,United States,1e5,20,FALSE,TRUE,5e3,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-40759,United States,11e4,4,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40757,United States,92000,9,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
+40758,United States,100000,20,FALSE,TRUE,5000,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+40759,United States,110000,4,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 40760,Germany,75268.8172043011,20,TRUE,FALSE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
-40761,United States,9e4,20,FALSE,TRUE,10,Remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40770,United States,178e3,20,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40761,United States,90000,20,FALSE,TRUE,10,Remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40770,United States,178000,20,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 40771,Canada,9090.90909090909,17,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-40776,United States,93e3,20,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40780,United States,135e3,9,TRUE,TRUE,1e3,Remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-40781,United States,1e5,20,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40782,United States,115e3,18,FALSE,FALSE,1e4,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40776,United States,93000,20,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40780,United States,135000,9,TRUE,TRUE,1000,Remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+40781,United States,100000,20,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40782,United States,115000,18,FALSE,FALSE,10000,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-40787,United States,115e3,20,FALSE,FALSE,20,Remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40788,United States,65e3,2,FALSE,TRUE,1e3,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
-40791,United States,133e3,15,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40793,United States,136e3,11,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+40787,United States,115000,20,FALSE,FALSE,20,Remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40788,United States,65000,2,FALSE,TRUE,1000,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
+40791,United States,133000,15,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40793,United States,136000,11,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-40796,Canada,34090.9090909091,2,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-40803,United States,116e3,11,TRUE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-40805,United States,115e3,18,FALSE,TRUE,100,Remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-40812,United States,75e3,4,TRUE,TRUE,10,Not remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-40819,India,11011.598884158,3,FALSE,TRUE,5e3,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+40796,Canada,34090.9090909091,2,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+40803,United States,116000,11,TRUE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+40805,United States,115000,18,FALSE,TRUE,100,Remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-40843,United States,8e4,9,TRUE,TRUE,10,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-40849,United States,55e3,2,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-40855,United States,145e3,2,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-40875,Germany,80645.1612903226,20,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE
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+40855,United States,145000,2,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+40875,Germany,80645.1612903226,20,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE
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-40893,United States,96e3,6,TRUE,TRUE,1,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-40902,United States,11e4,20,TRUE,FALSE,1,Not remote,7,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-40906,United States,11e4,20,FALSE,TRUE,5e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+40902,United States,110000,20,TRUE,FALSE,1,Not remote,7,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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-40912,United States,79500,7,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40918,United States,65e3,3,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-40930,India,2936.42636910879,9,FALSE,FALSE,5e3,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-40968,United States,127e3,20,TRUE,FALSE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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+40930,India,2936.42636910879,9,FALSE,FALSE,5000,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40968,United States,127000,20,TRUE,FALSE,1000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-40996,India,6562.91293495816,1,FALSE,TRUE,1e4,Not remote,3,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-41003,United States,15e4,16,TRUE,TRUE,1e4,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-41007,United States,79e3,14,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41015,United States,145e3,15,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41018,United States,75e3,2,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41019,United States,108e3,18,TRUE,TRUE,20,Not remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE
-41021,United States,12e4,15,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-41022,United States,7e4,2,FALSE,TRUE,1e4,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-41023,United Kingdom,5e4,4,FALSE,FALSE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+40996,India,6562.91293495816,1,FALSE,TRUE,10000,Not remote,3,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+41003,United States,150000,16,TRUE,TRUE,10000,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
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+41015,United States,145000,15,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41018,United States,75000,2,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41019,United States,108000,18,TRUE,TRUE,20,Not remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE
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+41022,United States,70000,2,FALSE,TRUE,10000,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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 41026,United Kingdom,58064.5161290323,7,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41029,Canada,49242.4242424242,9,FALSE,FALSE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41029,Canada,49242.4242424242,9,FALSE,FALSE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-41033,Canada,72727.2727272727,9,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41034,United States,45e3,1,FALSE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-41038,United States,125e3,8,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41040,United States,7e4,5,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41046,United States,129e3,16,TRUE,TRUE,1e3,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41048,United States,95e3,14,FALSE,TRUE,1e4,Not remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+41033,Canada,72727.2727272727,9,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41034,United States,45000,1,FALSE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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-41059,United Kingdom,4e4,1,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-41063,United Kingdom,106250,15,FALSE,TRUE,1e4,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-41108,United States,69e3,5,FALSE,TRUE,1e4,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-41109,United States,83e3,5,FALSE,TRUE,5e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-41172,United Kingdom,42750,1,FALSE,FALSE,1e3,Not remote,0,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+41160,United Kingdom,47500,11,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41172,United Kingdom,42750,1,FALSE,FALSE,1000,Not remote,0,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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+41181,Germany,43010.752688172,5,TRUE,FALSE,1000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
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-41197,United States,12e4,5,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-41212,United States,6e4,3,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-41221,United States,72e3,6,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-41233,United States,12e4,4,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-41242,United States,12e4,3,TRUE,TRUE,5e3,Not remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-41243,United States,125e3,11,FALSE,TRUE,1,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-41244,Canada,71e3,6,TRUE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41245,United States,12e4,6,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41247,United States,172e3,12,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-41249,United States,106e3,10,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41242,United States,120000,3,TRUE,TRUE,5000,Not remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+41243,United States,125000,11,FALSE,TRUE,1,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+41244,Canada,71000,6,TRUE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41245,United States,120000,6,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41247,United States,172000,12,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+41249,United States,106000,10,TRUE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-41256,United States,6e4,4,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41258,United States,1e5,9,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-41259,Canada,42424.2424242424,1,TRUE,TRUE,5e3,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+41256,United States,60000,4,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41258,United States,100000,9,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+41259,Canada,42424.2424242424,1,TRUE,TRUE,5000,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 41260,Canada,53030.303030303,5,FALSE,TRUE,100,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41263,United States,25e3,2,FALSE,TRUE,10,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41274,United States,68e3,1,TRUE,FALSE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-41275,United States,13e4,4,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-41278,United States,104e3,20,FALSE,FALSE,1,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-41298,India,5872.85273821759,2,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+41263,United States,25000,2,FALSE,TRUE,10,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41274,United States,68000,1,TRUE,FALSE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+41275,United States,130000,4,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+41278,United States,104000,20,FALSE,FALSE,1,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+41298,India,5872.85273821759,2,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 41306,Canada,47348.4848484848,3,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
-41308,United States,1e5,16,FALSE,TRUE,20,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
-41312,United States,6e4,19,FALSE,FALSE,1e3,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+41308,United States,100000,16,FALSE,TRUE,20,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+41312,United States,60000,19,FALSE,FALSE,1000,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 41315,Canada,47727.2727272727,20,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41320,United States,8e4,3,FALSE,TRUE,10,Not remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-41321,United States,88e3,10,TRUE,TRUE,500,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41322,United States,1e5,16,TRUE,TRUE,1e4,Not remote,9,TRUE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-41325,United States,45e3,2,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+41320,United States,80000,3,FALSE,TRUE,10,Not remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+41321,United States,88000,10,TRUE,TRUE,500,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41322,United States,100000,16,TRUE,TRUE,10000,Not remote,9,TRUE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+41325,United States,45000,2,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 41327,United Kingdom,43750,8,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 41330,United Kingdom,58750,19,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-41331,United States,92e3,10,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41332,United States,11e4,1,FALSE,TRUE,500,Remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-41336,United States,7e4,16,FALSE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-41339,United States,75e3,10,TRUE,TRUE,1e3,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41343,United States,6e4,2,FALSE,TRUE,1,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-41344,United States,5e4,0,FALSE,TRUE,500,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41347,United States,165e3,20,FALSE,FALSE,5e3,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41352,United States,7e4,2,TRUE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+41331,United States,92000,10,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41332,United States,110000,1,FALSE,TRUE,500,Remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+41336,United States,70000,16,FALSE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+41339,United States,75000,10,TRUE,TRUE,1000,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41343,United States,60000,2,FALSE,TRUE,1,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+41344,United States,50000,0,FALSE,TRUE,500,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41347,United States,165000,20,FALSE,FALSE,5000,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41352,United States,70000,2,TRUE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
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-41357,United States,125e3,17,FALSE,TRUE,20,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+41357,United States,125000,17,FALSE,TRUE,20,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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-41361,United States,3e4,8,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
-41362,United States,75e3,20,FALSE,TRUE,100,Not remote,4,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+41361,United States,30000,8,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
+41362,United States,75000,20,FALSE,TRUE,100,Not remote,4,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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-41365,United States,89573,20,TRUE,TRUE,1e4,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-41369,United States,135e3,3,TRUE,TRUE,1e4,Not remote,6,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-41372,United States,94e3,3,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41380,United States,77e3,20,TRUE,TRUE,500,Not remote,8,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-41383,United States,13e4,17,TRUE,FALSE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+41365,United States,89573,20,TRUE,TRUE,10000,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+41369,United States,135000,3,TRUE,TRUE,10000,Not remote,6,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+41372,United States,94000,3,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41380,United States,77000,20,TRUE,TRUE,500,Not remote,8,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+41383,United States,130000,17,TRUE,FALSE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 41389,Canada,60606.0606060606,1,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 41390,Canada,55303.0303030303,2,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-41392,United States,7e4,3,FALSE,TRUE,500,Not remote,6,TRUE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-41397,United States,108e3,5,FALSE,TRUE,1e4,Remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-41399,United States,195e3,16,TRUE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-41401,Canada,96969.696969697,10,FALSE,TRUE,1e4,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+41392,United States,70000,3,FALSE,TRUE,500,Not remote,6,TRUE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+41397,United States,108000,5,FALSE,TRUE,10000,Remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+41399,United States,195000,16,TRUE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+41401,Canada,96969.696969697,10,FALSE,TRUE,10000,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 41418,India,10571.1349287917,5,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 41421,India,17618.5582146528,2,FALSE,TRUE,1,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 41429,United Kingdom,43750,3,TRUE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41439,Germany,45161.2903225806,5,FALSE,TRUE,1e3,Not remote,2,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41458,United States,115e3,12,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41439,Germany,45161.2903225806,5,FALSE,TRUE,1000,Not remote,2,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41458,United States,115000,12,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 41471,Canada,58333.3333333333,20,TRUE,TRUE,20,Not remote,10,TRUE,TRUE,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE
-41473,United States,34e3,2,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41474,United States,68e3,2,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41481,United States,125e3,4,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+41473,United States,34000,2,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41474,United States,68000,2,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41481,United States,125000,4,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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-41485,United States,1e5,1,FALSE,TRUE,100,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-41487,United States,127e3,4,TRUE,FALSE,5e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+41485,United States,100000,1,FALSE,TRUE,100,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+41487,United States,127000,4,TRUE,FALSE,5000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
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-41492,United States,13e4,15,FALSE,FALSE,20,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41497,United Kingdom,41250,8,FALSE,FALSE,5e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41492,United States,130000,15,FALSE,FALSE,20,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41497,United Kingdom,41250,8,FALSE,FALSE,5000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-41502,United States,137500,20,TRUE,TRUE,1e4,Not remote,8,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41508,United States,5e4,3,FALSE,FALSE,10,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41510,United Kingdom,4e4,2,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-41511,United States,11e4,7,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-41512,Germany,64516.1290322581,3,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41502,United States,137500,20,TRUE,TRUE,10000,Not remote,8,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41508,United States,50000,3,FALSE,FALSE,10,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41510,United Kingdom,40000,2,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+41511,United States,110000,7,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+41512,Germany,64516.1290322581,3,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 41519,Germany,3440.86021505376,8,FALSE,TRUE,1,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41527,India,5872.85273821759,3,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE
-41537,United States,105e3,6,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE
+41527,India,5872.85273821759,3,TRUE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE
+41537,United States,105000,6,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE
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-41566,United States,125e3,12,TRUE,TRUE,1e4,Not remote,8,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+41566,United States,125000,12,TRUE,TRUE,10000,Not remote,8,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
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-41576,United States,62e3,5,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-41584,United States,11e4,5,FALSE,TRUE,10,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41585,United States,75e3,5,TRUE,TRUE,10,Not remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-41596,United Kingdom,131250,20,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+41576,United States,62000,5,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+41584,United States,110000,5,FALSE,TRUE,10,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41585,United States,75000,5,TRUE,TRUE,10,Not remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+41596,United Kingdom,131250,20,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-41613,Germany,80645.1612903226,14,TRUE,TRUE,1e3,Not remote,5,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41613,Germany,80645.1612903226,14,TRUE,TRUE,1000,Not remote,5,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 41621,United Kingdom,34375,6,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 41634,India,17618.5582146528,3,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-41647,Germany,14051.6129032258,4,FALSE,TRUE,1e4,Not remote,10,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE
-41649,United States,11e4,20,FALSE,TRUE,100,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+41647,Germany,14051.6129032258,4,FALSE,TRUE,10000,Not remote,10,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE
+41649,United States,110000,20,FALSE,TRUE,100,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 41659,Germany,59139.7849462366,4,TRUE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41660,Canada,113636.363636364,15,FALSE,FALSE,1e3,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-41663,United Kingdom,5e4,6,FALSE,FALSE,10,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-41928,United Kingdom,25e3,0,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41931,United States,105e3,2,FALSE,FALSE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-41949,United States,92500,4,TRUE,TRUE,1e4,Not remote,6,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-41960,United States,5e4,4,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+41949,United States,92500,4,TRUE,TRUE,10000,Not remote,6,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-41966,United States,99e3,6,FALSE,FALSE,1e4,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41975,United States,17e4,20,TRUE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-41976,United States,63e3,3,TRUE,TRUE,1e4,Remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-41980,Germany,28387.0967741935,3,FALSE,FALSE,1e3,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-41981,United States,15e4,11,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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@@ -5256,1737 +5256,1737 @@ Respondent,Country,Salary,YearsCodedJob,OpenSource,Hobby,CompanySizeNumber,Remot
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-42174,United States,6e4,2,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-42180,United States,63e3,4,FALSE,TRUE,10,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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+42833,United States,145000,20,TRUE,TRUE,500,Not remote,9,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,TRUE
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-42835,United States,11e4,10,FALSE,TRUE,1e3,Remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-42849,United States,67e3,5,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-42851,United States,93e3,5,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-42860,United States,16e4,16,TRUE,TRUE,500,Remote,9,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-42861,United States,12e3,2,TRUE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-42862,United States,6e4,3,FALSE,TRUE,1e4,Not remote,4,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+42835,United States,110000,10,FALSE,TRUE,1000,Remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+42849,United States,67000,5,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+42851,United States,93000,5,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+42860,United States,160000,16,TRUE,TRUE,500,Remote,9,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+42861,United States,12000,2,TRUE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+42862,United States,60000,3,FALSE,TRUE,10000,Not remote,4,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 42865,United States,55452,4,FALSE,TRUE,1,Not remote,4,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-42866,United States,9e4,5,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-42869,United States,15e4,5,TRUE,TRUE,500,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-42871,United States,4e4,1,TRUE,TRUE,1e3,Remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-42873,United Kingdom,5e4,3,FALSE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+42866,United States,90000,5,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+42869,United States,150000,5,TRUE,TRUE,500,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+42871,United States,40000,1,TRUE,TRUE,1000,Remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+42873,United Kingdom,50000,3,FALSE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 42881,India,24959.6241374248,7,FALSE,FALSE,100,Not remote,6,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 42887,India,11011.598884158,5,FALSE,FALSE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-42904,United Kingdom,47500,8,TRUE,FALSE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-42907,United States,78e3,6,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-42910,United Kingdom,41250,6,TRUE,FALSE,5e3,Not remote,8,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-42926,United States,11e4,2,FALSE,TRUE,1e4,Not remote,10,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+42904,United Kingdom,47500,8,TRUE,FALSE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+42907,United States,78000,6,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+42910,United Kingdom,41250,6,TRUE,FALSE,5000,Not remote,8,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+42926,United States,110000,2,FALSE,TRUE,10000,Not remote,10,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 42941,United Kingdom,56250,12,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-42947,United States,5e4,1,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-42953,United States,12e4,20,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE
+42947,United States,50000,1,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+42953,United States,120000,20,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE
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-42971,United States,104e3,11,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+42971,United States,104000,11,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 42976,India,7928.35119659375,1,TRUE,FALSE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 42979,India,5285.56746439583,2,TRUE,TRUE,100,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 42982,United Kingdom,42500,6,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 42987,India,6606.95933049479,1,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-42992,United Kingdom,6e4,9,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
+42992,United Kingdom,60000,9,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
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-43009,India,7708.11921891059,3,FALSE,TRUE,1e4,Not remote,4,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43011,United States,4e4,1,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-43014,Germany,48387.0967741935,3,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43009,India,7708.11921891059,3,FALSE,TRUE,10000,Not remote,4,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43011,United States,40000,1,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+43014,Germany,48387.0967741935,3,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 43016,Canada,41666.6666666667,3,FALSE,TRUE,10,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-43025,United States,91e3,9,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43025,United States,91000,9,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-43028,United States,14e4,20,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43028,United States,140000,20,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-43043,United States,75e3,4,FALSE,TRUE,500,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43045,United States,92e3,3,FALSE,FALSE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
-43069,United Kingdom,5e4,10,TRUE,TRUE,1,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43082,Germany,64516.1290322581,5,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43090,United States,105e3,20,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-43096,United States,1e5,7,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43103,Canada,48106.0606060606,2,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-43104,Canada,30303.0303030303,2,FALSE,FALSE,5e3,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-43107,United States,58e3,20,FALSE,TRUE,1e4,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43108,United States,96e3,12,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43043,United States,75000,4,FALSE,TRUE,500,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43045,United States,92000,3,FALSE,FALSE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+43069,United Kingdom,50000,10,TRUE,TRUE,1,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43082,Germany,64516.1290322581,5,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43090,United States,105000,20,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+43096,United States,100000,7,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43103,Canada,48106.0606060606,2,TRUE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+43104,Canada,30303.0303030303,2,FALSE,FALSE,5000,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43107,United States,58000,20,FALSE,TRUE,10000,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43108,United States,96000,12,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 43114,United Kingdom,56250,5,FALSE,TRUE,20,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43118,United States,12e4,17,TRUE,TRUE,1e4,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43120,United States,104e3,9,FALSE,TRUE,1e4,Not remote,4,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-43123,United States,70200,4,TRUE,FALSE,1e3,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43124,United States,94e3,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43133,United States,83e3,3,TRUE,TRUE,20,Remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43134,United States,8e4,9,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43138,United States,159e3,20,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43139,United States,88e3,9,TRUE,FALSE,1,Remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43147,United States,87e3,7,FALSE,TRUE,500,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-43150,United States,85e3,4,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43165,United States,61e3,3,FALSE,TRUE,1e3,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43168,United States,11e4,11,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43173,United States,65e3,1,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43174,United States,56567,1,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-43175,United States,6e4,4,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-43181,United States,83e3,7,FALSE,FALSE,1e3,Not remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43118,United States,120000,17,TRUE,TRUE,10000,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43120,United States,104000,9,FALSE,TRUE,10000,Not remote,4,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+43123,United States,70200,4,TRUE,FALSE,1000,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43124,United States,94000,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43133,United States,83000,3,TRUE,TRUE,20,Remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43134,United States,80000,9,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43138,United States,159000,20,TRUE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43139,United States,88000,9,TRUE,FALSE,1,Remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43147,United States,87000,7,FALSE,TRUE,500,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+43150,United States,85000,4,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43165,United States,61000,3,FALSE,TRUE,1000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43168,United States,110000,11,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43173,United States,65000,1,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43174,United States,56567,1,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43175,United States,60000,4,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43181,United States,83000,7,FALSE,FALSE,1000,Not remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 43183,United States,90050,6,TRUE,TRUE,20,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43189,United States,121e3,3,TRUE,TRUE,500,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
+43189,United States,121000,3,TRUE,TRUE,500,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
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-43193,United States,1e5,20,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43194,India,11011.598884158,5,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-43195,United States,119e3,12,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-43200,United States,8e4,13,FALSE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43193,United States,100000,20,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43194,India,11011.598884158,5,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+43195,United States,119000,12,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43200,United States,80000,13,FALSE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 43208,United States,78125,18,FALSE,FALSE,100,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 43209,Germany,35483.8709677419,3,FALSE,TRUE,20,Not remote,5,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 43212,United Kingdom,68750,8,FALSE,TRUE,10,Not remote,10,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-43224,United States,77e3,4,TRUE,TRUE,100,Not remote,10,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43226,United States,102e3,6,TRUE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43233,United States,135e3,7,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-43236,United States,65e3,2,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43238,United States,105e3,1,TRUE,TRUE,5e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43241,United States,95e3,7,FALSE,TRUE,10,Remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+43224,United States,77000,4,TRUE,TRUE,100,Not remote,10,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43226,United States,102000,6,TRUE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43233,United States,135000,7,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43236,United States,65000,2,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43238,United States,105000,1,TRUE,TRUE,5000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43241,United States,95000,7,FALSE,TRUE,10,Remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 43243,Canada,31060.6060606061,2,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-43253,United States,62e3,3,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE
-43254,United States,15e4,13,TRUE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43256,United States,72e3,5,TRUE,TRUE,20,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-43257,United States,65e3,2,TRUE,TRUE,5e3,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-43260,United States,32e3,1,FALSE,TRUE,5e3,Not remote,6,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-43267,United States,149e3,19,FALSE,TRUE,1e4,Remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43270,United States,148e3,18,TRUE,TRUE,100,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-43276,United States,145e3,20,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-43282,United States,6e4,8,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43294,United States,115e3,3,TRUE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43295,United States,12e4,9,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+43253,United States,62000,3,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE
+43254,United States,150000,13,TRUE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43256,United States,72000,5,TRUE,TRUE,20,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+43257,United States,65000,2,TRUE,TRUE,5000,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43260,United States,32000,1,FALSE,TRUE,5000,Not remote,6,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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+43276,United States,145000,20,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43282,United States,60000,8,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43294,United States,115000,3,TRUE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43295,United States,120000,9,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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-43301,United States,131e3,9,TRUE,TRUE,1e3,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43301,United States,131000,9,TRUE,TRUE,1000,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 43306,India,29364.2636910879,7,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-43313,United States,8e4,3,FALSE,TRUE,1e4,Remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE
-43317,United States,92e3,9,TRUE,TRUE,1e4,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43313,United States,80000,3,FALSE,TRUE,10000,Remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE
+43317,United States,92000,9,TRUE,TRUE,10000,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 43318,Germany,32258.064516129,2,FALSE,TRUE,20,Not remote,5,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43324,Germany,38709.6774193548,5,FALSE,FALSE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43335,Germany,91397.8494623656,9,TRUE,TRUE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
-43337,United Kingdom,5e4,5,FALSE,TRUE,10,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43344,Germany,51612.9032258064,8,TRUE,TRUE,1e3,Not remote,10,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43349,Germany,69892.4731182796,15,TRUE,TRUE,5e3,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43324,Germany,38709.6774193548,5,FALSE,FALSE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43335,Germany,91397.8494623656,9,TRUE,TRUE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
+43337,United Kingdom,50000,5,FALSE,TRUE,10,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43344,Germany,51612.9032258064,8,TRUE,TRUE,1000,Not remote,10,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43349,Germany,69892.4731182796,15,TRUE,TRUE,5000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 43372,Germany,25806.4516129032,14,TRUE,TRUE,100,Remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 43373,India,1409.48465717222,2,TRUE,TRUE,1,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 43375,United Kingdom,52500,4,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43383,Germany,69892.4731182796,6,FALSE,TRUE,1e4,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,TRUE,FALSE,TRUE,TRUE
+43383,Germany,69892.4731182796,6,FALSE,TRUE,10000,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,TRUE,FALSE,TRUE,TRUE
 43387,Germany,59139.7849462366,7,FALSE,FALSE,500,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 43392,United Kingdom,40625,15,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-43394,United Kingdom,53797.5,16,FALSE,FALSE,5e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43402,United States,12e4,9,FALSE,FALSE,100,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-43410,United States,11e4,20,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43411,Germany,53763.4408602151,17,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43394,United Kingdom,53797.5,16,FALSE,FALSE,5000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43402,United States,120000,9,FALSE,FALSE,100,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+43410,United States,110000,20,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43411,Germany,53763.4408602151,17,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 43417,United States,91500,2,TRUE,TRUE,500,Remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-43420,United States,89e3,9,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43420,United States,89000,9,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 43425,Germany,45161.2903225806,1,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43427,United States,67e3,3,FALSE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43427,United States,67000,3,FALSE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 43429,Germany,38709.6774193548,18,TRUE,FALSE,1,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 43430,United Kingdom,34375,4,FALSE,TRUE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43431,United Kingdom,23290.3225806452,1,FALSE,TRUE,1e3,Not remote,5,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
-43435,United Kingdom,67500,3,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43438,United States,92e3,2,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43431,United Kingdom,23290.3225806452,1,FALSE,TRUE,1000,Not remote,5,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
+43435,United Kingdom,67500,3,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43438,United States,92000,2,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 43440,Canada,83333.3333333333,14,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 43446,United Kingdom,43312.5,4,TRUE,TRUE,10,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43447,United States,1e5,4,TRUE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43456,United Kingdom,75e3,5,FALSE,TRUE,20,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43458,United States,9e4,20,FALSE,FALSE,1e3,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+43447,United States,100000,4,TRUE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43456,United Kingdom,75000,5,FALSE,TRUE,20,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43458,United States,90000,20,FALSE,FALSE,1000,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 43460,Germany,64516.1290322581,4,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 43461,United Kingdom,36875,3,FALSE,TRUE,500,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
-43462,United Kingdom,76250,15,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43463,United States,1e5,10,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-43464,United States,144e3,17,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-43467,United States,105e3,5,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-43473,United States,11e4,15,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43483,United States,109e3,9,FALSE,TRUE,100,Not remote,8,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43462,United Kingdom,76250,15,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43463,United States,100000,10,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+43464,United States,144000,17,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+43467,United States,105000,5,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43473,United States,110000,15,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43483,United States,109000,9,FALSE,TRUE,100,Not remote,8,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-43489,United States,106e3,17,FALSE,FALSE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-43490,United States,13e4,15,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43489,United States,106000,17,FALSE,FALSE,1000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43490,United States,130000,15,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 43493,Germany,60215.0537634409,20,FALSE,FALSE,10,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
 43507,Canada,50734.0909090909,11,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-43509,United States,147e3,9,TRUE,TRUE,1e3,Not remote,7,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-43513,United States,12e4,9,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43509,United States,147000,9,TRUE,TRUE,1000,Not remote,7,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+43513,United States,120000,9,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 43514,Canada,64393.9393939394,7,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-43519,United States,121e3,18,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-43524,United States,65e3,2,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-43528,United States,65e3,2,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-43530,United States,131e3,9,FALSE,FALSE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-43538,United States,15e4,14,TRUE,TRUE,1e4,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-43542,United States,86e3,12,FALSE,TRUE,20,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+43519,United States,121000,18,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43524,United States,65000,2,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+43528,United States,65000,2,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+43530,United States,131000,9,FALSE,FALSE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+43538,United States,150000,14,TRUE,TRUE,10000,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43542,United States,86000,12,FALSE,TRUE,20,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 43544,Canada,68181.8181818182,7,TRUE,TRUE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
 43545,Canada,54545.4545454545,2,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-43550,United States,69600,10,TRUE,TRUE,1e3,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-43553,United States,12e4,20,FALSE,FALSE,1e3,Not remote,9,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-43563,United States,111e3,7,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+43550,United States,69600,10,TRUE,TRUE,1000,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+43553,United States,120000,20,FALSE,FALSE,1000,Not remote,9,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43563,United States,111000,7,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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-43571,United States,81200,6,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+43571,United States,81200,6,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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 43583,United States,46350,1,FALSE,TRUE,20,Not remote,6,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-43597,India,20554.9845837616,18,FALSE,FALSE,1e4,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+43597,India,20554.9845837616,18,FALSE,FALSE,10000,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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-43618,United States,58e3,2,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43620,United Kingdom,40625,8,TRUE,TRUE,1e4,Remote,5,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+43618,United States,58000,2,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43620,United Kingdom,40625,8,TRUE,TRUE,10000,Remote,5,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
 43641,India,12332.9907502569,5,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43654,United States,104e3,20,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-43662,United Kingdom,51250,11,TRUE,TRUE,5e3,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43654,United States,104000,20,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43662,United Kingdom,51250,11,TRUE,TRUE,5000,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 43663,Canada,49242.4242424242,2,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-43664,United States,15e4,19,TRUE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-43669,Canada,78759.8484848485,10,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+43664,United States,150000,19,TRUE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+43669,Canada,78759.8484848485,10,TRUE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 43675,Germany,54838.7096774193,2,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-43676,United Kingdom,62500,10,FALSE,TRUE,1e4,Not remote,8,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+43676,United Kingdom,62500,10,FALSE,TRUE,10000,Not remote,8,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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-43688,Germany,55913.9784946237,1,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-43689,United Kingdom,3e4,3,FALSE,FALSE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43697,Germany,62365.5913978495,10,TRUE,FALSE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43698,United Kingdom,39375,2,FALSE,TRUE,1e3,Not remote,5,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-43704,United States,85e3,8,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43688,Germany,55913.9784946237,1,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+43689,United Kingdom,30000,3,FALSE,FALSE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43697,Germany,62365.5913978495,10,TRUE,FALSE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43698,United Kingdom,39375,2,FALSE,TRUE,1000,Not remote,5,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+43704,United States,85000,8,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 43705,United Kingdom,37500,11,TRUE,TRUE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 43707,Germany,80645.1612903226,18,FALSE,TRUE,100,Not remote,6,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-43708,United States,6e4,2,FALSE,FALSE,100,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-43710,United States,62e3,2,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43711,Germany,96774.1935483871,20,TRUE,FALSE,1e4,Not remote,10,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-43713,United States,77e3,9,TRUE,TRUE,100,Remote,10,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43714,United States,115e3,19,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-43721,United States,125e3,13,TRUE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-43736,United States,15e4,16,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE
+43708,United States,60000,2,FALSE,FALSE,100,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43710,United States,62000,2,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43711,Germany,96774.1935483871,20,TRUE,FALSE,10000,Not remote,10,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+43713,United States,77000,9,TRUE,TRUE,100,Remote,10,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43714,United States,115000,19,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+43721,United States,125000,13,TRUE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+43736,United States,150000,16,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE
 43742,India,2936.48509763618,0,TRUE,TRUE,1,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 43743,Germany,50537.6344086021,10,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 43744,Germany,49462.3655913978,2,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 43747,United Kingdom,53125,13,TRUE,TRUE,1,Not remote,6,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
-43751,United Kingdom,55e3,10,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43751,United Kingdom,55000,10,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-43762,United States,11e4,9,TRUE,TRUE,20,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+43762,United States,110000,9,TRUE,TRUE,20,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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-43781,United States,113e3,7,FALSE,TRUE,5e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43782,United States,62e3,1,FALSE,FALSE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43781,United States,113000,7,FALSE,TRUE,5000,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43782,United States,62000,1,FALSE,FALSE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-43785,United States,111e3,5,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-43795,United States,85e3,9,FALSE,TRUE,1e4,Not remote,10,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43799,United States,9e4,3,TRUE,TRUE,100,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-43821,United States,165e3,14,TRUE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43785,United States,111000,5,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+43795,United States,85000,9,FALSE,TRUE,10000,Not remote,10,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43799,United States,90000,3,TRUE,TRUE,100,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43821,United States,165000,14,TRUE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 43824,United Kingdom,31250,2,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
-43827,United States,115e3,3,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43828,United States,136e3,20,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-43832,United States,105e3,16,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-43840,United Kingdom,131250,12,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+43827,United States,115000,3,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43828,United States,136000,20,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+43832,United States,105000,16,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+43840,United Kingdom,131250,12,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
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-43846,United Kingdom,41250,4,FALSE,FALSE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43846,United Kingdom,41250,4,FALSE,FALSE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-43853,United States,14e4,18,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43863,United States,1e5,14,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-43869,United States,95e3,6,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-43870,United States,15e4,2,FALSE,TRUE,1e4,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-43871,United States,94500,9,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43853,United States,140000,18,TRUE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43863,United States,100000,14,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43869,United States,95000,6,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+43870,United States,150000,2,FALSE,TRUE,10000,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+43871,United States,94500,9,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-43874,United States,14e4,20,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43874,United States,140000,20,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 43878,Canada,68181.8181818182,3,TRUE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43879,United States,125e3,10,TRUE,TRUE,1,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-43880,United States,89e3,4,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-43883,United States,11e4,4,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-43885,United States,11e4,3,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43879,United States,125000,10,TRUE,TRUE,1,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43880,United States,89000,4,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+43883,United States,110000,4,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+43885,United States,110000,3,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-43891,United States,75e3,2,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43893,United States,62500,3,TRUE,TRUE,1e4,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-43894,United States,158e3,13,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+43891,United States,75000,2,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43893,United States,62500,3,TRUE,TRUE,10000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+43894,United States,158000,13,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 43896,United States,38460,3,FALSE,TRUE,100,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43899,United States,1e5,4,FALSE,FALSE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43909,United States,112e3,8,TRUE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43910,United States,88e3,2,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43915,United States,11e4,1,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43918,United States,65e3,5,FALSE,TRUE,1,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+43899,United States,100000,4,FALSE,FALSE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43909,United States,112000,8,TRUE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43910,United States,88000,2,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43915,United States,110000,1,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43918,United States,65000,5,FALSE,TRUE,1,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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-43921,United States,48e3,3,TRUE,TRUE,1,Not remote,10,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+43921,United States,48000,3,TRUE,TRUE,1,Not remote,10,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 43925,United Kingdom,82500,20,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43939,United States,7e4,2,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43940,United States,9e4,5,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43939,United States,70000,2,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43940,United States,90000,5,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 43948,Canada,63257.5757575758,6,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
-43956,India,6166.49537512847,2,TRUE,TRUE,1e4,Remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43958,United States,135e3,7,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+43956,India,6166.49537512847,2,TRUE,TRUE,10000,Remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43958,United States,135000,7,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
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-43960,United States,115e3,16,TRUE,TRUE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43961,United States,115e3,20,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43960,United States,115000,16,TRUE,TRUE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43961,United States,115000,20,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-43967,United States,92e3,10,FALSE,FALSE,1e3,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43970,United States,12e4,14,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43972,United States,141e3,18,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-43973,United States,41e3,9,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43989,United States,74e3,5,TRUE,TRUE,100,Not remote,9,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE
-43990,United States,184e3,20,TRUE,FALSE,1e4,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43967,United States,92000,10,FALSE,FALSE,1000,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43970,United States,120000,14,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43972,United States,141000,18,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+43973,United States,41000,9,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43989,United States,74000,5,TRUE,TRUE,100,Not remote,9,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE
+43990,United States,184000,20,TRUE,FALSE,10000,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-43995,United States,87e3,19,FALSE,FALSE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-43996,United States,107e3,9,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-43999,United States,144e3,4,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44001,United States,157e3,5,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE
-44003,United States,16e4,10,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+43995,United States,87000,19,FALSE,FALSE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+43996,United States,107000,9,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+43999,United States,144000,4,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44001,United States,157000,5,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE
+44003,United States,160000,10,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 44005,Canada,90909.0909090909,20,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-44010,United States,12e4,10,TRUE,TRUE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44010,United States,120000,10,TRUE,TRUE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 44011,Canada,54545.4545454545,20,TRUE,TRUE,1,Remote,9,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-44013,United States,65e3,2,FALSE,TRUE,100,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44022,United States,153e3,8,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+44013,United States,65000,2,FALSE,TRUE,100,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44022,United States,153000,8,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-44039,United Kingdom,4e4,1,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44039,United Kingdom,40000,1,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-44057,United States,115e3,15,FALSE,TRUE,1,Remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+44057,United States,115000,15,FALSE,TRUE,1,Remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
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-44061,United States,63e3,2,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-44065,United States,105e3,7,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44066,United States,9e4,2,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44061,United States,63000,2,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+44065,United States,105000,7,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44066,United States,90000,2,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 44072,Canada,61515.1515151515,17,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-44074,United States,9e4,8,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44077,United States,1e5,1,TRUE,FALSE,1e4,Not remote,4,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44078,United States,95e3,10,TRUE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44074,United States,90000,8,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44077,United States,100000,1,TRUE,FALSE,10000,Not remote,4,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44078,United States,95000,10,TRUE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 44081,India,4404.63955366319,2,FALSE,FALSE,1,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-44086,United States,106e3,13,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44086,United States,106000,13,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 44087,United States,82500,4,FALSE,TRUE,1,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44090,United States,6e4,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+44090,United States,60000,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
 44091,United Kingdom,56250,16,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 44093,Canada,49242.4242424242,3,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44101,United States,125e3,20,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+44101,United States,125000,20,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
 44123,United Kingdom,38750,7,FALSE,FALSE,1,Remote,4,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 44127,Germany,10752.688172043,4,FALSE,TRUE,20,Not remote,0,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 44142,Germany,64516.1290322581,6,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44145,United States,7e4,2,FALSE,TRUE,100,Remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+44145,United States,70000,2,FALSE,TRUE,100,Remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 44146,United States,38800,3,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 44149,United Kingdom,45500,3,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44163,United States,85e3,4,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+44163,United States,85000,4,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
 44166,India,4404.63955366319,2,FALSE,FALSE,10,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-44181,United States,155e3,15,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-44184,United States,84e3,7,FALSE,TRUE,1e4,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+44181,United States,155000,15,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+44184,United States,84000,7,FALSE,TRUE,10000,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 44187,United Kingdom,62500,2,TRUE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-44191,United States,12e4,3,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-44200,United States,12e4,2,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+44191,United States,120000,3,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+44200,United States,120000,2,TRUE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 44210,Germany,30967.7419354839,9,FALSE,TRUE,10,Not remote,9,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-44230,United Kingdom,36250,2,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
-44232,Canada,49242.4242424242,11,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44230,United Kingdom,36250,2,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+44232,Canada,49242.4242424242,11,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 44240,Germany,60215.0537634409,10,FALSE,FALSE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44246,United States,7e4,3,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44248,United States,1e4,2,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44246,United States,70000,3,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44248,United States,10000,2,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 44258,Germany,58064.5161290323,6,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 44270,United Kingdom,46875,3,TRUE,TRUE,1,Not remote,10,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 44274,United Kingdom,26875,2,FALSE,TRUE,20,Not remote,4,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
-44280,United States,132e3,20,TRUE,FALSE,1e4,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44283,United States,87e3,4,FALSE,TRUE,1e4,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44286,United Kingdom,58750,5,FALSE,TRUE,1e4,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+44280,United States,132000,20,TRUE,FALSE,10000,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44283,United States,87000,4,FALSE,TRUE,10000,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44286,United Kingdom,58750,5,FALSE,TRUE,10000,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 44291,United Kingdom,52500,2,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44295,Germany,64516.1290322581,4,TRUE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44295,Germany,64516.1290322581,4,TRUE,FALSE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 44300,United Kingdom,57500,16,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44320,United States,19e4,6,TRUE,TRUE,5e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44326,United States,12e4,20,FALSE,TRUE,20,Remote,2,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44327,United States,12e4,6,FALSE,TRUE,1,Remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-44329,United States,52e3,3,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE
-44330,United Kingdom,62500,16,TRUE,FALSE,1e4,Not remote,8,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-44332,Canada,53030.303030303,9,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-44333,United States,95e3,1,FALSE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-44334,United States,103e3,7,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-44335,United States,104e3,20,FALSE,FALSE,1,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44342,United States,85e3,7,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44343,United States,8e4,2,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44344,United States,73e3,20,FALSE,FALSE,5e3,Not remote,8,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
-44346,United Kingdom,93750,4,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-44347,United States,7e4,2,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+44320,United States,190000,6,TRUE,TRUE,5000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44326,United States,120000,20,FALSE,TRUE,20,Remote,2,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44327,United States,120000,6,FALSE,TRUE,1,Remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+44329,United States,52000,3,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE
+44330,United Kingdom,62500,16,TRUE,FALSE,10000,Not remote,8,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+44332,Canada,53030.303030303,9,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+44333,United States,95000,1,FALSE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+44334,United States,103000,7,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+44335,United States,104000,20,FALSE,FALSE,1,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44342,United States,85000,7,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44343,United States,80000,2,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44344,United States,73000,20,FALSE,FALSE,5000,Not remote,8,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
+44346,United Kingdom,93750,4,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+44347,United States,70000,2,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 44348,Germany,62365.5913978495,2,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 44350,United States,42500,1,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 44355,United Kingdom,37625,2,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 44357,United Kingdom,37500,9,FALSE,FALSE,500,Not remote,0,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44361,United States,75e3,5,TRUE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-44364,United States,6e4,3,TRUE,FALSE,10,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+44361,United States,75000,5,TRUE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+44364,United States,60000,3,TRUE,FALSE,10,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
 44365,Canada,75757.5757575758,14,TRUE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-44371,United States,15e4,10,TRUE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+44371,United States,150000,10,TRUE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 44379,Canada,64393.9393939394,4,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-44418,United Kingdom,103125,7,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-44422,United States,105e3,20,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44433,United States,85e3,7,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44451,United States,8e4,20,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44454,United States,7e4,5,TRUE,TRUE,20,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-44455,United States,7e4,1,FALSE,FALSE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44418,United Kingdom,103125,7,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+44422,United States,105000,20,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44433,United States,85000,7,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44451,United States,80000,20,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44454,United States,70000,5,TRUE,TRUE,20,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+44455,United States,70000,1,FALSE,FALSE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 44460,Canada,68181.8181818182,17,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44466,United States,105e3,16,FALSE,FALSE,1e3,Remote,8,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44469,United States,103e3,20,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+44466,United States,105000,16,FALSE,FALSE,1000,Remote,8,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44469,United States,103000,20,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 44470,Canada,31818.1818181818,1,TRUE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-44475,United States,124e3,1,TRUE,TRUE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44495,United Kingdom,32031.25,1,TRUE,TRUE,1e3,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-44497,United Kingdom,47500,3,TRUE,FALSE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+44475,United States,124000,1,TRUE,TRUE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44495,United Kingdom,32031.25,1,TRUE,TRUE,1000,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+44497,United Kingdom,47500,3,TRUE,FALSE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 44498,Germany,64516.1290322581,11,FALSE,TRUE,20,Remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-44500,United States,105e3,6,TRUE,TRUE,100,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+44500,United States,105000,6,TRUE,TRUE,100,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 44502,United Kingdom,52500,5,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-44505,United States,11e4,11,TRUE,TRUE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44505,United States,110000,11,TRUE,TRUE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 44511,United Kingdom,52500,8,FALSE,FALSE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-44516,United States,55e3,4,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44521,United States,87e3,18,FALSE,FALSE,1e4,Not remote,4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE
-44533,United States,88e3,10,FALSE,TRUE,100,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE
-44535,United States,13e4,20,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-44537,United States,54e3,1,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44547,United States,6e4,5,TRUE,TRUE,1e4,Remote,7,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+44516,United States,55000,4,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44521,United States,87000,18,FALSE,FALSE,10000,Not remote,4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE
+44533,United States,88000,10,FALSE,TRUE,100,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE
+44535,United States,130000,20,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+44537,United States,54000,1,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44547,United States,60000,5,TRUE,TRUE,10000,Remote,7,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 44550,United States,70500,9,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44551,United States,115e3,3,FALSE,TRUE,1e3,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44552,United States,35e3,9,TRUE,FALSE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44558,United States,75e3,5,FALSE,FALSE,1e4,Not remote,7,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+44551,United States,115000,3,FALSE,TRUE,1000,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44552,United States,35000,9,TRUE,FALSE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44558,United States,75000,5,FALSE,FALSE,10000,Not remote,7,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 44562,India,4404.63955366319,5,TRUE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 44572,United Kingdom,47500,13,TRUE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
-44591,United States,56e3,2,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44595,United Kingdom,125e3,20,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-44602,United States,7e4,18,TRUE,TRUE,20,Not remote,5,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE
-44603,Germany,59139.7849462366,10,FALSE,FALSE,5e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-44606,United States,143e3,20,FALSE,TRUE,1e4,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-44610,United States,13e4,20,FALSE,TRUE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+44591,United States,56000,2,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44595,United Kingdom,125000,20,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+44602,United States,70000,18,TRUE,TRUE,20,Not remote,5,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE
+44603,Germany,59139.7849462366,10,FALSE,FALSE,5000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+44606,United States,143000,20,FALSE,TRUE,10000,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+44610,United States,130000,20,FALSE,TRUE,1000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 44612,Germany,58064.5161290323,4,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44618,United States,12e4,20,TRUE,TRUE,5e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-44621,United States,105e3,1,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44624,United States,125e3,3,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44625,United States,65e3,1,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44627,United States,77e3,2,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44618,United States,120000,20,TRUE,TRUE,5000,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+44621,United States,105000,1,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44624,United States,125000,3,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44625,United States,65000,1,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44627,United States,77000,2,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-44629,United States,105e3,15,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44632,United States,1e5,2,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-44636,United States,5e4,1,TRUE,TRUE,10,Not remote,8,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+44629,United States,105000,15,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44632,United States,100000,2,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+44636,United States,50000,1,TRUE,TRUE,10,Not remote,8,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-44648,United States,18e4,18,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44650,United States,14e4,20,TRUE,TRUE,10,Remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+44648,United States,180000,18,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44650,United States,140000,20,TRUE,TRUE,10,Remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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-44675,United States,11e4,3,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-44685,United States,85e3,3,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44675,United States,110000,3,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+44685,United States,85000,3,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-44689,United States,95e3,3,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44691,United Kingdom,42500,2,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44689,United States,95000,3,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44691,United Kingdom,42500,2,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-44704,United Kingdom,45e3,3,TRUE,TRUE,1,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+44704,United Kingdom,45000,3,TRUE,TRUE,1,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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-44722,United States,15e4,9,TRUE,FALSE,1e3,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44722,United States,150000,9,TRUE,FALSE,1000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-44727,United States,31200,20,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-44736,India,33768.9032447511,10,TRUE,TRUE,1e4,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44727,United States,31200,20,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+44736,India,33768.9032447511,10,TRUE,TRUE,10000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 44745,Canada,45454.5454545455,1,FALSE,TRUE,20,Not remote,6,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 44751,India,7752.16561444722,4,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 44757,Germany,34408.6021505376,3,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-44763,United Kingdom,58150,12,FALSE,TRUE,1e3,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+44763,United Kingdom,58150,12,FALSE,TRUE,1000,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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 44789,India,27382.1758919395,10,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 44794,United Kingdom,22500,1,FALSE,TRUE,1,Not remote,4,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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 44800,United States,92700,10,TRUE,FALSE,20,Not remote,9,FALSE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE
-44809,United States,78e3,2,FALSE,TRUE,100,Not remote,6,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-44816,United States,8e4,5,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44824,United States,8e4,16,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-44826,United States,55e3,1,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44828,Canada,60606.0606060606,3,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-44834,United States,125e3,7,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44844,United States,108e3,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44848,United States,65e3,1,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44809,United States,78000,2,FALSE,TRUE,100,Not remote,6,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+44816,United States,80000,5,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44824,United States,80000,16,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+44826,United States,55000,1,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44828,Canada,60606.0606060606,3,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+44834,United States,125000,7,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44844,United States,108000,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44848,United States,65000,1,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-44880,United States,56e3,1,FALSE,FALSE,10,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44880,United States,56000,1,FALSE,FALSE,10,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 44886,United Kingdom,33750,1,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44898,United States,9e4,1,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44900,United States,85e3,4,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44903,United States,1e5,3,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-44907,United States,118e3,10,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44898,United States,90000,1,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44900,United States,85000,4,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44903,United States,100000,3,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+44907,United States,118000,10,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 44911,Canada,31060.6060606061,2,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE
-44912,United States,4e4,2,FALSE,FALSE,1,Not remote,5,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-44916,United States,78e3,3,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-44918,United States,75e3,4,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-44930,United States,55e3,6,FALSE,TRUE,20,Not remote,6,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-44938,United States,85e3,9,FALSE,TRUE,5e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44948,United States,41e3,4,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+44912,United States,40000,2,FALSE,FALSE,1,Not remote,5,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+44916,United States,78000,3,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+44918,United States,75000,4,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+44930,United States,55000,6,FALSE,TRUE,20,Not remote,6,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+44938,United States,85000,9,FALSE,TRUE,5000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44948,United States,41000,4,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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-44967,United Kingdom,28750,1,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-44976,United Kingdom,3e4,1,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45003,United States,105e3,10,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45004,United States,14e4,10,FALSE,FALSE,1,Remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE
-45008,United States,102e3,16,FALSE,FALSE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44967,United Kingdom,28750,1,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+44976,United Kingdom,30000,1,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45003,United States,105000,10,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45004,United States,140000,10,FALSE,FALSE,1,Remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE
+45008,United States,102000,16,FALSE,FALSE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45009,Germany,64516.1290322581,20,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 45012,Canada,113636.363636364,3,TRUE,TRUE,20,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45017,United States,157e3,16,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+45017,United States,157000,16,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 45035,India,4404.63955366319,1,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 45045,United Kingdom,46250,3,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-45051,United Kingdom,1e4,1,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+45051,United Kingdom,10000,1,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
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-45056,Germany,40860.2150537634,4,TRUE,TRUE,1e3,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45058,India,8809.27910732638,5,FALSE,FALSE,1e4,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45065,United States,85e3,9,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45076,United States,16e4,20,TRUE,TRUE,5e3,Not remote,7,TRUE,TRUE,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE,TRUE
-45077,United States,12e4,9,TRUE,TRUE,5e3,Remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+45056,Germany,40860.2150537634,4,TRUE,TRUE,1000,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45058,India,8809.27910732638,5,FALSE,FALSE,10000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45065,United States,85000,9,TRUE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45076,United States,160000,20,TRUE,TRUE,5000,Not remote,7,TRUE,TRUE,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE,TRUE
+45077,United States,120000,9,TRUE,TRUE,5000,Remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 45080,Canada,60606.0606060606,18,FALSE,FALSE,100,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 45082,United Kingdom,62500,3,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 45097,Germany,32258.064516129,5,TRUE,FALSE,10,Not remote,5,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE
-45098,United States,98e3,8,TRUE,FALSE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45105,United States,71e3,13,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45098,United States,98000,8,TRUE,FALSE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45105,United States,71000,13,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45112,Canada,66666.6666666667,5,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-45116,United States,66e3,3,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45119,United States,4e4,1,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45125,United States,125e3,8,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45116,United States,66000,3,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45119,United States,40000,1,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45125,United States,125000,8,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45140,India,1468.2131845544,1,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45157,United Kingdom,70625,19,FALSE,TRUE,20,Not remote,7,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
 45167,Germany,10752.688172043,1,TRUE,TRUE,20,Not remote,8,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-45173,United States,144e3,9,TRUE,TRUE,20,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+45173,United States,144000,9,TRUE,TRUE,20,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 45174,United States,58500,0,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45176,United Kingdom,72500,19,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45177,Canada,53030.303030303,1,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45179,Canada,56818.1818181818,20,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-45180,United States,68e3,4,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45180,United States,68000,4,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45184,Canada,44696.9696969697,1,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45186,United States,7e4,5,TRUE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+45186,United States,70000,5,TRUE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 45187,United States,95680,8,FALSE,TRUE,20,Not remote,7,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45191,Germany,75268.8172043011,16,TRUE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45195,Canada,62400,1,TRUE,FALSE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-45197,United States,125e3,8,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45200,Canada,45454.5454545455,13,FALSE,TRUE,1e3,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-45208,United States,15e4,15,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-45225,United Kingdom,68750,20,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+45197,United States,125000,8,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45200,Canada,45454.5454545455,13,FALSE,TRUE,1000,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+45208,United States,150000,15,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+45225,United Kingdom,68750,20,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 45227,Canada,61363.6363636364,12,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
-45233,United States,115e3,12,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45233,United States,115000,12,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45239,Canada,56818.1818181818,6,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45244,Canada,46969.696969697,4,TRUE,TRUE,1,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE
-45254,India,17618.5582146528,6,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
+45254,India,17618.5582146528,6,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
 45280,United Kingdom,37500,2,FALSE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45290,India,4991.92482748495,1,FALSE,TRUE,1e4,Not remote,6,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-45292,Germany,4086.02150537634,4,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+45290,India,4991.92482748495,1,FALSE,TRUE,10000,Not remote,6,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+45292,Germany,4086.02150537634,4,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 45297,Germany,32258.064516129,5,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-45314,India,27896.0505065335,9,TRUE,FALSE,5e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45319,Germany,53763.4408602151,5,FALSE,TRUE,1e3,Not remote,2,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+45314,India,27896.0505065335,9,TRUE,FALSE,5000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45319,Germany,53763.4408602151,5,FALSE,TRUE,1000,Not remote,2,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 45327,India,2695.63940684187,2,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45335,United States,127500,20,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45345,United States,115e3,6,TRUE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+45335,United States,127500,20,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45345,United States,115000,6,TRUE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 45346,United States,19040,2,TRUE,TRUE,10,Not remote,4,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45348,United Kingdom,11e4,18,TRUE,TRUE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45352,United States,135e3,20,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45354,United Kingdom,62500,20,FALSE,FALSE,1e3,Not remote,6,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-45357,United States,108e3,12,TRUE,TRUE,5e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45361,United States,78e3,1,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45348,United Kingdom,110000,18,TRUE,TRUE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45352,United States,135000,20,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45354,United Kingdom,62500,20,FALSE,FALSE,1000,Not remote,6,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+45357,United States,108000,12,TRUE,TRUE,5000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45361,United States,78000,1,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45362,United States,82500,1,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45368,United States,13e4,3,FALSE,TRUE,1e3,Remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-45385,United States,17e4,16,FALSE,FALSE,1e4,Not remote,10,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45392,India,27161.9439142563,7,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45368,United States,130000,3,FALSE,TRUE,1000,Remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+45385,United States,170000,16,FALSE,FALSE,10000,Not remote,10,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45392,India,27161.9439142563,7,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45400,United Kingdom,93750,4,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
 45408,United Kingdom,27500,4,FALSE,FALSE,10,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45410,United States,65e3,5,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-45417,United States,118e3,20,TRUE,TRUE,100,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-45419,United States,73e3,16,FALSE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45421,United States,8e4,6,TRUE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45427,United States,92e3,2,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-45430,United States,136e3,6,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45410,United States,65000,5,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+45417,United States,118000,20,TRUE,TRUE,100,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+45419,United States,73000,16,FALSE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45421,United States,80000,6,TRUE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45427,United States,92000,2,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+45430,United States,136000,6,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45432,Canada,41666.6666666667,2,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45434,United States,11e4,4,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45437,United States,147e3,18,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+45434,United States,110000,4,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45437,United States,147000,18,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 45439,United Kingdom,31250,3,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-45443,Canada,44696.9696969697,3,FALSE,TRUE,5e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-45444,United States,171e3,10,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45451,Canada,102272.727272727,9,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45454,United States,91e3,4,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45461,United States,98e3,10,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45463,United States,115900,10,FALSE,FALSE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+45443,Canada,44696.9696969697,3,FALSE,TRUE,5000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+45444,United States,171000,10,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45451,Canada,102272.727272727,9,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45454,United States,91000,4,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45461,United States,98000,10,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45463,United States,115900,10,FALSE,FALSE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 45464,United States,30160,2,FALSE,FALSE,1,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45471,United States,105e3,10,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45475,Germany,80645.1612903226,14,TRUE,TRUE,5e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45477,United States,93e3,4,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45488,United States,6e4,2,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-45489,United States,15e4,20,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45496,United States,36e3,3,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45507,United States,37e3,2,FALSE,TRUE,10,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-45516,United Kingdom,3e4,3,FALSE,TRUE,1,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-45521,United States,57e3,4,FALSE,FALSE,100,Not remote,0,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-45523,United Kingdom,125e3,20,FALSE,TRUE,1,Remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-45524,United States,1e5,6,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-45526,United States,1e5,2,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45528,United States,26e3,2,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45530,United States,97e3,12,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-45536,United States,95e3,2,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-45537,United States,9e4,12,FALSE,TRUE,1,Remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-45540,United States,92e3,8,TRUE,TRUE,1e4,Not remote,5,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE
-45544,United States,15e4,4,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-45546,United States,11e4,5,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE
+45471,United States,105000,10,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45475,Germany,80645.1612903226,14,TRUE,TRUE,5000,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45477,United States,93000,4,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45488,United States,60000,2,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+45489,United States,150000,20,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45496,United States,36000,3,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45507,United States,37000,2,FALSE,TRUE,10,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+45516,United Kingdom,30000,3,FALSE,TRUE,1,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+45521,United States,57000,4,FALSE,FALSE,100,Not remote,0,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+45523,United Kingdom,125000,20,FALSE,TRUE,1,Remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+45524,United States,100000,6,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+45526,United States,100000,2,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45528,United States,26000,2,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45530,United States,97000,12,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+45536,United States,95000,2,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+45537,United States,90000,12,FALSE,TRUE,1,Remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+45540,United States,92000,8,TRUE,TRUE,10000,Not remote,5,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE
+45544,United States,150000,4,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+45546,United States,110000,5,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE
 45556,United States,98300,5,FALSE,TRUE,100,Remote,6,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45557,United States,72e3,1,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+45557,United States,72000,1,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
 45561,United Kingdom,87500,19,TRUE,TRUE,10,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-45565,United States,6e4,5,FALSE,TRUE,10,Not remote,6,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
-45568,Germany,43010.752688172,2,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45575,United States,115e3,6,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-45576,United States,175e3,13,TRUE,TRUE,1e3,Remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45583,United States,13e4,17,FALSE,TRUE,1e4,Not remote,10,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-45584,United States,1e5,8,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
-45586,United Kingdom,6e4,15,TRUE,TRUE,20,Not remote,4,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-45588,United States,9e4,8,FALSE,TRUE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45589,United States,72e3,4,TRUE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-45590,United States,114e3,4,TRUE,FALSE,1e3,Not remote,8,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
-45594,United States,1e5,4,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+45565,United States,60000,5,FALSE,TRUE,10,Not remote,6,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
+45568,Germany,43010.752688172,2,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45575,United States,115000,6,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+45576,United States,175000,13,TRUE,TRUE,1000,Remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45583,United States,130000,17,FALSE,TRUE,10000,Not remote,10,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+45584,United States,100000,8,TRUE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+45586,United Kingdom,60000,15,TRUE,TRUE,20,Not remote,4,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+45588,United States,90000,8,FALSE,TRUE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45589,United States,72000,4,TRUE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+45590,United States,114000,4,TRUE,FALSE,1000,Not remote,8,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
+45594,United States,100000,4,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 45596,United Kingdom,37500,2,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45604,United States,6e4,7,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-45606,United States,9e4,5,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45609,United States,52148,2,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45624,United States,1e5,6,TRUE,TRUE,10,Not remote,9,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE
-45636,United States,13e4,5,TRUE,FALSE,1,Not remote,10,TRUE,TRUE,FALSE,TRUE,TRUE,TRUE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,TRUE
-45637,United States,14e4,18,TRUE,FALSE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45604,United States,60000,7,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+45606,United States,90000,5,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45609,United States,52148,2,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45624,United States,100000,6,TRUE,TRUE,10,Not remote,9,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE
+45636,United States,130000,5,TRUE,FALSE,1,Not remote,10,TRUE,TRUE,FALSE,TRUE,TRUE,TRUE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,TRUE
+45637,United States,140000,18,TRUE,FALSE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45640,Canada,45454.5454545455,1,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45641,United States,135e3,20,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45646,United States,129e3,7,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45657,United States,9e4,10,TRUE,TRUE,1,Remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45663,United States,85e3,2,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45641,United States,135000,20,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45646,United States,129000,7,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45657,United States,90000,10,TRUE,TRUE,1,Remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45663,United States,85000,2,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-45685,United States,115e3,3,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+45685,United States,115000,3,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 45695,India,7341.06592277199,2,TRUE,TRUE,100,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45696,United Kingdom,42500,1,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45697,United Kingdom,63750,8,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45714,India,6606.95933049479,2,TRUE,TRUE,20,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45720,India,22023.197768316,9,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45727,United Kingdom,81250,15,TRUE,TRUE,10,Not remote,6,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45734,India,17618.5582146528,7,TRUE,TRUE,1e4,Not remote,8,TRUE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+45734,India,17618.5582146528,7,TRUE,TRUE,10000,Not remote,8,TRUE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
 45755,United Kingdom,40062.5,10,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45772,United Kingdom,45e3,5,FALSE,TRUE,20,Not remote,5,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+45772,United Kingdom,45000,5,FALSE,TRUE,20,Not remote,5,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 45775,Germany,50537.6344086021,3,TRUE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-45792,United States,75e3,1,FALSE,FALSE,1,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45797,United States,145e3,20,FALSE,TRUE,20,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-45807,United States,105e3,20,TRUE,TRUE,20,Remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45828,United States,16e4,18,FALSE,TRUE,100,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-45844,United States,105e3,3,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45845,United States,72e3,8,FALSE,FALSE,5e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45848,United States,18e4,18,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45792,United States,75000,1,FALSE,FALSE,1,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45797,United States,145000,20,FALSE,TRUE,20,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+45807,United States,105000,20,TRUE,TRUE,20,Remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45828,United States,160000,18,FALSE,TRUE,100,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+45844,United States,105000,3,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45845,United States,72000,8,FALSE,FALSE,5000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45848,United States,180000,18,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45852,Germany,43010.752688172,16,TRUE,TRUE,20,Not remote,8,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-45856,United States,124e3,14,TRUE,TRUE,100,Remote,9,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-45858,United States,135e3,7,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-45866,United States,125e3,20,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45869,United States,7e4,1,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45856,United States,124000,14,TRUE,TRUE,100,Remote,9,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+45858,United States,135000,7,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+45866,United States,125000,20,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45869,United States,70000,1,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45870,Germany,26451.6129032258,4,FALSE,TRUE,20,Not remote,4,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-45871,United States,78e3,4,FALSE,TRUE,1e3,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45873,United States,104440,19,TRUE,TRUE,5e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45871,United States,78000,4,FALSE,TRUE,1000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45873,United States,104440,19,TRUE,TRUE,5000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45881,India,2642.78373219792,1,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 45888,Canada,68181.8181818182,12,TRUE,FALSE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45898,United States,94e3,2,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45899,United States,85e3,14,FALSE,TRUE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45901,United States,7e4,5,TRUE,TRUE,20,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-45905,United Kingdom,47500,8,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-45906,United States,168e3,9,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-45907,United States,146e3,6,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-45916,United States,15e4,4,TRUE,FALSE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45919,United States,13e4,6,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45920,United States,139e3,10,TRUE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+45898,United States,94000,2,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45899,United States,85000,14,FALSE,TRUE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45901,United States,70000,5,TRUE,TRUE,20,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+45905,United Kingdom,47500,8,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+45906,United States,168000,9,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+45907,United States,146000,6,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+45916,United States,150000,4,TRUE,FALSE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45919,United States,130000,6,TRUE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45920,United States,139000,10,TRUE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
 45929,Germany,51612.9032258064,12,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-45935,United States,85e3,5,TRUE,TRUE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45935,United States,85000,5,TRUE,TRUE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45951,India,9690.20701805902,5,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45976,United Kingdom,68750,7,TRUE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-45978,United States,165e3,18,TRUE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-45984,United States,6e4,2,TRUE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45978,United States,165000,18,TRUE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+45984,United States,60000,2,TRUE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 45988,United States,60500,3,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-45993,India,28630.1570988107,2,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-45996,United States,8e4,5,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46002,Canada,43939.3939393939,6,FALSE,TRUE,5e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46006,United Kingdom,87500,3,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-46031,Canada,5e4,4,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46035,United States,107e3,20,TRUE,FALSE,1e4,Not remote,4,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-46065,United States,6e4,4,TRUE,TRUE,1,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+45993,India,28630.1570988107,2,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+45996,United States,80000,5,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46002,Canada,43939.3939393939,6,FALSE,TRUE,5000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46006,United Kingdom,87500,3,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+46031,Canada,50000,4,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46035,United States,107000,20,TRUE,FALSE,10000,Not remote,4,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+46065,United States,60000,4,TRUE,TRUE,1,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 46079,Canada,27272.7272727273,2,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 46081,Canada,45454.5454545455,9,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 46084,Germany,69892.4731182796,10,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 46088,India,4052.26838937014,2,FALSE,TRUE,20,Not remote,2,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46092,United Kingdom,62500,18,TRUE,TRUE,5e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+46092,United Kingdom,62500,18,TRUE,TRUE,5000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 46098,United Kingdom,53750,4,FALSE,TRUE,1,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 46100,India,32300.6900601967,10,FALSE,FALSE,20,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE
 46101,United Kingdom,22500,2,FALSE,TRUE,1,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 46116,United Kingdom,34375,1,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-46119,United States,69e3,4,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+46119,United States,69000,4,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 46122,United Kingdom,56250,4,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 46134,Canada,68181.8181818182,14,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46136,United States,76e3,4,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-46143,United States,92500,5,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE
+46136,United States,76000,4,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+46143,United States,92500,5,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE
 46145,United States,54500,2,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46148,United States,65e3,2,FALSE,TRUE,500,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE
-46155,Canada,37878.7878787879,1,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46156,United States,11e4,14,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+46148,United States,65000,2,FALSE,TRUE,500,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE
+46155,Canada,37878.7878787879,1,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46156,United States,110000,14,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 46157,United Kingdom,87500,10,TRUE,TRUE,1,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
-46158,United Kingdom,9e4,20,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-46159,United States,155e3,10,TRUE,TRUE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46162,United States,7e4,1,FALSE,TRUE,1e4,Not remote,3,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-46163,United States,75e3,2,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-46166,United States,12e4,4,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46173,United States,155e3,15,FALSE,FALSE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46158,United Kingdom,90000,20,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+46159,United States,155000,10,TRUE,TRUE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46162,United States,70000,1,FALSE,TRUE,10000,Not remote,3,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+46163,United States,75000,2,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+46166,United States,120000,4,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46173,United States,155000,15,FALSE,FALSE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 46179,Germany,43010.752688172,5,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 46183,Germany,61290.3225806452,2,FALSE,TRUE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 46192,India,13213.9186609896,16,FALSE,FALSE,1,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-46197,United Kingdom,75e3,20,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-46209,United States,136e3,16,FALSE,TRUE,1e4,Remote,8,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+46197,United Kingdom,75000,20,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+46209,United States,136000,16,FALSE,TRUE,10000,Remote,8,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 46212,United Kingdom,37500,5,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 46230,Canada,59090.9090909091,9,FALSE,TRUE,20,Not remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46234,United States,125e3,11,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-46235,United States,75e3,2,FALSE,TRUE,1e3,Not remote,9,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-46236,United States,98e3,14,FALSE,FALSE,1e3,Not remote,2,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
-46237,United States,85e3,5,TRUE,TRUE,5e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+46234,United States,125000,11,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+46235,United States,75000,2,FALSE,TRUE,1000,Not remote,9,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+46236,United States,98000,14,FALSE,FALSE,1000,Not remote,2,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+46237,United States,85000,5,TRUE,TRUE,5000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 46240,United Kingdom,65625,11,FALSE,TRUE,1,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46245,United States,9e4,10,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46246,United States,115e3,6,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46259,United States,95e3,4,FALSE,FALSE,1e4,Not remote,10,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46245,United States,90000,10,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46246,United States,115000,6,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46259,United States,95000,4,FALSE,FALSE,10000,Not remote,10,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 46260,Germany,49462.3655913978,4,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-46275,United States,64400,1,FALSE,TRUE,1e3,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-46277,United States,95e3,12,TRUE,TRUE,1e3,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+46275,United States,64400,1,FALSE,TRUE,1000,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+46277,United States,95000,12,TRUE,TRUE,1000,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 46279,United States,138500,8,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46309,United Kingdom,4e4,6,TRUE,TRUE,10,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+46309,United Kingdom,40000,6,TRUE,TRUE,10,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 46310,Germany,12903.2258064516,4,FALSE,TRUE,100,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 46322,India,2936.42636910879,1,TRUE,TRUE,100,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 46326,United Kingdom,43750,9,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46332,Germany,105913.978494624,20,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46335,United States,95e3,1,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-46341,United States,116e3,17,TRUE,FALSE,5e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46343,United States,58e3,2,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46348,United States,9e4,2,TRUE,TRUE,10,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46359,United States,131e3,3,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46360,United States,93e3,9,TRUE,TRUE,1e3,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-46361,United Kingdom,35e3,20,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46362,United States,134e3,15,TRUE,TRUE,1e4,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46332,Germany,105913.978494624,20,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46335,United States,95000,1,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+46341,United States,116000,17,TRUE,FALSE,5000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46343,United States,58000,2,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46348,United States,90000,2,TRUE,TRUE,10,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46359,United States,131000,3,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46360,United States,93000,9,TRUE,TRUE,1000,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+46361,United Kingdom,35000,20,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46362,United States,134000,15,TRUE,TRUE,10000,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 46366,Canada,75757.5757575758,14,FALSE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 46371,Canada,60606.0606060606,5,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 46373,United States,43680,2,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46374,United States,1e5,13,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+46374,United States,100000,13,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 46375,United Kingdom,52500,2,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46379,United States,96e3,11,TRUE,TRUE,20,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-46382,United States,18e4,20,FALSE,TRUE,1e3,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46387,United States,86e3,5,FALSE,TRUE,100,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-46391,United States,74e3,13,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-46394,United States,74e3,5,FALSE,TRUE,500,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+46379,United States,96000,11,TRUE,TRUE,20,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+46382,United States,180000,20,FALSE,TRUE,1000,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46387,United States,86000,5,FALSE,TRUE,100,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+46391,United States,74000,13,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+46394,United States,74000,5,FALSE,TRUE,500,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 46399,United Kingdom,37500,1,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-46406,United States,135e3,15,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+46406,United States,135000,15,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 46407,Germany,48387.0967741935,9,TRUE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-46414,United States,125e3,6,TRUE,TRUE,20,Not remote,10,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+46414,United States,125000,6,TRUE,TRUE,20,Not remote,10,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
 46426,United States,82500,1,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 46427,India,13918.6609895757,2,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46429,India,8809.27910732638,3,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-46451,United States,72e3,9,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+46429,India,8809.27910732638,3,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+46451,United States,72000,9,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 46459,Canada,36363.6363636364,1,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE
-46460,United States,116e3,12,FALSE,FALSE,1e4,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-46467,Canada,75757.5757575758,20,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-46468,United States,115e3,20,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46476,United States,106e3,15,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46477,Germany,48387.0967741935,4,TRUE,TRUE,1e3,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46478,United States,8e4,3,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46460,United States,116000,12,FALSE,FALSE,10000,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+46467,Canada,75757.5757575758,20,TRUE,TRUE,10000,Not remote,10,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+46468,United States,115000,20,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46476,United States,106000,15,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46477,Germany,48387.0967741935,4,TRUE,TRUE,1000,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46478,United States,80000,3,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 46481,United Kingdom,56625,3,FALSE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 46489,Canada,110606.060606061,16,TRUE,TRUE,10,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46494,United States,1e5,10,FALSE,TRUE,500,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+46494,United States,100000,10,FALSE,TRUE,500,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 46495,Canada,87121.2121212121,16,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46497,United States,59e3,1,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46497,United States,59000,1,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 46500,Germany,59139.7849462366,5,TRUE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-46501,United States,57500,0,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46501,United States,57500,0,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 46503,Canada,71969.696969697,10,FALSE,FALSE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-46504,United States,135e3,12,TRUE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46505,United States,85e3,5,FALSE,TRUE,5e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,TRUE
-46506,United States,82e3,3,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46515,United States,69e3,9,FALSE,TRUE,1e4,Remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46521,United States,72e3,1,FALSE,FALSE,5e3,Not remote,3,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46522,United Kingdom,5e4,20,TRUE,TRUE,1e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46524,United States,74e3,17,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46504,United States,135000,12,TRUE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46505,United States,85000,5,FALSE,TRUE,5000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,TRUE
+46506,United States,82000,3,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46515,United States,69000,9,FALSE,TRUE,10000,Remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46521,United States,72000,1,FALSE,FALSE,5000,Not remote,3,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46522,United Kingdom,50000,20,TRUE,TRUE,1000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46524,United States,74000,17,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 46530,Germany,73118.2795698925,12,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 46537,United States,81120,1,FALSE,FALSE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-46543,United States,85696,3,FALSE,FALSE,1e4,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-46548,Germany,53763.4408602151,2,TRUE,FALSE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46556,United States,11e4,6,TRUE,TRUE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46560,United States,5e4,1,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46565,India,15856.7023931875,3,FALSE,FALSE,5e3,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+46543,United States,85696,3,FALSE,FALSE,10000,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+46548,Germany,53763.4408602151,2,TRUE,FALSE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46556,United States,110000,6,TRUE,TRUE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46560,United States,50000,1,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46565,India,15856.7023931875,3,FALSE,FALSE,5000,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 46571,Canada,60606.0606060606,6,TRUE,TRUE,100,Not remote,6,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-46572,Germany,77419.3548387097,2,FALSE,FALSE,1e4,Remote,6,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+46572,Germany,77419.3548387097,2,FALSE,FALSE,10000,Remote,6,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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 46581,United Kingdom,41250,3,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46595,India,12479.8120687124,4,TRUE,TRUE,1e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46601,Germany,57526.8817204301,8,TRUE,TRUE,1e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE
-46606,United States,11e4,6,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-46609,United States,158100,19,TRUE,TRUE,1e4,Not remote,10,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+46595,India,12479.8120687124,4,TRUE,TRUE,1000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46601,Germany,57526.8817204301,8,TRUE,TRUE,1000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE
+46606,United States,110000,6,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+46609,United States,158100,19,TRUE,TRUE,10000,Not remote,10,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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 46613,Germany,58064.5161290323,10,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-46614,United States,6e4,1,FALSE,TRUE,20,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46615,United States,6e4,3,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46614,United States,60000,1,FALSE,TRUE,20,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46615,United States,60000,3,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 46617,United States,97500,9,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46619,United States,92e3,18,FALSE,FALSE,100,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46620,United States,145e3,20,FALSE,TRUE,20,Not remote,10,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
-46623,United States,5e4,0,FALSE,TRUE,1,Not remote,8,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+46619,United States,92000,18,FALSE,FALSE,100,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46620,United States,145000,20,FALSE,TRUE,20,Not remote,10,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
+46623,United States,50000,0,FALSE,TRUE,1,Not remote,8,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
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-46632,United States,102e3,4,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
-46641,United States,68e3,1,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46643,United States,117e3,6,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-46646,United States,4e4,1,FALSE,TRUE,1,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-46651,United States,18e4,10,TRUE,TRUE,20,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-46654,United States,7e4,2,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46669,United Kingdom,125e3,12,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46670,United States,125e3,19,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46689,Germany,59139.7849462366,7,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE
+46632,United States,102000,4,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
+46641,United States,68000,1,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46643,United States,117000,6,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+46646,United States,40000,1,FALSE,TRUE,1,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+46651,United States,180000,10,TRUE,TRUE,20,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+46654,United States,70000,2,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46669,United Kingdom,125000,12,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46670,United States,125000,19,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46689,Germany,59139.7849462366,7,TRUE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE
 46699,India,3876.08280722361,0,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-46704,India,29364.2636910879,1,TRUE,FALSE,1e4,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-46713,United States,98e3,7,FALSE,TRUE,100,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46717,United States,5263.15789473684,7,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46729,United States,123e3,16,TRUE,TRUE,1e4,Not remote,9,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-46734,United States,144e3,20,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
-46737,United States,12e4,20,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
-46738,United States,15e4,20,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46704,India,29364.2636910879,1,TRUE,FALSE,10000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+46713,United States,98000,7,FALSE,TRUE,100,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46717,United States,5263.15789473684,7,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46729,United States,123000,16,TRUE,TRUE,10000,Not remote,9,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+46734,United States,144000,20,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+46737,United States,120000,20,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
+46738,United States,150000,20,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 46750,Germany,75268.8172043011,20,TRUE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 46751,Germany,53763.4408602151,17,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46758,Germany,53763.4408602151,11,FALSE,TRUE,5e3,Not remote,3,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46760,United States,135e3,15,FALSE,TRUE,100,Remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-46763,United States,125e3,4,TRUE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46758,Germany,53763.4408602151,11,FALSE,TRUE,5000,Not remote,3,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46760,United States,135000,15,FALSE,TRUE,100,Remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+46763,United States,125000,4,TRUE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-46775,United States,75e3,3,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46779,United States,78600,5,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+46775,United States,75000,3,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46779,United States,78600,5,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-46793,United States,11e4,5,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46795,India,5285.56746439583,1,FALSE,TRUE,1e4,Not remote,0,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+46793,United States,110000,5,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46795,India,5285.56746439583,1,FALSE,TRUE,10000,Not remote,0,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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 46816,Germany,45161.2903225806,1,FALSE,TRUE,10,Not remote,6,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 46821,Germany,43010.752688172,7,FALSE,FALSE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 46828,India,4404.63955366319,1,FALSE,FALSE,20,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-46829,United States,135e3,17,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46846,United States,1e5,6,TRUE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+46829,United States,135000,17,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46846,United States,100000,6,TRUE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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-46860,United States,6e4,1,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46865,United States,46e3,4,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-46874,United States,11e4,3,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-46876,United States,83e3,2,FALSE,TRUE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+46860,United States,60000,1,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46865,United States,46000,4,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+46874,United States,110000,3,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+46876,United States,83000,2,FALSE,TRUE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 46878,United Kingdom,38750,2,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46884,United States,7e4,2,TRUE,TRUE,500,Not remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-46885,United Kingdom,47500,4,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46889,United States,185e3,15,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-46894,United States,13e4,8,FALSE,FALSE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+46884,United States,70000,2,TRUE,TRUE,500,Not remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+46885,United Kingdom,47500,4,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46889,United States,185000,15,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+46894,United States,130000,8,FALSE,FALSE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 46907,Germany,50537.6344086021,11,FALSE,TRUE,100,Not remote,5,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
 46908,Germany,37634.4086021505,1,FALSE,FALSE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46913,India,11745.7054764352,3,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46930,United States,11e4,1,FALSE,FALSE,10,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46913,India,11745.7054764352,3,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46930,United States,110000,1,FALSE,FALSE,10,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 46934,United Kingdom,56250,20,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 46940,United Kingdom,37500,20,FALSE,FALSE,20,Remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 46946,United Kingdom,32500,1,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 46950,Canada,41666.6666666667,20,TRUE,TRUE,100,Not remote,3,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46954,United States,35e3,2,TRUE,TRUE,1,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-46956,United States,47500,10,TRUE,TRUE,5e3,Not remote,9,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-46957,United States,105e3,12,FALSE,TRUE,100,Remote,10,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+46954,United States,35000,2,TRUE,TRUE,1,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+46956,United States,47500,10,TRUE,TRUE,5000,Not remote,9,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+46957,United States,105000,12,FALSE,TRUE,100,Remote,10,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-46970,United States,174e3,20,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-46971,United States,125e3,7,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46970,United States,174000,20,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+46971,United States,125000,7,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-46983,United States,107e3,17,FALSE,FALSE,500,Not remote,9,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE
-46985,United States,91e3,1,FALSE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46983,United States,107000,17,FALSE,FALSE,500,Not remote,9,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE
+46985,United States,91000,1,FALSE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 46990,Canada,41666.6666666667,4,TRUE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 46994,Canada,87121.2121212121,20,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46997,United States,9e4,4,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-46999,United States,52e3,5,FALSE,TRUE,1e4,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-47009,United States,82e3,3,FALSE,TRUE,20,Not remote,8,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE
-47012,United States,4e4,1,FALSE,TRUE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47013,United States,7e4,5,FALSE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-47022,United States,59e3,1,FALSE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-47023,United States,75e3,1,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47025,United States,14e4,20,TRUE,TRUE,10,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47029,United States,126e3,20,TRUE,TRUE,100,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47031,United States,1e5,19,FALSE,FALSE,1e3,Remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+46997,United States,90000,4,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+46999,United States,52000,5,FALSE,TRUE,10000,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+47009,United States,82000,3,FALSE,TRUE,20,Not remote,8,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE
+47012,United States,40000,1,FALSE,TRUE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47013,United States,70000,5,FALSE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+47022,United States,59000,1,FALSE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+47023,United States,75000,1,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47025,United States,140000,20,TRUE,TRUE,10,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47029,United States,126000,20,TRUE,TRUE,100,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47031,United States,100000,19,FALSE,FALSE,1000,Remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-47034,United States,6e4,3,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-47035,United States,72e3,7,TRUE,TRUE,500,Remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+47034,United States,60000,3,TRUE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+47035,United States,72000,7,TRUE,TRUE,500,Remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 47056,India,6049.03832036412,2,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47058,India,5138.74614594039,1,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47065,United Kingdom,38750,8,TRUE,FALSE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47065,United Kingdom,38750,8,TRUE,FALSE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 47091,United States,68600,4,TRUE,TRUE,100,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47092,India,21289.0911760388,7,TRUE,FALSE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 47101,Germany,54838.7096774193,4,TRUE,TRUE,500,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE
-47102,United States,105e3,5,TRUE,TRUE,5e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-47108,United Kingdom,27500,2,FALSE,TRUE,1e3,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47122,United States,111e3,20,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
-47126,United States,55e3,1,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47128,United Kingdom,37500,5,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47102,United States,105000,5,TRUE,TRUE,5000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+47108,United Kingdom,27500,2,FALSE,TRUE,1000,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47122,United States,111000,20,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+47126,United States,55000,1,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47128,United Kingdom,37500,5,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47133,United Kingdom,57500,14,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 47134,United Kingdom,71875,9,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47137,Germany,64516.1290322581,5,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-47139,United States,62e3,1,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47139,United States,62000,1,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47142,Germany,55913.9784946237,5,TRUE,FALSE,100,Not remote,5,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-47164,Germany,50537.6344086021,5,TRUE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47164,Germany,50537.6344086021,5,TRUE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47173,India,2114.22698575833,1,TRUE,TRUE,1,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47178,United Kingdom,63636.3636363636,2,FALSE,TRUE,20,Not remote,9,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47195,Germany,53763.4408602151,2,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 47196,Germany,32258.064516129,8,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 47211,Canada,62121.2121212121,4,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-47213,United States,133e3,17,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE
-47218,United States,9e4,10,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-47221,United States,14e4,8,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47222,United States,115e3,20,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47231,United States,6e4,1,FALSE,FALSE,1e4,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47233,United Kingdom,47500,3,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47234,United States,81500,4,TRUE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-47242,United States,85e3,15,TRUE,FALSE,1,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47244,United States,75e3,1,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-47261,United States,142e3,20,TRUE,TRUE,100,Not remote,6,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-47263,United States,78e3,1,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-47265,United States,104e3,5,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47268,United States,12e4,1,TRUE,TRUE,10,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47269,United States,32e3,1,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
+47213,United States,133000,17,TRUE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE
+47218,United States,90000,10,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+47221,United States,140000,8,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47222,United States,115000,20,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47231,United States,60000,1,FALSE,FALSE,10000,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47233,United Kingdom,47500,3,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47234,United States,81500,4,TRUE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+47242,United States,85000,15,TRUE,FALSE,1,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47244,United States,75000,1,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+47261,United States,142000,20,TRUE,TRUE,100,Not remote,6,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+47263,United States,78000,1,TRUE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+47265,United States,104000,5,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47268,United States,120000,1,TRUE,TRUE,10,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47269,United States,32000,1,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
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-47277,United States,62400,5,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE
+47277,United States,62400,5,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE
 47282,Canada,34125,3,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47292,Canada,49242.4242424242,3,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47298,United States,80500,2,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+47298,United States,80500,2,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 47300,India,2936.42636910879,1,FALSE,FALSE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-47306,United Kingdom,13750,1,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47306,United Kingdom,13750,1,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47311,India,8001.76185582147,2,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47320,Germany,12903.2258064516,3,TRUE,TRUE,1e3,Not remote,9,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47337,United Kingdom,75e3,12,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47338,United States,12e4,3,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+47320,Germany,12903.2258064516,3,TRUE,TRUE,1000,Not remote,9,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47337,United Kingdom,75000,12,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47338,United States,120000,3,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 47340,India,2936.42636910879,5,TRUE,TRUE,500,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
 47345,Canada,30303.0303030303,2,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE
-47352,United States,75e3,4,FALSE,TRUE,5e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-47355,Canada,30303.0303030303,1,TRUE,TRUE,5e3,Not remote,5,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE
-47360,United States,7e4,2,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47363,United States,103e3,9,TRUE,TRUE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE
-47369,United States,44e3,4,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47370,United States,75e3,4,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47352,United States,75000,4,FALSE,TRUE,5000,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+47355,Canada,30303.0303030303,1,TRUE,TRUE,5000,Not remote,5,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE
+47360,United States,70000,2,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47363,United States,103000,9,TRUE,TRUE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE
+47369,United States,44000,4,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47370,United States,75000,4,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47372,Germany,94623.6559139785,18,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE
 47377,Canada,45454.5454545455,2,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-47379,United States,72e3,7,FALSE,TRUE,20,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47380,United States,52e3,4,FALSE,TRUE,1e3,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+47379,United States,72000,7,FALSE,TRUE,20,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47380,United States,52000,4,FALSE,TRUE,1000,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 47382,United Kingdom,32500,3,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47386,United States,83250,2,TRUE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47389,United States,85e3,4,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-47392,Germany,67741.935483871,3,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-47395,United States,16e4,10,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+47389,United States,85000,4,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+47392,Germany,67741.935483871,3,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+47395,United States,160000,10,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 47397,United States,14300,1,TRUE,TRUE,1,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
-47399,United States,89e3,20,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE
-47402,United States,1e5,2,FALSE,TRUE,10,Not remote,6,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+47399,United States,89000,20,TRUE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE
+47402,United States,100000,2,FALSE,TRUE,10,Not remote,6,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 47419,India,24959.6241374248,5,FALSE,FALSE,100,Not remote,4,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-47434,United States,83e3,5,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47437,Canada,98484.8484848485,11,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-47443,India,5872.85273821759,2,TRUE,TRUE,1e4,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47434,United States,83000,5,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47437,Canada,98484.8484848485,11,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+47443,India,5872.85273821759,2,TRUE,TRUE,10000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47444,United Kingdom,77500,9,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47445,United States,55e3,1,FALSE,TRUE,10,Not remote,6,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+47445,United States,55000,1,FALSE,TRUE,10,Not remote,6,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 47448,United Kingdom,56875,4,FALSE,TRUE,20,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47453,United States,55e3,2,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+47453,United States,55000,2,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 47460,Canada,45454.5454545455,1,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-47463,United Kingdom,37658.75,3,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+47463,United Kingdom,37658.75,3,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 47467,Germany,43225.8064516129,5,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 47468,United Kingdom,41250,4,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47477,United States,12e4,12,TRUE,TRUE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47477,United States,120000,12,TRUE,TRUE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47489,India,8060.49038320364,5,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-47497,United States,11e4,4,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-47513,United Kingdom,58750,6,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47497,United States,110000,4,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+47513,United Kingdom,58750,6,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47518,Germany,45161.2903225806,2,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
 47537,Canada,37878.7878787879,3,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47541,United States,83200,2,FALSE,FALSE,1,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47547,United States,112e3,4,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47548,United States,106e3,9,FALSE,TRUE,1e4,Not remote,10,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47550,Germany,139784.946236559,20,TRUE,TRUE,1e4,Remote,10,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-47551,United States,165e3,18,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-47554,United States,13e4,6,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47555,United States,134e3,6,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+47547,United States,112000,4,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47548,United States,106000,9,FALSE,TRUE,10000,Not remote,10,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47550,Germany,139784.946236559,20,TRUE,TRUE,10000,Remote,10,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+47551,United States,165000,18,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+47554,United States,130000,6,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47555,United States,134000,6,TRUE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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-47571,United Kingdom,57e3,5,FALSE,TRUE,1,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47574,Germany,58064.5161290323,2,FALSE,TRUE,1e4,Not remote,9,TRUE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-47577,India,6e3,6,FALSE,TRUE,20,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47571,United Kingdom,57000,5,FALSE,TRUE,1,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47574,Germany,58064.5161290323,2,FALSE,TRUE,10000,Not remote,9,TRUE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+47577,India,6000,6,FALSE,TRUE,20,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-47581,India,44046.3955366319,4,TRUE,TRUE,1e3,Not remote,8,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-47616,United States,1e5,4,FALSE,TRUE,100,Not remote,9,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47581,India,44046.3955366319,4,TRUE,TRUE,1000,Not remote,8,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+47616,United States,100000,4,FALSE,TRUE,100,Not remote,9,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 47628,Germany,38709.6774193548,5,FALSE,TRUE,20,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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-47633,United States,147e3,18,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+47633,United States,147000,18,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-47637,United States,12e4,8,TRUE,TRUE,1e3,Not remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-47644,Canada,31818.1818181818,2,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47645,United States,6e4,2,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47646,United States,95e3,20,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-47647,United States,5e4,9,FALSE,TRUE,10,Not remote,3,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+47637,United States,120000,8,TRUE,TRUE,1000,Not remote,10,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+47644,Canada,31818.1818181818,2,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47645,United States,60000,2,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47646,United States,95000,20,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+47647,United States,50000,9,FALSE,TRUE,10,Not remote,3,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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-47653,United States,65e3,3,TRUE,TRUE,1,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47658,United States,78e3,4,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-47668,United States,65e3,18,FALSE,TRUE,1,Remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+47653,United States,65000,3,TRUE,TRUE,1,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47658,United States,78000,4,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+47668,United States,65000,18,FALSE,TRUE,1,Remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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-47675,United States,61e3,4,FALSE,TRUE,500,Not remote,5,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-47677,United States,76505,4,FALSE,TRUE,5e3,Not remote,3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+47675,United States,61000,4,FALSE,TRUE,500,Not remote,5,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+47677,United States,76505,4,FALSE,TRUE,5000,Not remote,3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 47678,United Kingdom,71250,17,TRUE,TRUE,100,Not remote,6,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47680,United States,9e4,8,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47680,United States,90000,8,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47684,Canada,54545.4545454545,7,FALSE,FALSE,10,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47690,India,3303.47966524739,3,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47691,India,7928.35119659375,5,TRUE,TRUE,500,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 47721,India,2202.3197768316,1,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 47734,United Kingdom,23437.5,2,TRUE,TRUE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47743,United States,1e5,20,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
-47754,United Kingdom,5e4,9,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-47756,United States,13e4,6,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-47758,United States,85e3,2,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-47769,United States,9e4,4,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
-47771,United States,60500,1,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47774,United States,83500,9,FALSE,TRUE,5e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47775,United Kingdom,5e4,8,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-47778,United States,85e3,5,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47788,United States,3e4,4,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47743,United States,100000,20,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
+47754,United Kingdom,50000,9,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+47756,United States,130000,6,TRUE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+47758,United States,85000,2,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+47769,United States,90000,4,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
+47771,United States,60500,1,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47774,United States,83500,9,FALSE,TRUE,5000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47775,United Kingdom,50000,8,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+47778,United States,85000,5,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47788,United States,30000,4,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47792,Canada,34090.9090909091,1,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47795,United States,75e3,11,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47797,United States,124e3,20,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47808,United States,92e3,6,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+47795,United States,75000,11,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47797,United States,124000,20,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47808,United States,92000,6,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 47810,United States,145600,6,TRUE,TRUE,100,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47836,India,8809.27910732638,3,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-47845,Germany,29540.8602150538,1,FALSE,FALSE,1e3,Not remote,3,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+47845,Germany,29540.8602150538,1,FALSE,FALSE,1000,Not remote,3,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 47852,India,4316.54676258993,3,FALSE,TRUE,10,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47872,Germany,69892.4731182796,5,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-47879,United Kingdom,56250,4,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47872,Germany,69892.4731182796,5,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+47879,United Kingdom,56250,4,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47894,United Kingdom,33750,2,FALSE,TRUE,1,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 47896,India,16150.3450300984,4,TRUE,TRUE,100,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 47908,United States,132392,20,FALSE,TRUE,100,Not remote,9,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-47910,Germany,86021.5053763441,10,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-47911,United States,85e3,7,FALSE,TRUE,100,Not remote,8,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47910,Germany,86021.5053763441,10,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+47911,United States,85000,7,FALSE,TRUE,100,Not remote,8,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47912,Canada,35606.0606060606,1,FALSE,TRUE,20,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47915,Canada,53030.303030303,2,FALSE,FALSE,100,Not remote,7,TRUE,TRUE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-47924,United States,15e4,20,FALSE,FALSE,1e4,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+47924,United States,150000,20,FALSE,FALSE,10000,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 47933,Canada,26515.1515151515,1,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47941,Canada,45454.5454545455,9,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-47947,United States,9e4,1,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47962,Germany,38709.6774193548,1,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47947,United States,90000,1,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47962,Germany,38709.6774193548,1,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 47964,India,13213.9186609896,5,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 47975,United Kingdom,43750,5,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-47979,United States,12e4,6,TRUE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-47982,United States,18e4,20,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-47983,United States,77e3,1,TRUE,FALSE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47979,United States,120000,6,TRUE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+47982,United States,180000,20,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+47983,United States,77000,1,TRUE,FALSE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 48003,United Kingdom,52500,6,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 48009,United States,62500,4,TRUE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48017,United States,105e3,9,TRUE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48018,Germany,59139.7849462366,3,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48019,United States,82e3,6,TRUE,TRUE,1e4,Not remote,8,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48025,United States,50300,2,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48017,United States,105000,9,TRUE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48018,Germany,59139.7849462366,3,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48019,United States,82000,6,TRUE,TRUE,10000,Not remote,8,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48025,United States,50300,2,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 48026,United Kingdom,26250,5,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48030,United States,91e3,10,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48032,United States,135e3,20,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48030,United States,91000,10,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48032,United States,135000,20,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 48034,India,27896.0505065335,7,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48037,United States,76e3,5,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-48044,United States,62e3,1,FALSE,TRUE,20,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48049,United States,51192,7,FALSE,TRUE,5e3,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-48052,United States,74e3,9,FALSE,FALSE,5e3,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48071,United States,11e4,5,TRUE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48072,United States,134e3,3,TRUE,TRUE,5e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48037,United States,76000,5,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+48044,United States,62000,1,FALSE,TRUE,20,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48049,United States,51192,7,FALSE,TRUE,5000,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+48052,United States,74000,9,FALSE,FALSE,5000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48071,United States,110000,5,TRUE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48072,United States,134000,3,TRUE,TRUE,5000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 48079,India,63133.1669358391,11,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 48083,India,3523.71164293055,1,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 48092,Germany,58064.5161290323,6,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-48099,Germany,69892.4731182796,3,TRUE,TRUE,1e3,Not remote,6,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-48112,Germany,38709.6774193548,3,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48118,United States,12e4,20,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48099,Germany,69892.4731182796,3,TRUE,TRUE,1000,Not remote,6,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+48112,Germany,38709.6774193548,3,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48118,United States,120000,20,FALSE,FALSE,10,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 48120,Germany,40860.2150537634,8,FALSE,TRUE,100,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48132,United States,83e3,10,FALSE,TRUE,20,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48139,United States,7e4,4,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48143,United States,12e4,5,TRUE,TRUE,1e3,Not remote,3,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-48154,United States,9e4,16,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48157,United States,14e4,15,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48160,United States,126e3,3,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48172,India,10277.4922918808,1,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48132,United States,83000,10,FALSE,TRUE,20,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48139,United States,70000,4,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48143,United States,120000,5,TRUE,TRUE,1000,Not remote,3,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+48154,United States,90000,16,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48157,United States,140000,15,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48160,United States,126000,3,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48172,India,10277.4922918808,1,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 48191,India,16150.3450300984,2,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 48196,Germany,76344.0860215054,18,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48223,United States,17e4,20,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE
-48227,India,4991.92482748495,1,TRUE,TRUE,1e4,Not remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48235,India,5872.85273821759,18,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-48245,United States,8e4,16,TRUE,TRUE,20,Remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+48223,United States,170000,20,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE
+48227,India,4991.92482748495,1,TRUE,TRUE,10000,Not remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48235,India,5872.85273821759,18,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+48245,United States,80000,16,TRUE,TRUE,20,Remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
 48246,India,2202.3197768316,1,TRUE,TRUE,20,Remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-48261,United States,6e4,10,TRUE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48263,United States,9e4,20,FALSE,FALSE,500,Not remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+48261,United States,60000,10,TRUE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48263,United States,90000,20,FALSE,FALSE,500,Not remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 48268,Canada,45454.5454545455,5,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE
-48269,United States,125e3,4,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48270,United States,45e3,5,TRUE,TRUE,1,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-48273,United States,105e3,3,TRUE,TRUE,20,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48269,United States,125000,4,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48270,United States,45000,5,TRUE,TRUE,1,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+48273,United States,105000,3,TRUE,TRUE,20,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 48280,India,2642.78373219792,1,FALSE,FALSE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 48282,India,8075.17251504918,4,TRUE,TRUE,100,Not remote,6,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 48287,India,8456.90794303333,4,FALSE,TRUE,100,Not remote,10,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 48288,India,1174.57054764352,1,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-48297,India,17618.5582146528,1,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48297,India,17618.5582146528,1,TRUE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 48302,India,5733.05464317707,2,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-48307,India,25e3,7,TRUE,TRUE,20,Remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+48307,India,25000,7,TRUE,TRUE,20,Remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 48319,Germany,43010.752688172,3,TRUE,TRUE,10,Not remote,5,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-48332,United States,65e3,3,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48333,United Kingdom,42500,9,FALSE,FALSE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48335,United States,82e3,9,TRUE,FALSE,1e4,Not remote,10,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
-48348,United States,85e3,3,FALSE,FALSE,1e4,Not remote,10,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-48353,Germany,45161.2903225806,3,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48357,United Kingdom,26250,1,FALSE,TRUE,1e3,Not remote,7,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48359,United States,9e4,5,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-48372,United States,14e4,17,FALSE,TRUE,100,Not remote,10,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-48376,United States,115e3,2,TRUE,FALSE,5e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48386,United States,1e5,3,FALSE,TRUE,1e4,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48388,India,8075.17251504918,4,FALSE,FALSE,1e4,Not remote,3,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48332,United States,65000,3,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48333,United Kingdom,42500,9,FALSE,FALSE,1000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48335,United States,82000,9,TRUE,FALSE,10000,Not remote,10,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
+48348,United States,85000,3,FALSE,FALSE,10000,Not remote,10,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+48353,Germany,45161.2903225806,3,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48357,United Kingdom,26250,1,FALSE,TRUE,1000,Not remote,7,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48359,United States,90000,5,TRUE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+48372,United States,140000,17,FALSE,TRUE,100,Not remote,10,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+48376,United States,115000,2,TRUE,FALSE,5000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48386,United States,100000,3,FALSE,TRUE,10000,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48388,India,8075.17251504918,4,FALSE,FALSE,10000,Not remote,3,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 48392,India,3171.3404786375,1,FALSE,TRUE,1,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48395,United States,9e4,1,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+48395,United States,90000,1,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 48398,India,7341.06592277199,3,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 48410,Germany,32258.064516129,2,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 48417,United Kingdom,43750,3,FALSE,FALSE,10,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 48431,United Kingdom,38750,2,FALSE,TRUE,20,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48432,Germany,46506.4516129032,6,TRUE,FALSE,1e4,Not remote,7,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-48441,United States,6e4,2,FALSE,FALSE,10,Not remote,9,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+48432,Germany,46506.4516129032,6,TRUE,FALSE,10000,Not remote,7,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+48441,United States,60000,2,FALSE,FALSE,10,Not remote,9,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
 48451,Germany,44086.0215053763,6,TRUE,TRUE,500,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 48458,United Kingdom,81250,17,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48459,United States,13e4,20,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-48461,United States,7e4,4,TRUE,TRUE,100,Remote,6,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-48468,United States,9e4,2,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48477,United Kingdom,1e5,9,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-48479,United States,59450,1,FALSE,FALSE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48482,United States,136e3,5,TRUE,FALSE,5e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48483,United States,84e3,4,FALSE,TRUE,5e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48488,United States,65717,8,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48496,United States,72e3,4,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48499,United States,13e4,16,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48459,United States,130000,20,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+48461,United States,70000,4,TRUE,TRUE,100,Remote,6,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+48468,United States,90000,2,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48477,United Kingdom,100000,9,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+48479,United States,59450,1,FALSE,FALSE,1000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48482,United States,136000,5,TRUE,FALSE,5000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48483,United States,84000,4,FALSE,TRUE,5000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48488,United States,65717,8,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48496,United States,72000,4,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48499,United States,130000,16,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 48502,United Kingdom,37500,4,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48503,United States,95e3,17,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48503,United States,95000,17,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 48512,Germany,77419.3548387097,10,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48517,United States,57e3,20,FALSE,FALSE,100,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48518,United States,85e3,4,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+48517,United States,57000,20,FALSE,FALSE,100,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48518,United States,85000,4,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 48519,Germany,40860.2150537634,1,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-48520,United Kingdom,45e3,3,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48521,United States,42e3,6,TRUE,TRUE,1,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-48523,United States,134e3,11,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48524,United Kingdom,75e3,17,TRUE,TRUE,100,Remote,9,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+48520,United Kingdom,45000,3,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48521,United States,42000,6,TRUE,TRUE,1,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+48523,United States,134000,11,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48524,United Kingdom,75000,17,TRUE,TRUE,100,Remote,9,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 48528,Canada,106060.606060606,20,TRUE,TRUE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 48532,United States,92500,4,TRUE,TRUE,1,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48534,United Kingdom,51e3,4,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-48536,United States,63e3,2,TRUE,TRUE,1e4,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-48539,United States,117e3,20,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48542,United States,62e3,6,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48534,United Kingdom,51000,4,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+48536,United States,63000,2,TRUE,TRUE,10000,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+48539,United States,117000,20,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48542,United States,62000,6,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 48546,Canada,69696.9696969697,19,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48547,United States,7e4,1,FALSE,FALSE,20,Not remote,8,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48547,United States,70000,1,FALSE,FALSE,20,Not remote,8,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 48550,United Kingdom,131250,20,TRUE,TRUE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48551,United States,105e3,1,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48561,United States,66e3,4,FALSE,FALSE,1e3,Not remote,4,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48562,United States,8e4,20,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48569,United States,11e4,6,FALSE,TRUE,20,Not remote,10,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-48572,United States,83e3,6,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48576,United Kingdom,93750,17,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48577,United States,3e4,1,TRUE,TRUE,10,Not remote,6,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48581,United States,75e3,5,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-48582,United States,124e3,19,TRUE,FALSE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-48583,United States,75e3,18,FALSE,FALSE,20,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-48587,United States,75e3,5,TRUE,FALSE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-48588,United States,91e3,7,TRUE,TRUE,1,Not remote,8,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
-48592,United States,96750,8,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48593,United States,152e3,20,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48594,United States,95e3,20,TRUE,TRUE,5e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-48597,United States,1e5,10,TRUE,TRUE,20,Not remote,10,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-48605,United States,87e3,14,FALSE,TRUE,100,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-48608,United States,95e3,5,TRUE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48609,United States,187e3,20,TRUE,FALSE,20,Remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-48610,United Kingdom,75e3,20,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48612,United States,12e4,6,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE
-48616,United States,73e3,9,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48617,Germany,55913.9784946237,3,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48551,United States,105000,1,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48561,United States,66000,4,FALSE,FALSE,1000,Not remote,4,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48562,United States,80000,20,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48569,United States,110000,6,FALSE,TRUE,20,Not remote,10,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+48572,United States,83000,6,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48576,United Kingdom,93750,17,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48577,United States,30000,1,TRUE,TRUE,10,Not remote,6,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48581,United States,75000,5,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+48582,United States,124000,19,TRUE,FALSE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+48583,United States,75000,18,FALSE,FALSE,20,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+48587,United States,75000,5,TRUE,FALSE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+48588,United States,91000,7,TRUE,TRUE,1,Not remote,8,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
+48592,United States,96750,8,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48593,United States,152000,20,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48594,United States,95000,20,TRUE,TRUE,5000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+48597,United States,100000,10,TRUE,TRUE,20,Not remote,10,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+48605,United States,87000,14,FALSE,TRUE,100,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+48608,United States,95000,5,TRUE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48609,United States,187000,20,TRUE,FALSE,20,Remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+48610,United Kingdom,75000,20,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48612,United States,120000,6,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE
+48616,United States,73000,9,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48617,Germany,55913.9784946237,3,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 48622,United Kingdom,52500,11,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48624,United States,8e4,8,TRUE,FALSE,1,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-48627,United States,45e3,4,TRUE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48633,United States,138004,17,FALSE,FALSE,1e4,Remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48644,United States,87e3,6,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-48645,United States,89e3,3,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48650,United States,57e3,1,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48653,United States,16e4,15,FALSE,TRUE,1e4,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48654,United States,125e3,20,TRUE,FALSE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48657,United States,8e4,2,FALSE,FALSE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48662,United States,12e4,7,TRUE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-48664,United States,44e3,4,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48665,United States,127e3,14,TRUE,FALSE,100,Remote,9,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-48666,United States,72500,4,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48670,United States,83e3,2,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+48624,United States,80000,8,TRUE,FALSE,1,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+48627,United States,45000,4,TRUE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48633,United States,138004,17,FALSE,FALSE,10000,Remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48644,United States,87000,6,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+48645,United States,89000,3,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48650,United States,57000,1,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48653,United States,160000,15,FALSE,TRUE,10000,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48654,United States,125000,20,TRUE,FALSE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48657,United States,80000,2,FALSE,FALSE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48662,United States,120000,7,TRUE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+48664,United States,44000,4,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48665,United States,127000,14,TRUE,FALSE,100,Remote,9,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+48666,United States,72500,4,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48670,United States,83000,2,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 48677,Canada,62121.2121212121,20,FALSE,TRUE,500,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-48690,United States,13e4,13,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48691,India,8163.26530612245,2,FALSE,TRUE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+48690,United States,130000,13,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48691,India,8163.26530612245,2,FALSE,TRUE,1000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 48703,United States,32796,20,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48705,India,10571.1349287917,2,TRUE,FALSE,1e3,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48705,India,10571.1349287917,2,TRUE,FALSE,1000,Not remote,7,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 48709,India,44046.3955366319,3,TRUE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48721,United Kingdom,4e4,2,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48727,Germany,59139.7849462366,4,TRUE,TRUE,5e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48721,United Kingdom,40000,2,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48727,Germany,59139.7849462366,4,TRUE,TRUE,5000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 48748,United Kingdom,38750,5,FALSE,TRUE,20,Not remote,5,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-48749,United States,175e3,19,TRUE,FALSE,1e4,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48751,United States,135e3,5,FALSE,TRUE,1e4,Not remote,10,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48749,United States,175000,19,TRUE,FALSE,10000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48751,United States,135000,5,FALSE,TRUE,10000,Not remote,10,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 48765,Germany,48387.0967741935,4,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-48772,United Kingdom,125e3,7,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48772,United Kingdom,125000,7,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 48781,Canada,119696.96969697,19,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 48790,United Kingdom,42500,9,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 48802,Germany,59139.7849462366,4,FALSE,FALSE,20,Not remote,1,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48805,Germany,63440.8602150538,3,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48808,United States,14e4,20,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48809,United States,147e3,20,FALSE,TRUE,10,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48805,Germany,63440.8602150538,3,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48808,United States,140000,20,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48809,United States,147000,20,FALSE,TRUE,10,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 48817,United Kingdom,38750,5,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 48819,India,4404.63955366319,1,FALSE,TRUE,1,Not remote,5,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 48820,Germany,53763.4408602151,3,TRUE,TRUE,20,Not remote,8,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE
 48821,Canada,62878.7878787879,4,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48825,United States,64e3,2,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48826,United States,13e4,10,TRUE,FALSE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48828,United Kingdom,53750,10,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48825,United States,64000,2,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48826,United States,130000,10,TRUE,FALSE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48828,United Kingdom,53750,10,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 48839,United Kingdom,62500,17,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-48841,United Kingdom,72500,10,TRUE,TRUE,1e4,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48845,United States,1e5,12,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48859,United States,68750,2,FALSE,TRUE,5e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48863,United States,105e3,16,FALSE,TRUE,100,Remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48864,United States,65e3,5,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48866,United States,11e4,17,TRUE,TRUE,1e4,Remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48841,United Kingdom,72500,10,TRUE,TRUE,10000,Not remote,7,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48845,United States,100000,12,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48859,United States,68750,2,FALSE,TRUE,5000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48863,United States,105000,16,FALSE,TRUE,100,Remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48864,United States,65000,5,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48866,United States,110000,17,TRUE,TRUE,10000,Remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 48867,United States,82500,3,TRUE,TRUE,500,Not remote,9,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE
 48870,United Kingdom,43750,3,TRUE,TRUE,20,Not remote,7,TRUE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
-48871,United States,16e4,20,TRUE,TRUE,1,Not remote,10,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+48871,United States,160000,20,TRUE,TRUE,1,Not remote,10,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 48873,Germany,48387.0967741935,4,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48879,United States,97e3,10,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48883,United States,1e5,4,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48884,United States,7e4,2,FALSE,TRUE,500,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48885,United States,88e3,14,FALSE,FALSE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48879,United States,97000,10,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48883,United States,100000,4,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48884,United States,70000,2,FALSE,TRUE,500,Not remote,9,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48885,United States,88000,14,FALSE,FALSE,1,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 48886,United Kingdom,62862.5,5,TRUE,TRUE,10,Not remote,9,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48887,United States,62e3,2,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48895,United States,33e3,1,FALSE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48887,United States,62000,2,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48895,United States,33000,1,FALSE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 48904,Canada,36363.6363636364,4,TRUE,TRUE,20,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48905,United Kingdom,52500,2,FALSE,TRUE,1e3,Not remote,6,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48905,United Kingdom,52500,2,FALSE,TRUE,1000,Not remote,6,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 48908,Canada,103787.878787879,20,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
-48914,United States,125e3,11,FALSE,FALSE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48915,United Kingdom,5e4,9,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48916,United States,108e3,4,FALSE,TRUE,1e4,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-48928,United States,85e3,18,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-48929,United States,102e3,18,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48932,United States,1e5,2,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48943,United States,9e4,14,FALSE,FALSE,5e3,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48914,United States,125000,11,FALSE,FALSE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48915,United Kingdom,50000,9,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48916,United States,108000,4,FALSE,TRUE,10000,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+48928,United States,85000,18,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+48929,United States,102000,18,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48932,United States,100000,2,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48943,United States,90000,14,FALSE,FALSE,5000,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 48952,Canada,113636.363636364,20,TRUE,TRUE,500,Not remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
 48959,United States,87500,2,FALSE,TRUE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 48961,Germany,48387.0967741935,10,FALSE,TRUE,1,Remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48967,United States,83e3,3,TRUE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-48971,United States,12e4,12,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-48972,United States,135e3,5,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-48977,United States,11e4,1,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE
-48978,United States,13e4,6,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48981,United States,97e3,10,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-48987,United States,14e4,4,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48995,India,24959.6241374248,10,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-48996,United States,139939,14,TRUE,TRUE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE
+48967,United States,83000,3,TRUE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+48971,United States,120000,12,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+48972,United States,135000,5,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+48977,United States,110000,1,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE
+48978,United States,130000,6,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48981,United States,97000,10,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+48987,United States,140000,4,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48995,India,24959.6241374248,10,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+48996,United States,139939,14,TRUE,TRUE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE
 48997,India,11745.7054764352,2,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49027,Germany,96774.1935483871,7,TRUE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-49040,United Kingdom,86375,17,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49027,Germany,96774.1935483871,7,TRUE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+49040,United Kingdom,86375,17,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49043,United States,62500,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49048,Canada,53030.303030303,16,FALSE,FALSE,500,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 49054,Germany,64516.1290322581,6,FALSE,FALSE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-49058,Germany,53763.4408602151,4,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+49058,Germany,53763.4408602151,4,TRUE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 49064,Germany,86021.5053763441,15,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-49068,Canada,74242.4242424242,14,FALSE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-49069,United States,88e3,16,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49071,United States,152900,11,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49077,United States,12e3,9,TRUE,FALSE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49079,United States,104e3,17,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-49109,Germany,4301.0752688172,1,TRUE,FALSE,5e3,Not remote,5,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49111,United States,155e3,20,FALSE,FALSE,20,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-49120,United States,103e3,20,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+49068,Canada,74242.4242424242,14,FALSE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+49069,United States,88000,16,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49071,United States,152900,11,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49077,United States,12000,9,TRUE,FALSE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49079,United States,104000,17,TRUE,TRUE,20,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+49109,Germany,4301.0752688172,1,TRUE,FALSE,5000,Not remote,5,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49111,United States,155000,20,FALSE,FALSE,20,Remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+49120,United States,103000,20,TRUE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 49121,India,10277.4922918808,2,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-49128,United States,75e3,4,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-49144,United States,11e4,20,FALSE,FALSE,10,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49150,United Kingdom,43750,4,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+49128,United States,75000,4,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+49144,United States,110000,20,FALSE,FALSE,10,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49150,United Kingdom,43750,4,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 49151,United Kingdom,68750,8,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49156,United Kingdom,62500,11,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 49167,India,1468.2131845544,1,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-49176,United States,95e3,7,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49179,India,17618.5582146528,5,FALSE,FALSE,1e4,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49181,Germany,32258.064516129,3,FALSE,TRUE,1e3,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49176,United States,95000,7,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49179,India,17618.5582146528,5,FALSE,FALSE,10000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49181,Germany,32258.064516129,3,FALSE,TRUE,1000,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49182,Germany,10322.5806451613,2,FALSE,TRUE,500,Not remote,6,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49184,India,2290.41256790486,0,FALSE,TRUE,20,Not remote,6,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-49189,United States,16e4,20,FALSE,FALSE,100,Not remote,9,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-49193,United States,95e3,6,TRUE,TRUE,20,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+49189,United States,160000,20,FALSE,FALSE,100,Not remote,9,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+49193,United States,95000,6,TRUE,TRUE,20,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
 49201,Canada,93181.8181818182,8,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49202,United States,1e5,13,FALSE,FALSE,5e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49206,United States,115e3,9,TRUE,FALSE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49208,United States,145e3,18,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49211,United Kingdom,72500,10,TRUE,TRUE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49212,United States,14e4,8,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-49218,United States,11e4,9,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49220,United States,11e4,7,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-49221,United States,15e4,8,TRUE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+49202,United States,100000,13,FALSE,FALSE,5000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49206,United States,115000,9,TRUE,FALSE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49208,United States,145000,18,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49211,United Kingdom,72500,10,TRUE,TRUE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49212,United States,140000,8,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+49218,United States,110000,9,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49220,United States,110000,7,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+49221,United States,150000,8,TRUE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 49225,India,3171.3404786375,1,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49228,Germany,41935.4838709677,5,FALSE,TRUE,1e4,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-49230,United Kingdom,65e3,15,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+49228,Germany,41935.4838709677,5,FALSE,TRUE,10000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+49230,United Kingdom,65000,15,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 49231,India,6166.49537512847,2,TRUE,TRUE,100,Not remote,0,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49234,India,12039.3481133461,3,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49240,United States,85e3,1,FALSE,FALSE,1e4,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+49240,United States,85000,1,FALSE,FALSE,10000,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 49244,India,5872.85273821759,3,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 49253,Germany,51612.9032258064,7,FALSE,FALSE,20,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-49263,Germany,46236.5591397849,1,FALSE,FALSE,1e4,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-49271,United States,1e5,8,FALSE,TRUE,500,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+49263,Germany,46236.5591397849,1,FALSE,FALSE,10000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+49271,United States,100000,8,FALSE,TRUE,500,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 49274,Germany,64516.1290322581,20,TRUE,TRUE,20,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-49278,United States,8e4,2,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-49279,United States,7e4,1,TRUE,TRUE,5e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-49280,United States,172e3,20,TRUE,TRUE,100,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-49286,Canada,46969.696969697,3,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49278,United States,80000,2,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+49279,United States,70000,1,TRUE,TRUE,5000,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+49280,United States,172000,20,TRUE,TRUE,100,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+49286,Canada,46969.696969697,3,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49288,Canada,83333.3333333333,16,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 49291,Canada,75763.6363636364,9,FALSE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49292,United States,115e3,20,FALSE,TRUE,5e3,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+49292,United States,115000,20,FALSE,TRUE,5000,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 49293,Canada,79545.4545454545,14,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 49294,United Kingdom,52500,1,TRUE,TRUE,20,Not remote,10,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
 49296,Germany,51612.9032258064,8,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 49302,Germany,50537.6344086021,16,FALSE,TRUE,10,Not remote,8,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-49304,Germany,19354.8387096774,4,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49328,United States,172300,20,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49341,United States,15e4,15,FALSE,TRUE,1e4,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+49304,Germany,19354.8387096774,4,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49328,United States,172300,20,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49341,United States,150000,15,FALSE,TRUE,10000,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 49347,India,1761.85582146528,1,TRUE,TRUE,20,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49348,India,13067.0973425341,3,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 49356,India,4404.63955366319,1,FALSE,TRUE,1,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49358,United States,6e4,2,FALSE,TRUE,1,Not remote,9,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49358,United States,60000,2,FALSE,TRUE,1,Not remote,9,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49360,United Kingdom,56250,6,FALSE,FALSE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49361,Germany,48387.0967741935,2,FALSE,TRUE,500,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49387,United States,55e3,1,FALSE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49388,India,7341.06592277199,3,TRUE,FALSE,1e3,Not remote,8,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-49389,United Kingdom,65e3,20,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49400,United States,65e3,2,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49387,United States,55000,1,FALSE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49388,India,7341.06592277199,3,TRUE,FALSE,1000,Not remote,8,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+49389,United Kingdom,65000,20,FALSE,TRUE,500,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49400,United States,65000,2,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49404,United States,88500,7,TRUE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-49408,United States,11e4,18,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49408,United States,110000,18,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49409,Germany,48387.0967741935,2,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49410,United States,147e3,12,FALSE,TRUE,1e4,Not remote,8,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+49410,United States,147000,12,FALSE,TRUE,10000,Not remote,8,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
 49414,Canada,60606.0606060606,3,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49416,Canada,46969.696969697,3,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49417,United Kingdom,31250,3,FALSE,TRUE,20,Not remote,7,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-49419,United States,9e4,1,FALSE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-49423,United States,8e4,2,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49424,United States,7e4,6,TRUE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49426,United States,96e3,16,FALSE,FALSE,1e3,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49431,India,2642.78373219792,1,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
-49434,United States,64e3,3,FALSE,TRUE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49441,United States,13e4,16,FALSE,TRUE,1,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-49446,United States,21e3,7,FALSE,TRUE,1e4,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE
-49447,United States,115e3,5,TRUE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49450,United States,12e4,6,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-49458,United States,145e3,17,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49465,United States,52e3,3,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-49469,United States,52e3,2,TRUE,TRUE,1e4,Not remote,6,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-49472,United States,14e4,20,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-49473,United States,135e3,2,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-49479,United States,116e3,1,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49419,United States,90000,1,FALSE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+49423,United States,80000,2,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49424,United States,70000,6,TRUE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49426,United States,96000,16,FALSE,FALSE,1000,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49431,India,2642.78373219792,1,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE
+49434,United States,64000,3,FALSE,TRUE,1000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49441,United States,130000,16,FALSE,TRUE,1,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+49446,United States,21000,7,FALSE,TRUE,10000,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE
+49447,United States,115000,5,TRUE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49450,United States,120000,6,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+49458,United States,145000,17,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49465,United States,52000,3,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+49469,United States,52000,2,TRUE,TRUE,10000,Not remote,6,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+49472,United States,140000,20,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+49473,United States,135000,2,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+49479,United States,116000,1,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49480,Canada,29545.4545454545,3,FALSE,TRUE,100,Not remote,4,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-49482,United States,16e4,20,TRUE,TRUE,1,Remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-49484,India,13948.0252532668,6,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-49485,India,8809.27910732638,3,TRUE,TRUE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+49482,United States,160000,20,TRUE,TRUE,1,Remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+49484,India,13948.0252532668,6,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+49485,India,8809.27910732638,3,TRUE,TRUE,10000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 49488,India,23491.4109528704,7,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49492,Canada,51515.1515151515,2,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 49493,India,20554.9845837616,3,TRUE,TRUE,20,Not remote,10,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 49498,Germany,64516.1290322581,11,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49501,United Kingdom,36718.75,3,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49503,United States,12e4,3,TRUE,TRUE,100,Not remote,5,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+49501,United Kingdom,36718.75,3,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49503,United States,120000,3,TRUE,TRUE,100,Not remote,5,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
 49504,Germany,64516.1290322581,14,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49514,Germany,2688.17204301075,1,TRUE,TRUE,1e4,Not remote,6,TRUE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,TRUE
-49530,United Kingdom,85e3,5,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49531,United Kingdom,51875,13,TRUE,FALSE,5e3,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-49532,United States,158e3,8,TRUE,TRUE,500,Remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49535,United States,75e3,10,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-49539,United States,8e4,4,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-49541,United States,5e4,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49514,Germany,2688.17204301075,1,TRUE,TRUE,10000,Not remote,6,TRUE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,TRUE
+49530,United Kingdom,85000,5,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49531,United Kingdom,51875,13,TRUE,FALSE,5000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+49532,United States,158000,8,TRUE,TRUE,500,Remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49535,United States,75000,10,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+49539,United States,80000,4,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+49541,United States,50000,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49543,United States,117500,10,FALSE,TRUE,20,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49546,United States,6e4,2,FALSE,TRUE,20,Remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49546,United States,60000,2,FALSE,TRUE,20,Remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49547,United Kingdom,56250,11,TRUE,TRUE,10,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 49549,India,18132.4328292468,7,TRUE,TRUE,100,Not remote,7,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49553,United States,92e3,15,FALSE,TRUE,5e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49556,United States,67e3,3,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+49553,United States,92000,15,FALSE,TRUE,5000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49556,United States,67000,3,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 49557,Canada,31818.1818181818,7,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49559,United Kingdom,56250,10,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 49560,United Kingdom,46875,10,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-49564,United States,133e3,19,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+49564,United States,133000,19,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 49565,Germany,66666.6666666667,7,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49566,United States,8e4,5,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49566,United States,80000,5,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49568,United Kingdom,56250,7,FALSE,FALSE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49570,United States,122500,6,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49571,Canada,68181.8181818182,10,TRUE,TRUE,100,Not remote,6,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 49575,Canada,63636.3636363636,20,FALSE,FALSE,20,Remote,5,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49578,United States,45e3,1,FALSE,TRUE,500,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49585,United States,72e3,2,TRUE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-49586,United Kingdom,75e3,16,FALSE,TRUE,5e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49593,United States,82e3,11,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49594,United States,8e4,11,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49595,United States,13e4,6,TRUE,TRUE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49597,United States,9e4,1,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49598,United States,14e4,20,TRUE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+49578,United States,45000,1,FALSE,TRUE,500,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49585,United States,72000,2,TRUE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+49586,United Kingdom,75000,16,FALSE,TRUE,5000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49593,United States,82000,11,FALSE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49594,United States,80000,11,TRUE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49595,United States,130000,6,TRUE,TRUE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49597,United States,90000,1,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49598,United States,140000,20,TRUE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-49600,United States,72e3,10,FALSE,TRUE,100,Not remote,7,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
-49608,United States,135e3,5,FALSE,TRUE,1e4,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+49600,United States,72000,10,FALSE,TRUE,100,Not remote,7,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
+49608,United States,135000,5,FALSE,TRUE,10000,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
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-49611,United States,108e3,15,TRUE,TRUE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49615,United States,115e3,14,TRUE,FALSE,20,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49616,United States,4e4,1,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-49617,United States,15e4,13,TRUE,FALSE,10,Not remote,5,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+49611,United States,108000,15,TRUE,TRUE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49615,United States,115000,14,TRUE,FALSE,20,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49616,United States,40000,1,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+49617,United States,150000,13,TRUE,FALSE,10,Not remote,5,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
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-49639,India,10277.4922918808,3,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+49639,India,10277.4922918808,3,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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 49665,United Kingdom,63750,8,TRUE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-49671,Canada,37878.7878787879,2,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49671,Canada,37878.7878787879,2,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49678,Germany,50322.5806451613,6,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
-49683,United States,135e3,17,TRUE,TRUE,10,Not remote,8,FALSE,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-49685,United States,111e3,5,FALSE,FALSE,5e3,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49694,United Kingdom,56250,1,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49702,United States,11e4,4,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49714,United States,9e4,18,FALSE,TRUE,10,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-49716,Canada,116666.666666667,20,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
-49721,United States,12e4,2,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49729,United States,102e3,3,TRUE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
-49763,Germany,63440.8602150538,17,TRUE,TRUE,1e4,Not remote,6,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49779,United States,125e3,3,TRUE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49683,United States,135000,17,TRUE,TRUE,10,Not remote,8,FALSE,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+49685,United States,111000,5,FALSE,FALSE,5000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49694,United Kingdom,56250,1,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49702,United States,110000,4,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49714,United States,90000,18,FALSE,TRUE,10,Not remote,10,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+49716,Canada,116666.666666667,20,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
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+49729,United States,102000,3,TRUE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+49763,Germany,63440.8602150538,17,TRUE,TRUE,10000,Not remote,6,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49779,United States,125000,3,TRUE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-49811,United Kingdom,111250,4,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+49811,United Kingdom,111250,4,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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 49814,Canada,62121.2121212121,4,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49819,United Kingdom,28750,1,FALSE,TRUE,1,Not remote,5,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49822,United Kingdom,27500,0,FALSE,TRUE,20,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-49824,United Kingdom,106250,6,FALSE,TRUE,1e4,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49831,United States,63e3,2,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
+49824,United Kingdom,106250,6,FALSE,TRUE,10000,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49831,United States,63000,2,FALSE,TRUE,500,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
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-49848,Germany,51161.2903225806,4,FALSE,FALSE,1e4,Not remote,4,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-49850,Germany,12903.2258064516,3,FALSE,TRUE,1e3,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+49848,Germany,51161.2903225806,4,FALSE,FALSE,10000,Not remote,4,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+49850,Germany,12903.2258064516,3,FALSE,TRUE,1000,Not remote,5,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 49853,United Kingdom,63750,7,TRUE,TRUE,500,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49861,India,14623.4033181618,5,FALSE,FALSE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-49866,Canada,75757.5757575758,10,FALSE,TRUE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49861,India,14623.4033181618,5,FALSE,FALSE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+49866,Canada,75757.5757575758,10,FALSE,TRUE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 49879,Canada,87121.2121212121,19,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49888,United States,7e4,2,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49889,United States,114e3,20,FALSE,TRUE,10,Not remote,10,FALSE,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE
-49892,United States,84e3,20,FALSE,FALSE,5e3,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-49894,United States,67e3,3,FALSE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
-49896,United States,12e4,2,TRUE,TRUE,100,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49897,United States,77e3,3,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-49904,United States,11e4,9,TRUE,TRUE,1,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49888,United States,70000,2,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49889,United States,114000,20,FALSE,TRUE,10,Not remote,10,FALSE,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE
+49892,United States,84000,20,FALSE,FALSE,5000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+49894,United States,67000,3,FALSE,TRUE,100,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+49896,United States,120000,2,TRUE,TRUE,100,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49897,United States,77000,3,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+49904,United States,110000,9,TRUE,TRUE,1,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-49913,United Kingdom,4e4,2,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49918,United States,143e3,17,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+49913,United Kingdom,40000,2,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49918,United States,143000,17,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-49941,United States,118e3,2,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-49949,United States,65e3,9,FALSE,TRUE,1,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+49931,United States,75000,1,FALSE,TRUE,100,Not remote,8,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+49937,United States,115000,5,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49941,United States,118000,2,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+49949,United States,65000,9,FALSE,TRUE,1,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
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-49967,United States,105e3,5,TRUE,TRUE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+49967,United States,105000,5,TRUE,TRUE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
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-50017,United States,8e4,12,FALSE,FALSE,100,Not remote,7,TRUE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-50019,United Kingdom,56250,17,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-50027,United States,65e3,2,TRUE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-50028,United States,13e4,12,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50032,United Kingdom,75e3,6,FALSE,TRUE,5e3,Not remote,4,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+50017,United States,80000,12,FALSE,FALSE,100,Not remote,7,TRUE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+50019,United Kingdom,56250,17,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+50027,United States,65000,2,TRUE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+50028,United States,130000,12,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50032,United Kingdom,75000,6,FALSE,TRUE,5000,Not remote,4,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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-50051,United States,74e3,8,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50055,United States,8e4,12,FALSE,TRUE,100,Not remote,4,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-50058,United States,165e3,10,FALSE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50059,United States,14e4,14,TRUE,TRUE,100,Not remote,9,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-50064,United States,115e3,20,FALSE,TRUE,1e4,Remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50081,United States,4e4,5,TRUE,TRUE,100,Not remote,5,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE
-50086,United States,14e4,9,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE
-50087,India,8809.27910732638,1,FALSE,FALSE,5e3,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+50051,United States,74000,8,TRUE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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+50058,United States,165000,10,FALSE,TRUE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50059,United States,140000,14,TRUE,TRUE,100,Not remote,9,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+50064,United States,115000,20,FALSE,TRUE,10000,Remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50081,United States,40000,5,TRUE,TRUE,100,Not remote,5,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE
+50086,United States,140000,9,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE
+50087,India,8809.27910732638,1,FALSE,FALSE,5000,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-50114,India,4e3,3,FALSE,TRUE,1,Not remote,7,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50114,India,4000,3,FALSE,TRUE,1,Not remote,7,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-50129,United States,119500,20,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+50129,United States,119500,20,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-50143,United Kingdom,4e4,2,FALSE,TRUE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50144,United States,125e3,5,FALSE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-50145,United States,12e4,4,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-50146,United States,102e3,14,FALSE,TRUE,20,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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+50143,United Kingdom,40000,2,FALSE,TRUE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50144,United States,125000,5,FALSE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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+50146,United States,102000,14,FALSE,TRUE,20,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-50154,United States,11e4,13,TRUE,FALSE,1e4,Not remote,7,TRUE,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-50159,Germany,54838.7096774193,9,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-50163,United States,40800,2,FALSE,TRUE,5e3,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50164,United States,68e3,1,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50154,United States,110000,13,TRUE,FALSE,10000,Not remote,7,TRUE,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+50159,Germany,54838.7096774193,9,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+50163,United States,40800,2,FALSE,TRUE,5000,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50164,United States,68000,1,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 50169,Canada,49242.4242424242,16,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 50183,Canada,69696.9696969697,20,FALSE,FALSE,20,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-50184,United States,83e3,2,FALSE,TRUE,1e3,Not remote,1,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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+50184,United States,83000,2,FALSE,TRUE,1000,Not remote,1,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+50199,United Kingdom,27500,1,FALSE,TRUE,5000,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
 50203,Germany,59139.7849462366,3,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 50221,Canada,64393.9393939394,6,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 50226,United Kingdom,46875,1,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 50228,United Kingdom,68750,9,FALSE,TRUE,20,Not remote,4,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50237,United States,89600,10,TRUE,TRUE,1e4,Not remote,9,TRUE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE
+50237,United States,89600,10,TRUE,TRUE,10000,Not remote,9,TRUE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE
 50241,United Kingdom,31250,3,FALSE,TRUE,1,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50242,United States,7e4,1,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
-50246,United States,65e3,5,TRUE,TRUE,1e3,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50253,United States,11e4,3,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-50260,United States,165e3,8,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50263,United States,75e3,1,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50268,United States,12e4,6,FALSE,TRUE,500,Not remote,8,TRUE,TRUE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-50270,United States,73e3,2,FALSE,FALSE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
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+50260,United States,165000,8,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-50276,United States,11e4,9,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-50284,United States,117e3,19,TRUE,FALSE,1e3,Remote,3,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-50297,United States,11e4,3,FALSE,TRUE,20,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50276,United States,110000,9,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+50284,United States,117000,19,TRUE,FALSE,1000,Remote,3,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+50297,United States,110000,3,FALSE,TRUE,20,Not remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 50304,India,2300,16,TRUE,TRUE,500,Not remote,8,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 50313,United Kingdom,55625,4,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 50314,United Kingdom,56250,8,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50323,India,4889.14990456614,1,FALSE,TRUE,1e4,Not remote,2,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+50323,India,4889.14990456614,1,FALSE,TRUE,10000,Not remote,2,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 50326,India,3523.71164293055,2,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 50328,United Kingdom,68750,11,FALSE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-50342,United States,13e4,16,FALSE,TRUE,5e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50342,United States,130000,16,FALSE,TRUE,5000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 50345,Germany,38709.6774193548,2,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 50346,United Kingdom,32877.5,2,TRUE,TRUE,10,Not remote,10,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE
 50351,Canada,42424.2424242424,12,TRUE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 50361,United Kingdom,38125,4,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50362,Canada,56818.1818181818,3,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50366,United States,85e3,3,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
-50367,United States,8e4,9,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50373,United States,106e3,11,FALSE,TRUE,1e4,Remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+50362,Canada,56818.1818181818,3,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50366,United States,85000,3,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+50367,United States,80000,9,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50373,United States,106000,11,FALSE,TRUE,10000,Remote,9,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
 50374,India,3699.89722507708,1,FALSE,TRUE,10,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 50379,United Kingdom,31250,1,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50386,United States,182e3,20,TRUE,FALSE,1e4,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50389,United States,105e3,5,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50393,United States,14e4,11,TRUE,TRUE,20,Remote,6,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-50396,United States,9e4,3,TRUE,TRUE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50386,United States,182000,20,TRUE,FALSE,10000,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50389,United States,105000,5,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50393,United States,140000,11,TRUE,TRUE,20,Remote,6,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+50396,United States,90000,3,TRUE,TRUE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 50397,Canada,62121.2121212121,8,FALSE,TRUE,100,Not remote,7,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-50399,United States,9e4,8,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50399,United States,90000,8,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 50400,Canada,50757.5757575758,8,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50401,United States,104e3,6,TRUE,TRUE,500,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50401,United States,104000,6,TRUE,TRUE,500,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 50406,India,1761.85582146528,0,FALSE,TRUE,1,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50410,United States,9e4,9,TRUE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50419,India,15e3,11,TRUE,TRUE,1,Not remote,10,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50410,United States,90000,9,TRUE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50419,India,15000,11,TRUE,TRUE,1,Not remote,10,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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 50429,Canada,37878.7878787879,2,TRUE,TRUE,100,Not remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50430,United States,142500,18,FALSE,TRUE,1e4,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-50436,Canada,45075.7575757576,3,FALSE,FALSE,1e4,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+50430,United States,142500,18,FALSE,TRUE,10000,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+50436,Canada,45075.7575757576,3,FALSE,FALSE,10000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 50437,Canada,79545.4545454545,3,FALSE,TRUE,10,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 50448,Canada,60606.0606060606,11,TRUE,TRUE,20,Not remote,10,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE
 50450,Germany,58064.5161290323,5,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50451,Germany,96774.1935483871,20,TRUE,TRUE,1e3,Not remote,9,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+50451,Germany,96774.1935483871,20,TRUE,TRUE,1000,Not remote,9,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
 50453,Canada,90909.0909090909,10,TRUE,TRUE,1,Remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 50454,United States,7961.78343949045,20,FALSE,FALSE,1,Remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 50457,India,11745.7054764352,3,FALSE,TRUE,500,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 50459,Canada,56818.1818181818,4,FALSE,TRUE,500,Not remote,3,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 50471,Germany,51612.9032258064,1,TRUE,TRUE,10,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 50473,Canada,113636.363636364,9,FALSE,TRUE,1,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-50476,United States,7e4,4,FALSE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50477,United States,12e4,12,TRUE,TRUE,100,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50487,United States,11e4,3,FALSE,TRUE,5e3,Not remote,1,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-50489,United States,74e3,19,FALSE,FALSE,1e3,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50516,United States,57e3,7,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+50476,United States,70000,4,FALSE,FALSE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50477,United States,120000,12,TRUE,TRUE,100,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50487,United States,110000,3,FALSE,TRUE,5000,Not remote,1,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+50489,United States,74000,19,FALSE,FALSE,1000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50516,United States,57000,7,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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-50523,United Kingdom,62500,15,FALSE,TRUE,1e3,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+50523,United Kingdom,62500,15,FALSE,TRUE,1000,Not remote,8,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
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-50529,United States,87e3,10,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+50529,United States,87000,10,TRUE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-50546,United States,11e4,4,TRUE,TRUE,5e3,Not remote,3,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
+50546,United States,110000,4,TRUE,TRUE,5000,Not remote,3,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE
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-50558,India,7047.42328586111,3,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-50567,United Kingdom,29375,2,FALSE,FALSE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+50558,India,7047.42328586111,3,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+50567,United Kingdom,29375,2,FALSE,FALSE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
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-50594,United States,14e4,20,FALSE,TRUE,1,Remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
-50607,United Kingdom,25e3,1,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50594,United States,140000,20,FALSE,TRUE,1,Remote,10,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
+50607,United Kingdom,25000,1,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-50610,United Kingdom,53750,6,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
-50617,United States,11e4,10,TRUE,FALSE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-50621,United States,96e3,7,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-50625,United States,135e3,14,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50626,United States,24e3,2,FALSE,FALSE,20,Not remote,2,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50629,United States,6e4,3,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-50631,United States,35e3,1,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+50610,United Kingdom,53750,6,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
+50617,United States,110000,10,TRUE,FALSE,100,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+50621,United States,96000,7,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+50625,United States,135000,14,FALSE,TRUE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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+50631,United States,35000,1,FALSE,TRUE,20,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 50632,Canada,53030.303030303,1,FALSE,TRUE,10,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 50633,Germany,59139.7849462366,5,FALSE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50646,United States,85e3,7,TRUE,TRUE,1e4,Not remote,6,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
+50646,United States,85000,7,TRUE,TRUE,10000,Not remote,6,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE
 50652,Canada,78787.8787878788,5,TRUE,TRUE,100,Not remote,8,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 50655,Canada,34090.9090909091,1,FALSE,FALSE,10,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 50657,United Kingdom,72500,6,TRUE,TRUE,10,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50660,United States,82e3,11,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50664,United States,137e3,4,FALSE,FALSE,5e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-50672,United States,46e3,1,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50684,Germany,32258.064516129,2,TRUE,TRUE,1e4,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
+50660,United States,82000,11,TRUE,TRUE,1000,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50664,United States,137000,4,FALSE,FALSE,5000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+50672,United States,46000,1,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50684,Germany,32258.064516129,2,TRUE,TRUE,10000,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
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 50691,India,17618.5582146528,7,FALSE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-50711,United Kingdom,93750,10,TRUE,FALSE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50711,United Kingdom,93750,10,TRUE,FALSE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-50724,United States,57e3,5,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50724,United States,57000,5,TRUE,TRUE,100,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-50731,United States,75e3,5,TRUE,TRUE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50752,United States,1e5,1,FALSE,FALSE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50731,United States,75000,5,TRUE,TRUE,20,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50752,United States,100000,1,FALSE,FALSE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-50755,United States,8e4,6,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50766,United States,11e4,3,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
-50769,United States,68e3,2,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50755,United States,80000,6,FALSE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50766,United States,110000,3,FALSE,TRUE,500,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE
+50769,United States,68000,2,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 50794,United Kingdom,52500,16,FALSE,TRUE,10,Not remote,8,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
 50796,United Kingdom,52883.75,9,FALSE,TRUE,20,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
 50803,India,5138.74614594039,2,FALSE,TRUE,10,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE
 50804,India,5872.85273821759,2,TRUE,FALSE,20,Remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 50816,Germany,30967.7419354839,8,TRUE,TRUE,20,Not remote,2,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE
 50846,United Kingdom,68750,1,FALSE,FALSE,20,Not remote,8,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-50854,United States,98e3,11,TRUE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50866,United States,9e4,20,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50854,United States,98000,11,TRUE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50866,United States,90000,20,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 50868,United States,77500,3,FALSE,FALSE,20,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-50870,United States,73e3,4,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE
-50884,United States,9e4,1,FALSE,TRUE,1e4,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50887,United States,9e4,15,TRUE,TRUE,1e3,Remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50870,United States,73000,4,FALSE,TRUE,20,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE
+50884,United States,90000,1,FALSE,TRUE,10000,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50887,United States,90000,15,TRUE,TRUE,1000,Remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 50907,India,1233.29907502569,0,TRUE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-50908,India,17618.5582146528,3,FALSE,FALSE,5e3,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+50908,India,17618.5582146528,3,FALSE,FALSE,5000,Not remote,6,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 50929,Germany,34408.6021505376,4,TRUE,TRUE,10,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50952,United Kingdom,65e3,10,TRUE,TRUE,100,Not remote,7,TRUE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE,TRUE
-50958,United States,114e3,13,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50952,United Kingdom,65000,10,TRUE,TRUE,100,Not remote,7,TRUE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE,TRUE
+50958,United States,114000,13,FALSE,TRUE,20,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-50968,United States,97e3,9,FALSE,TRUE,1e4,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-50974,United States,14e4,20,TRUE,TRUE,1e4,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50975,Canada,45454.5454545455,1,FALSE,TRUE,1e3,Not remote,10,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+50968,United States,97000,9,FALSE,TRUE,10000,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+50974,United States,140000,20,TRUE,TRUE,10000,Remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50975,Canada,45454.5454545455,1,FALSE,TRUE,1000,Not remote,10,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
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 50977,United States,107500,18,TRUE,FALSE,20,Remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-50979,United States,12e4,5,TRUE,TRUE,100,Not remote,7,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
-50981,Germany,68817.2043010753,20,TRUE,FALSE,1e3,Not remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-50983,United States,84999,1,FALSE,FALSE,1e4,Not remote,3,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50979,United States,120000,5,TRUE,TRUE,100,Not remote,7,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+50981,Germany,68817.2043010753,20,TRUE,FALSE,1000,Not remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+50983,United States,84999,1,FALSE,FALSE,10000,Not remote,3,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
 50987,United States,71500,3,FALSE,TRUE,100,Not remote,7,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50988,United States,71500,5,FALSE,TRUE,1e4,Not remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50995,United States,125e3,7,TRUE,TRUE,500,Remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-50996,United States,155e3,2,FALSE,TRUE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
-51009,United States,65e3,4,FALSE,FALSE,1e4,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
-51013,United States,88e3,9,FALSE,TRUE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-51017,United States,143e3,20,TRUE,TRUE,1e4,Not remote,8,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
-51021,United States,11e4,5,FALSE,FALSE,20,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-51023,United States,125e3,7,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-51054,United Kingdom,48750,10,FALSE,TRUE,1e4,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-51060,India,23491.4109528704,9,FALSE,FALSE,1e4,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+50988,United States,71500,5,FALSE,TRUE,10000,Not remote,10,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50995,United States,125000,7,TRUE,TRUE,500,Remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+50996,United States,155000,2,FALSE,TRUE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
+51009,United States,65000,4,FALSE,FALSE,10000,Not remote,7,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE
+51013,United States,88000,9,FALSE,TRUE,20,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+51017,United States,143000,20,TRUE,TRUE,10000,Not remote,8,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE
+51021,United States,110000,5,FALSE,FALSE,20,Not remote,9,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+51023,United States,125000,7,TRUE,TRUE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+51054,United Kingdom,48750,10,FALSE,TRUE,10000,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+51060,India,23491.4109528704,9,FALSE,FALSE,10000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
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-51085,United Kingdom,36250,20,FALSE,FALSE,1e3,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+51085,United Kingdom,36250,20,FALSE,FALSE,1000,Not remote,5,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-51087,India,5872.85273821759,1,TRUE,FALSE,1e3,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-51101,United Kingdom,55e3,6,TRUE,TRUE,1,Remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-51106,United States,11e4,12,FALSE,TRUE,500,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-51115,United States,135e3,8,FALSE,TRUE,100,Not remote,9,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-51116,United States,80250,3,TRUE,TRUE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-51121,United States,76e3,20,TRUE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-51123,United States,71e3,1,TRUE,FALSE,1e4,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
-51127,United States,95e3,9,FALSE,FALSE,500,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-51128,United States,8e4,17,FALSE,FALSE,100,Not remote,10,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-51136,United States,15e3,3,TRUE,TRUE,1,Remote,6,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE
-51150,India,16884.4516223756,4,TRUE,TRUE,1e3,Not remote,7,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-51154,Germany,17204.3010752688,3,TRUE,TRUE,1e4,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
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+51154,Germany,17204.3010752688,3,TRUE,TRUE,10000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
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-51184,Germany,60215.0537634409,13,TRUE,FALSE,1e4,Remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
+51179,Germany,48387.0967741935,4,FALSE,TRUE,10000,Not remote,5,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+51184,Germany,60215.0537634409,13,TRUE,FALSE,10000,Remote,10,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE
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-51217,United States,11e4,20,FALSE,TRUE,1e3,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+51217,United States,110000,20,FALSE,TRUE,1000,Remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-51267,United States,8e4,5,TRUE,TRUE,1e4,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-51272,United Kingdom,45e3,13,FALSE,FALSE,20,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+51267,United States,80000,5,TRUE,TRUE,10000,Not remote,8,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+51272,United Kingdom,45000,13,FALSE,FALSE,20,Not remote,3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
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-51285,United Kingdom,43750,3,TRUE,TRUE,1e3,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-51294,United States,88e3,4,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-51295,United States,165e3,19,TRUE,TRUE,1e3,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-51300,United States,54e3,4,FALSE,FALSE,5e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-51302,United States,75e3,9,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-51310,United States,52e3,1,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-51311,United States,5e4,1,FALSE,TRUE,1,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
-51313,United States,12e4,4,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
-51316,United States,14e4,10,TRUE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+51285,United Kingdom,43750,3,TRUE,TRUE,1000,Not remote,9,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+51294,United States,88000,4,FALSE,FALSE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+51295,United States,165000,19,TRUE,TRUE,1000,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+51300,United States,54000,4,FALSE,FALSE,5000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+51302,United States,75000,9,FALSE,FALSE,20,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+51310,United States,52000,1,TRUE,TRUE,100,Not remote,7,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+51311,United States,50000,1,FALSE,TRUE,1,Not remote,7,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE
+51313,United States,120000,4,FALSE,FALSE,500,Not remote,7,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+51316,United States,140000,10,TRUE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 51329,India,4404.63955366319,5,FALSE,TRUE,1,Not remote,8,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-51336,United Kingdom,88750,8,FALSE,TRUE,1e3,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-51341,India,6460.13801203935,2,FALSE,TRUE,1e4,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
+51336,United Kingdom,88750,8,FALSE,TRUE,1000,Not remote,8,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+51341,India,6460.13801203935,2,FALSE,TRUE,10000,Not remote,6,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE
 51344,India,4228.45397151666,2,FALSE,TRUE,1,Not remote,10,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE
 51356,United Kingdom,33750,1,TRUE,TRUE,100,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-51388,United States,58e3,1,FALSE,TRUE,100,Not remote,7,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
-51391,United States,4e4,3,FALSE,TRUE,1,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
+51388,United States,58000,1,FALSE,TRUE,100,Not remote,7,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE
+51391,United States,40000,3,FALSE,TRUE,1,Not remote,6,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE
diff --git a/data/stack_rf.rds b/data/stack_rf.rds
index 86a5804..2a0b00d 100644
Binary files a/data/stack_rf.rds and b/data/stack_rf.rds differ
diff --git a/data/stack_tree.rds b/data/stack_tree.rds
new file mode 100644
index 0000000..f7088a5
Binary files /dev/null and b/data/stack_tree.rds differ
diff --git a/data/tidy_sisters.rds b/data/tidy_sisters.rds
new file mode 100644
index 0000000..d87f502
Binary files /dev/null and b/data/tidy_sisters.rds differ
diff --git a/data/vote_glm.rds b/data/vote_glm.rds
index 796f21f..8bd6f40 100644
Binary files a/data/vote_glm.rds and b/data/vote_glm.rds differ
diff --git a/data/vote_rf.rds b/data/vote_rf.rds
index f609f64..f57f593 100644
Binary files a/data/vote_rf.rds and b/data/vote_rf.rds differ
diff --git a/exercises/exc_01_06.R b/exercises/exc_01_06.R
index 88de2f5..233d538 100644
--- a/exercises/exc_01_06.R
+++ b/exercises/exc_01_06.R
@@ -1,13 +1,15 @@
-library(tidyverse)
-car_vars <- readRDS("data/c1_cars_vars_full.rds")
-
-# Load rsample
-___
-
-# Split the data into training and test sets
-set.seed(1234)
-car_split <- car_vars %>%
-    initial_split(prop = ___, strata = ___)
-
-car_train <- training(___)
-car_test <- testing(___)
+car_vars <- readRDS("data/c1_car_vars.rds")
+
+# Load tidymodels
+___
+
+# Split the data into training and test sets
+set.seed(1234)
+car_split <- car_vars %>%
+    initial_split(prop = ___, strata = ___)
+
+car_train <- training(___)
+car_test <- testing(___)
+
+glimpse(car_train)
+glimpse(car_test)
diff --git a/exercises/exc_01_07_1.R b/exercises/exc_01_07_1.R
index 6080587..333a5b3 100644
--- a/exercises/exc_01_07_1.R
+++ b/exercises/exc_01_07_1.R
@@ -1,17 +1,17 @@
-library(tidyverse)
-
-car_train <- readRDS("data/c1_training_full.rds")
-car_test <- readRDS("data/c1_testing_full.rds")
-
-# Load caret
-___
-
-# Train a linear regression model
-fit_lm <- train(log(MPG) ~ ., 
-                method = ___, 
-                data = ___,
-                trControl = trainControl(method = "none"))
-
-# Print the model object
-fit_lm
-
+car_train <- readRDS("data/c1_train.rds")
+car_test <- readRDS("data/c1_test.rds")
+
+# Load tidymodels
+___
+
+# Build a linear regression model specification
+lm_mod <- ___ %>%
+    set_engine("lm")
+
+# Train a linear regression model
+fit_lm <- lm_mod %>%
+    fit(log(MPG) ~ ., 
+        data = ___)
+
+# Print the model object
+fit_lm
diff --git a/exercises/exc_01_07_2.R b/exercises/exc_01_07_2.R
index 4b3dce4..d069a35 100644
--- a/exercises/exc_01_07_2.R
+++ b/exercises/exc_01_07_2.R
@@ -1,15 +1,17 @@
-library(tidyverse)
-library(caret)
-library(randomForest)
-
-car_train <- readRDS("data/c1_training_full.rds")
-car_test <- readRDS("data/c1_testing_full.rds")
-
-# Train a random forest model
-fit_rf <- ___(log(MPG) ~ ., 
-                method = ___, 
-                data = ___,
-                trControl = trainControl(method = "none"))
-
-# Print the model object
-fit_rf
+library(tidymodels)
+
+car_train <- readRDS("data/c1_train.rds")
+car_test <- readRDS("data/c1_test.rds")
+
+# Build a random forest model specification
+rf_mod <- ___ %>%
+    set_engine("randomForest") %>%
+    set_mode("regression")
+
+# Train a random forest model
+fit_rf <- rf_mod %>%
+    ___(log(MPG) ~ ., 
+        data = ___)
+
+# Print the model object
+fit_rf
diff --git a/exercises/exc_01_08.R b/exercises/exc_01_08.R
index 8c3f29b..9a8999d 100644
--- a/exercises/exc_01_08.R
+++ b/exercises/exc_01_08.R
@@ -1,19 +1,19 @@
-library(caret)
-library(tidyverse)
-
-car_train <- readRDS("data/c1_training_full.rds")
+library(randomForest)
+car_train <- readRDS("data/c1_train.rds")
 fit_lm <- readRDS("data/c1_fit_lm.rds")
 fit_rf <- readRDS("data/c1_fit_rf.rds")
 
-# Load yardstick
+# Load tidymodels
 library(___)
 
 # Create the new columns
 results <- car_train %>%
-    mutate(MPG = log(MPG),
-           `Linear regression` = predict(___, car_train),
-           `Random forest` = predict(___, car_train))
+    mutate(MPG = log(MPG)) %>%
+    bind_cols(predict(___, car_train) %>%
+                  rename(.pred_lm = .pred)) %>%
+    bind_cols(predict(___, car_train) %>%
+                  rename(.pred_rf = .pred))
 
 # Evaluate the performance
-metrics(results, truth = ___, estimate = `Linear regression`)
-metrics(results, truth = ___, estimate = `Random forest`)
+metrics(results, truth = ___, estimate = .pred_lm)
+metrics(results, truth = ___, estimate = .pred_rf)
diff --git a/exercises/exc_01_09.R b/exercises/exc_01_09.R
index 406a12b..4e6c984 100644
--- a/exercises/exc_01_09.R
+++ b/exercises/exc_01_09.R
@@ -1,18 +1,18 @@
-library(caret)
-library(tidyverse)
-library(yardstick)
-
-car_test <- readRDS("data/c1_testing_full.rds")
-fit_lm <- readRDS("data/c1_fit_lm.rds")
-fit_rf <- readRDS("data/c1_fit_rf.rds")
-
-# Create the new columns
-results <- ___ %>%
-    mutate(MPG = log(MPG),
-           `Linear regression` = predict(fit_lm, ___),
-           `Random forest` = predict(fit_rf, ___))
-
-# Evaluate the performance
-metrics(results, truth = MPG, estimate = `Linear regression`)
-metrics(results, truth = MPG, estimate = `Random forest`)
-
+library(tidymodels)
+library(randomForest)
+
+car_test <- readRDS("data/c1_test.rds")
+fit_lm <- readRDS("data/c1_fit_lm.rds")
+fit_rf <- readRDS("data/c1_fit_rf.rds")
+
+# Create the new columns
+results <- ___ %>%
+    mutate(MPG = log(MPG)) %>%
+    bind_cols(predict(fit_lm, ___) %>%
+                  rename(.pred_lm = .pred)) %>%
+    bind_cols(predict(fit_rf, ___) %>%
+                  rename(.pred_rf = .pred))
+
+# Evaluate the performance
+metrics(results, truth = MPG, estimate = .pred_lm)
+metrics(results, truth = MPG, estimate = .pred_rf)
diff --git a/exercises/exc_01_11.R b/exercises/exc_01_11.R
index 2b0fe4c..08ba1c6 100644
--- a/exercises/exc_01_11.R
+++ b/exercises/exc_01_11.R
@@ -1,19 +1,30 @@
-library(caret)
-library(tidyverse)
-
-car_train <- readRDS("data/c1_training_one_percent.rds")
-
-# Fit the models with bootstrap resampling
-cars_lm_bt <- train(log(MPG) ~ ., 
-                    method = "lm", 
-                    data = ___,
-                    trControl = trainControl(method = ___))
-
-cars_rf_bt <- train(log(MPG) ~ ., 
-                    method = "rf", 
-                    data = ___,
-                    trControl = ___(method = ___))
-                   
-# Quick look at the models
-cars_lm_bt
-cars_rf_bt
+library(tidymodels)
+
+car_train <- readRDS("data/c1_train_10_percent.rds")
+
+lm_mod <- linear_reg() %>%
+    set_engine("lm")
+
+rf_mod <- rand_forest() %>%
+    set_engine("randomForest") %>%
+    set_mode("regression")
+
+## Create bootstrap resamples
+car_boot <- ___(car_train)
+
+# Evaluate the models with bootstrap resampling
+lm_res <- ___ %>%
+    fit_resamples(
+        log(MPG) ~ .,
+        resamples = ___,
+        control = control_resamples(save_pred = TRUE)
+    )
+
+rf_res <- ___ %>%
+    fit_resamples(
+        log(MPG) ~ .,
+        resamples = ___,
+        control = control_resamples(save_pred = TRUE)
+    )
+
+glimpse(rf_res)
diff --git a/exercises/exc_01_12_1.R b/exercises/exc_01_12_1.R
index 083ec3d..fc4e120 100644
--- a/exercises/exc_01_12_1.R
+++ b/exercises/exc_01_12_1.R
@@ -1,15 +1,13 @@
-library(caret)
-library(tidyverse)
-library(yardstick)
+library(tidymodels)
 
-car_test <- readRDS("data/c1_testing_full.rds")
-cars_lm_bt <- readRDS("data/cars_lm_bt.rds")
-cars_rf_bt <- readRDS("data/cars_rf_bt.rds")
+lm_res <- readRDS("data/c1_lm_res.rds")
+rf_res <- readRDS("data/c1_rf_res.rds")
 
-results <- car_test %>%
-    ___(MPG = log(MPG),
-        `Linear regression` = predict(cars_lm_bt, car_test),
-           `Random forest` = predict(cars_rf_bt, car_test))
+results <-  bind_rows(___ %>%
+                          collect_predictions() %>%
+                          mutate(model = "lm"),
+                      ___ %>%
+                          collect_predictions() %>%
+                          mutate(model = "rf"))
 
-metrics(results, ___ = MPG, ___ = `Linear regression`)
-metrics(results, ___ = MPG, ___ = `Random forest`)
+glimpse(results)
diff --git a/exercises/exc_01_12_2.R b/exercises/exc_01_12_2.R
index af4a387..94ce4d5 100644
--- a/exercises/exc_01_12_2.R
+++ b/exercises/exc_01_12_2.R
@@ -1,21 +1,19 @@
-library(caret)
 library(tidyverse)
-library(yardstick)
+library(tidymodels)
 
-car_test <- readRDS("data/c1_testing_full.rds")
-cars_lm_bt <- readRDS("data/cars_lm_bt.rds")
-cars_rf_bt <- readRDS("data/cars_rf_bt.rds")
+lm_res <- readRDS("data/c1_lm_res.rds")
+rf_res <- readRDS("data/c1_rf_res.rds")
 
-results <- car_test %>%
-    mutate(MPG = log(MPG),
-           `Linear regression` = predict(cars_lm_bt, car_test),
-           `Random forest` = predict(cars_rf_bt, car_test))
+results <-  bind_rows(lm_res %>%
+                          collect_predictions() %>%
+                          mutate(model = "lm"),
+                      rf_res %>%
+                          collect_predictions() %>%
+                          mutate(model = "rf"))
 
 results %>%
-    gather(Method, Result, `Linear regression`:`Random forest`) %>%
-    ggplot(aes(MPG, Result, color = Method)) +
-    geom_point(size = 1.5, alpha = 0.5) +
-    facet_wrap(~Method) +
+    ggplot(aes(`log(MPG)`, .pred)) +
     geom_abline(lty = 2, color = "gray50") +
-    geom_smooth(method = "lm")
-
+    geom_point(aes(color = id), size = 1.5, alpha = 0.3, show.legend = FALSE) +
+    geom_smooth(method = "lm") +
+    facet_wrap(~ model)
diff --git a/exercises/exc_02_03_1.R b/exercises/exc_02_03_1.R
index 8a7039f..3849cfc 100644
--- a/exercises/exc_02_03_1.R
+++ b/exercises/exc_02_03_1.R
@@ -1,13 +1,13 @@
 library(tidyverse)
-stackoverflow <- read_csv("data/stackoverflow.csv")
+stack_overflow <- read_csv("data/stack_overflow.csv")
 
-# Print stackoverflow
+# Take a look at stack_overflow
 glimpse(___)
 
-# First count for Remote
-stackoverflow %>% 
+# First count for `remote`
+stack_overflow %>% 
     count(___, sort = TRUE)
 
-# then count for Country
-stackoverflow %>% 
+# then count for `country`
+stack_overflow %>% 
     ___(___, sort = TRUE)
diff --git a/exercises/exc_02_03_2.R b/exercises/exc_02_03_2.R
index 07b0326..e9c76f0 100644
--- a/exercises/exc_02_03_2.R
+++ b/exercises/exc_02_03_2.R
@@ -1,8 +1,8 @@
-library(tidyverse)
-stackoverflow <- read_csv("data/stackoverflow.csv")
-
-ggplot(stackoverflow, aes(___, ___)) +
-    geom_boxplot() +
-    labs(x = NULL,
-         y = "Years of professional coding experience") 
-
+library(tidyverse)
+stack_overflow <- read_csv("data/stack_overflow.csv")
+
+ggplot(stack_overflow, aes(___, ___)) +
+    geom_boxplot() +
+    labs(x = NULL,
+         y = "Years of professional coding experience") 
+
diff --git a/exercises/exc_02_04.R b/exercises/exc_02_04.R
index 3b2c703..ad4158c 100644
--- a/exercises/exc_02_04.R
+++ b/exercises/exc_02_04.R
@@ -1,14 +1,23 @@
-library(tidyverse)
-stackoverflow <- read_csv("data/stackoverflow.csv") %>%
-    mutate(Remote = factor(Remote, levels = c("Remote", "Not remote")))
-
-# Build a simple logistic regression model
-simple_glm <- stackoverflow %>%
-        select(-___) %>%
-        glm(___,
-            family = "binomial",
-            data = ___)
-
-
-# Print the summary of the model
-summary(simple_glm)
+library(tidyverse)
+stack_overflow <- read_csv("data/stack_overflow.csv") %>%
+    mutate(remote = factor(remote, levels = c("Remote", "Not remote"))) %>%
+    mutate_if(is.character, factor)
+
+# Load tidymodels
+library(___)
+
+# Create stack_select dataset
+stack_select <- stack_overflow %>%
+    select(-respondent)
+
+# Split the data into training and testing sets
+set.seed(1234)
+stack_split <- stack_select %>%
+    initial_split(___,
+                  strata = ___)
+
+stack_train <- ___(stack_split)
+stack_test <- ___(stack_split)
+
+glimpse(stack_train)
+glimpse(stack_test)
diff --git a/exercises/exc_02_06.R b/exercises/exc_02_06.R
index 10e090d..d02be0f 100644
--- a/exercises/exc_02_06.R
+++ b/exercises/exc_02_06.R
@@ -1,21 +1,8 @@
-library(tidyverse)
-stackoverflow <- read_csv("data/stackoverflow.csv") %>%
-    mutate(Remote = factor(Remote, levels = c("Remote", "Not remote")))
+library(tidymodels)
 
-# Load rsample
-library(___)
-
-# Create stack_select dataset
-stack_select <- stackoverflow %>%
-    select(-Respondent)
-
-# Split the data into training and testing sets
-set.seed(1234)
-stack_split <- stack_select %>%
-    initial_split(___,
-                  strata = "___")
-
-stack_train <- training(___)
-stack_test <- testing(___)
+stack_train <- readRDS("data/c2_train.rds")
 
+stack_recipe <- ___(remote ~ ., data = stack_train) %>% 
+    step_downsample(___)
 
+stack_recipe
diff --git a/exercises/exc_02_07.R b/exercises/exc_02_07.R
index a7655cc..2c944f7 100644
--- a/exercises/exc_02_07.R
+++ b/exercises/exc_02_07.R
@@ -1,16 +1,12 @@
-library(tidyverse)
-library(caret)
-
-stack_train <- readRDS("data/c2_training_full.rds")
-stack_test <- readRDS("data/c2_testing_full.rds")
-
-# Create the upsampled training set
-up_train <- upSample(x = select(___, -Remote),
-                     y = ___,
-                     yname = "___") %>%
-    as_tibble()
-
-# Count the number of each type of Remote employee
-up_train %>%
-    count(Remote)
-
+library(tidymodels)
+
+stack_train <- readRDS("data/c2_train.rds")
+
+stack_recipe <- recipe(remote ~ ., data = stack_train) %>% 
+    step_downsample(remote)
+
+stack_prep <- prep(___)
+stack_down <- juice(___)
+
+stack_down %>%
+    count(remote)
diff --git a/exercises/exc_02_11_1.R b/exercises/exc_02_11_1.R
index 7a6e3d3..50cc940 100644
--- a/exercises/exc_02_11_1.R
+++ b/exercises/exc_02_11_1.R
@@ -1,13 +1,22 @@
-library(tidyverse)
-library(caret)
+library(tidymodels)
 
-stack_train <- readRDS("data/c2_training_one_percent.rds")
+stack_train <- readRDS("data/c2_train.rds")
 
-# Build a logistic regression model
-stack_glm <- train(Remote ~ ., ___, ___,
-                   data = stack_train,
-                   trControl = trainControl(method = "boot",
-                                            ___))
+stack_recipe <- recipe(remote ~ ., data = stack_train) %>% 
+    step_downsample(remote)
 
-# Print the model object
-stack_glm
\ No newline at end of file
+## Build a logistic regression model
+glm_spec <- ___ %>%
+    set_engine("glm")
+
+## Start a workflow (recipe only)
+stack_wf <- ___ %>%
+    add_recipe(stack_recipe)
+
+## Add the model and fit the workflow
+stack_glm <- stack_wf %>%
+    add_model(___) %>%
+    fit(data = stack_train)
+
+# Print the fitted model
+stack_glm
diff --git a/exercises/exc_02_11_2.R b/exercises/exc_02_11_2.R
index 5d67c19..798db01 100644
--- a/exercises/exc_02_11_2.R
+++ b/exercises/exc_02_11_2.R
@@ -1,14 +1,23 @@
-library(tidyverse)
-library(caret)
+library(tidymodels)
 
-stack_train <- readRDS("data/c2_training_one_percent.rds")
+stack_train <- readRDS("data/c2_train.rds")
 
-# Build a random forest model
-stack_rf <- train(Remote ~ ., ___, 
-                  data = stack_train,
-                  trControl = trainControl(method = "boot",
-                                           ___))
+stack_recipe <- recipe(remote ~ ., data = stack_train) %>% 
+    step_downsample(remote)
 
-# Print the model object
-stack_rf
+## Build a decision tree model
+tree_spec <- ___ %>%         
+    set_engine("rpart") %>%      
+    set_mode("classification") 
 
+## Start a workflow (recipe only)
+stack_wf <- workflow() %>%
+    ___(___)
+
+## Add the model and fit the workflow
+stack_tree <- stack_wf %>%
+    add_model(tree_spec) %>%
+    __(data = stack_train)
+
+# Print the fitted model
+stack_tree
diff --git a/exercises/exc_02_12_1.R b/exercises/exc_02_12_1.R
index 5f78620..9e41013 100644
--- a/exercises/exc_02_12_1.R
+++ b/exercises/exc_02_12_1.R
@@ -1,15 +1,14 @@
-library(caret)
-library(tidyverse)
-library(yardstick)
-
-stack_train <- readRDS("data/c2_training_full.rds")
-stack_test <- readRDS("data/c2_testing_full.rds")
-stack_glm <- readRDS("data/stack_glm.rds")
-stack_rf <- readRDS("data/stack_rf.rds")
-
-# Confusion matrix for logistic regression model
-stack_test %>%
-    mutate(`Logistic regression` = predict(stack_glm, ___)) %>%
-    conf_mat(___ = Remote, ___ = "Logistic regression")
-
-
+library(tidymodels)
+
+stack_train <- readRDS("data/c2_train.rds")
+stack_test <- readRDS("data/c2_test.rds")
+stack_glm <- readRDS("data/stack_glm.rds")
+stack_tree <- readRDS("data/stack_tree.rds")
+
+results <- stack_test %>%
+    bind_cols(predict(stack_glm, stack_test) %>%
+                  rename(.pred_glm = .pred_class))
+
+# Confusion matrix for logistic regression model
+results %>%
+    conf_mat(___ = remote, ___ = .pred_glm)
diff --git a/exercises/exc_02_12_2.R b/exercises/exc_02_12_2.R
index d639c7c..d290db1 100644
--- a/exercises/exc_02_12_2.R
+++ b/exercises/exc_02_12_2.R
@@ -1,15 +1,14 @@
-library(caret)
-library(tidyverse)
-library(yardstick)
-
-stack_train <- readRDS("data/c2_training_full.rds")
-stack_test <- readRDS("data/c2_testing_full.rds")
-stack_glm <- readRDS("data/stack_glm.rds")
-stack_rf <- readRDS("data/stack_rf.rds")
-
-# Confusion matrix for random forest model
-stack_test %>%
-    mutate(`Random forest` = predict(stack_rf, ___)) %>%
-    ___(___ = Remote, ___ = "Random forest")
-
-
+library(tidymodels)
+
+stack_train <- readRDS("data/c2_train.rds")
+stack_test <- readRDS("data/c2_test.rds")
+stack_glm <- readRDS("data/stack_glm.rds")
+stack_tree <- readRDS("data/stack_tree.rds")
+
+results <- stack_test %>%
+    bind_cols(predict(stack_tree, ___) %>%
+                  rename(.pred_tree = .pred_class))
+
+# Confusion matrix for decision tree model
+results %>%
+    ___(___ = remote, ___ = .pred_tree)
diff --git a/exercises/exc_02_13.R b/exercises/exc_02_13.R
index 420d7b2..c382fe7 100644
--- a/exercises/exc_02_13.R
+++ b/exercises/exc_02_13.R
@@ -1,23 +1,20 @@
-library(tidyverse)
-library(caret)
+library(tidymodels)
 
-stack_test <- readRDS("data/c2_testing_full.rds")
+stack_train <- readRDS("data/c2_train.rds")
+stack_test <- readRDS("data/c2_test.rds")
 stack_glm <- readRDS("data/stack_glm.rds")
-stack_rf <- readRDS("data/stack_rf.rds")
+stack_tree <- readRDS("data/stack_tree.rds")
 
-# Load yardstick
-library(___)
-
-# Predict values
-testing_results <- stack_test %>%
-    mutate(`Logistic regression` = predict(___, stack_test),
-           `Random forest` = predict(___, stack_test))
+results <- stack_test %>%
+    bind_cols(predict(stack_glm, ___) %>%
+                  rename(.pred_glm = .pred_class)) %>%
+    bind_cols(predict(stack_tree, ___) %>%
+                  rename(.pred_tree = .pred_class))
 
 ## Calculate accuracy
-___(testing_results, truth = Remote, estimate = `Logistic regression`)
-___(testing_results, truth = Remote, estimate = `Random forest`)
+___(results, truth = remote, estimate = .pred_glm)
+___(results, truth = remote, estimate = .pred_tree)
 
 ## Calculate positive predict value
-___(testing_results, truth = Remote, estimate = `Logistic regression`)
-___(testing_results, truth = Remote, estimate = `Random forest`)
-
+___(results, truth = remote, estimate = .pred_glm)
+___(results, truth = remote, estimate = .pred_tree)
diff --git a/exercises/exc_03_03_1.R b/exercises/exc_03_03_1.R
index b9e06bf..87f1a04 100644
--- a/exercises/exc_03_03_1.R
+++ b/exercises/exc_03_03_1.R
@@ -3,7 +3,7 @@ ___
 
 voters <- read_csv("data/voters.csv")
 
-# Print voters
+# Take a look at voters
 glimpse(___)
 
 # How many people voted?
diff --git a/exercises/exc_03_03_2.R b/exercises/exc_03_03_2.R
index 08f743a..e883af8 100644
--- a/exercises/exc_03_03_2.R
+++ b/exercises/exc_03_03_2.R
@@ -1,11 +1,11 @@
-library(tidyverse)
-voters <- read_csv("data/voters.csv")
-
-# How do the reponses on the survey vary with voting behavior?
-voters %>%
-    ___(turnout16_2016) %>%
-    ___(`Elections don't matter` = mean(RIGGED_SYSTEM_1_2016 <= 2),
-              `Economy is getting better` = mean(econtrend_2016 == 1),
-              `Crime is very important` = mean(imiss_a_2016 == 2))
-
-
+library(tidyverse)
+voters <- read_csv("data/voters.csv")
+
+# How do the responses on the survey vary with voting behavior?
+voters %>%
+    ___(turnout16_2016) %>%
+    ___(`Elections don't matter` = mean(RIGGED_SYSTEM_1_2016 <= 2),
+              `Economy is getting better` = mean(econtrend_2016 == 1),
+              `Crime is very important` = mean(imiss_a_2016 == 2))
+
+
diff --git a/exercises/exc_03_04.R b/exercises/exc_03_04.R
index 47e6ed1..26ca30c 100644
--- a/exercises/exc_03_04.R
+++ b/exercises/exc_03_04.R
@@ -1,10 +1,10 @@
-library(tidyverse)
-voters <- read_csv("data/voters.csv") %>%
-    mutate(turnout16_2016 = factor(turnout16_2016))
-
-## Visualize difference by voter turnout
-voters %>%
-    ___(aes(econtrend_2016, ..density.., fill = turnout16_2016)) +
-    ___(alpha = 0.5, position = "identity", binwidth = 1) +
-    labs(title = "Overall, is the economy getting better or worse?")
-
+library(tidyverse)
+voters <- read_csv("data/voters.csv") %>%
+    mutate(turnout16_2016 = factor(turnout16_2016))
+
+## Visualize difference by voter turnout
+voters %>%
+    ___(aes(econtrend_2016, after_stat(density), fill = turnout16_2016)) +
+    ___(alpha = 0.5, position = "identity", binwidth = 1) +
+    labs(title = "Overall, is the economy getting better or worse?")
+
diff --git a/exercises/exc_03_06.R b/exercises/exc_03_06.R
index 4b8398e..5230c82 100644
--- a/exercises/exc_03_06.R
+++ b/exercises/exc_03_06.R
@@ -1,15 +1,18 @@
-library(tidyverse)
-voters <- read_csv("data/voters.csv") %>%
-    mutate(turnout16_2016 = factor(turnout16_2016))
-
-# Remove the case_indetifier column
-voters_select <- voters %>%
-        ___(-case_identifier)
-
-# Build a simple logistic regression model
-simple_glm <- glm(___,  family = ___, 
-                  data = voters_select)
-
-# Print the summary                  
-___(simple_glm)
-
+library(tidyverse)
+voters_select <- read_csv("data/voters.csv") %>%
+    mutate(turnout16_2016 = factor(turnout16_2016)) %>% 
+    select(-case_identifier)
+
+# Load tidymodels
+___
+
+# Split data into training and testing sets
+set.seed(1234)
+vote_split <- ___ %>%
+    ___(p = ___,
+                  strata = ___)
+vote_train <- ___
+vote_test <- ___
+
+glimpse(vote_train)
+glimpse(vote_test)
diff --git a/exercises/exc_03_08.R b/exercises/exc_03_08.R
index 9f11ce0..7ca5e7e 100644
--- a/exercises/exc_03_08.R
+++ b/exercises/exc_03_08.R
@@ -1,15 +1,8 @@
-library(tidyverse)
-voters_select <- read_csv("data/voters.csv") %>%
-    mutate(turnout16_2016 = factor(turnout16_2016)) %>% 
-    select(-case_identifier)
-
-# Load rsample
-___
-
-# Split data into training and testing sets
-set.seed(1234)
-vote_split <- ___ %>%
-    ___(p = ___,
-                  strata = "___")
-vote_train <- ___
-vote_test <- ___
+library(tidymodels)
+
+vote_train <- readRDS("data/c3_train.rds")
+
+vote_recipe <- ___(turnout16_2016 ~ ., data = ___) %>% 
+    ___(turnout16_2016)
+
+vote_recipe
diff --git a/exercises/exc_03_09.R b/exercises/exc_03_09.R
index 1a3c4ba..177fde0 100644
--- a/exercises/exc_03_09.R
+++ b/exercises/exc_03_09.R
@@ -1,12 +1,18 @@
-library(tidyverse)
-library(caret)
-
-vote_train <- readRDS("data/c3_training_full.rds")
-
-# Perform logistic regression with upsampling and no resampling
-vote_glm <- train(turnout16_2016 ~ ., 
-                  method = "glm", family = "binomial",
-                  data = vote_train,
-                  trControl = ___(method = ___,
-                                           ___))
-
+library(tidymodels)
+
+vote_train <- readRDS("data/c3_train.rds")
+
+vote_recipe <- recipe(turnout16_2016 ~ ., data = vote_train) %>% 
+    step_upsample(turnout16_2016)
+
+## Specify a ranger model
+rf_spec <- ___ %>%
+    set_engine("ranger") %>%
+    set_mode("classification")
+
+## Add the recipe + model to a workflow
+vote_wf <- workflow() %>%
+    ___(vote_recipe) %>%
+    ___(rf_spec)
+
+vote_wf
diff --git a/exercises/exc_03_12.R b/exercises/exc_03_12.R
new file mode 100644
index 0000000..86e54d0
--- /dev/null
+++ b/exercises/exc_03_12.R
@@ -0,0 +1,7 @@
+library(tidymodels)
+
+vote_train <- readRDS("data/c3_train.rds")
+
+vote_folds <- vfold_cv(vote_train, ___ = 10, ___ = 5)
+
+glimpse(vote_folds)
diff --git a/exercises/exc_03_12_1.R b/exercises/exc_03_12_1.R
deleted file mode 100644
index b2bb38d..0000000
--- a/exercises/exc_03_12_1.R
+++ /dev/null
@@ -1,15 +0,0 @@
-library(tidyverse)
-library(caret)
-
-vote_train <- readRDS("data/c3_training_two_percent.rds")
-
-# Logistic regression
-vote_glm <- train(turnout16_2016 ~ ., 
-                  method = "glm", family = "binomial",
-                  data = vote_train,
-                  trControl = trainControl(method = ___,
-                                           repeats = ___,
-                                           sampling = "up"))
-
-# Print vote_glm
-vote_glm
diff --git a/exercises/exc_03_12_2.R b/exercises/exc_03_12_2.R
deleted file mode 100644
index 8145004..0000000
--- a/exercises/exc_03_12_2.R
+++ /dev/null
@@ -1,15 +0,0 @@
-library(tidyverse)
-library(caret)
-
-vote_train <- readRDS("data/c3_training_two_percent.rds")
-
-# Random forest
-vote_rf <- train(turnout16_2016 ~ ., method = "rf", 
-                 data = vote_train,
-                 trControl = trainControl(___,
-                                          ___,
-                                          sampling = "up"))
-
-# Print vote_rf
-vote_rf
-
diff --git a/exercises/exc_03_14_1.R b/exercises/exc_03_14_1.R
index 15a0a12..b4215b4 100644
--- a/exercises/exc_03_14_1.R
+++ b/exercises/exc_03_14_1.R
@@ -1,14 +1,25 @@
-library(tidyverse)
-library(caret)
-library(yardstick)
-
-vote_train <- readRDS("data/c3_training_full.rds")
-vote_test <- readRDS("data/c3_testing_full.rds")
-vote_glm <- readRDS("data/vote_glm.rds")
-vote_rf <- readRDS("data/vote_rf.rds")
-
-# Confusion matrix for logistic regression model on training data
-vote_train %>%
-    mutate(`Logistic regression` = predict(vote_glm, ___)) %>%
-    ___(truth = ___, estimate = "Logistic regression")
-
+library(tidymodels)
+
+vote_train <- readRDS("data/c3_train_10_percent.rds")
+
+vote_folds <- vfold_cv(vote_train, v = 10)
+
+vote_recipe <- recipe(turnout16_2016 ~ ., data = vote_train) %>% 
+    step_upsample(turnout16_2016)
+
+glm_spec <- logistic_reg() %>%
+    set_engine("glm")
+
+vote_wf <- workflow() %>%
+    add_recipe(vote_recipe) %>%
+    add_model(glm_spec)
+
+set.seed(234)
+glm_res <- vote_wf %>%
+    ___(
+        vote_folds,
+        metrics = metric_set(roc_auc, sens, spec),
+        control = control_resamples(save_pred = TRUE)
+    )
+
+glimpse(glm_res)
diff --git a/exercises/exc_03_14_2.R b/exercises/exc_03_14_2.R
index 1913395..a5d0eda 100644
--- a/exercises/exc_03_14_2.R
+++ b/exercises/exc_03_14_2.R
@@ -1,14 +1,26 @@
-library(tidyverse)
-library(caret)
-library(yardstick)
-
-vote_train <- readRDS("data/c3_training_full.rds")
-vote_test <- readRDS("data/c3_testing_full.rds")
-vote_glm <- readRDS("data/vote_glm.rds")
-vote_rf <- readRDS("data/vote_rf.rds")
-
-# Confusion matrix for random forest model on training data
-vote_train %>%
-    mutate(`Random forest` = ___(___, ___)) %>%
-    conf_mat(truth = ___, estimate = "Random forest")
-
+library(tidymodels)
+
+vote_train <- readRDS("data/c3_train_10_percent.rds")
+
+vote_folds <- vfold_cv(vote_train, v = 10)
+
+vote_recipe <- recipe(turnout16_2016 ~ ., data = vote_train) %>% 
+    step_upsample(turnout16_2016)
+
+rf_spec <- rand_forest() %>%
+    set_engine("ranger") %>%
+    set_mode("classification")
+
+vote_wf <- workflow() %>%
+    add_recipe(vote_recipe) %>%
+    add_model(rf_spec)
+
+set.seed(234)
+rf_res <- vote_wf %>%
+    fit_resamples(
+        ___,
+        metrics = metric_set(___),
+        control = control_resamples(save_pred = TRUE)
+    )
+
+glimpse(rf_res)
diff --git a/exercises/exc_03_15.R b/exercises/exc_03_15.R
new file mode 100644
index 0000000..a821d90
--- /dev/null
+++ b/exercises/exc_03_15.R
@@ -0,0 +1,7 @@
+library(tidymodels)
+
+glm_res <- readRDS("data/c3_glm_res.rds")
+rf_res <- readRDS("data/c3_rf_res.rds")
+
+___(glm_res)
+___(rf_res)
diff --git a/exercises/exc_03_15_1.R b/exercises/exc_03_15_1.R
deleted file mode 100644
index be9d26e..0000000
--- a/exercises/exc_03_15_1.R
+++ /dev/null
@@ -1,13 +0,0 @@
-library(tidyverse)
-library(caret)
-library(yardstick)
-
-vote_train <- readRDS("data/c3_training_full.rds")
-vote_test <- readRDS("data/c3_testing_full.rds")
-vote_glm <- readRDS("data/vote_glm.rds")
-vote_rf <- readRDS("data/vote_rf.rds")
-
-# Confusion matrix for logistic regression model on testing data
-vote_test %>%
-    mutate(`Logistic regression` = ___(___, ___)) %>%
-    ___(truth = ___, estimate = "___")
diff --git a/exercises/exc_03_15_2.R b/exercises/exc_03_15_2.R
deleted file mode 100644
index f3f0194..0000000
--- a/exercises/exc_03_15_2.R
+++ /dev/null
@@ -1,14 +0,0 @@
-library(tidyverse)
-library(caret)
-library(yardstick)
-
-vote_train <- readRDS("data/c3_training_full.rds")
-vote_test <- readRDS("data/c3_testing_full.rds")
-vote_glm <- readRDS("data/vote_glm.rds")
-vote_rf <- readRDS("data/vote_rf.rds")
-
-# Confusion matrix for random forest model on testing data
-vote_test %>%
-    ___(`Random forest` = ___(___, ___)) %>%
-    ___(truth = ___, estimate = "Random forest")
-
diff --git a/exercises/exc_03_17.R b/exercises/exc_03_17.R
new file mode 100644
index 0000000..23620ef
--- /dev/null
+++ b/exercises/exc_03_17.R
@@ -0,0 +1,36 @@
+library(tidyverse)
+library(tidymodels)
+
+voters_select <- read_csv("data/voters.csv") %>%
+    mutate(turnout16_2016 = factor(turnout16_2016)) %>% 
+    select(-case_identifier)
+
+## Training / testing split
+set.seed(1234)
+vote_split <- voters_select %>%
+    initial_split(p = 0.8,
+                  strata = turnout16_2016)
+vote_train <- training(vote_split)
+vote_test <- testing(vote_split)
+
+## Preprocess with a recipe
+vote_recipe <- recipe(turnout16_2016 ~ ., data = vote_train) %>% 
+    step_upsample(turnout16_2016)
+
+## Model specification
+glm_spec <- logistic_reg() %>%
+    set_engine("glm")
+
+## Combine in workflow
+vote_wf <- workflow() %>%
+    add_recipe(vote_recipe) %>%
+    add_model(glm_spec)
+
+## Final fit
+vote_final <- vote_wf %>%
+    ___(vote_split)
+
+## Confusion matrix
+vote_final %>% 
+    collect_predictions() %>% 
+    ___(turnout16_2016, .pred_class)
diff --git a/exercises/exc_04_04_1.R b/exercises/exc_04_04_1.R
index fd49435..a504845 100644
--- a/exercises/exc_04_04_1.R
+++ b/exercises/exc_04_04_1.R
@@ -1,13 +1,13 @@
-library(tidyverse)
-sisters67 <- read_csv("data/sisters.csv")
-
-# Print the structure of sisters67
-glimpse(sisters67)
-
-# Tidy the data set
-tidy_sisters <- sisters67 %>%
-    select(-sister) %>%
-    ___(key, value, -age)
-
-# Print the structure of tidy_sisters
-___
+library(tidyverse)
+sisters67 <- read_csv("data/sisters.csv")
+
+# Print the structure of sisters67
+glimpse(sisters67)
+
+# Tidy the data set
+tidy_sisters <- sisters67 %>%
+    select(-sister) %>%
+    ___(-age, names_to = "question", values_to = "rating")
+
+# Print the structure of tidy_sisters
+___
diff --git a/exercises/exc_04_04_2.R b/exercises/exc_04_04_2.R
index b4dc696..8466a17 100644
--- a/exercises/exc_04_04_2.R
+++ b/exercises/exc_04_04_2.R
@@ -1,11 +1,11 @@
-library(tidyverse)
-tidy_sisters <- readRDS("data/c4_tidy_sisters.rds")
-
-# Overall agreement with all questions by age
-tidy_sisters %>%
-    ___(age) %>%
-    ___(value = mean(value, na.rm = TRUE))
-
-# Number of respondents agreed or disagreed overall
-tidy_sisters %>%
-    ___(value)
+library(tidyverse)
+tidy_sisters <- readRDS("data/tidy_sisters.rds")
+
+# Overall agreement with all questions by age
+tidy_sisters %>%
+    ___(age) %>%
+    ___(rating = mean(rating, na.rm = TRUE))
+
+# Number of respondents agreed or disagreed overall
+tidy_sisters %>%
+    ___(rating)
diff --git a/exercises/exc_04_06.R b/exercises/exc_04_06.R
index e51e7b5..0543ab1 100644
--- a/exercises/exc_04_06.R
+++ b/exercises/exc_04_06.R
@@ -1,11 +1,11 @@
-library(tidyverse)
-tidy_sisters <- readRDS("data/c4_tidy_sisters.rds")
-
-# Visualize agreement with age
-tidy_sisters %>%
-    filter(key %in% paste0("v", 153:170)) %>%
-    ___(key, value) %>%
-    ___(age = mean(age, na.rm = TRUE)) %>%
-    ggplot(aes(value, age, color = key)) +
-    ___(show.legend = FALSE) +
-    facet_wrap(~key, nrow = 3)
+library(tidyverse)
+tidy_sisters <- readRDS("data/tidy_sisters.rds")
+
+# Visualize agreement with age
+tidy_sisters %>%
+    filter(question %in% paste0("v", 153:170)) %>%
+    ___(question, rating) %>%
+    ___(age = mean(age, na.rm = TRUE)) %>%
+    ggplot(aes(rating, age, color = question)) +
+    ___(show.legend = FALSE) +
+    facet_wrap(~question, nrow = 3)
diff --git a/exercises/exc_04_07.R b/exercises/exc_04_07.R
index 8bb0aae..816aeef 100644
--- a/exercises/exc_04_07.R
+++ b/exercises/exc_04_07.R
@@ -1,13 +1,17 @@
-library(tidyverse)
-sisters67 <- read_csv("data/sisters.csv")
-
-# Remove the sister column
-sisters_select <- sisters67 %>% 
-    ___(-sister)
-
-# Build a simple linear regression model
-simple_lm <- lm(___, 
-                data = sisters_select)
-
-# Print the summary of the model
-___(simple_lm)
\ No newline at end of file
+library(tidyverse)
+library(tidymodels)
+sisters_select <- read_csv("data/sisters.csv") %>%
+    select(-sister)
+
+# Split off the testing set
+set.seed(123)
+sisters_split <- ___(sisters_select, strata = age)
+
+sisters_other <- training(___)
+sisters_test <- testing(___)
+
+# Create the validation split
+set.seed(123)
+sisters_val <- ___(sisters_other, strata = age)
+
+glimpse(sisters_val)
diff --git a/exercises/exc_04_08.R b/exercises/exc_04_08.R
deleted file mode 100644
index ae2a766..0000000
--- a/exercises/exc_04_08.R
+++ /dev/null
@@ -1,21 +0,0 @@
-library(tidyverse)
-library(rsample)
-sisters_select <- read_csv("data/sisters.csv") %>%
-    select(-sister)
-
-# Split the data into training and validation/test sets
-train_split <- sisters_select %>%
-    ___(prop = 0.6,
-                  strata = "age")
-
-sisters_train <- training(___)
-validate_test <- testing(___)
-
-# Split the validation and test sets
-set.seed(1234)
-validation_split <- validate_test %>%
-    ___(prop = 0.5,
-                  strata = "age")
-
-sisters_validate <- training(___)
-sisters_test <- testing(___)
diff --git a/exercises/exc_04_10_1.R b/exercises/exc_04_10_1.R
new file mode 100644
index 0000000..3509726
--- /dev/null
+++ b/exercises/exc_04_10_1.R
@@ -0,0 +1,9 @@
+library(tidymodels)
+
+sisters_other <- readRDS("data/c4_other.rds")
+
+sisters_recipe <- recipe(age ~ ., data = sisters_other) %>% 
+    ___(all_predictors()) %>%
+    ___(all_predictors(), num_comp = ___)
+
+sisters_recipe
diff --git a/exercises/exc_04_10_2.R b/exercises/exc_04_10_2.R
new file mode 100644
index 0000000..51b1488
--- /dev/null
+++ b/exercises/exc_04_10_2.R
@@ -0,0 +1,10 @@
+library(tidymodels)
+
+tree_spec <- ___(
+    ___ = tune(),
+    ___ = tune()
+) %>% 
+    set_engine("rpart") %>% 
+    set_mode("regression")
+
+tree_spec
diff --git a/exercises/exc_04_10_3.R b/exercises/exc_04_10_3.R
new file mode 100644
index 0000000..75d2d2f
--- /dev/null
+++ b/exercises/exc_04_10_3.R
@@ -0,0 +1,20 @@
+library(tidymodels)
+
+sisters_other <- readRDS("data/c4_other.rds")
+
+sisters_recipe <- recipe(age ~ ., data = sisters_other) %>% 
+    step_normalize(all_predictors()) %>%
+    step_pca(all_predictors(), num_comp = tune())
+
+tree_spec <- decision_tree(
+    cost_complexity = tune(),
+    tree_depth = tune()
+) %>% 
+    set_engine("rpart") %>% 
+    set_mode("regression")
+
+tree_wf <- ___ %>%
+    ___(sisters_recipe) %>%
+    ___(tree_spec)
+
+tree_wf
diff --git a/exercises/exc_04_11.R b/exercises/exc_04_11.R
index 3ba7b3a..459fd80 100644
--- a/exercises/exc_04_11.R
+++ b/exercises/exc_04_11.R
@@ -1,11 +1,8 @@
-library(tidyverse)
-sisters_train <- readRDS("data/c4_training_500.rds")
-
-# Load caret
-library(caret)
-
-# Fit a CART model
-sisters_cart <- ___(___, method = ___, data = ___)
-
-# Print the CART model
-sisters_cart
+library(tidymodels)
+
+tree_grid <- ___(num_comp(c(3, 12)),
+                          cost_complexity(),
+                          ___,
+                          levels = 5)
+
+glimpse(tree_grid)
diff --git a/exercises/exc_04_12.R b/exercises/exc_04_12.R
index 0793eae..482945a 100644
--- a/exercises/exc_04_12.R
+++ b/exercises/exc_04_12.R
@@ -1,18 +1,32 @@
-library(tidyverse)
-library(caret)
+library(tidymodels)
 
-sisters_validate <- readRDS("data/c4_validation_full.rds")
-sisters_test <- readRDS("data/c4_testing_full.rds")
-sisters_cart <- readRDS("data/sisters_cart.rds")
-sisters_gbm <- readRDS("data/sisters_gbm.rds")
-sisters_xgb <- readRDS("data/sisters_xg.rds")
+sisters_other <- readRDS("data/c4_other.rds")
+sisters_val <- readRDS("data/c4_val.rds")
 
-# Make predictions on the three models
-modeling_results <- sisters_validate %>%
-    mutate(CART = predict(sisters_cart, ___),
-           GBM = predict(sisters_gbm, ___),
-           XGB = predict(sisters_xgb, ___))
+sisters_recipe <- recipe(age ~ ., data = sisters_other) %>% 
+    step_normalize(all_predictors()) %>%
+    step_pca(all_predictors(), num_comp = tune())
 
-# View the predictions
-modeling_results %>% 
-    select(CART, GBM, XGB)
+tree_spec <- decision_tree(
+    cost_complexity = tune(),
+    tree_depth = tune()
+) %>% 
+    set_engine("rpart") %>% 
+    set_mode("regression")
+
+tree_wf <- workflow() %>%
+    add_recipe(sisters_recipe) %>%
+    add_model(tree_spec)
+
+tree_grid <- grid_regular(num_comp(c(3, 12)),
+                          cost_complexity(),
+                          tree_depth(),
+                          levels = 2)
+set.seed(123)
+tree_res <- ___(
+    ___,
+    resamples = sisters_val,
+    grid = ___
+)
+
+glimpse(tree_res)
diff --git a/exercises/exc_04_13.R b/exercises/exc_04_13.R
index e8a899b..c46d225 100644
--- a/exercises/exc_04_13.R
+++ b/exercises/exc_04_13.R
@@ -1,16 +1,19 @@
 library(tidyverse)
-library(caret)
+library(tidymodels)
 
-modeling_results <- readRDS("data/c4_modeling_results.rds")
+tree_res <- readRDS("data/c4_tree_res.rds")
 
-# Load yardstick
-___
+tree_metrics <- tree_res %>%
+    ___ 
 
-# Compare performance for...
+glimpse(tree_metrics)
 
-# ...CART model
-metrics(modeling_results, truth = ___, estimate = ___)
-# ...gbm model
-metrics(modeling_results, truth = ___, estimate = ___)
-# ...xgboost model
-___(modeling_results, truth = ___, estimate = ___)
+tree_metrics %>%
+    mutate(tree_depth = factor(tree_depth),
+           num_comp = paste("num_comp =", num_comp),
+           num_comp = fct_inorder(num_comp)) %>%
+    ggplot(aes(___, mean, color = ___)) +
+    geom_line(size = 1.5, alpha = 0.6) +
+    geom_point(size = 2) +
+    scale_x_log10() +
+    facet_grid(.metric ~ num_comp, scales = "free")
diff --git a/exercises/exc_04_14.R b/exercises/exc_04_14.R
index 6c5d85e..7ac7b2f 100644
--- a/exercises/exc_04_14.R
+++ b/exercises/exc_04_14.R
@@ -1,13 +1,34 @@
 library(tidyverse)
-library(caret)
-library(yardstick)
-
-sisters_train <- readRDS("data/c4_training_500.rds")
-sisters_validate <- readRDS("data/c4_validation_full.rds")
-sisters_test <- readRDS("data/c4_testing_full.rds")
-sisters_xgb <- readRDS("data/sisters_xg.rds")
-
-# Calculate RMSE
-___ %>%
-    mutate(prediction = predict(sisters_xgb, ___)) %>%
-    ___(truth = age, estimate = prediction)
+library(tidymodels)
+
+tree_res <- readRDS("data/c4_tree_res.rds")
+sisters_other <- readRDS("data/c4_other.rds")
+
+sisters_recipe <- recipe(age ~ ., data = sisters_other) %>% 
+    step_normalize(all_predictors()) %>%
+    step_pca(all_predictors(), num_comp = tune())
+
+tree_spec <- decision_tree(
+    cost_complexity = tune(),
+    tree_depth = tune()
+) %>% 
+    set_engine("rpart") %>% 
+    set_mode("regression")
+
+tree_wf <- workflow() %>%
+    add_recipe(sisters_recipe) %>%
+    add_model(tree_spec)
+
+tree_wf
+
+
+best_tree <- tree_res %>%
+    ___("rmse")
+
+best_tree
+
+final_wf <- tree_wf %>% 
+    ___(best_tree)
+
+final_wf
+
diff --git a/exercises/exc_04_15.R b/exercises/exc_04_15.R
new file mode 100644
index 0000000..38e9344
--- /dev/null
+++ b/exercises/exc_04_15.R
@@ -0,0 +1,15 @@
+library(tidyverse)
+library(tidymodels)
+
+sisters_select <- read_csv("data/sisters.csv") %>%
+    select(-sister)
+final_wf <- readRDS("data/c4_final_wf.rds")
+
+set.seed(123)
+sisters_split <- initial_split(sisters_select, strata = age)
+
+final_tree <- final_wf %>%
+    ___(sisters_split) 
+
+final_tree %>%
+    ___
diff --git a/exercises/solution_01_06.R b/exercises/solution_01_06.R
index cb88967..530bdd8 100644
--- a/exercises/solution_01_06.R
+++ b/exercises/solution_01_06.R
@@ -1,13 +1,15 @@
-library(tidyverse)
-car_vars <- readRDS("data/c1_cars_vars_full.rds")
-
-# Load rsample
-library(rsample)
-
-# Split the data into training and test sets
-set.seed(1234)
-car_split <- car_vars %>%
-    initial_split(prop = 0.8, strata = "Transmission")
-
-car_train <- training(car_split)
-car_test <- testing(car_split)
+car_vars <- readRDS("data/c1_car_vars.rds")
+
+# Load tidymodels
+library(tidymodels)
+
+# Split the data into training and test sets
+set.seed(1234)
+car_split <- car_vars %>%
+    initial_split(prop = 0.8, strata = Transmission)
+
+car_train <- training(car_split)
+car_test <- testing(car_split)
+
+glimpse(car_train)
+glimpse(car_test)
diff --git a/exercises/solution_01_07_1.R b/exercises/solution_01_07_1.R
index c37e7e9..cdbff33 100644
--- a/exercises/solution_01_07_1.R
+++ b/exercises/solution_01_07_1.R
@@ -1,16 +1,17 @@
-library(tidyverse)
+car_train <- readRDS("data/c1_train.rds")
+car_test <- readRDS("data/c1_test.rds")
 
-car_train <- readRDS("data/c1_training_full.rds")
-car_test <- readRDS("data/c1_testing_full.rds")
+# Load tidymodels
+library(tidymodels)
 
-# Load caret
-library(caret)
+# Build a linear regression model specification
+lm_mod <- linear_reg() %>%
+    set_engine("lm")
 
 # Train a linear regression model
-fit_lm <- train(log(MPG) ~ ., 
-                method = "lm", 
-                data = car_train,
-                trControl = trainControl(method = "none"))
+fit_lm <- lm_mod %>%
+    fit(log(MPG) ~ ., 
+        data = car_train)
 
 # Print the model object
 fit_lm
diff --git a/exercises/solution_01_07_2.R b/exercises/solution_01_07_2.R
index 3506eed..a198856 100644
--- a/exercises/solution_01_07_2.R
+++ b/exercises/solution_01_07_2.R
@@ -1,14 +1,17 @@
-library(tidyverse)
-library(caret)
-
-car_train <- readRDS("data/c1_training_full.rds")
-car_test <- readRDS("data/c1_testing_full.rds")
-
-# Train a random forest model
-fit_rf <- train(log(MPG) ~ ., 
-                method = "rf", 
-                data = car_train,
-                trControl = trainControl(method = "none"))
-
-# Print the model object
-fit_rf
+library(tidymodels)
+
+car_train <- readRDS("data/c1_train.rds")
+car_test <- readRDS("data/c1_test.rds")
+
+# Build a random forest model specification
+rf_mod <- rand_forest() %>%
+    set_engine("randomForest") %>%
+    set_mode("regression")
+
+# Train a random forest model
+fit_rf <- rf_mod %>%
+    fit(log(MPG) ~ ., 
+        data = car_train)
+
+# Print the model object
+fit_rf
diff --git a/exercises/solution_01_08.R b/exercises/solution_01_08.R
index 6e55f20..09b8fbf 100644
--- a/exercises/solution_01_08.R
+++ b/exercises/solution_01_08.R
@@ -1,19 +1,19 @@
-library(caret)
-library(tidyverse)
-
-car_train <- readRDS("data/c1_training_full.rds")
+library(randomForest)
+car_train <- readRDS("data/c1_train.rds")
 fit_lm <- readRDS("data/c1_fit_lm.rds")
 fit_rf <- readRDS("data/c1_fit_rf.rds")
 
-# Load yardstick
-library(yardstick)
+# Load tidymodels
+library(tidymodels)
 
 # Create the new columns
 results <- car_train %>%
-    mutate(MPG = log(MPG),
-           `Linear regression` = predict(fit_lm, car_train),
-           `Random forest` = predict(fit_rf, car_train))
+    mutate(MPG = log(MPG)) %>%
+    bind_cols(predict(fit_lm, car_train) %>%
+                  rename(.pred_lm = .pred)) %>%
+    bind_cols(predict(fit_rf, car_train) %>%
+                  rename(.pred_rf = .pred))
 
 # Evaluate the performance
-metrics(results, truth = MPG, estimate = `Linear regression`)
-metrics(results, truth = MPG, estimate = `Random forest`)
+metrics(results, truth = MPG, estimate = .pred_lm)
+metrics(results, truth = MPG, estimate = .pred_rf)
diff --git a/exercises/solution_01_09.R b/exercises/solution_01_09.R
index cba929b..dd3f80b 100644
--- a/exercises/solution_01_09.R
+++ b/exercises/solution_01_09.R
@@ -1,17 +1,18 @@
-library(caret)
-library(tidyverse)
-library(yardstick)
+library(tidymodels)
+library(randomForest)
 
-car_test <- readRDS("data/c1_testing_full.rds")
+car_test <- readRDS("data/c1_test.rds")
 fit_lm <- readRDS("data/c1_fit_lm.rds")
 fit_rf <- readRDS("data/c1_fit_rf.rds")
 
 # Create the new columns
 results <- car_test %>%
-    mutate(MPG = log(MPG),
-           `Linear regression` = predict(fit_lm, car_test),
-           `Random forest` = predict(fit_rf, car_test))
+    mutate(MPG = log(MPG)) %>%
+    bind_cols(predict(fit_lm, car_test) %>%
+                  rename(.pred_lm = .pred)) %>%
+    bind_cols(predict(fit_rf, car_test) %>%
+                  rename(.pred_rf = .pred))
 
 # Evaluate the performance
-metrics(results, truth = MPG, estimate = `Linear regression`)
-metrics(results, truth = MPG, estimate = `Random forest`)
+metrics(results, truth = MPG, estimate = .pred_lm)
+metrics(results, truth = MPG, estimate = .pred_rf)
diff --git a/exercises/solution_01_11.R b/exercises/solution_01_11.R
index f2383b3..a103d98 100644
--- a/exercises/solution_01_11.R
+++ b/exercises/solution_01_11.R
@@ -1,19 +1,30 @@
-library(caret)
-library(tidyverse)
-
-car_train <- readRDS("data/c1_training_one_percent.rds")
-
-# Fit the models with bootstrap resampling
-cars_lm_bt <- train(log(MPG) ~ ., 
-                    method = "lm", 
-                    data = car_train,
-                    trControl = trainControl(method = "boot"))
-
-cars_rf_bt <- train(log(MPG) ~ ., 
-                    method = "rf", 
-                    data = car_train,
-                    trControl = trainControl(method = "boot"))
-
-# Quick look at the models
-cars_lm_bt
-cars_rf_bt
+library(tidymodels)
+
+car_train <- readRDS("data/c1_train_10_percent.rds")
+
+lm_mod <- linear_reg() %>%
+    set_engine("lm")
+
+rf_mod <- rand_forest() %>%
+    set_engine("randomForest") %>%
+    set_mode("regression")
+
+## Create bootstrap resamples
+car_boot <- bootstraps(car_train)
+
+# Evaluate the models with bootstrap resampling
+lm_res <- lm_mod %>%
+    fit_resamples(
+        log(MPG) ~ .,
+        resamples = car_boot,
+        control = control_resamples(save_pred = TRUE)
+    )
+
+rf_res <- rf_mod %>%
+    fit_resamples(
+        log(MPG) ~ .,
+        resamples = car_boot,
+        control = control_resamples(save_pred = TRUE)
+    )
+
+glimpse(rf_res)
diff --git a/exercises/solution_01_12_1.R b/exercises/solution_01_12_1.R
index c20a1a9..2a43cf6 100644
--- a/exercises/solution_01_12_1.R
+++ b/exercises/solution_01_12_1.R
@@ -1,15 +1,13 @@
-library(caret)
-library(tidyverse)
-library(yardstick)
+library(tidymodels)
 
-car_test <- readRDS("data/c1_testing_full.rds")
-cars_lm_bt <- readRDS("data/cars_lm_bt.rds")
-cars_rf_bt <- readRDS("data/cars_rf_bt.rds")
+lm_res <- readRDS("data/c1_lm_res.rds")
+rf_res <- readRDS("data/c1_rf_res.rds")
 
-results <- car_test %>%
-    mutate(MPG = log(MPG),
-           `Linear regression` = predict(cars_lm_bt, car_test),
-           `Random forest` = predict(cars_rf_bt, car_test))
+results <-  bind_rows(lm_res %>%
+                          collect_predictions() %>%
+                          mutate(model = "lm"),
+                      rf_res %>%
+                          collect_predictions() %>%
+                          mutate(model = "rf"))
 
-metrics(results, truth = MPG, estimate = `Linear regression`)
-metrics(results, truth = MPG, estimate = `Random forest`)
\ No newline at end of file
+glimpse(results)
diff --git a/exercises/solution_01_12_2.R b/exercises/solution_01_12_2.R
index da60557..94ce4d5 100644
--- a/exercises/solution_01_12_2.R
+++ b/exercises/solution_01_12_2.R
@@ -1,20 +1,19 @@
-library(caret)
 library(tidyverse)
-library(yardstick)
+library(tidymodels)
 
-car_test <- readRDS("data/c1_testing_full.rds")
-cars_lm_bt <- readRDS("data/cars_lm_bt.rds")
-cars_rf_bt <- readRDS("data/cars_rf_bt.rds")
+lm_res <- readRDS("data/c1_lm_res.rds")
+rf_res <- readRDS("data/c1_rf_res.rds")
 
-results <- car_test %>%
-    mutate(MPG = log(MPG),
-           `Linear regression` = predict(cars_lm_bt, car_test),
-           `Random forest` = predict(cars_rf_bt, car_test))
+results <-  bind_rows(lm_res %>%
+                          collect_predictions() %>%
+                          mutate(model = "lm"),
+                      rf_res %>%
+                          collect_predictions() %>%
+                          mutate(model = "rf"))
 
 results %>%
-    gather(Method, Result, `Linear regression`:`Random forest`) %>%
-    ggplot(aes(log(MPG), Result, color = Method)) +
-    geom_point(size = 1.5, alpha = 0.5) +
-    facet_wrap(~Method) +
+    ggplot(aes(`log(MPG)`, .pred)) +
     geom_abline(lty = 2, color = "gray50") +
-    geom_smooth(method = "lm")
+    geom_point(aes(color = id), size = 1.5, alpha = 0.3, show.legend = FALSE) +
+    geom_smooth(method = "lm") +
+    facet_wrap(~ model)
diff --git a/exercises/solution_02_03_1.R b/exercises/solution_02_03_1.R
index c546772..8c24662 100644
--- a/exercises/solution_02_03_1.R
+++ b/exercises/solution_02_03_1.R
@@ -1,13 +1,13 @@
 library(tidyverse)
-stackoverflow <- read_csv("data/stackoverflow.csv")
+stack_overflow <- read_csv("data/stack_overflow.csv")
 
-# Print stackoverflow
-glimpse(stackoverflow)
+# Take a look at stack_overflow
+glimpse(stack_overflow)
 
-# First count for Remote
-stackoverflow %>% 
-    count(Remote, sort = TRUE)
+# First count for `remote`
+stack_overflow %>% 
+    count(remote, sort = TRUE)
 
-# then count for Country
-stackoverflow %>% 
-    count(Country, sort = TRUE)
+# then count for `country`
+stack_overflow %>% 
+    count(country, sort = TRUE)
diff --git a/exercises/solution_02_03_2.R b/exercises/solution_02_03_2.R
index f0eeec6..d7de2ba 100644
--- a/exercises/solution_02_03_2.R
+++ b/exercises/solution_02_03_2.R
@@ -1,7 +1,7 @@
-library(tidyverse)
-stackoverflow <- read_csv("data/stackoverflow.csv")
-
-ggplot(stackoverflow, aes(Remote, YearsCodedJob)) +
-    geom_boxplot() +
-    labs(x = NULL,
-         y = "Years of professional coding experience")
+library(tidyverse)
+stack_overflow <- read_csv("data/stack_overflow.csv")
+
+ggplot(stack_overflow, aes(remote, years_coded_job)) +
+    geom_boxplot() +
+    labs(x = NULL,
+         y = "Years of professional coding experience")
diff --git a/exercises/solution_02_04.R b/exercises/solution_02_04.R
index 4810810..98cbc2d 100644
--- a/exercises/solution_02_04.R
+++ b/exercises/solution_02_04.R
@@ -1,13 +1,23 @@
-library(tidyverse)
-stackoverflow <- read_csv("data/stackoverflow.csv") %>%
-    mutate(Remote = factor(Remote, levels = c("Remote", "Not remote")))
-
-# Build a simple logistic regression model
-simple_glm <- stackoverflow %>%
-        select(-Respondent) %>%
-        glm(Remote ~ .,
-            family = "binomial",
-            data = .)
-
-# Print the summary of the model
-summary(simple_glm)
+library(tidyverse)
+stack_overflow <- read_csv("data/stack_overflow.csv") %>%
+    mutate(remote = factor(remote, levels = c("Remote", "Not remote"))) %>%
+    mutate_if(is.character, factor)
+
+# Load tidymodels
+library(tidymodels)
+
+# Create stack_select dataset
+stack_select <- stack_overflow %>%
+    select(-respondent)
+
+# Split the data into training and testing sets
+set.seed(1234)
+stack_split <- stack_select %>%
+    initial_split(p = 0.8,
+                  strata = remote)
+
+stack_train <- training(stack_split)
+stack_test <- testing(stack_split)
+
+glimpse(stack_train)
+glimpse(stack_test)
diff --git a/exercises/solution_02_06.R b/exercises/solution_02_06.R
index f6eb60d..3cfce5e 100644
--- a/exercises/solution_02_06.R
+++ b/exercises/solution_02_06.R
@@ -1,19 +1,8 @@
-library(tidyverse)
-stackoverflow <- read_csv("data/stackoverflow.csv") %>%
-    mutate(Remote = factor(Remote, levels = c("Remote", "Not remote")))
+library(tidymodels)
 
-# Load rsample
-library(rsample)
+stack_train <- readRDS("data/c2_train.rds")
 
-# Create stack_select dataset
-stack_select <- stackoverflow %>%
-    select(-Respondent)
+stack_recipe <- recipe(remote ~ ., data = stack_train) %>% 
+    step_downsample(remote)
 
-# Split the data into training and testing sets
-set.seed(1234)
-stack_split <- stack_select %>%
-    initial_split(p = 0.8,
-                  strata = "Remote")
-
-stack_train <- training(stack_split)
-stack_test <- testing(stack_split)
+stack_recipe
diff --git a/exercises/solution_02_07.R b/exercises/solution_02_07.R
index 794f226..1469f95 100644
--- a/exercises/solution_02_07.R
+++ b/exercises/solution_02_07.R
@@ -1,15 +1,12 @@
-library(tidyverse)
-library(caret)
-
-stack_train <- readRDS("data/c2_training_full.rds")
-stack_test <- readRDS("data/c2_testing_full.rds")
-
-# Create the upsampled training set
-up_train <- upSample(x = select(stack_train, -Remote),
-                     y = stack_train$Remote,
-                     yname = "Remote") %>%
-    as_tibble()
-
-# Count the number of each type of Remote employee
-up_train %>%
-    count(Remote)
+library(tidymodels)
+
+stack_train <- readRDS("data/c2_train.rds")
+
+stack_recipe <- recipe(remote ~ ., data = stack_train) %>% 
+    step_downsample(remote)
+
+stack_prep <- prep(stack_recipe)
+stack_down <- juice(stack_prep)
+
+stack_down %>%
+    count(remote)
diff --git a/exercises/solution_02_11_1.R b/exercises/solution_02_11_1.R
index ac8f022..d6b435f 100644
--- a/exercises/solution_02_11_1.R
+++ b/exercises/solution_02_11_1.R
@@ -1,13 +1,22 @@
-library(tidyverse)
-library(caret)
+library(tidymodels)
 
-stack_train <- readRDS("data/c2_training_one_percent.rds")
+stack_train <- readRDS("data/c2_train.rds")
 
-# Build a logistic regression model
-stack_glm <- train(Remote ~ ., method = "glm", family = "binomial",
-                   data = stack_train,
-                   trControl = trainControl(method = "boot",
-                                            sampling = "up"))
+stack_recipe <- recipe(remote ~ ., data = stack_train) %>% 
+    step_downsample(remote)
 
-# Print the model object
-stack_glm
\ No newline at end of file
+## Build a logistic regression model
+glm_spec <- logistic_reg() %>%
+    set_engine("glm")
+
+## Start a workflow (recipe only)
+stack_wf <- workflow() %>%
+    add_recipe(stack_recipe)
+
+## Add the model and fit the workflow
+stack_glm <- stack_wf %>%
+    add_model(glm_spec) %>%
+    fit(data = stack_train)
+
+# Print the fitted model
+stack_glm
diff --git a/exercises/solution_02_11_2.R b/exercises/solution_02_11_2.R
index 690246e..c8525cb 100644
--- a/exercises/solution_02_11_2.R
+++ b/exercises/solution_02_11_2.R
@@ -1,14 +1,23 @@
-library(tidyverse)
-library(caret)
+library(tidymodels)
 
-stack_train <- readRDS("data/c2_training_one_percent.rds")
+stack_train <- readRDS("data/c2_train.rds")
 
-# Build a random forest model
-stack_rf <- train(Remote ~ ., method = "rf", 
-                  data = stack_train,
-                  trControl = trainControl(method = "boot",
-                                           sampling = "up"))
+stack_recipe <- recipe(remote ~ ., data = stack_train) %>% 
+    step_downsample(remote)
 
-# Print the model object
-stack_rf
+## Build a decision tree model
+tree_spec <- decision_tree() %>%         
+    set_engine("rpart") %>%      
+    set_mode("classification") 
 
+## Start a workflow (recipe only)
+stack_wf <- workflow() %>%
+    add_recipe(stack_recipe)
+
+## Add the model and fit the workflow
+stack_tree <- stack_wf %>%
+    add_model(tree_spec) %>%
+    fit(data = stack_train)
+
+# Print the fitted model
+stack_tree
diff --git a/exercises/solution_02_12_1.R b/exercises/solution_02_12_1.R
index 0a0fd9b..968950a 100644
--- a/exercises/solution_02_12_1.R
+++ b/exercises/solution_02_12_1.R
@@ -1,13 +1,14 @@
-library(caret)
-library(tidyverse)
-library(yardstick)
-
-stack_train <- readRDS("data/c2_training_full.rds")
-stack_test <- readRDS("data/c2_testing_full.rds")
-stack_glm <- readRDS("data/stack_glm.rds")
-stack_rf <- readRDS("data/stack_rf.rds")
-
-# Confusion matrix for logistic regression model
-stack_test %>%
-    mutate(`Logistic regression` = predict(stack_glm, stack_test)) %>%
-    conf_mat(truth = Remote, estimate = "Logistic regression")
+library(tidymodels)
+
+stack_train <- readRDS("data/c2_train.rds")
+stack_test <- readRDS("data/c2_test.rds")
+stack_glm <- readRDS("data/stack_glm.rds")
+stack_tree <- readRDS("data/stack_tree.rds")
+
+results <- stack_test %>%
+    bind_cols(predict(stack_glm, stack_test) %>%
+                  rename(.pred_glm = .pred_class))
+
+# Confusion matrix for logistic regression model
+results %>%
+    conf_mat(truth = remote, estimate = .pred_glm)
diff --git a/exercises/solution_02_12_2.R b/exercises/solution_02_12_2.R
index 667960f..2bf723d 100644
--- a/exercises/solution_02_12_2.R
+++ b/exercises/solution_02_12_2.R
@@ -1,13 +1,14 @@
-library(caret)
-library(tidyverse)
-library(yardstick)
-
-stack_train <- readRDS("data/c2_training_full.rds")
-stack_test <- readRDS("data/c2_testing_full.rds")
-stack_glm <- readRDS("data/stack_glm.rds")
-stack_rf <- readRDS("data/stack_rf.rds")
-
-# Confusion matrix for random forest model
-stack_test %>%
-    mutate(`Random forest` = predict(stack_rf, stack_test)) %>%
-    conf_mat(truth = Remote, estimate = "Random forest")
+library(tidymodels)
+
+stack_train <- readRDS("data/c2_train.rds")
+stack_test <- readRDS("data/c2_test.rds")
+stack_glm <- readRDS("data/stack_glm.rds")
+stack_tree <- readRDS("data/stack_tree.rds")
+
+results <- stack_test %>%
+    bind_cols(predict(stack_tree, stack_test) %>%
+                  rename(.pred_tree = .pred_class))
+
+# Confusion matrix for decision tree model
+results %>%
+    conf_mat(truth = remote, estimate = .pred_tree)
diff --git a/exercises/solution_02_13.R b/exercises/solution_02_13.R
index f3b5c31..8389a40 100644
--- a/exercises/solution_02_13.R
+++ b/exercises/solution_02_13.R
@@ -1,22 +1,20 @@
-library(tidyverse)
-library(caret)
+library(tidymodels)
 
-stack_test <- readRDS("data/c2_testing_full.rds")
+stack_train <- readRDS("data/c2_train.rds")
+stack_test <- readRDS("data/c2_test.rds")
 stack_glm <- readRDS("data/stack_glm.rds")
-stack_rf <- readRDS("data/stack_rf.rds")
+stack_tree <- readRDS("data/stack_tree.rds")
 
-# Load yardstick
-library(yardstick)
-
-# Predict values
-testing_results <- stack_test %>%
-    mutate(`Logistic regression` = predict(stack_glm, stack_test),
-           `Random forest` = predict(stack_rf, stack_test))
+results <- stack_test %>%
+    bind_cols(predict(stack_glm, stack_test) %>%
+                  rename(.pred_glm = .pred_class)) %>%
+    bind_cols(predict(stack_tree, stack_test) %>%
+                  rename(.pred_tree = .pred_class))
 
 ## Calculate accuracy
-accuracy(testing_results, truth = Remote, estimate = `Logistic regression`)
-accuracy(testing_results, truth = Remote, estimate = `Random forest`)
+accuracy(results, truth = remote, estimate = .pred_glm)
+accuracy(results, truth = remote, estimate = .pred_tree)
 
 ## Calculate positive predict value
-ppv(testing_results, truth = Remote, estimate = `Logistic regression`)
-ppv(testing_results, truth = Remote, estimate = `Random forest`)
\ No newline at end of file
+ppv(results, truth = remote, estimate = .pred_glm)
+ppv(results, truth = remote, estimate = .pred_tree)
diff --git a/exercises/solution_03_03_1.R b/exercises/solution_03_03_1.R
index 618358e..686cf06 100644
--- a/exercises/solution_03_03_1.R
+++ b/exercises/solution_03_03_1.R
@@ -3,7 +3,7 @@ library(tidyverse)
 
 voters <- read_csv("data/voters.csv")
 
-# Print voters
+# Take a look at voters
 glimpse(voters)
 
 # How many people voted?
diff --git a/exercises/solution_03_03_2.R b/exercises/solution_03_03_2.R
index bd16cd3..3059907 100644
--- a/exercises/solution_03_03_2.R
+++ b/exercises/solution_03_03_2.R
@@ -1,9 +1,9 @@
-library(tidyverse)
-voters <- read_csv("data/voters.csv")
-
-# How do the reponses on the survey vary with voting behavior?
-voters %>%
-    group_by(turnout16_2016) %>%
-    summarise(`Elections don't matter` = mean(RIGGED_SYSTEM_1_2016 <= 2),
-              `Economy is getting better` = mean(econtrend_2016 == 1),
+library(tidyverse)
+voters <- read_csv("data/voters.csv")
+
+# How do the responses on the survey vary with voting behavior?
+voters %>%
+    group_by(turnout16_2016) %>%
+    summarise(`Elections don't matter` = mean(RIGGED_SYSTEM_1_2016 <= 2),
+              `Economy is getting better` = mean(econtrend_2016 == 1),
               `Crime is very important` = mean(imiss_a_2016 == 2))
\ No newline at end of file
diff --git a/exercises/solution_03_04.R b/exercises/solution_03_04.R
index 1f74cd7..59d75ce 100644
--- a/exercises/solution_03_04.R
+++ b/exercises/solution_03_04.R
@@ -1,9 +1,9 @@
-library(tidyverse)
-voters <- read_csv("data/voters.csv") %>%
-    mutate(turnout16_2016 = factor(turnout16_2016))
-
-## Visualize difference by voter turnout
-voters %>%
-    ggplot(aes(econtrend_2016, ..density.., fill = turnout16_2016)) +
-    geom_histogram(alpha = 0.5, position = "identity", binwidth = 1) +
+library(tidyverse)
+voters <- read_csv("data/voters.csv") %>%
+    mutate(turnout16_2016 = factor(turnout16_2016))
+
+## Visualize difference by voter turnout
+voters %>%
+    ggplot(aes(econtrend_2016, after_stat(density), fill = turnout16_2016)) +
+    geom_histogram(alpha = 0.5, position = "identity", binwidth = 1) +
     labs(title = "Overall, is the economy getting better or worse?")
\ No newline at end of file
diff --git a/exercises/solution_03_06.R b/exercises/solution_03_06.R
index 66a24d5..4d1b1f7 100644
--- a/exercises/solution_03_06.R
+++ b/exercises/solution_03_06.R
@@ -1,14 +1,18 @@
-library(tidyverse)
-voters <- read_csv("data/voters.csv") %>%
-    mutate(turnout16_2016 = factor(turnout16_2016))
-
-# Remove the case_indetifier column
-voters_select <- voters %>%
-        select(-case_identifier)
-
-# Build a simple logistic regression model
-simple_glm <- glm(turnout16_2016 ~ .,  family = "binomial", 
-                  data = voters_select)
-
-# Print the summary                  
-summary(simple_glm)
\ No newline at end of file
+library(tidyverse)
+voters_select <- read_csv("data/voters.csv") %>%
+    mutate(turnout16_2016 = factor(turnout16_2016)) %>% 
+    select(-case_identifier)
+
+# Load tidymodels
+library(tidymodels)
+
+# Split data into training and testing sets
+set.seed(1234)
+vote_split <- voters_select %>%
+    initial_split(p = 0.8,
+                  strata = turnout16_2016)
+vote_train <- training(vote_split)
+vote_test <- testing(vote_split)
+
+glimpse(vote_train)
+glimpse(vote_test)
diff --git a/exercises/solution_03_08.R b/exercises/solution_03_08.R
index 71586fa..3635c7c 100644
--- a/exercises/solution_03_08.R
+++ b/exercises/solution_03_08.R
@@ -1,15 +1,8 @@
-library(tidyverse)
-voters_select <- read_csv("data/voters.csv") %>%
-    mutate(turnout16_2016 = factor(turnout16_2016)) %>% 
-    select(-case_identifier)
-
-# Load caret
-library(rsample)
-
-# Split data into training and testing sets
-set.seed(1234)
-vote_split <- voters_select %>%
-    initial_split(p = 0.8,
-                  strata = "turnout16_2016")
-vote_train <- training(vote_split)
-vote_test <- testing(vote_split)
+library(tidymodels)
+
+vote_train <- readRDS("data/c3_train.rds")
+
+vote_recipe <- recipe(turnout16_2016 ~ ., data = vote_train) %>% 
+    step_upsample(turnout16_2016)
+
+vote_recipe
diff --git a/exercises/solution_03_09.R b/exercises/solution_03_09.R
index e6fbd88..28dd42e 100644
--- a/exercises/solution_03_09.R
+++ b/exercises/solution_03_09.R
@@ -1,11 +1,18 @@
-library(tidyverse)
-library(caret)
-
-vote_train <- readRDS("data/c3_training_full.rds")
-
-# Perform logistic regression with upsampling and no resampling
-vote_glm <- train(turnout16_2016 ~ ., 
-                  method = "glm", family = "binomial",
-                  data = vote_train,
-                  trControl = trainControl(method = "none",
-                                           sampling = "up"))
\ No newline at end of file
+library(tidymodels)
+
+vote_train <- readRDS("data/c3_train.rds")
+
+vote_recipe <- recipe(turnout16_2016 ~ ., data = vote_train) %>% 
+    step_upsample(turnout16_2016)
+
+## Specify a ranger model
+rf_spec <- rand_forest() %>%
+    set_engine("ranger") %>%
+    set_mode("classification")
+
+## Add the recipe + model to a workflow
+vote_wf <- workflow() %>%
+    add_recipe(vote_recipe) %>%
+    add_model(rf_spec)
+
+vote_wf
diff --git a/exercises/solution_03_12.R b/exercises/solution_03_12.R
new file mode 100644
index 0000000..493868d
--- /dev/null
+++ b/exercises/solution_03_12.R
@@ -0,0 +1,7 @@
+library(tidymodels)
+
+vote_train <- readRDS("data/c3_train.rds")
+
+vote_folds <- vfold_cv(vote_train, v = 10, repeats = 5)
+
+glimpse(vote_folds)
diff --git a/exercises/solution_03_12_1.R b/exercises/solution_03_12_1.R
deleted file mode 100644
index e372a34..0000000
--- a/exercises/solution_03_12_1.R
+++ /dev/null
@@ -1,15 +0,0 @@
-library(tidyverse)
-library(caret)
-
-vote_train <- readRDS("data/c3_training_two_percent.rds")
-
-# Logistic regression
-vote_glm <- train(turnout16_2016 ~ ., 
-                  method = "glm", family = "binomial",
-                  data = vote_train,
-                  trControl = trainControl(method = "repeatedcv",
-                                           repeats = 2,
-                                           sampling = "up"))
-
-# Print vote_glm
-vote_glm
diff --git a/exercises/solution_03_12_2.R b/exercises/solution_03_12_2.R
deleted file mode 100644
index 7eea041..0000000
--- a/exercises/solution_03_12_2.R
+++ /dev/null
@@ -1,14 +0,0 @@
-library(tidyverse)
-library(caret)
-
-vote_train <- readRDS("data/c3_training_two_percent.rds")
-
-# Random forest
-vote_rf <- train(turnout16_2016 ~ ., method = "rf", 
-                 data = vote_train,
-                 trControl = trainControl(method = "repeatedcv",
-                                          repeats = 2,
-                                          sampling = "up"))
-
-# Print vote_rf
-vote_rf
diff --git a/exercises/solution_03_14_1.R b/exercises/solution_03_14_1.R
index 82a3909..434a6a8 100644
--- a/exercises/solution_03_14_1.R
+++ b/exercises/solution_03_14_1.R
@@ -1,13 +1,25 @@
-library(tidyverse)
-library(caret)
-library(yardstick)
-
-vote_train <- readRDS("data/c3_training_full.rds")
-vote_test <- readRDS("data/c3_testing_full.rds")
-vote_glm <- readRDS("data/vote_glm.rds")
-vote_rf <- readRDS("data/vote_rf.rds")
-
-# Confusion matrix for logistic regression model on training data
-vote_train %>%
-    mutate(`Logistic regression` = predict(vote_glm, vote_train)) %>%
-    conf_mat(truth = turnout16_2016, estimate = "Logistic regression")
+library(tidymodels)
+
+vote_train <- readRDS("data/c3_train_10_percent.rds")
+
+vote_folds <- vfold_cv(vote_train, v = 10)
+
+vote_recipe <- recipe(turnout16_2016 ~ ., data = vote_train) %>% 
+    step_upsample(turnout16_2016)
+
+glm_spec <- logistic_reg() %>%
+    set_engine("glm")
+
+vote_wf <- workflow() %>%
+    add_recipe(vote_recipe) %>%
+    add_model(glm_spec)
+
+set.seed(234)
+glm_res <- vote_wf %>%
+    fit_resamples(
+        vote_folds,
+        metrics = metric_set(roc_auc, sens, spec),
+        control = control_resamples(save_pred = TRUE)
+    )
+
+glimpse(glm_res)
diff --git a/exercises/solution_03_14_2.R b/exercises/solution_03_14_2.R
index 76cdaa2..63d74bb 100644
--- a/exercises/solution_03_14_2.R
+++ b/exercises/solution_03_14_2.R
@@ -1,13 +1,26 @@
-library(tidyverse)
-library(caret)
-library(yardstick)
-
-vote_train <- readRDS("data/c3_training_full.rds")
-vote_test <- readRDS("data/c3_testing_full.rds")
-vote_glm <- readRDS("data/vote_glm.rds")
-vote_rf <- readRDS("data/vote_rf.rds")
-
-# Confusion matrix for random forest model on training data
-vote_train %>%
-    mutate(`Random forest` = predict(vote_rf, vote_train)) %>%
-    conf_mat(truth = turnout16_2016, estimate = "Random forest")
+library(tidymodels)
+
+vote_train <- readRDS("data/c3_train_10_percent.rds")
+
+vote_folds <- vfold_cv(vote_train, v = 10)
+
+vote_recipe <- recipe(turnout16_2016 ~ ., data = vote_train) %>% 
+    step_upsample(turnout16_2016)
+
+rf_spec <- rand_forest() %>%
+    set_engine("ranger") %>%
+    set_mode("classification")
+
+vote_wf <- workflow() %>%
+    add_recipe(vote_recipe) %>%
+    add_model(rf_spec)
+
+set.seed(234)
+rf_res <- vote_wf %>%
+    fit_resamples(
+        vote_folds,
+        metrics = metric_set(roc_auc, sens, spec),
+        control = control_resamples(save_pred = TRUE)
+    )
+
+glimpse(rf_res)
diff --git a/exercises/solution_03_15.R b/exercises/solution_03_15.R
new file mode 100644
index 0000000..f333b5a
--- /dev/null
+++ b/exercises/solution_03_15.R
@@ -0,0 +1,7 @@
+library(tidymodels)
+
+glm_res <- readRDS("data/c3_glm_res.rds")
+rf_res <- readRDS("data/c3_rf_res.rds")
+
+collect_metrics(glm_res)
+collect_metrics(rf_res)
diff --git a/exercises/solution_03_15_1.R b/exercises/solution_03_15_1.R
deleted file mode 100644
index d08d02d..0000000
--- a/exercises/solution_03_15_1.R
+++ /dev/null
@@ -1,13 +0,0 @@
-library(tidyverse)
-library(caret)
-library(yardstick)
-
-vote_train <- readRDS("data/c3_training_full.rds")
-vote_test <- readRDS("data/c3_testing_full.rds")
-vote_glm <- readRDS("data/vote_glm.rds")
-vote_rf <- readRDS("data/vote_rf.rds")
-
-# Confusion matrix for logistic regression model on testing data
-vote_test %>%
-    mutate(`Logistic regression` = predict(vote_glm, vote_test)) %>%
-    conf_mat(truth = turnout16_2016, estimate = "Logistic regression")
diff --git a/exercises/solution_03_15_2.R b/exercises/solution_03_15_2.R
deleted file mode 100644
index 7763951..0000000
--- a/exercises/solution_03_15_2.R
+++ /dev/null
@@ -1,13 +0,0 @@
-library(tidyverse)
-library(caret)
-library(yardstick)
-
-vote_train <- readRDS("data/c3_training_full.rds")
-vote_test <- readRDS("data/c3_testing_full.rds")
-vote_glm <- readRDS("data/vote_glm.rds")
-vote_rf <- readRDS("data/vote_rf.rds")
-
-# Confusion matrix for random forest model on testing data
-vote_test %>%
-    mutate(`Random forest` = predict(vote_rf, vote_test)) %>%
-    conf_mat(truth = turnout16_2016, estimate = "Random forest")
diff --git a/exercises/solution_03_17.R b/exercises/solution_03_17.R
new file mode 100644
index 0000000..24f6a8c
--- /dev/null
+++ b/exercises/solution_03_17.R
@@ -0,0 +1,36 @@
+library(tidyverse)
+library(tidymodels)
+
+voters_select <- read_csv("data/voters.csv") %>%
+    mutate(turnout16_2016 = factor(turnout16_2016)) %>% 
+    select(-case_identifier)
+
+## Training / testing split
+set.seed(1234)
+vote_split <- voters_select %>%
+    initial_split(p = 0.8,
+                  strata = turnout16_2016)
+vote_train <- training(vote_split)
+vote_test <- testing(vote_split)
+
+## Preprocess with a recipe
+vote_recipe <- recipe(turnout16_2016 ~ ., data = vote_train) %>% 
+    step_upsample(turnout16_2016)
+
+## Model specification
+glm_spec <- logistic_reg() %>%
+    set_engine("glm")
+
+## Combine in workflow
+vote_wf <- workflow() %>%
+    add_recipe(vote_recipe) %>%
+    add_model(glm_spec)
+
+## Final fit
+vote_final <- vote_wf %>%
+    last_fit(vote_split)
+
+## Confusion matrix
+vote_final %>% 
+    collect_predictions() %>% 
+    conf_mat(turnout16_2016, .pred_class)
diff --git a/exercises/solution_04_04_1.R b/exercises/solution_04_04_1.R
index 2f2fac2..2221558 100644
--- a/exercises/solution_04_04_1.R
+++ b/exercises/solution_04_04_1.R
@@ -1,13 +1,13 @@
-library(tidyverse)
-sisters67 <- read_csv("data/sisters.csv")
-
-# Print the structure of sisters67
-glimpse(sisters67)
-
-# Tidy the data set
-tidy_sisters <- sisters67 %>%
-    select(-sister) %>%
-    gather(key, value, -age)
-
-# Print the structure of tidy_sisters
-glimpse(tidy_sisters)
\ No newline at end of file
+library(tidyverse)
+sisters67 <- read_csv("data/sisters.csv")
+
+# Print the structure of sisters67
+glimpse(sisters67)
+
+# Tidy the data set
+tidy_sisters <- sisters67 %>%
+    select(-sister) %>%
+    pivot_longer(-age, names_to = "question", values_to = "rating")
+
+# Print the structure of tidy_sisters
+glimpse(tidy_sisters)
diff --git a/exercises/solution_04_04_2.R b/exercises/solution_04_04_2.R
index 03a2aa2..65216d9 100644
--- a/exercises/solution_04_04_2.R
+++ b/exercises/solution_04_04_2.R
@@ -1,11 +1,11 @@
-library(tidyverse)
-tidy_sisters <- readRDS("data/c4_tidy_sisters.rds")
-
-# Overall agreement with all questions varied by age
-tidy_sisters %>%
-    group_by(age) %>%
-    summarize(value = mean(value, na.rm = TRUE))
-
-# Number of respondents agreed or disagreed overall
-tidy_sisters %>%
-    count(value)
\ No newline at end of file
+library(tidyverse)
+tidy_sisters <- readRDS("data/tidy_sisters.rds")
+
+# Overall agreement with all questions varied by age
+tidy_sisters %>%
+    group_by(age) %>%
+    summarize(rating = mean(rating, na.rm = TRUE))
+
+# Number of respondents agreed or disagreed overall
+tidy_sisters %>%
+    count(rating)
diff --git a/exercises/solution_04_06.R b/exercises/solution_04_06.R
index 2bf9dd9..92bad73 100644
--- a/exercises/solution_04_06.R
+++ b/exercises/solution_04_06.R
@@ -1,11 +1,11 @@
-library(tidyverse)
-tidy_sisters <- readRDS("data/c4_tidy_sisters.rds")
-
-# Visualize agreement with age
-tidy_sisters %>%
-    filter(key %in% paste0("v", 153:170)) %>%
-    group_by(key, value) %>%
-    summarise(age = mean(age, na.rm = TRUE)) %>%
-    ggplot(aes(value, age, color = key)) +
-    geom_line(show.legend = FALSE) +
-    facet_wrap(~key, nrow = 3)
\ No newline at end of file
+library(tidyverse)
+tidy_sisters <- readRDS("data/tidy_sisters.rds")
+
+# Visualize agreement with age
+tidy_sisters %>%
+    filter(question %in% paste0("v", 153:170)) %>%
+    group_by(question, rating) %>%
+    summarise(age = mean(age, na.rm = TRUE)) %>%
+    ggplot(aes(rating, age, color = question)) +
+    geom_line(show.legend = FALSE) +
+    facet_wrap(~question, nrow = 3)
diff --git a/exercises/solution_04_07.R b/exercises/solution_04_07.R
index dacf3a4..435dc48 100644
--- a/exercises/solution_04_07.R
+++ b/exercises/solution_04_07.R
@@ -1,13 +1,17 @@
-library(tidyverse)
-sisters67 <- read_csv("data/sisters.csv")
-
-# Remove the sister column
-sisters_select <- sisters67 %>% 
-    select(-sister)
-
-# Build a simple linear regression model
-simple_lm <- lm(age ~ ., 
-                data = sisters_select)
-
-# Print the summary of the model
-summary(simple_lm)
\ No newline at end of file
+library(tidyverse)
+library(tidymodels)
+sisters_select <- read_csv("data/sisters.csv") %>%
+    select(-sister)
+
+# Split off the testing set
+set.seed(123)
+sisters_split <- initial_split(sisters_select, strata = age)
+
+sisters_other <- training(sisters_split)
+sisters_test <- testing(sisters_split)
+
+# Create the validation split
+set.seed(123)
+sisters_val <- validation_split(sisters_other, strata = age)
+
+glimpse(sisters_val)
diff --git a/exercises/solution_04_08.R b/exercises/solution_04_08.R
deleted file mode 100644
index c3bf0f9..0000000
--- a/exercises/solution_04_08.R
+++ /dev/null
@@ -1,21 +0,0 @@
-library(tidyverse)
-library(rsample)
-sisters_select <- read_csv("data/sisters.csv") %>%
-    select(-sister)
-
-# Split the data into training and validation/test sets
-train_split <- sisters_select %>%
-    initial_split(prop = 0.6,
-                  strata = "age")
-
-sisters_train <- training(train_split)
-validate_test <- testing(train_split)
-
-# Split the validation and test sets
-set.seed(1234)
-validation_split <- validate_test %>%
-    initial_split(prop = 0.5,
-                  strata = "age")
-
-sisters_validate <- training(validation_split)
-sisters_test <- testing(validation_split)
diff --git a/exercises/solution_04_10_1.R b/exercises/solution_04_10_1.R
new file mode 100644
index 0000000..a7a2a52
--- /dev/null
+++ b/exercises/solution_04_10_1.R
@@ -0,0 +1,9 @@
+library(tidymodels)
+
+sisters_other <- readRDS("data/c4_other.rds")
+
+sisters_recipe <- recipe(age ~ ., data = sisters_other) %>% 
+    step_normalize(all_predictors()) %>%
+    step_pca(all_predictors(), num_comp = tune())
+
+sisters_recipe
diff --git a/exercises/solution_04_10_2.R b/exercises/solution_04_10_2.R
new file mode 100644
index 0000000..652acbb
--- /dev/null
+++ b/exercises/solution_04_10_2.R
@@ -0,0 +1,10 @@
+library(tidymodels)
+
+tree_spec <- decision_tree(
+    cost_complexity = tune(),
+    tree_depth = tune()
+) %>% 
+    set_engine("rpart") %>% 
+    set_mode("regression")
+
+tree_spec
diff --git a/exercises/solution_04_10_3.R b/exercises/solution_04_10_3.R
new file mode 100644
index 0000000..94e3f5e
--- /dev/null
+++ b/exercises/solution_04_10_3.R
@@ -0,0 +1,20 @@
+library(tidymodels)
+
+sisters_other <- readRDS("data/c4_other.rds")
+
+sisters_recipe <- recipe(age ~ ., data = sisters_other) %>% 
+    step_normalize(all_predictors()) %>%
+    step_pca(all_predictors(), num_comp = tune())
+
+tree_spec <- decision_tree(
+    cost_complexity = tune(),
+    tree_depth = tune()
+) %>% 
+    set_engine("rpart") %>% 
+    set_mode("regression")
+
+tree_wf <- workflow() %>%
+    add_recipe(sisters_recipe) %>%
+    add_model(tree_spec)
+
+tree_wf
diff --git a/exercises/solution_04_11.R b/exercises/solution_04_11.R
index 2b82734..3485449 100644
--- a/exercises/solution_04_11.R
+++ b/exercises/solution_04_11.R
@@ -1,11 +1,8 @@
-library(tidyverse)
-sisters_train <- readRDS("data/c4_training_500.rds")
-
-# Load caret
-library(caret)
-
-# Fit a CART model
-sisters_cart <- train(age ~ ., method = "rpart", data = sisters_train)
-
-# Print the CART model
-sisters_cart
\ No newline at end of file
+library(tidymodels)
+
+tree_grid <- grid_regular(num_comp(c(3, 12)),
+                          cost_complexity(),
+                          tree_depth(),
+                          levels = 5)
+
+glimpse(tree_grid)
diff --git a/exercises/solution_04_12.R b/exercises/solution_04_12.R
index 9cf7513..fff51a5 100644
--- a/exercises/solution_04_12.R
+++ b/exercises/solution_04_12.R
@@ -1,18 +1,32 @@
-library(tidyverse)
-library(caret)
+library(tidymodels)
 
-sisters_validate <- readRDS("data/c4_validation_full.rds")
-sisters_test <- readRDS("data/c4_testing_full.rds")
-sisters_cart <- readRDS("data/sisters_cart.rds")
-sisters_gbm <- readRDS("data/sisters_gbm.rds")
-sisters_xgb <- readRDS("data/sisters_xg.rds")
+sisters_other <- readRDS("data/c4_other.rds")
+sisters_val <- readRDS("data/c4_val.rds")
 
-# Make predictions on the three models
-modeling_results <- sisters_validate %>%
-    mutate(CART = predict(sisters_cart, sisters_validate),
-           GBM = predict(sisters_gbm, sisters_validate),
-           XGB = predict(sisters_xgb, sisters_validate))
+sisters_recipe <- recipe(age ~ ., data = sisters_other) %>% 
+    step_normalize(all_predictors()) %>%
+    step_pca(all_predictors(), num_comp = tune())
 
-# View the predictions
-modeling_results %>% 
-    select(CART, GBM, XGB)
\ No newline at end of file
+tree_spec <- decision_tree(
+    cost_complexity = tune(),
+    tree_depth = tune()
+) %>% 
+    set_engine("rpart") %>% 
+    set_mode("regression")
+
+tree_wf <- workflow() %>%
+    add_recipe(sisters_recipe) %>%
+    add_model(tree_spec)
+
+tree_grid <- grid_regular(num_comp(c(3, 12)),
+                          cost_complexity(),
+                          tree_depth(),
+                          levels = 2)
+set.seed(123)
+tree_res <- tune_grid(
+    tree_wf,
+    resamples = sisters_val,
+    grid = tree_grid
+)
+
+glimpse(tree_res)
diff --git a/exercises/solution_04_13.R b/exercises/solution_04_13.R
index 75ee050..83ef495 100644
--- a/exercises/solution_04_13.R
+++ b/exercises/solution_04_13.R
@@ -1,16 +1,19 @@
 library(tidyverse)
-library(caret)
+library(tidymodels)
 
-modeling_results <- readRDS("data/c4_modeling_results.rds")
+tree_res <- readRDS("data/c4_tree_res.rds")
 
-# Load yardstick
-library(yardstick)
+tree_metrics <- tree_res %>%
+    collect_metrics() 
 
-# Compare performance for...
+glimpse(tree_metrics)
 
-# ...CART model
-metrics(modeling_results, truth = age, estimate = CART)
-# ...gbm model
-metrics(modeling_results, truth = age, estimate = GBM)
-# ...xgboost model
-metrics(modeling_results, truth = age, estimate = XGB)
+tree_metrics %>%
+    mutate(tree_depth = factor(tree_depth),
+           num_comp = paste("num_comp =", num_comp),
+           num_comp = fct_inorder(num_comp)) %>%
+    ggplot(aes(cost_complexity, mean, color = tree_depth)) +
+    geom_line(size = 1.5, alpha = 0.6) +
+    geom_point(size = 2) +
+    scale_x_log10() +
+    facet_grid(.metric ~ num_comp, scales = "free")
diff --git a/exercises/solution_04_14.R b/exercises/solution_04_14.R
index eea79cc..bfd9a70 100644
--- a/exercises/solution_04_14.R
+++ b/exercises/solution_04_14.R
@@ -1,13 +1,34 @@
 library(tidyverse)
-library(caret)
-library(yardstick)
-
-sisters_train <- readRDS("data/c4_training_500.rds")
-sisters_validate <- readRDS("data/c4_validation_full.rds")
-sisters_test <- readRDS("data/c4_testing_full.rds")
-sisters_xgb <- readRDS("data/sisters_xg.rds")
-
-# Calculate RMSE
-sisters_test %>%
-    mutate(prediction = predict(sisters_xgb, sisters_test)) %>%
-    rmse(truth = age, estimate = prediction)
+library(tidymodels)
+
+tree_res <- readRDS("data/c4_tree_res.rds")
+sisters_other <- readRDS("data/c4_other.rds")
+
+sisters_recipe <- recipe(age ~ ., data = sisters_other) %>% 
+    step_normalize(all_predictors()) %>%
+    step_pca(all_predictors(), num_comp = tune())
+
+tree_spec <- decision_tree(
+    cost_complexity = tune(),
+    tree_depth = tune()
+) %>% 
+    set_engine("rpart") %>% 
+    set_mode("regression")
+
+tree_wf <- workflow() %>%
+    add_recipe(sisters_recipe) %>%
+    add_model(tree_spec)
+
+tree_wf
+
+
+best_tree <- tree_res %>%
+    select_best("rmse")
+
+best_tree
+
+final_wf <- tree_wf %>% 
+    finalize_workflow(best_tree)
+
+final_wf
+
diff --git a/exercises/solution_04_15.R b/exercises/solution_04_15.R
new file mode 100644
index 0000000..5f40d0c
--- /dev/null
+++ b/exercises/solution_04_15.R
@@ -0,0 +1,15 @@
+library(tidyverse)
+library(tidymodels)
+
+sisters_select <- read_csv("data/sisters.csv") %>%
+    select(-sister)
+final_wf <- readRDS("data/c4_final_wf.rds")
+
+set.seed(123)
+sisters_split <- initial_split(sisters_select, strata = age)
+
+final_tree <- final_wf %>%
+    last_fit(sisters_split) 
+
+final_tree %>%
+    collect_metrics()
diff --git a/exercises/test_01_07_2.R b/exercises/test_01_07_2.R
index d828382..3b3c42f 100644
--- a/exercises/test_01_07_2.R
+++ b/exercises/test_01_07_2.R
@@ -1,2 +1,2 @@
-test <- function(){success('Great job! You just trained two models with caret. 💪')}
+test <- function(){success('Great job! You just trained two models with tidymodels. 💪')}
 
diff --git a/exercises/test_01_08.R b/exercises/test_01_08.R
index f5378f5..2aca9bb 100644
--- a/exercises/test_01_08.R
+++ b/exercises/test_01_08.R
@@ -1 +1 @@
-test <- function(){success('Nice job! 🏆')}
+test <- function(){success('Nice job! 🏆 You predicted with your models, but think about the data used here. Is that a good idea?!')}
diff --git a/exercises/test_01_09.R b/exercises/test_01_09.R
index 4ab924c..f6aeeb7 100644
--- a/exercises/test_01_09.R
+++ b/exercises/test_01_09.R
@@ -1 +1 @@
-test <- function(){success('Great! The metrics are not worse on the testing data for either model, indicating we have not overfitted in either case.')}
+test <- function(){success('Great! These metrics using the testing data will be more reliable.')}
diff --git a/exercises/test_02_04.R b/exercises/test_02_04.R
index 38dda59..6da57d5 100644
--- a/exercises/test_02_04.R
+++ b/exercises/test_02_04.R
@@ -1,2 +1 @@
-test <- function(){success('Great job! While this model is not the best for predicting on new data, you can get an idea of which predictors have larger effect sizes and which are significant or not significant.')}
-
+test <- function(){success('Great job creating training and testing data sets! Now you can deal with that class imbalance.')}
diff --git a/exercises/test_02_06.R b/exercises/test_02_06.R
index 6da57d5..b794edc 100644
--- a/exercises/test_02_06.R
+++ b/exercises/test_02_06.R
@@ -1 +1 @@
-test <- function(){success('Great job creating training and testing data sets! Now you can deal with that class imbalance.')}
+test <- function(){success('Nice job preprocessing that data! 💪')}
diff --git a/exercises/test_02_12_2.R b/exercises/test_02_12_2.R
index 5aedfb5..b8feae4 100644
--- a/exercises/test_02_12_2.R
+++ b/exercises/test_02_12_2.R
@@ -1 +1 @@
-test <- function(){success('Nice! A confusion matrix is used to evaluate the performance of models, so you should use the `testing` set.')}
+test <- function(){success('Nice! A confusion matrix is used to evaluate the performance of models, so you should use the testing set.')}
diff --git a/exercises/test_02_13.R b/exercises/test_02_13.R
index 3c8695d..8d097b3 100644
--- a/exercises/test_02_13.R
+++ b/exercises/test_02_13.R
@@ -1,2 +1,2 @@
-test <- function(){success('Congratulations on finishing the second case study! 🏆 In terms of overall accuracy and positive predictive value, the random forest model outperforms the logistic regression model. We can predict the remote status of a developer more accurately with a random forest model.')}
+test <- function(){success('Congratulations on finishing the second case study! 🏆 In terms of overall accuracy and positive predictive value, the decision tree model outperforms the logistic regression model. We can predict the remote status of a developer more accurately with a decision tree model.')}
 
diff --git a/exercises/test_03_06.R b/exercises/test_03_06.R
index 9500d1d..20f42ad 100644
--- a/exercises/test_03_06.R
+++ b/exercises/test_03_06.R
@@ -1 +1,2 @@
-test <- function(){success('Nice job! You likely will not want to use something this simple as your final model, but this step allows you to understand which predictors have larger effect sizes and which are significant.')}
+test <- function(){success('Excellent! 🎯 You have now created training and testing sets.')}
+
diff --git a/exercises/test_03_08.R b/exercises/test_03_08.R
index 20f42ad..e06403c 100644
--- a/exercises/test_03_08.R
+++ b/exercises/test_03_08.R
@@ -1,2 +1,2 @@
-test <- function(){success('Excellent! 🎯 You have now created training and testing sets.')}
+test <- function(){success('Great job! 💪')}
 
diff --git a/exercises/test_03_09.R b/exercises/test_03_09.R
index 6c66b54..6aa37fd 100644
--- a/exercises/test_03_09.R
+++ b/exercises/test_03_09.R
@@ -1,2 +1,2 @@
-test <- function(){success('Great job! 💁 That is how you implement upsampling, and there are other options available for dealing with class imbalance, should you need them.')}
+test <- function(){success('Great job! 💁 That is how you combine a recipe and a model into a workflow.')}
 
diff --git a/exercises/test_03_12.R b/exercises/test_03_12.R
new file mode 100644
index 0000000..f0328a7
--- /dev/null
+++ b/exercises/test_03_12.R
@@ -0,0 +1,2 @@
+test <- function(){success('Excellent! ✨')}
+
diff --git a/exercises/test_03_12_1.R b/exercises/test_03_12_1.R
deleted file mode 100644
index cc52d2a..0000000
--- a/exercises/test_03_12_1.R
+++ /dev/null
@@ -1,2 +0,0 @@
-test <- function(){success('Well done! 😺')}
-
diff --git a/exercises/test_03_12_2.R b/exercises/test_03_12_2.R
deleted file mode 100644
index 2a91eb0..0000000
--- a/exercises/test_03_12_2.R
+++ /dev/null
@@ -1 +0,0 @@
-test <- function(){success('Excellent! Machine learning models trained with 10-fold cross-validation repeated 5 times often have optimal performance.')}
diff --git a/exercises/test_03_14_2.R b/exercises/test_03_14_2.R
index 237ee0b..fbe5527 100644
--- a/exercises/test_03_14_2.R
+++ b/exercises/test_03_14_2.R
@@ -1 +1 @@
-test <- function(){success('Nice! Notice that here the random forest has close to perfect performance on the training data.')}
+test <- function(){success('Nice! 💫')}
diff --git a/exercises/test_03_15.R b/exercises/test_03_15.R
new file mode 100644
index 0000000..abdffab
--- /dev/null
+++ b/exercises/test_03_15.R
@@ -0,0 +1,2 @@
+test <- function(){success('Well done! ⚡️ Notice that the sensitivity for the random forest model is ZERO.')}
+
diff --git a/exercises/test_03_15_1.R b/exercises/test_03_15_1.R
deleted file mode 100644
index c7f5aa5..0000000
--- a/exercises/test_03_15_1.R
+++ /dev/null
@@ -1,2 +0,0 @@
-test <- function(){success('Well done! ⚡️')}
-
diff --git a/exercises/test_03_15_2.R b/exercises/test_03_15_2.R
deleted file mode 100644
index 86098a2..0000000
--- a/exercises/test_03_15_2.R
+++ /dev/null
@@ -1 +0,0 @@
-test <- function(){success('Great job! Notice the difference in how these models are performing on the testing data.')}
diff --git a/exercises/test_03_15_3.R b/exercises/test_03_15_3.R
deleted file mode 100644
index d5f0c2c..0000000
--- a/exercises/test_03_15_3.R
+++ /dev/null
@@ -1,2 +0,0 @@
-test <- function(){success('Well done! 🏆')}
-
diff --git a/exercises/test_03_17.R b/exercises/test_03_17.R
new file mode 100644
index 0000000..de8d1b6
--- /dev/null
+++ b/exercises/test_03_17.R
@@ -0,0 +1 @@
+test <- function(){success('Great job in this chapter! 🙌️ Notice there is some difference in how we predict the positive and negative cases.')}
diff --git a/exercises/test_04_07.R b/exercises/test_04_07.R
index fecdce5..c019415 100644
--- a/exercises/test_04_07.R
+++ b/exercises/test_04_07.R
@@ -1,2 +1,2 @@
-test <- function(){success('Excellent! This is not the best model you can build with this data, but it *does* give you an idea of what is possible and where to start.')}
+test <- function(){success('Excellent! ✨ You have now created training, validation, and testing sets.')}
 
diff --git a/exercises/test_04_08.R b/exercises/test_04_08.R
deleted file mode 100644
index c019415..0000000
--- a/exercises/test_04_08.R
+++ /dev/null
@@ -1,2 +0,0 @@
-test <- function(){success('Excellent! ✨ You have now created training, validation, and testing sets.')}
-
diff --git a/exercises/test_04_10_1.R b/exercises/test_04_10_1.R
new file mode 100644
index 0000000..d19cf90
--- /dev/null
+++ b/exercises/test_04_10_1.R
@@ -0,0 +1,2 @@
+test <- function(){success('Well done! 🔥')}
+
diff --git a/exercises/test_04_10_2.R b/exercises/test_04_10_2.R
new file mode 100644
index 0000000..c216527
--- /dev/null
+++ b/exercises/test_04_10_2.R
@@ -0,0 +1 @@
+test <- function(){success('Excellent! This model specification is ready for tuning.')}
diff --git a/exercises/test_04_10_3.R b/exercises/test_04_10_3.R
new file mode 100644
index 0000000..ad64a7f
--- /dev/null
+++ b/exercises/test_04_10_3.R
@@ -0,0 +1 @@
+test <- function(){success('Your workflow is ready to go! 💫')}
diff --git a/exercises/test_04_11.R b/exercises/test_04_11.R
index 6043a1e..8b60f12 100644
--- a/exercises/test_04_11.R
+++ b/exercises/test_04_11.R
@@ -1 +1 @@
-test <- function(){success('Great job! In this case study, you will evaluate this model, plus two kinds of gradient boosting models.')}
+test <- function(){success('Great job! In this case study, you will fit a whole set of models for a grid of hyperparameters like this.')}
diff --git a/exercises/test_04_12.R b/exercises/test_04_12.R
index a1c08fe..09b9a03 100644
--- a/exercises/test_04_12.R
+++ b/exercises/test_04_12.R
@@ -1,2 +1,2 @@
-test <- function(){success('Nice! 👍 If you are training and considering many models, it is important to use a validation training set.')}
+test <- function(){success('Nice tuning results! 👍')}
 
diff --git a/exercises/test_04_13.R b/exercises/test_04_13.R
index 907f05f..8f0550c 100644
--- a/exercises/test_04_13.R
+++ b/exercises/test_04_13.R
@@ -1 +1 @@
-test <- function(){success('Excellent! Notice that the XGBoost gradient boosting regression model performed best, at least with the default tuning parameters we used in training.')}
+test <- function(){success('Excellent! Notice that the tree depth of 4 looks the best.')}
diff --git a/exercises/test_04_14.R b/exercises/test_04_14.R
index 0b1a351..df25304 100644
--- a/exercises/test_04_14.R
+++ b/exercises/test_04_14.R
@@ -1,2 +1,2 @@
-test <- function(){success('That is correct! 🎯 Use the testing data to estimate RMSE for new predictions.')}
+test <- function(){success('That is correct! 🎯 This finalized workflow can be used to predict on new data.')}
 
diff --git a/exercises/test_04_15.R b/exercises/test_04_15.R
new file mode 100644
index 0000000..75398a6
--- /dev/null
+++ b/exercises/test_04_15.R
@@ -0,0 +1,2 @@
+test <- function(){success('Fantastic! 💫')}
+
diff --git a/img/age_histogram.png b/img/age_histogram.png
index 258fe76..7064dfb 100644
Binary files a/img/age_histogram.png and b/img/age_histogram.png differ
diff --git a/img/upsample1.png b/img/downsample1.png
similarity index 100%
rename from img/upsample1.png
rename to img/downsample1.png
diff --git a/img/downsample2.png b/img/downsample2.png
new file mode 100644
index 0000000..5fd14a4
Binary files /dev/null and b/img/downsample2.png differ
diff --git a/img/mpg_histogram.png b/img/mpg_histogram.png
new file mode 100644
index 0000000..7f42611
Binary files /dev/null and b/img/mpg_histogram.png differ
diff --git a/img/remote_size.png b/img/remote_size.png
index c8c67f6..2ccc40b 100644
Binary files a/img/remote_size.png and b/img/remote_size.png differ
diff --git a/img/tidymodels_hex.png b/img/tidymodels_hex.png
new file mode 100644
index 0000000..99284f9
Binary files /dev/null and b/img/tidymodels_hex.png differ
diff --git a/img/tidymodels_small.png b/img/tidymodels_small.png
new file mode 100644
index 0000000..ceed4ef
Binary files /dev/null and b/img/tidymodels_small.png differ
diff --git a/img/tune_results.png b/img/tune_results.png
new file mode 100644
index 0000000..fd2060b
Binary files /dev/null and b/img/tune_results.png differ
diff --git a/meta.json b/meta.json
index bebca49..9faecd1 100644
--- a/meta.json
+++ b/meta.json
@@ -3,7 +3,7 @@
     "title": "Supervised machine learning case studies in R!",
     "slogan": "A free interactive course",
     "description": "<p>This is a free, open source course on supervised machine learning in R. In this course, you'll work through four case studies and practice skills from exploratory data analysis through model evaluation. <a href='https://ines.io/'>Ines Montani</a> designed the web framework that runs this course, and <a href='https://florencia.netlify.com/'>Florencia D'Andrea</a> helped build the site.</p><p>Contributions and comments on how to improve this course are welcome! Please <a href='https://github.com/juliasilge/supervised-ML-case-studies-course/issues'>file an issue</a> or submit a pull request if you find something that could be fixed or improved.</p><p><a rel='license' href='http://creativecommons.org/licenses/by/4.0'><img alt='Creative Commons License' src='https://i.creativecommons.org/l/by/4.0/88x31.png'/></a></p>",
-    "bio": "<p>My name is Julia Silge and I'm a data scientist and software engineer at <a href='https://rstudio.com/'>RStudio</a> where I build modeling tools. I am both an international keynote speaker and a real-world practitioner focused on data analysis and machine learning practice. I love making beautiful charts and communicating about technical topics with diverse audiences.</p><p><a href='https://www.netlify.com'><img src='https://www.netlify.com/img/global/badges/netlify-color-accent.svg'/></a></p>",
+    "bio": "<p>My name is Julia Silge and I'm a data scientist and software engineer at <a href='https://rstudio.com/'>RStudio</a> where I <a href='https://www.tidymodels.org/'>build modeling tools</a>. I am both an international keynote speaker and a real-world practitioner focused on data analysis and machine learning practice. I love making beautiful charts and communicating about technical topics with diverse audiences.</p><p><a href='https://www.netlify.com'><img src='https://www.netlify.com/img/global/badges/netlify-color-accent.svg'/></a></p>",
     "siteUrl": "https://supervised-ml-course.netlify.com",
     "twitter": "juliasilge",
     "fonts": "IBM+Plex+Mono:500|IBM+Plex+Sans:700|Lato:400,400i,700,700i",
diff --git a/slides/chapter1_01.md b/slides/chapter1_01.md
index 01d045b..2a85d9e 100644
--- a/slides/chapter1_01.md
+++ b/slides/chapter1_01.md
@@ -147,7 +147,6 @@ Notes: Notice that some of these column names have spaces in them; you may not h
 ```r
 cars2018 %>%
     select(`Fuel injection`)
-    
 ```
 ```out
 # A tibble: 1,144 x 1
diff --git a/slides/chapter1_05.md b/slides/chapter1_05.md
index 9997187..bb755c9 100644
--- a/slides/chapter1_05.md
+++ b/slides/chapter1_05.md
@@ -2,7 +2,7 @@
 type: slides
 ---
 
-# Getting started with caret 💫
+# Getting started with tidymodels 💫
 
 Notes: You just performed some exploratory data analysis and built a simple linear model using base R's `lm()` function.
 
@@ -11,7 +11,7 @@ Notes: You just performed some exploratory data analysis and built a simple line
 
 # Predicting fuel efficiency ⛽ 
 
-![Alt text](https://github.com/juliasilge/supervised-ML-case-studies-course/blob/master/img/histogram.png?raw=true)
+![Histogram](https://github.com/juliasilge/course-ML-tidymodels/blob/master/img/mpg_histogram.png?raw=true)
 
 Notes: You were able to see how the fuel efficiency for these cars is distributed and to get an idea about whether you will be able to train accurate models. Now it's time to bring out a more powerful and flexible set of tools for predictive modeling. 
 
@@ -19,15 +19,17 @@ Notes: You were able to see how the fuel efficiency for these cars is distribute
 
 # Tools for predictive modeling
 
-### the [tidymodels](https://github.com/tidymodels/tidymodels) metapackage
+![tidymodels](https://github.com/juliasilge/course-ML-tidymodels/blob/master/img/tidymodels_small.png?raw=true)
 
-### the [caret](https://topepo.github.io/caret/) package
+Learn more at [`tidymodels.org`](https://www.tidymodels.org/)!
 
-Notes: We are going to use packages from the tidymodels toolkit, as well as the caret package, in this course and the first thing we are going to practice is splitting your data into a training set and a testing set.
+Notes: We are going to use packages from tidymodels in this course. 
+
+When you type `library(tidymodels)`, you load a collection of packages for modeling and machine learning using tidyverse principles. I usually just load them all at once if I am working on a modeling project. All the packages are designed to be consistent, modular, and to support good modeling practices. The first thing we are going to practice is splitting your data into a training set and a testing set.
 
 ---
 
-![Alt text](https://github.com/juliasilge/supervised-ML-case-studies-course/blob/master/img/testtrain.png?raw=true)
+![test train](https://github.com/juliasilge/supervised-ML-case-studies-course/blob/master/img/testtrain.png?raw=true)
 
 Notes: It is best practice to hold out some of your data for **testing** in order to get a better estimate of how your models will perform on new data, especially when you use very powerful machine learning techniques. Linear regression doesn't really fall into that category, but we are going to practice this anyway. The tidymodels package [rsample](https://tidymodels.github.io/rsample/) has functions that help you specify training and testing sets.
 
@@ -36,11 +38,11 @@ Notes: It is best practice to hold out some of your data for **testing** in orde
 # Training data and testing data with [rsample](https://tidymodels.github.io/rsample/)
 
 ```r
-library(rsample)
+library(tidymodels)
  
 car_split <- car_vars %>%
     initial_split(prop = 0.8,
-                  strata = "Aspiration")
+                  strata = Aspiration)
 
 car_training <- training(car_split)
 car_testing <- testing(car_split)
@@ -53,7 +55,7 @@ Notes: You can create these sets so that they balance some characteristic in you
 # Training data and testing data
 
 - **Build** your model with your training data 
-- **Choose** your model with your validation data 
+- **Choose** your model with your validation data, or resampled datasets 
 - **Evaluate** your model with your testing data 
 
 Notes:  Why are we even bothering with this? 
@@ -67,23 +69,42 @@ It's also possible to divide your data into *three* partitions as you build, cho
 # Training a model
 
 ```r
-library(caret)
+library(tidymodels)
+
+## a linear regression model specification
+lm_mod <- linear_reg() %>%
+    set_engine("lm")
+
+lm_fit <- lm_mod %>%
+    fit(log(MPG) ~ ., 
+        data = car_train)
 
-fit_lm <- train(log(MPG) ~ ., 
-                method = "lm", 
-                data = car_training,
-                trControl = trainControl(method = "none"))
+## a random forest model specification
+rf_mod <- rand_forest() %>%
+    set_mode("regression") %>%
+    set_engine("randomForest")
+
+fit_rf <- rf_mod %>%
+    fit(log(MPG) ~ ., 
+        data = car_train)        
 
 ```
 
-- Train a model
-- Evaluate that model using [yardstick](https://tidymodels.github.io/yardstick/)
+#### Three concepts in specifying a model
+
+- Model **type**
+- Model **mode**
+- Model **engine**
 
 Notes: Once you have a training dataset, you can train a model using that dataset! 
 
-In caret, you specify models using the `train()` function, with details of what kind of model it is, and in what way you want to train it. 
+In tidymodels, you specify models using three concepts. 
+
+- Model **type** differentiates models such as logistic regression, decision tree models, and so forth. 
+- Model **mode** includes common options like regression and classification; some model types support either of these while some only have one mode. (Notice in the example on this slide that we didn't need to set the mode for `linear_reg()` because it only does regression.)
+- Model **engine** is the computational tool which will be used to fit the model. Often these are R packages, such as `"lm"` for OLS or the different implementations of random forest models.
 
-We're going to start with `method = "none"` in `trainControl()`, as you see here. This means we're telling caret, "Just train the model one time, on the whole training set". Once your model is trained, you can evaluate how well the model is performing. 
+After a model has been _specified_, it can be _fit_, typically using a symbolic description of the model (a formula) and some data. We're going to start fitting models with `data = car_train`, as shown here. This means we're saying, "Just fit the model one time, on the whole training set". Once you have fit your model, you can evaluate how well the model is performing. 
 
 ---
 
diff --git a/slides/chapter1_10.md b/slides/chapter1_10.md
index f3c7e0b..42ec1e9 100644
--- a/slides/chapter1_10.md
+++ b/slides/chapter1_10.md
@@ -2,10 +2,12 @@
 type: slides
 ---
 
-# Training a model with resampling
+# Evaluating models with resampling
 
 
-Notes: You just built and then evaluated models that were trained one time on the whole training set at once. Data scientists have come up with a slew of approaches to build models that perform better than this; a lot of important ones fall under the category of **resampling**.
+Notes: You just trained models one time on the whole training set and then evaluated them on the testing set. Statisticians have come up with a slew of approaches to evaluate models in better ways than this; many important ones fall under the category of **resampling**.
+
+The idea of resampling is to create simulated data sets that can be used to estimate the performance of your model, say, because you want to compare models. You can create these resampled data sets instead of using either your training set (which can give overly optimistic results, especially for powerful ML algorithms) or your testing set (which is extremely valuable and can only be used once or at most twice).
 
 ---
 
@@ -15,7 +17,9 @@ Sample with replacement from the original dataset
 
 Notes: The first resampling approach we're going to try in this course is called the bootstrap. Bootstrap resampling means drawing with replacement from our original dataset and then fitting on that dataset.
 
-Let's think about...cars! 🚗🚌🚙🚕 Let's say our training dataset has 900 cars in it. 
+Let's think about...cars! 🚗🚌🚙🚕 
+
+Let's say our training dataset has 900 cars in it. 
 
 ---
 
@@ -24,7 +28,7 @@ Let's think about...cars! 🚗🚌🚙🚕 Let's say our training dataset has 90
 
 Notes: To make a bootstrap sample, we draw with replacement 900 times from that training data to get the same size sample that we started with. 
 
-Since we're drawing with replacement, we will probably draw some cars more than once. We then fit our model on that new set of 900 cars that contains some duplicates. 
+Since we're drawing with replacement, we will probably draw some cars more than once. We then fit our model on that new set of 900 cars that contains some duplicates, and evaluate the model on the cars that are not included in the new set of 900. 
 
 Then we do that again.
 
@@ -33,45 +37,80 @@ Then we do that again.
 ![Alt text](https://github.com/juliasilge/supervised-ML-case-studies-course/blob/master/img/bootstrap2.png?raw=true)
 
 
-Notes: We draw 900 times from the training dataset with replacement again and fit another model. We repeat that some number of times, look at all the models we fit on the bootstrap samples, combine them, and then take an average of some kind.
+Notes: We draw 900 times from the training dataset with replacement again and fit another model. We repeat that some number of times, look at all the models we fit on the bootstrap samples, determine each model's individual performance by evaluating on the cars that were not included in each bootstrap resample, and then take an average of the performance metrics.
 
-This approach does take longer, obviously, than training the data one time. In your exercise, you will have a subset of the complete dataset to try this out with.
+This approach does take longer, obviously, than fitting on the data one time. In your exercise, you will have a subset of the complete dataset to try this out with.
 
 ---
 
-# Bootstrap resampling with caret
+# Bootstrap resampling with tidymodels
 
 ```r
-> ca_rf_bt <- train(log(MPG) ~ ., 
-+                   method = "rf", 
-+                   data = car_train, 
-+                   trControl = trainControl(method = "boot"))
+bootstraps(car_train)
+```
+
+```out
+# Bootstrap sampling 
+# A tibble: 25 x 2
+   splits            id         
+   <list>            <chr>      
+ 1 <split [916/328]> Bootstrap01
+ 2 <split [916/347]> Bootstrap02
+ 3 <split [916/331]> Bootstrap03
+ 4 <split [916/333]> Bootstrap04
+ 5 <split [916/346]> Bootstrap05
+ 6 <split [916/329]> Bootstrap06
+ 7 <split [916/320]> Bootstrap07
+ 8 <split [916/342]> Bootstrap08
+ 9 <split [916/339]> Bootstrap09
+10 <split [916/334]> Bootstrap10
+# … with 15 more rows
 ```
 
-Notes: I am very happy to be able to tell you that training a model with bootstrap resampling is not too complicated with caret. 
+Notes: I am very happy to be able to tell you that creating resamples is not too complicated with tidymodels. There are functions such as `bootstraps()` and similar for other types of resampling. The default behavior is to do 25 bootstrap resamplings, but you can change this if you want to. Notice that we resampled the `car_train` dataset, which is the _training_ data.
+
+The column `splits` is of type `list`. Instead of containing numbers or characters, this column contains lists. Each split in that column keeps track of which of the original data points are in the analysis set for that resample.
+
+---
+
+# Evaluating models with resampling
+
+```r
+lm_mod %>%
+    fit_resamples(
+        log(MPG) ~ .,
+        car_boot,
+        control = control_resamples(save_pred = TRUE)
+    )
+```
+
+Notes: Once you have created a set of resamples, you can use the function `fit_resamples()` to fit a model to each resample and compute performance metrics for each. 
+
+The code on this slide shows how to fit our model specification `lm_mod` to the 25 bootstrap resamples in `car_boot`. This will fit our regression model 25 times, each time to a different bootstrapped version of the training data. We also determine how well our regression model performed 25 times, each time on the smaller subset of training data set aside when fitting. The fitted models themselves are just thrown away and not stored in the output, because they are only used for computing performance metrics. 
+
+To fit the random forest to these resamples and find performance metrics, we would use `rf_mod` instead.
 
-All you have to do is specify `method = "boot"` in `trainControl()`, like you see here. The default behavior is to do 25 bootstrap resamplings, but you can change this if you want to.
 
 ---
 
 # Comparing predicted to real values ⛽ 
 
 ```out
-  `log(MPG)` `Linear regression` `Random forest`
-        <dbl>               <dbl>           <dbl>
- 1       2.89                2.79            2.83
- 2       2.89                3.00            2.89
- 3       3.26                3.22            3.26
- 4       3.14                3.09            3.10
- 5       3.26                3.22            3.26
- 6       2.89                3.11            2.98
- 7       2.48                2.59            2.51
- 8       2.71                2.81            2.82
- 9       3.37                3.29            3.27
-10       2.83                2.90            2.90
+   `log(MPG)` .pred_lm .pred_rf
+        <dbl>    <dbl>    <dbl>
+ 1       2.71     2.77     2.84
+ 2       3.37     3.45     3.38
+ 3       2.94     2.96     2.91
+ 4       2.89     2.94     2.99
+ 5       3.14     3.26     3.24
+ 6       3.22     3.39     3.47
+ 7       3.40     3.31     3.35
+ 8       3.22     3.31     3.19
+ 9       2.89     2.79     2.87
+10       3.22     3.35     3.26
 ```
 
-Notes: We are going to evaluate our models again using `metrics()` from the yardstick package so I want to emphasize what it is that we are comparing when we do that. 
+Notes: We will not save the fitted models but we *are* going to save our predictions in `fit_resamples()` using `save_pred = TRUE`. This is so we can be especially clear about what it is that we are comparing during this process. 
 
 Each car has a real fuel efficiency as reported by the Department of Energy and then we have built models that predict fuel efficiency for each car. When we evaluate a model, we are calculating how far apart each *predicted* value is from each *real* value.
 
@@ -83,13 +122,13 @@ Each car has a real fuel efficiency as reported by the Department of Energy and
 
 Notes: In this lesson, you also are going to visualize these differences, like you see here. The x-axis has the actual fuel efficiency and the y-axis has the predicted fuel efficiency for each kind of model. 
 
-The difference between linear regression and random forest isn't huge here, but in this case, we can see visually that the random forest model is performing better.
+The difference between linear regression and random forest isn't huge here, but in this case, we can see visually that the random forest model is performing better. The slope for the random forest model is closer to the dotted line (the `slope = 1` line) and the spread around the line is smaller for the random forest model.
 
 ---
 
 # Let's practice!⚡️
 
-Notes: OK, now it's your turn. Let's see if you can fit these kinds of models with bootstrap resampling and find which model performs better.
+Notes: OK, now it's your turn. Let's see if you can evaluate these kinds of models with bootstrap resampling and discover which model performs better.
 
 
 
diff --git a/slides/chapter2_01.md b/slides/chapter2_01.md
index 039f66a..efd3ccc 100644
--- a/slides/chapter2_01.md
+++ b/slides/chapter2_01.md
@@ -18,33 +18,29 @@ Notes: Stack Overflow is the world's largest, most trusted online community for
 
 # Stack Overflow Developer Survey
 
-```
-> stackoverflow
-
+```out
 # A tibble: 6,991 x 22
-   Respondent Country    Salary YearsCodedJob OpenSource Hobby CompanySizeNumb…
-        <int> <chr>       <dbl>         <dbl> <lgl>      <lgl>            <dbl>
- 1          3 United Ki… 113750         20.0  T          T              10000  
- 2         15 United Ki… 100000         20.0  F          T               5000  
- 3         18 United St… 130000         20.0  T          T               1000  
- 4         19 United St…  82500          3.00 F          T              10000  
- 5         26 United St… 175000         16.0  F          T              10000  
- 6         55 Germany     64516          4.00 F          F               1000  
- 7         62 India        6636          1.00 F          T               5000  
- 8         71 United St…  65000          1.00 F          T                 20.0
- 9         73 United St… 120000         20.0  T          T                100  
-10         77 United St…  96283         20.0  T          T               1000  
-# ... with 6,981 more rows, and 15 more variables: Remote <fct>,
-#   CareerSatisfaction <int>, `Data scientist` <lgl>, `Database
-#   administrator` <lgl>, `Desktop applications developer` <lgl>, `Developer
-#   with stats/math background` <lgl>, DevOps <lgl>, `Embedded
-#   developer` <lgl>, `Graphic designer` <lgl>, `Graphics programming` <lgl>,
-#   `Machine learning specialist` <lgl>, `Mobile developer` <lgl>, `Quality
-#   assurance engineer` <lgl>, `Systems administrator` <lgl>, `Web
-#   developer` <lgl>
+   respondent country salary years_coded_job open_source hobby company_size_nu… remote
+        <dbl> <chr>    <dbl>           <dbl> <lgl>       <lgl>            <dbl> <fct> 
+ 1          3 United… 1.14e5              20 TRUE        TRUE             10000 Not r…
+ 2         15 United… 1.00e5              20 FALSE       TRUE              5000 Remote
+ 3         18 United… 1.30e5              20 TRUE        TRUE              1000 Remote
+ 4         19 United… 8.25e4               3 FALSE       TRUE             10000 Not r…
+ 5         26 United… 1.75e5              16 FALSE       TRUE             10000 Not r…
+ 6         55 Germany 6.45e4               4 FALSE       FALSE             1000 Not r…
+ 7         62 India   6.64e3               1 FALSE       TRUE              5000 Not r…
+ 8         71 United… 6.50e4               1 FALSE       TRUE                20 Not r…
+ 9         73 United… 1.20e5              20 TRUE        TRUE               100 Remote
+10         77 United… 9.63e4              20 TRUE        TRUE              1000 Remote
+# … with 6,981 more rows, and 14 more variables: career_satisfaction <dbl>, data_scientist <lgl>,
+#   database_administrator <lgl>, desktop_applications_developer <lgl>,
+#   developer_with_stats_math_background <lgl>, dev_ops <lgl>, embedded_developer <lgl>,
+#   graphic_designer <lgl>, graphics_programming <lgl>, machine_learning_specialist <lgl>,
+#   mobile_developer <lgl>, quality_assurance_engineer <lgl>, systems_administrator <lgl>,
+#   web_developer <lgl>
 ```
 
-Notes: In this case study, you are going to use data from the Developer Survey to build predictive models. First, you'll do exploratory data analysis to understand what's in the dataset, and how some of the quantities in the survey are distributed, and then you'll practice your machine learning skills by training classification models.
+Notes: In this case study, you are going to use data from the annual Developer Survey to build predictive models. First, you'll do exploratory data analysis to understand what's in the dataset, and how some of the quantities in the survey are distributed, and then you'll practice your machine learning skills by training classification models.
 
 ---
 
@@ -56,7 +52,7 @@ Notes: Every year, the data for the Stack Overflow Developer Survey is made publ
 
 ---
 
-![](https://github.com/juliasilge/supervised-ML-case-studies-course/blob/master/img/remote_size.png?raw=true)
+![](https://github.com/juliasilge/course-ML-tidymodels/blob/master/img/remote_size.png?raw=true)
 
 Notes: The specific question we are going to address is what makes a developer more likely to work remotely. Developers can work in their company offices or they can work remotely, and it turns out that there are specific characteristics of developers, such as the size of the company that they work for, how much experience they have, or where in the world they live, that affect how likely they are to be a remote developer.
 
@@ -65,48 +61,25 @@ Notes: The specific question we are going to address is what makes a developer m
 # Class imbalance ⚖️
 
 ```r
-stackoverflow %>% 
-        count(Remote)
+stack_overflow %>% 
+    count(remote)
 ```
 
 ```out
 # A tibble: 2 x 2
-  Remote         n
-  <fctr>     <int>
+  remote         n
+  <fct>      <int>
 1 Remote       718
 2 Not remote  6273
 ```
 
-Notes: That is what you are going to model! One of the things you'll notice right away about this dataset, however, is that the proportion of developers who are remote and those who work in an office is not balanced. This kind of class imbalance can have a significant negative impact on model performance, so we are going to have to cope with it.
-
----
-
-# Building a simple model
-
-```r
-simple_glm <- stackoverflow %>%
-    select(-Respondent) %>%
-    glm(Remote ~ .,
-        family = "binomial",
-        data = .)
-
-summary(simple_glm)
-```
-
-- `Remote ~ .` 
-- `data = .` 
-
-Notes: It's a good idea to start any predictive modeling project by building the simplest possible model. In this case, that's a logistic regression model, trained on all the data without any special tricks. Let's talk about the syntax shown here on this slide because there are two instances of the dot. 
-
-The first dot you see is in the formula that specifies the model that is being trained. It says `Remote ~ .`, which means let's predict remote status with all the other variables in the dataset. 
-
-The second dot there says `data = .`, and we are using *this* because we are piping in our dataset using the pipe operator from dplyr and magrittr. That dot is telling the modeling function where the data is coming from, i.e., that it is the first argument we're sending it. So there are two dots and they mean different things! 😵 Try to keep that in mind as we move forward doing exploratory data analysis.
+Notes: That is what you are going to model! One of the things you'll notice right away about this dataset, however, is that the proportion of developers who are remote and those who work in an office is not balanced. This kind of class imbalance can have a significant negative impact on model performance, so we are going to have to cope with it. We will need to **preprocess** our data before we model it.
 
 ---
 
 # Let's explore the data! 🌟
 
-Notes: Let's start by thinking through our modeling approach and exploring this new dataset.
+Notes: Let's start by exploring this new dataset, and then splitting our data into testing and training sets.
 
 
 
diff --git a/slides/chapter2_05.md b/slides/chapter2_05.md
index 4045c7d..9a4e25f 100644
--- a/slides/chapter2_05.md
+++ b/slides/chapter2_05.md
@@ -5,7 +5,7 @@ type: slides
 # Dealing with imbalanced data ⚖️
 
 
-Notes: You just fit a simple logistic regression model to these survey results in order to predict which developers work remotely and which do not. Before we go any further, we need to talk about the class imbalance in our dataset.
+Notes: You just took this data about which developers work remotely and which do not, and split it into testing and training sets. Before we go any further, we need to talk about the class imbalance in our dataset.
 
 ---
 
@@ -23,14 +23,14 @@ Notes: It's good that we're going to talk about class imbalance because it comes
 # Class imbalance
 
 ```r
-stackoverflow %>% 
-    count(Remote)
+stack_overflow %>% 
+    count(remote)
 ```
 
 ```out
 # A tibble: 2 x 2
-  Remote         n
-  <fctr>     <int>
+  remote         n
+  <fct>      <int>
 1 Remote       718
 2 Not remote  6273
 ```
@@ -39,53 +39,75 @@ Notes: This is in fact what happens with our dataset here (I know because I test
 
 ---
 
-# Upsampling or oversampling
+# Downsampling
 
-- Add more of the minority class so it has more effect on the predictive model
-- Randomly sample with replacement from the minority class until it is the same size as the majority class
+- Remove some of the majority class so it has less effect on the predictive model
+- Randomly remove examples from the majority class until it is the same size as the minority class
 
-Notes: In this case study, we're going to implement **upsampling**, also known as oversampling. With this approach, we randomly sample with replacement from the minority class until it's just as big as the majority class and it can have just as much effect on the machine learning model we're training.
+Notes: In this case study, we're going to implement **downsampling**, also known as undersampling. With this approach, we randomly remove observations from the majority class until it's the same size as the minority class and both classes can have the same effect on the machine learning model we're training. 
+
+Are we really going to throw out a large percentage of our data here?! 😱 Yes! We do this because such an approach can be helpful at producing a useful model that can recognize both classes, instead of only one.
 
 ---
 
-![](https://github.com/juliasilge/supervised-ML-case-studies-course/blob/master/img/upsample1.png?raw=true)
+![](https://github.com/juliasilge/course-ML-tidymodels/blob/master/img/downsample1.png?raw=true)
 
 Notes: In our case study, there are roughly ten times more non-remote developers compared to the remote developers.
 
 
 ---
 
-![](https://github.com/juliasilge/supervised-ML-case-studies-course/blob/master/img/upsample2.png?raw=true)
+![](https://github.com/juliasilge/course-ML-tidymodels/blob/master/img/downsample2.png?raw=true)
 
-Notes: When we implement upsampling, we add more of the remote developers (just more of the same ones we already have) until the proportion is equal, until the classes are balanced. This approach is simple to implement and understand, but it can lead a classifier to overfit to just a few examples, if you're not lucky. There are other more complex approaches to class imbalance available as well, but we will focus on upsampling here.
+Notes: When we implement downsampling, we remove some of the non-remote developers until the proportion is equal and the classes are balanced. This approach is simple to implement and understand, but there are other more complex approaches to class imbalance available as well.
 
 ---
 
-# Implementing upsampling
+# Implementing downsampling
 
 ```r
-up_train <- upSample(x = select(training, -Remote),
-                     y = training$Remote,
-                     yname = "Remote") %>%
-    as_tibble()
+stack_recipe <- recipe(remote ~ ., data = stack_train) %>% 
+    step_downsample(remote)
 ```
 
-Notes: You can implement upsampling using the `upSample()` function in caret or you can include it in a call where you specify a resampling approach like the bootstrap.
+Notes: Downsampling is an example of a preprocessing step for modeling. In tidymodels, you can preprocess your data using [recipes](https://tidymodels.github.io/recipes/). The recipe shown in this slide only has one preprocessing step (downsampling), but you can implement many steps on one dataset during preprocessing. There are an enormous number of different kinds of preprocessing you can do, from creating indicator variables to implementing principal component analysis to extracting date features and more.
 
 ---
 
-# Implementing upsampling
+# Implementing downsampling
 
 
 ```r
-stack_glm <- train(Remote ~ ., method = "glm", 
-                   family = "binomial",
-                   data = stack_train,
-                   trControl = trainControl(method = "boot",
-                                            sampling = "up"))
+stack_prep <- prep(stack_recipe)
+
+juice(stack_prep)
+```
+```out
+# A tibble: 1,168 x 21
+   country salary years_coded_job open_source hobby company_size_nu… career_satisfac… data_scientist
+   <fct>    <dbl>           <dbl> <lgl>       <lgl>            <dbl>            <dbl> <lgl>         
+ 1 United… 100000              20 FALSE       TRUE              5000                8 FALSE         
+ 2 United… 130000              20 TRUE        TRUE              1000                9 FALSE         
+ 3 United… 120000              20 TRUE        TRUE               100                8 FALSE         
+ 4 United…  96283              20 TRUE        TRUE              1000               10 FALSE         
+ 5 United… 100297              15 FALSE       TRUE               100                8 FALSE         
+ 6 United… 146000              15 TRUE        TRUE             10000                8 FALSE         
+ 7 United… 160000              11 TRUE        TRUE               500                7 FALSE         
+ 8 United… 103000              15 TRUE        TRUE               500                8 FALSE         
+ 9 United… 115000               8 TRUE        FALSE               20                6 FALSE         
+10 United…  97000               9 FALSE       TRUE               100                5 FALSE         
+# … with 1,158 more rows, and 13 more variables: database_administrator <lgl>,
+#   desktop_applications_developer <lgl>, developer_with_stats_math_background <lgl>,
+#   dev_ops <lgl>, embedded_developer <lgl>, graphic_designer <lgl>, graphics_programming <lgl>,
+#   machine_learning_specialist <lgl>, mobile_developer <lgl>, quality_assurance_engineer <lgl>,
+#   systems_administrator <lgl>, web_developer <lgl>, remote <fct>
 ```
 
-Notes: That second option is probably the best approach in most circumstances because you'll get a more realistic measure of model uncertainty when the resampling procedure also knows about the subsampling you're doing. Also, notice here that I'm working with the training dataset. 
+Notes: When you [`prep()`](https://tidymodels.github.io/recipes/reference/prep.html) a recipe, you estimate the required parameters from a data set for the preprocessing steps in that recipe (as an example, think about finding the mean and standard deviation if you are centering and scaling). 
+
+When you [`juice()`](https://tidymodels.github.io/recipes/reference/juice.html) a prepped recipe, you get the preprocessed data back out. 
+
+You don't typically need to `prep()` and `juice()` recipes when you use tidymodels, but they are heplful functions to have in your toolkit for confirming that recipes are doing what you expect.
 
 ---
 
diff --git a/slides/chapter2_10.md b/slides/chapter2_10.md
index dbb3329..d50c8ba 100644
--- a/slides/chapter2_10.md
+++ b/slides/chapter2_10.md
@@ -4,7 +4,7 @@ type: slides
 
 # Predicting remote status
 
-Notes: Now that you have understood and implemented upsampling, or oversampling, we can finally get down to the business of building supervised machine learning models to predict which developers work remotely and which do not.
+Notes: Now that you have understood and implemented downsampling, or undersampling, we can finally get down to the business of building supervised machine learning models to predict which developers work remotely and which do not.
 
 ---
 
@@ -13,11 +13,11 @@ Notes: Now that you have understood and implemented upsampling, or oversampling,
 ### Classification models
 
 - Logistic regression
-- Random forest
+- Decision tree
 
-Notes: Unlike the first case study, when you built regression models to predict a numeric or continuous variable, in this case study you are going to build classification models, to predict the class: **remote** or **not remote**. We are going to stick with two methods to understand and implement classification models, logistic regression and random forest. 
+Notes: Unlike the first case study, when you built regression models to predict a numeric or continuous variable, in this case study you are going to build classification models, to predict the class: **remote** or **not remote**. We are going to stick with two methods to understand and implement classification models, logistic regression and a decision tree. 
 
-There are lots of other options, and one of the great characteristics of using caret for predictive modeling is that if you want to try something else, you can extend your work to new model types within the same framework. 💁
+There are lots of other options, and one of the great characteristics of using tidymodels for predictive modeling is that if you want to try something else, you can extend your work to new model types within the same framework. 💁
 
 ---
 
@@ -26,66 +26,113 @@ There are lots of other options, and one of the great characteristics of using c
 ### Logistic regression
 
 ```r
-stack_glm <- train(Remote ~ ., method = "glm", family = "binomial",
-                   data = stack_train,
-                   trControl = trainControl(method = "boot",
-                                            sampling = "up"))
+glm_spec <- logistic_reg() %>%
+    set_engine("glm")
 ```
 
-### Random forest
+### Decision tree
 
 ```r
-stack_rf <- train(Remote ~ ., method = "rf", 
-                  data = stack_train,
-                  trControl = trainControl(method = "boot",
-                                           sampling = "up"))
+tree_spec <- decision_tree() %>%         
+    set_engine("rpart") %>%      
+    set_mode("classification") 
 ```
 
 
-Notes: We are going to use the `train()` function from caret to set up the models. Notice here that one model is logistic regression while the other is random forest, but for both we are implementing bootstrap resampling and upsampling to deal with the class imbalance of remote developers in our dataset.
+Notes: We are going to use model specifications from parsnip to set up the models. Notice here that one model is logistic regression while the other is a decision tree. How do we combine these model specifications with the data preprocessing we need to do from our recipe? 🤔
+
+---
+
+# Build a `workflow()`
+
+```r
+stack_wf <- workflow() %>%
+    add_recipe(stack_recipe)
+    
+stack_wf %>%
+    add_model(glm_spec)
+```
+
+```out
+══ Workflow ══════════════════════════════════════════════════════════════════
+Preprocessor: Recipe
+Model: logistic_reg()
+
+── Preprocessor ──────────────────────────────────────────────────────────────
+1 Recipe Step
+
+● step_downsample()
+
+── Model ─────────────────────────────────────────────────────────────────────
+Logistic Regression Model Specification (classification)
+
+Computational engine: glm 
+```
+
+Notes: You have a few options for that, but one straightforward way is to use a [`workflow()`](https://tidymodels.github.io/workflows/), an object that makes it easier to carry around pieces of, well, modeling workflows! The components of a `workflow()` go together like LEGO blocks; you add a preprocessor like a recipe or a formula, and a model.
+
+If you don't add one of those components (for example, `stack_wf` on this slide) the `workflow()` holds an empty spot ready for, say, the model. You may find this a convenient way to write your modeling code when you want to fit with the same preprocessor but different model specifications.
+
+---
+
+# Fit a `workflow()`
+
+```r
+stack_wf <- workflow() %>%
+    add_recipe(stack_recipe)
+
+stack_wf %>%
+    add_model(tree_spec) %>%
+    fit(data = stack_train)
+```
+
+Notes: A `workflow()` can be fit in much the same way a model can, and all the pieces are composable and pipeable. 🎉
 
-Bootstrap resampling can take a while ⏳ so when you implement this code in an exercise, you'll have a subset of the data to work with in your environment.
 
 ---
 
 # Evaluating your models 📏
   
 ```r
-library(yardstick)
- 
-stack_test %>%
-    mutate(`Logistic regression` = predict(stack_glm, stack_test)) %>%
-    conf_mat(truth = Remote, estimate = "Logistic regression")
+results %>%
+    conf_mat(truth = remote, estimate = .pred_tree)
 ```
 
 ```out
             Truth
 Prediction   Remote Not remote
-  Remote         85        431
-  Not remote     47        835
+  Remote         73        366
+  Not remote     61        898
    
 ```
 
-Notes: Classification models can be evaluated using a confusion matrix. This kind of matrix or table counts which examples were classified correctly and incorrectly. Notice here that with the logistic regression model being evaluated with the testing data, 85 real remote developers were classified as remote, and 835 not remote developers were classified as not remote. The `conf_mat()` function in yardstick is very helpful!
+Notes: Classification models can be evaluated using a confusion matrix. This kind of matrix or table counts which examples were classified correctly and incorrectly. Notice here that with the decision tree model being evaluated with the testing data, 73 real remote developers were classified as remote, and 898 not remote developers were classified as not remote. The `conf_mat()` function in yardstick is very helpful!
 
 ---
 
 # Evaluating your models 📏
 
 ```out
-library(yardstick)
-
-> accuracy(testing_results, truth = Remote, estimate = `Logistic regression`)
-[1] 0.6456693
-
-> ppv(testing_results, truth = Remote, estimate = `Logistic regression`)
-[1] 0.1740741
-
-> npv(testing_results, truth = Remote, estimate = `Logistic regression`)
-[1] 0.9428238
+> accuracy(results, truth = remote, estimate = .pred_glm)
+# A tibble: 1 x 3
+  .metric  .estimator .estimate
+  <chr>    <chr>          <dbl>
+1 accuracy binary         0.657
+
+> ppv(results, truth = remote, estimate = .pred_glm)
+# A tibble: 1 x 3
+  .metric .estimator .estimate
+  <chr>   <chr>          <dbl>
+1 ppv     binary         0.160
+
+> npv(results, truth = remote, estimate = .pred_glm)
+# A tibble: 1 x 3
+  .metric .estimator .estimate
+  <chr>   <chr>          <dbl>
+1 npv     binary         0.941
 ```
 
-Notes: Often you want other measures of model performance, though, in a format that will be friendlier to data frames, and for that you can use the yardstick package. 
+Notes: Often you want other measures of model performance, though, in a format that will be friendlier to data frames, and for that you can use other functions from the yardstick package. 
 
 Here we can see the overall accuracy, as well as the positive and negative predictive values, for the logistic regression model evaluated on the testing data. We'll pass three arguments to these functions: first, a data frame with real data on remote status and predicted remote status for our observations, and then the columns in that data frame that give us the true class and the predicted class for each developer in our data set.
 
diff --git a/slides/chapter3_07.md b/slides/chapter3_07.md
index d1ecdec..db2044e 100644
--- a/slides/chapter3_07.md
+++ b/slides/chapter3_07.md
@@ -27,112 +27,69 @@ Notes: ...and how much of a difference you see in survey responses between the t
 
 ![Alt text](https://github.com/juliasilge/supervised-ML-case-studies-course/blob/master/img/econtrend.png?raw=true)
 
-Notes: Visualizing your data before modeling is always a good idea. 👍 Here, for example, we can see that people who say the economy is getting better are more likely to vote.
+Notes: Visualizing your data before modeling is always a good idea. 👍 
+
+Here, for example, we can see that people who say the economy is getting better are more likely to vote.
 
 ---
 
-# Fitting a simple model
+![](https://github.com/juliasilge/course-ML-tidymodels/blob/master/img/downsample1.png?raw=true)
 
-```r
-simple_glm <- glm(turnout16_2016 ~ .,  family = "binomial", 
-                  data = select(voters, -case_identifier))
- 
-summary(simple_glm)
-```
+Notes: This is another case study with imbalanced data. We are again going to preprocess our training data so we can build a better performing model, but this time we are going to **upsample** (or oversample) our data.
 
-```out
-Call:
-glm(formula = turnout16_2016 ~ ., family = "binomial", 
-    data = select(voters, -case_identifier))
-
-Deviance Residuals: 
-    Min       1Q   Median       3Q      Max  
--3.2373   0.1651   0.2214   0.3004   1.7708  
-
-Coefficients:
-                      Estimate Std. Error z value Pr(>|z|)    
-(Intercept)           2.457036   0.732721   3.353 0.000799 ***
-RIGGED_SYSTEM_1_2016  0.236284   0.085081   2.777 0.005484 ** 
-RIGGED_SYSTEM_2_2016  0.064749   0.089208   0.726 0.467946    
-RIGGED_SYSTEM_3_2016  0.049357   0.107352   0.460 0.645680    
-RIGGED_SYSTEM_4_2016 -0.074694   0.087583  -0.853 0.393749    
-RIGGED_SYSTEM_5_2016  0.190252   0.096454   1.972 0.048556 *  
-RIGGED_SYSTEM_6_2016 -0.005881   0.101381  -0.058 0.953740    
-track_2016            0.241075   0.121467   1.985 0.047178 *  
-persfinretro_2016    -0.040229   0.106714  -0.377 0.706191    
-econtrend_2016       -0.295370   0.087224  -3.386 0.000708 ***
-Americatrend_2016    -0.105213   0.080845  -1.301 0.193116    
-futuretrend_2016      0.210568   0.071201   2.957 0.003103 ** 
-wealth_2016          -0.069405   0.026344  -2.635 0.008424 ** 
-values_culture_2016  -0.041402   0.038670  -1.071 0.284332    
-US_respect_2016      -0.068200   0.043785  -1.558 0.119322    
-trustgovt_2016        0.315354   0.166655   1.892 0.058456 .  
-trust_people_2016     0.040423   0.041518   0.974 0.330236    
-helpful_people_2016  -0.037513   0.035353  -1.061 0.288643    
-fair_people_2016     -0.017081   0.030170  -0.566 0.571294    
-imiss_a_2016          0.397121   0.138987   2.857 0.004273 ** 
-imiss_b_2016         -0.250803   0.155454  -1.613 0.106667    
-imiss_c_2016          0.017536   0.090647   0.193 0.846606    
-imiss_d_2016          0.043510   0.122118   0.356 0.721619    
-imiss_e_2016         -0.095552   0.078603  -1.216 0.224126    
-imiss_f_2016         -0.323280   0.105432  -3.066 0.002168 ** 
-imiss_g_2016         -0.332034   0.078673  -4.220 2.44e-05 ***
-imiss_h_2016         -0.157298   0.107111  -1.469 0.141954    
-imiss_i_2016          0.088695   0.091467   0.970 0.332196    
-imiss_j_2016          0.060271   0.138429   0.435 0.663280    
-imiss_k_2016         -0.181030   0.082726  -2.188 0.028646 *  
-imiss_l_2016          0.274689   0.106781   2.572 0.010098 *  
-imiss_m_2016         -0.124269   0.147888  -0.840 0.400746    
-imiss_n_2016         -0.441612   0.090040  -4.905 9.36e-07 ***
-imiss_o_2016          0.198635   0.143160   1.388 0.165286    
-imiss_p_2016          0.102987   0.105669   0.975 0.329751    
-imiss_q_2016          0.244567   0.119093   2.054 0.040017 *  
-imiss_r_2016          0.198839   0.121969   1.630 0.103050    
-imiss_s_2016         -0.067310   0.134465  -0.501 0.616666    
-imiss_t_2016         -0.116757   0.068143  -1.713 0.086639 .  
-imiss_u_2016          0.022902   0.097312   0.235 0.813939    
-imiss_x_2016         -0.017789   0.097349  -0.183 0.855003    
-imiss_y_2016          0.150205   0.094536   1.589 0.112092    
 
+---
+
+![](https://github.com/juliasilge/course-ML-tidymodels/blob/master/img/upsample2.png?raw=true)
+
+Notes: When we implement upsampling, we add more of the people who did not vote (just more of the same ones we already have) until the proportion is equal and the classes are balanced. 
+
+We are going to use [`step_upsample()`](https://tidymodels.github.io/recipes/reference/step_upsample.html) for oversampling because it is simple to implement and understand, but it can lead a classifier to overfit to just a few examples, if you're not lucky. There are other more complex approaches to oversampling available in the [themis](https://tidymodels.github.io/themis/) package, but we will focus on random upsampling with replacement here.
+
+---
+
+# Preprocess your data
+
+```r
+vote_recipe <- recipe(turnout16_2016 ~ ., data = vote_train) %>% 
+    step_upsample(turnout16_2016)
 ```
 
-Notes: Another good step before you start training more complex models is to start with just the absolute, simplest model possible, to get your bearings and have a baseline for comparison. You also can use a model like this to understand which predictors are driving, in our case here, the likelihood of people to vote.
+Notes: Upsampling is another example of a preprocessing step for modeling. You can again preprocess your data using [recipes](https://tidymodels.github.io/recipes/). The recipe shown in this slide again has just one preprocessing step (upsampling) but you can create recipes for preprocessing with as many steps as you need.
 
 ---
 
-# Fitting a simple model
+# Build a `workflow()`
 
 ```r
-library(broom)
- 
-tidy(simple_glm) %>%
-    filter(p.value < 0.05) %>%
-    arrange(desc(estimate))
+vote_wf <- workflow() %>%
+    add_recipe(vote_recipe) %>%
+    add_model(rf_spec)
+
+vote_wf
 ```
 
 ```out
-                   term    estimate  std.error statistic      p.value
-1           (Intercept)  2.45703562 0.73272138  3.353301 7.985370e-04
-2          imiss_a_2016  0.39712084 0.13898678  2.857256 4.273207e-03
-3          imiss_l_2016  0.27468893 0.10678119  2.572447 1.009825e-02
-4          imiss_q_2016  0.24456695 0.11909335  2.053573 4.001699e-02
-5            track_2016  0.24107452 0.12146679  1.984695 4.717843e-02
-6  RIGGED_SYSTEM_1_2016  0.23628350 0.08508091  2.777162 5.483579e-03
-7      futuretrend_2016  0.21056782 0.07120079  2.957380 3.102651e-03
-8  RIGGED_SYSTEM_5_2016  0.19025188 0.09645384  1.972466 4.855648e-02
-9           wealth_2016 -0.06940523 0.02634395 -2.634580 8.424157e-03
-10         imiss_k_2016 -0.18103020 0.08272555 -2.188323 2.864611e-02
-11       econtrend_2016 -0.29536980 0.08722417 -3.386330 7.083422e-04
-12         imiss_f_2016 -0.32328040 0.10543220 -3.066240 2.167694e-03
-13         imiss_g_2016 -0.33203385 0.07867346 -4.220405 2.438640e-05
-14         imiss_n_2016 -0.44161183 0.09003981 -4.904628 9.360434e-07
+══ Workflow ══════════════════════════════════════════════════════════════════
+Preprocessor: Recipe
+Model: rand_forest()
+
+── Preprocessor ──────────────────────────────────────────────────────────────
+1 Recipe Step
+
+● step_upsample()
+
+── Model ─────────────────────────────────────────────────────────────────────
+Random Forest Model Specification (classification)
+
+Computational engine: ranger 
 ```
 
-Notes: If you look at what these survey questions are, you'll see that when a respondent thinks that crime is an important issue, tabulated in the column `imiss_a_2016`, they are less likely to vote but when a respondent thinks that infrastructure improvements are an important issue, the column `imiss_n_2016`, they are more likely to vote.
+Notes: To put our recipe and our model specification together, let's use a [`workflow()`](https://tidymodels.github.io/workflows/). We can fit our workflow much like we would fit a model.
 
 ---
 
 # Let's build some models!✨
 
-Notes: Now that you have explored your data and have some understanding of it, it's time to move into preparing for machine learning.
+Notes: Now that you have explored your data and have some understanding of it, it's time to move into machine learning.
 
diff --git a/slides/chapter3_10.md b/slides/chapter3_10.md
index 567eed9..673282e 100644
--- a/slides/chapter3_10.md
+++ b/slides/chapter3_10.md
@@ -5,7 +5,7 @@ type: slides
 # Cross-validation
 
 
-Notes: You have created a training set and testing set and laid out how to deal with class imbalance via upsampling. Now it's time to talk about a new resampling approach. In the first two case studies, we used bootstrap resampling and talked through what that means. In this chapter, we're going to use **cross-validation**.
+Notes: You have created a training set and testing set and laid out how to deal with class imbalance via upsampling. Now it's time to talk about a new resampling approach. In the first case study, we used bootstrap resampling and talked through what that means. In this chapter, we're going to use **cross-validation**.
 
 ---
 
@@ -15,7 +15,7 @@ Partitioning your data into subsets and using one subset for validation
 
 Notes: Cross-validation means taking your training set and randomly dividing it up evenly into subsets, sometimes called "folds". A fold here means a group or subset or partition. 
 
-You use one of the folds for validation and the rest for training, then you repeat these steps with all the subsets and combine the results, usually by taking the mean. The reason we do this is the same reason we would use bootstrap resampling; cross-validation allows you to reduce overfitting and get a more accurate estimate of how your model will perform on new data.
+You use one of the folds for validation and the rest for training, then you repeat these steps with all the subsets and combine the results, usually by taking the mean. The reason we do this is the same reason we would use bootstrap resampling; cross-validation allows you to get a more accurate estimate of how your model will perform on new data.
 
 ---
 
@@ -23,39 +23,43 @@ You use one of the folds for validation and the rest for training, then you repe
 
 Partitioning your data into subsets and using one subset for validation
 
-- `method = "cv"`
-- `method = "repeatedcv"`
+- `vfold_cv(vote_train, v = 10)`
+- `vfold_cv(vote_train, v = 10, repeats = 5)`
 
 
-Notes: In caret, you implement this within the call to `trainControl()` with `method = "cv"` or `method = "repeatedcv"`. Let's look at this in more detail. 🧐
+Notes: In tidymodels, you can create cross-validation resamples with the function `vfold_cv()`, either with or without the `repeats` argument. 
+
+Let's look at this in more detail. 🧐
 
 ---
 
 ![Alt text](https://github.com/juliasilge/supervised-ML-case-studies-course/blob/master/img/crossvalidation1.png?raw=true)
 
 
-Notes: Let's say we have a sample of lots of people, some of whom voted and some of whom did not, and we want to implement 10-fold cross-validation. This means we divide our training data into 10 groups or folds, and 1 subset or fold acts as our validation fold. We train our model on 9 of the folds and then evaluate the model on the validation fold.
+Notes: Let's say we have a sample of lots of people, some of whom voted and some of whom did not, and we want to implement 10-fold cross-validation. This means we divide our training data into 10 groups or folds, and 1 subset or fold acts as our assessment fold (like a mini testing test). We train our model on 9 of the folds and then evaluate the model on the assessment fold.
+
+If we are using preprocessing steps such as upsampling that should **only** be applied to the 9/10 of the data used for analysis (not the 1/10 of the data used for assessment), the [recipes](https://tidymodels.github.io/recipes/) package will automatically take care of that for us. 👍
 
 ---
 
 ![Alt text](https://github.com/juliasilge/supervised-ML-case-studies-course/blob/master/img/crossvalidation2.png?raw=true)
 
-Notes: Now we move to the next fold and do this again. We train the model on the rest of the data, the other 9 folds, and evaluate the model on 1/10 of the data, the fold that is currently acting as our validation fold.
+Notes: Now we move to the next fold and do this again. We train the model on the rest of the data, the other 9 folds, and evaluate the model on 1/10 of the data, the fold that is currently acting as our assessment fold.
 
 ---
 
 ![Alt text](https://github.com/juliasilge/supervised-ML-case-studies-course/blob/master/img/crossvalidation3.png?raw=true)
 
-Notes: We do it again using another of our folds as the validation fold, training the model on the rest of the data, and we move through all the subsets or folds of the data that we made...
+Notes: We do it again using another of our folds as the assessment fold, training the model on the rest of the data, and we move through all the subsets or folds of the data that we made...
 
 ---
 
 
 ![Alt text](https://github.com/juliasilge/supervised-ML-case-studies-course/blob/master/img/crossvalidation4.png?raw=true)
 
-Notes: ... until we do them all, and have trained the model 10 times, on 10 different subsets of the data, with 10 different validation sets. We then combine all those models together to get one, better performing model. 
+Notes: ... until we do them all, and have trained the model 10 times, on 10 different subsets of the data, with 10 different assessment sets. We then combine all those results together to get one, better estimate of how our model will perform. 
 
-This procedure I just described is **one round of 10-fold cross-validation**. It's typical practice to do this more than once, perhaps 5 times. In that case, you repeat the whole process of 10-fold cross-validation 5 times, with 5 different random partitionings into 10 subsets. This is an approach to training models that has demonstrated good performance.
+This procedure I just described is **one round of 10-fold cross-validation**. Sometimes practictioners do this more than once, perhaps 5 times. In that case, you repeat the whole process of 10-fold cross-validation 5 times, with 5 different random partitionings into 10 subsets. This is an approach to training models that has demonstrated good performance.
 
 ---
 
diff --git a/slides/chapter3_13.md b/slides/chapter3_13.md
index 7063a3d..036058b 100644
--- a/slides/chapter3_13.md
+++ b/slides/chapter3_13.md
@@ -2,122 +2,95 @@
 type: slides
 ---
 
-# Comparing model performance
+# Evaluate model performance
 
-Notes: Excellent job! You trained logistic regression models and random forest models with oversampling to account for class imbalance and cross-validation to get a more accurate estimate for model performance. 😎 Let's talk about that model performance now.
+Notes: Excellent job! You preprocessed this data, built a modeling workflow, and created cross-validation folds to evaluate model performance. 😎 
+
+Let's talk about that model performance now, how to set _non-default performance metrics_ and save _predictions_ from resampled data.
 
 ---
 
-# Confusion matrix
+# Evaluate models with resampling
 
 ```r
-vote_train %>%
-    mutate(`Logistic regression` = predict(vote_glm, vote_train)) %>%
-    conf_mat(truth = turnout16_2016, estimate = "Logistic regression")
-```
-```out
-              Truth
-Prediction     Did not vote Voted
-  Did not vote          160  1557
-  Voted                  62  3575
-```
+vote_wf %>%
+    fit_resamples(
+        vote_folds,
+        metrics = metric_set(roc_auc, sens, spec),
+        control = control_resamples(save_pred = TRUE)
+    )
+```    
 
-Notes: If we start by looking at the confusion matrix for the training data and the logistic regression model, you can see that sensitivity and specificity (the true positive and true negative rates) are both around 70%, which means that most people are being classified into the right categories.
+Notes: Just like in our first case study, we can use the function `fit_resamples()` to fit a model (a workflow in this case, actually, that holds both a preprocessor and a model specification) to each cross-validation fold and compute performance metrics. The code shown on this slide will fit our workflow `vote_wf` to the cross-validation folds in `vote_folds` and determine how well the model performed each time.
 
+The fitted models themselves are not kept or stored because they are only used for computing performance metrics. However, we are saving the predictions with `save_pred = TRUE` so we can build a confusion matrix, and we have also set _specific performance metrics_ to be computed (instead of the defaults) with `metric_set(roc_auc, sens, spec)`. We will have: 
+
+- the area under the ROC curve, 
+- sensitivity, and 
+- specificity.
 
 ---
 
-# Confusion matrix
+# Metrics for classification models
 
 ```r
-vote_train %>%
-    mutate(`Random forest` = predict(vote_rf, vote_train)) %>%
-    conf_mat(truth = turnout16_2016, estimate = "Random forest")
+collect_metrics(glm_res)
 ```
-
 ```out
-              Truth
-Prediction     Did not vote Voted
-  Did not vote          222     0
-  Voted                   0  5132   
+# A tibble: 3 x 5
+  .metric .estimator  mean     n std_err
+  <chr>   <chr>      <dbl> <int>   <dbl>
+1 roc_auc binary     0.726    10 0.0131 
+2 sens    binary     0.639    10 0.0330 
+3 spec    binary     0.706    10 0.00810
 ```
 
-Notes: When we look at the confusion matrix for the training data and the random forest model, we see much higher performance. Random forest models are much more powerful and in general, capable of much higher accuracy than logistic regression models. This model has done a perfect job of classifying the training data into these two categories. Almost *too* perfect, we might suspect. 😒 To evaluate how the models will perform on new data, we don't want to look at the training data; we want to look at the **testing data**.
+Notes: If we start by looking at the metrics for the logistic regression model, you can see that sensitivity and specificity (the true positive and true negative rates) are both around 0.6 or 0.7, which means that most people are being classified into the right categories but we are not getting fantastic results with this model.
 
 ---
 
-# Confusion matrix for the testing data
+# Metrics for classification models
 
 ```r
-vote_test %>%
-    mutate(`Logistic regression` = predict(vote_glm, vote_test)) %>%
-    conf_mat(truth = turnout16_2016, estimate = "Logistic regression")
+collect_metrics(rf_res)
 ```
-
 ```out
-              Truth
-Prediction     Did not vote Voted
-  Did not vote           28   359
-  Voted                  14   937
+# A tibble: 3 x 5
+  .metric .estimator  mean     n  std_err
+  <chr>   <chr>      <dbl> <int>    <dbl>
+1 roc_auc binary     0.746    10 0.0159  
+2 sens    binary     0        10 0       
+3 spec    binary     1.00     10 0.000193
 ```
 
-Notes: When we look at the testing data and the logistic regression model, we see performance that is about the same as what we saw with the training data. This means that this model is not overfit. We will expect this model to perform about this well on any new data. 😊
+Notes: When we look at the metrics for the random forest model, we see that the AUC is higher, but sensitivity (the true positive rate, or recall) has dropped to zero! 😱 The random forest model is not able to identify **any** of the people who did not vote.  
 
+What we're seeing here is evidence of dramatic overfitting, despite the fact that we used cross-validation. For the amount of data we have available to train this model, the power of a random forest ends up resulting in memorization of the features of the training set, instead of building a useful predictive model. Our choice to use upsampling (where the same small number of positive cases were drawn from again and again) likely made this worse!
 
+Notice that this is the first time that this has happened in this course. In the first and second case studies we did, the more powerful machine learning algorithm outperformed the simpler model.
 ---
 
-# Confusion matrix for the testing data
-
+# Confusion matrix
 
 ```r
-vote_test %>%
-    mutate(`Random forest` = predict(vote_rf, vote_test)) %>%
-    conf_mat(truth = turnout16_2016, estimate = "Random forest")
+vote_final <- vote_wf %>%
+    last_fit(vote_split)
+
+vote_final %>% 
+    collect_predictions() %>% 
+    conf_mat(turnout16_2016, .pred_class)
 ```
 
 ```out
               Truth
 Prediction     Did not vote Voted
-  Did not vote            0     3
-  Voted                  42  1293
+  Did not vote           25   372
+  Voted                  23   918
 ```
 
-Notes: The same, sadly, cannot be said for the random forest model. Notice that here with the testing data, it did not correctly predict for any of the people who did not vote. 😱 What we're seeing here is evidence of dramatic overfitting, despite the fact that we used cross-validation. For the amount of data we have available to train this model, the power of a random forest ends up resulting in memorization of the features of the training set, instead of building a useful predictive model.
-
-
----
-
-# Comparing model performance
-
-```
-> library(yardstick)
-> 
-> sens(testing_results, truth = turnout16_2016, estimate = `Logistic regression`)
-# A tibble: 1 x 3
-  .metric .estimator .estimate
-  <chr>   <chr>          <dbl>
-1 sens    binary         0.667
-> 
-> spec(testing_results, truth = turnout16_2016, estimate = `Logistic regression`)
-# A tibble: 1 x 3
-  .metric .estimator .estimate
-  <chr>   <chr>          <dbl>
-1 spec    binary         0.723
-> 
-> sens(testing_results, truth = turnout16_2016, estimate = `Random forest`)
-# A tibble: 1 x 3
-  .metric .estimator .estimate
-  <chr>   <chr>          <dbl>
-1 sens    binary             0
-> 
-> spec(testing_results, truth = turnout16_2016, estimate = `Random forest`)
-# A tibble: 1 x 3
-  .metric .estimator .estimate
-  <chr>   <chr>          <dbl>
-1 spec    binary         0.998
-```
+Notes: The logistic regression model will likely be the best option, so we can evaluate its performance on the testing data. We can use the [`last_fit()`](https://tidymodels.github.io/tune/reference/last_fit.html) function with a workflow to fit to the entire training set and evaluate on the testing set. You only need to give this function the **split** object!
 
-Notes: When we look here at some of the individual model metrics, you can see this again, that the sensitivity, or true positive rate, is dramatically lower for the random forest model than for the logistic regression model when evaluated on the testing data. Notice that this is the first time that this has happened in this course. In the first and second case studies we did, the more powerful machine learning algorithm outperformed the simpler model.
+We can see that we did a better job identifying the people who voted than those who did not.
 
 ---
 
diff --git a/slides/chapter4_01.md b/slides/chapter4_01.md
index ebbf619..89cc994 100644
--- a/slides/chapter4_01.md
+++ b/slides/chapter4_01.md
@@ -38,32 +38,32 @@ Notes: There is demographic information in the survey, along with a lot of diver
 
 # Opinions and attitudes in the 1960s
 
-```
+```r
 > sisters67
-
+```
+```out
 # A tibble: 77,112 x 67
-     age sister  v116  v117  v118  v119  v120  v121  v122  v123  v124  v125
-   <dbl>  <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int>
- 1  60.0      1     1     1     3     5     1     1     3     5     3     1
- 2  70.0      2     2     2     4     4     1     3     1     5     4     1
- 3  60.0      3     1     1     3     2     2     3     1     1     3     1
- 4  60.0      4     5     1     2     4     1     3     4     3     3     4
- 5  50.0      5     2     3     3     3     2     2     1     5     2     5
- 6  40.0      7     4     3     2     5     4     3     1     5     2     5
- 7  50.0      9     5     4     5     4     4     5     3     5     4     2
- 8  40.0     10     5     4     3     5     1     3     5     5     5     4
- 9  30.0     11     2     2     3     5     1     3     3     5     1     3
-10  30.0     12     4     1     5     5     1     4     3     5     1     5
-# ... with 77,102 more rows, and 55 more variables: v126 <int>, v127 <int>,
-#   v128 <int>, v129 <int>, v130 <int>, v131 <int>, v132 <int>, v133 <int>,
-#   v134 <int>, v135 <int>, v136 <int>, v137 <int>, v138 <int>, v139 <int>,
-#   v140 <int>, v141 <int>, v142 <int>, v143 <int>, v144 <int>, v145 <int>,
-#   v146 <int>, v147 <int>, v148 <int>, v149 <int>, v150 <int>, v151 <int>,
-#   v152 <int>, v153 <int>, v154 <int>, v155 <int>, v156 <int>, v157 <int>,
-#   v158 <int>, v159 <int>, v160 <int>, v161 <int>, v162 <int>, v163 <int>,
-#   v164 <int>, v165 <int>, v166 <int>, v167 <int>, v168 <int>, v169 <int>,
-#   v170 <int>, v171 <int>, v172 <int>, v173 <int>, v174 <int>, v175 <int>,
-#   v176 <int>, v177 <int>, v178 <int>, v179 <int>, v180 <int>
+     age sister  v116  v117  v118  v119  v120  v121  v122  v123  v124  v125  v126  v127
+   <dbl>  <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+ 1    60      1     1     1     3     5     1     1     3     5     3     1     1     3
+ 2    70      2     2     2     4     4     1     3     1     5     4     1     4     4
+ 3    60      3     1     1     3     2     2     3     1     1     3     1     1     1
+ 4    60      4     5     1     2     4     1     3     4     3     3     4     1     1
+ 5    50      5     2     3     3     3     2     2     1     5     2     5     5     5
+ 6    40      7     4     3     2     5     4     3     1     5     2     5     4     4
+ 7    50      9     5     4     5     4     4     5     3     5     4     2     1     5
+ 8    40     10     5     4     3     5     1     3     5     5     5     4     1     5
+ 9    30     11     2     2     3     5     1     3     3     5     1     3     1     2
+10    30     12     4     1     5     5     1     4     3     5     1     5     1     1
+# … with 77,102 more rows, and 53 more variables: v128 <dbl>, v129 <dbl>, v130 <dbl>,
+#   v131 <dbl>, v132 <dbl>, v133 <dbl>, v134 <dbl>, v135 <dbl>, v136 <dbl>, v137 <dbl>,
+#   v138 <dbl>, v139 <dbl>, v140 <dbl>, v141 <dbl>, v142 <dbl>, v143 <dbl>, v144 <dbl>,
+#   v145 <dbl>, v146 <dbl>, v147 <dbl>, v148 <dbl>, v149 <dbl>, v150 <dbl>, v151 <dbl>,
+#   v152 <dbl>, v153 <dbl>, v154 <dbl>, v155 <dbl>, v156 <dbl>, v157 <dbl>, v158 <dbl>,
+#   v159 <dbl>, v160 <dbl>, v161 <dbl>, v162 <dbl>, v163 <dbl>, v164 <dbl>, v165 <dbl>,
+#   v166 <dbl>, v167 <dbl>, v168 <dbl>, v169 <dbl>, v170 <dbl>, v171 <dbl>, v172 <dbl>,
+#   v173 <dbl>, v174 <dbl>, v175 <dbl>, v176 <dbl>, v177 <dbl>, v178 <dbl>, v179 <dbl>,
+#   v180 <dbl>
 ```
 
 Notes: The integer 1 corresponds to "disagree very much" and 5 corresponds to "agree very much". This kind of coding is convenient for our modeling purposes here. The data that you will have available within this case study is only this subset of the survey: the agree/disagree statements, plus age.
@@ -71,7 +71,7 @@ Notes: The integer 1 corresponds to "disagree very much" and 5 corresponds to "a
 
 ---
 
-![Alt text](https://github.com/juliasilge/supervised-ML-case-studies-course/blob/master/img/age_histogram.png?raw=true)
+![Alt text](https://github.com/juliasilge/course-ML-tidymodels/blob/master/img/age_histogram.png?raw=true)
 
 Notes: The original survey question asked for age in bins of 10 years, under 20, from 21 to 30, from 31 to 40, and so forth. I have recoded these as numeric values corresponding to the top of each age bin, 20, 30, 40, and so on. This means that this isn't quite a continuous variable, since we haven't measured these women's ages very precisely, but we can do a pretty good job modeling it as if it is. There are more sophisticated modeling approaches possible with these kinds of measurements that you could explore.  
 
@@ -95,27 +95,29 @@ I do want to point out that this survey was fielded during the 1960s and there a
 ```r
 sisters67 %>%
     select(-sister) %>%
-    gather(key, value, -age)
+    pivot_longer(-age, names_to = "question", values_to = "rating")
 ```
 
 ```out
 # A tibble: 5,012,280 x 3
-     age key   value
-   <dbl> <chr> <int>
- 1  60.0 v116      1
- 2  70.0 v116      2
- 3  60.0 v116      1
- 4  60.0 v116      5
- 5  50.0 v116      2
- 6  40.0 v116      4
- 7  50.0 v116      5
- 8  40.0 v116      5
- 9  30.0 v116      2
-10  30.0 v116      4
-# ... with 5,012,270 more rows
+     age question rating
+   <dbl> <chr>     <dbl>
+ 1    60 v116          1
+ 2    60 v117          1
+ 3    60 v118          3
+ 4    60 v119          5
+ 5    60 v120          1
+ 6    60 v121          1
+ 7    60 v122          3
+ 8    60 v123          5
+ 9    60 v124          3
+10    60 v125          1
+# … with 5,012,270 more rows
 ```
 
-Notes: In this case study, we are going to spend a bit more effort on exploratory data analysis. You are going to create a tidy version of the survey data with one row per observation. In the original way the data is structured, there is one row per respondent with a separate column for each answer. After you tidy the data, using the function [`gather()`](https://tidyr.tidyverse.org/reference/gather.html), you will have one row for each combination of respondent and question, a much longer and skinnier dataset. This kind of tidy data structure is well suited to exploratory data analysis.
+Notes: In this case study, we are going to spend a bit more effort on exploratory data analysis. You are going to create a tidy version of the survey data with one row per observation. 
+
+In the original way the data is structured, there is one row per respondent with a separate column for each answer. After you tidy the data, using the function [`pivot_longer()`](https://tidyr.tidyverse.org/reference/pivot_longer.html), you will have one row for each combination of respondent and question, a much longer and skinnier dataset. This kind of tidy data structure is well suited to exploratory data analysis.
 
 ---
 
diff --git a/slides/chapter4_05.md b/slides/chapter4_05.md
index dce8c86..2de1f08 100644
--- a/slides/chapter4_05.md
+++ b/slides/chapter4_05.md
@@ -12,13 +12,13 @@ Notes: You just created a tidy version of this survey data, which allows you to
 
 ```r
 tidy_sisters %>%
-    count(value)
+    count(rating)
 ```
 
 ```out
 # A tibble: 5 x 2
-  value       n
-  <int>   <int>
+  rating      n
+  <dbl>   <int>
 1     1 1303555
 2     2  844311
 3     3  645401
@@ -37,22 +37,22 @@ We can see here that 1 was the most commonly chosen option; this corresponds to
 ```r
 tidy_sisters %>%
     group_by(age) %>%
-    summarise(value = mean(value))
+    summarise(rating = mean(rating))
 ```
 
 ```out
 # A tibble: 9 x 2
-    age value
-  <dbl> <dbl>
-1  20.0  2.86
-2  30.0  2.81
-3  40.0  2.83
-4  50.0  2.94
-5  60.0  3.10
-6  70.0  3.26
-7  80.0  3.42
-8  90.0  3.51
-9 100    3.60
+    age rating
+  <dbl>  <dbl>
+1    20   2.86
+2    30   2.81
+3    40   2.83
+4    50   2.94
+5    60   3.10
+6    70   3.26
+7    80   3.42
+8    90   3.51
+9   100   3.60
 ```
 
 Notes: You can also check out how the overall answers to all survey questions vary with age. There were more statements on the survey that older respondents agreed with than statements younger respondents agreed with.
@@ -63,13 +63,13 @@ Notes: You can also check out how the overall answers to all survey questions va
 
 ```r
 tidy_sisters %>%
-    filter(key %in% paste0("v", 153:170)) %>%
-    group_by(key, value) %>%
+    filter(question %in% paste0("v", 153:170)) %>%
+    group_by(question, rating) %>%
     summarise(age = mean(age)) %>%
-    ggplot(aes(value, age, color = key)) +
+    ggplot(aes(rating, age, color = question)) +
     geom_line(alpha = 0.5, size = 1.5) +
     geom_point(size = 2) +
-    facet_wrap(~key)
+    facet_wrap(~question)
 ```
 
 Notes: We can go a few steps further and dig into how the answers to individual questions depend on age. This code first filters to a subset of questions on the survey, groups by these survey questions and the possible answers to them, and then calculates the mean age for each possible answer to each of the questions we're considering. 
@@ -144,6 +144,41 @@ Notes: In this case study, you are going to split the original data into three s
 
 You've already used training and test sets throughout this course, and in this last case study we're going to talk about how to use a **validation set** to choose a model. 🧐
 
+---
+
+![Alt text](https://github.com/juliasilge/supervised-ML-case-studies-course/blob/master/img/validation.png?raw=true)
+
+Notes: In previous case studies, we used **resampling** to choose a model. Resampling lets you use your training data to create simulated datasets. These simulated datasets can help you learn which model is best without relying on performance metrics for the training set as a whole (which are overly optimistic) or the testing set (which can only be used one time at the very end of your analysis.)
+
+If you have enough data, you may not need resampling at all and instead can divide your data into a training set, a validation set, and a testing set. Instead of computing performance metrics on resampled datasets, you can compute them for the validation set. This survey of nuns is quite large so we can create a validation set to use for choosing a model. You can think of a validation set as a single resample.
+
+---
+
+```r
+set.seed(123)
+sisters_splits <- initial_split(sisters_select, strata = age)
+
+sisters_other <- training(sisters_splits)
+sisters_test <- testing(sisters_splits)
+
+set.seed(123)
+sisters_val <- validation_split(sisters_other, strata = age)
+
+sisters_val
+```
+
+```out
+# Validation Set Split (0.75/0.25)  using stratification 
+# A tibble: 1 x 2
+  splits                id        
+  <named list>          <chr>     
+1 <split [43.4K/14.5K]> validation
+```
+
+
+Notes: To split your data into **three** sets (training, validation, and testing), first make an `initial_split()` to split off your testing set from the rest. Then use the function `validation_split()` to create what you can think of as a single resample of that data.
+
+
 ---
 
 # Let's explore!
diff --git a/slides/chapter4_09.md b/slides/chapter4_09.md
new file mode 100644
index 0000000..3ae02f9
--- /dev/null
+++ b/slides/chapter4_09.md
@@ -0,0 +1,109 @@
+---
+type: slides
+---
+
+# Tune model hyperparameters
+
+Julia Silge
+Data Scientist at Stack Overflow
+
+Notes: You have prepared training, validation, and test sets and now it's time to build predictive models.
+
+---
+
+# What is a model hyperparameter?
+
+```r
+tree_spec <- decision_tree(
+  cost_complexity = tune(),
+  tree_depth = tune()
+) %>% 
+  set_engine("rpart") %>% 
+  set_mode("regression")
+```
+
+Notes: In this last case study, you are going to work with model hyperparameters for the first time in this course. Some model parameters cannot be learned directly from a dataset during model training; these kinds of parameters are called **hyperparameters**. 💥 Some examples of hyperparameters include the number of predictors that are sampled at splits in a tree-based model (we call this `mtry` in tidymodels) or the learning rate in a boosted tree model (we call this `learn_rate`). 
+
+Instead of learning these kinds of hyperparameters during model training, we can estimate the best values for these values by training many models on a resampled data set (like the validation set you just created) and measuring how well all these models perform. This process is called **tuning**.
+
+You can identify which parameters to `tune()` in a model specification as shown here. Let's build a decision tree model to predict age for our nuns, and tune the cost complexity and the maximum tree depth.
+
+---
+
+# Preprocessing and tuning
+
+```r
+sisters_recipe <- recipe(age ~ ., data = sisters_other) %>% 
+  step_normalize(all_predictors()) %>%
+  step_pca(all_predictors(), num_comp = tune())
+```
+
+Notes: Model hyperparameters aren't the only things you can tune. You can also tune steps in your preprocessing pipeline. This recipe has two steps:
+
+- First, this recipe centers and scales all those numeric predictors we have in this dataset, cataloging the nuns' responses to the survey questions.
+- Second, this recipe implements principal component analysis on these same predictors. Except... this recipe identifies that we _want_ to implement PCA and we aren't sure how many predictors we should use. We want to choose the best 🏆 number of predictors. 
+
+---
+
+# Grid of tuning parameters
+
+```r
+grid_regular(num_comp(c(3, 12)),
+             cost_complexity(),
+             tree_depth(),
+             levels = 5)
+```
+
+```out
+# A tibble: 125 x 3
+   num_comp cost_complexity tree_depth
+      <int>           <dbl>      <int>
+ 1        3    0.0000000001          1
+ 2        5    0.0000000001          1
+ 3        7    0.0000000001          1
+ 4        9    0.0000000001          1
+ 5       12    0.0000000001          1
+ 6        3    0.0000000178          1
+ 7        5    0.0000000178          1
+ 8        7    0.0000000178          1
+ 9        9    0.0000000178          1
+10       12    0.0000000178          1
+```
+
+Notes: You have a couple of options for how to choose which possible values for the tuning parameters to try. One option is to set up a grid of possible parameter values.
+
+Here, we are using default ranges for cost complexity and tree depth, and we are going to try 3 to 12 principal components. When we set `levels = 5`, we are saying we want five levels for each parameter, which means there will be 125 (`5 * 5 * 5`) total models to try. 
+
+You can use the function `tune_grid()` to fit all these models; you can tune either a workflow or a model specification with a set of resampled data, such as the validation set you created (i.e. a single resample).
+
+---
+
+![Validation](https://github.com/juliasilge/supervised-ML-case-studies-course/blob/master/img/validation.png?raw=true)
+
+Notes: You train these 125 possible models on the training data and use the validation data to compare all the results in terms of performance. We won't use the testing data until the very end of our modeling process, when we use it to estimate how our model will perform on new data.
+
+---
+
+# Why three data partitions?
+
+Don't overestimate how well your model is performing! 🙅
+
+Notes: For some modeling use cases, an approach with three data partitions is overkill, perhaps a bit too much, but if you have enough data that you can use some of these powerful machine learning algorithms or techniques, the danger you face is underestimating your uncertainty for new data if you estimate it with data that you used to pick a model. 
+
+To get a reliable estimate from tuning, for example, you need to use another heldout dataset for assessing the models, either a validation set or a set of simulated datasets created through resampling.
+
+---
+
+![tune results](https://github.com/juliasilge/course-ML-tidymodels/blob/master/img/tune_results.png?raw=true)
+
+
+Notes: This dataset of extensive survey responses from Catholic nuns in the 1960s is a great demonstration of all of these issues. You will use your validation set to find which values of the parameters (cost complexity, tree depth, and number of principal components) result in the highest R-squared and lowest RMSE. Notice here that we get the best results with a tree depth of 4 and 5 principal components.
+
+As you work through the final set of exercises, you will see all of this come together, along with all the other practical predictive modeling skills we've explored in this course.
+
+---
+
+# Let's practice! ✨
+
+Notes: It's time to finish out this course with the final models that you need to train and evaluate.
+
diff --git a/slides/chapter4_10.md b/slides/chapter4_10.md
deleted file mode 100644
index d7dca1c..0000000
--- a/slides/chapter4_10.md
+++ /dev/null
@@ -1,95 +0,0 @@
----
-type: slides
----
-
-# Predicting age with supervised machine learning
-
-Julia Silge
-Data Scientist at Stack Overflow
-
-Notes: You have prepared training, validation, and test sets and now it's time to build predictive models.
-
----
-
-# Build models
-
-- `"rpart"` 
-- `"xgbLinear"` 
-- `"gbm"` 
-
-Notes: In this last case study, you are going to experiment with three new model types, [all available in caret](https://topepo.github.io/caret/available-models.html), that we haven't had a chance to try out yet in this course. The first kind, that you will train in an exercise, is a CART model, implemented in the rpart package. This is a moderately simple tree-based model. 
-
-The second kind of model, that we will provide in your environment as a trained model, is an extreme gradient boosting model, often called xgboost. 
-
-The third type of model is a different implementation of gradient boosting regression. Gradient boosting involves taking a whole lot of very simple predictive models (usually trees, again) and then ensembling them to get a really good predictive model. They can take a long time to train, so we'll provide you with already trained models to evaluate. These kinds of models do have tuning parameters, but understanding those in detail is beyond the scope of this course. We're going to stick with the defaults.
-
----
-
-# Choosing between multiple models
-
-```r
-## CART
-sisters_cart <- train(age ~ ., method = "rpart", data = sisters_train)
-
-## xgboost
-sisters_xg <- train(age ~ ., method = "xgbLinear", data = sisters_train)
-
-## gbm
-sisters_gbm <- train(age ~ ., method = "gbm", data = sisters_train)
-```
-
-Notes: You will use your training dataset when you train the models, as you have throughout this course. In the other case studies, we stuck with just two kinds of models and didn't explore a lot of ways to tune them. We trained the models using the training set, and then tested them using the testing set. 
-
-If you stop 🛑 to think about what we were doing when we used the test set, though, you'll realize there is more than one thing going on. We looked at model performance on the test set, decided which model was best, and then assumed that same model performance would apply to new data.
-
----
-
-![Alt text](https://github.com/juliasilge/supervised-ML-case-studies-course/blob/master/img/validation.png?raw=true)
-
-Notes: Once you start exploring multiple kinds of models, say linear regression plus random forest plus gradient boosting plus maybe trying out different kinds of resampling techniques, then you need to take a step back and recognize that you need three datasets.
-
-You will train your models on the training data, use the validation data to compare all these different models you are trying out, and then estimate uncertainty or error using the test data, which is a separate set of data that you have not touched yet in this whole process.
-
----
-
-# Why three data partitions?
-
-Don't overestimate how well your model is performing! 🙅
-
-Notes: In some cases, this approach is overkill, just too much and not appropriate, but if you have enough data that you can use some of these powerful machine learning techniques, the danger you face is underestimating your uncertainty for new data if you estimate it with data that you used to pick a model. To get the best estimate for prediction errors or prediction uncertainty, you need to use another heldout dataset.
-
----
-
-# Why three data partitions?
-
-```r
-sisters_validate %>%
-    mutate(prediction = predict(sisters_gbm, sisters_validate)) %>%
-    rmse(truth = age, estimate = prediction)
-```
-```out
-# A tibble: 1 x 3
-  .metric .estimator .estimate
-  <chr>   <chr>          <dbl>
-1 rmse    standard        12.6
-```
-```r
-sisters_test %>%
-    mutate(prediction = predict(sisters_gbm, sisters_test)) %>%
-    rmse(truth = age, estimate = prediction)
-```
-```out
-# A tibble: 1 x 3
-  .metric .estimator .estimate
-  <chr>   <chr>          <dbl>
-1 rmse    standard        12.7
-```
-
-Notes: This dataset of extensive survey responses from Catholic nuns in the 1960s is a great demonstration of all of these issues. As you work through the final set of exercises, you will see all of this come together, along with all the other practical predictive modeling skills we've explored in this course.
-
----
-
-# Let's practice! ✨
-
-Notes: It's time to finish out this course with the final models that you need to train and evaluate.
-
diff --git a/slides/chapter4_15.md b/slides/chapter4_15.md
deleted file mode 100644
index b389937..0000000
--- a/slides/chapter4_15.md
+++ /dev/null
@@ -1,129 +0,0 @@
----
-type: slides
----
-
-# You made it! 💪
-
-Notes: Congratulations! You finished our fourth and final case study in this course on case studies in supervised machine learning.
-
----
-
-# Predicting age
-
-```r
-rmse(modeling_results, truth = age, estimate = CART)
-```
-
-```out
-# A tibble: 3 x 3
-  .metric .estimator .estimate
-  <chr>   <chr>          <dbl>
-1 rmse    standard        14.7
-```
-
-```r
-rmse(modeling_results, truth = age, estimate = GBM)
-```
-
-```out
-# A tibble: 3 x 3
-  .metric .estimator .estimate
-  <chr>   <chr>          <dbl>
-1 rmse    standard        12.6 
-```
-
-```r
-rmse(modeling_results, truth = age, estimate = XBG)
-```
-
-```out
-# A tibble: 3 x 3
-  .metric .estimator .estimate
-  <chr>   <chr>          <dbl>
-1 rmse    standard        12.5
-```
-
-Notes: You found that in this case study on the beliefs and opinions of Catholic nuns in the 1960s, the XGBoost gradient boosting model performed best, at least using the defaults for the various tuning parameters. 
-
----
-
-# Predicting age
-
-- **Build** your model with your training data
-- **Choose** your model with your validation data
-- **Evaluate** your model with your testing data
-
-Notes: You divided your data into three subsets, used a training set to train your models, a validation set to choose between them, and then a testing set to evaluate the performance of your model and estimate how it will do with new data.
-
----
-
-# Diverse data, powerful tools
-
-- Fuel efficiency of cars 🚗
-- Developers working remotely in the Stack Overflow survey 💻
-- Voter turnout in 2016 🗳
-- Catholic nuns' ages based on beliefs and attitudes ⛪
-
-Notes: This analysis was just the final example in the series of predictive projects you approached in this course. 
-
-You learned how to go from raw data to exploring that data to training models to evaluating those models using the [caret](https://topepo.github.io/caret/) package, the [tidymodels](https://github.com/tidymodels) metapackage, and important tools for exploratory data analysis from the [tidyverse](https://tidyverse.tidyverse.org/) ecosystem, like dplyr and ggplot2.
-
----
-
-#  Practical machine learning
-
-- Dealing with class imbalance
-- Improving performance with resampling (bootstrap, cross-validation)
-
-Notes: In this course, I've chosen to spend our energy and time on some of the issues that I have found to be the most important and most impactful from my real world, practical predictive modeling experience. These include knowing what to do when you are faced with class imbalance, and having some options in your toolkit for resampling approaches. 
-
----
-
-# Practical machine learning
-
-- Dealing with class imbalance
-- Improving performance with resampling (bootstrap, cross-validation)
-- Hyperparameter tuning?
-
-Notes: By contrast, we haven't talked about hyperparameter tuning for any of these models. That is something you can do to improve performance for models like xgboost, but I'll be honest, in my real world work, the gains from optimizing hyperparameters have been smaller, compared to gains from time spent on the other practical considerations we have explored in this course.
-
----
-
-# Practical machine learning
-
-- Try out multiple modeling approaches for each new problem 
-- Overall, [gradient tree boosting and random forest](https://arxiv.org/abs/1708.05070v1) 🌳 perform well
-
-Notes: The high level takeaways that you should remember from this course are first, that each time you have a new predictive modeling problem you are working on, you need to try out multiple different kinds of models. You don't know ahead of time which kind of model is going to perform best. This paper linked here uses some super interesting analysis to show that most often, the two kinds of models that perform best are gradient tree boosting and random forest. 
-
-However, depending on how much data you have and the specifics of your problem, that may not be true, so you have to try it for yourself. Also, start with a **simple model** to compare to. 
-
----
-
-# Never skip exploratory data analysis ✅
-
-
-
-Notes: And perhaps most importantly, never skip exploratory data analysis when you build machine learning models. It is time well spent, because when you understand a data set better, you can do a better job of building accurate models that perform better.
-
----
-
-# Go train some models!
-
-Notes: And that's our ultimate goal here! Thanks for spending time with me on this course. Now it's time for you to take what you've been practicing here and go apply it in the real world.
-
-If this course has been helpful to you, you can [buy me a coffee](https://ko-fi.com/U7U4WG9B) or chip in for hosting costs.
-
-[![ko-fi](https://www.ko-fi.com/img/githubbutton_sm.svg)](https://ko-fi.com/U7U4WG9B)
-
-
-
-
-
-
-
-
-
-
-
-
diff --git a/slides/chapter4_16.md b/slides/chapter4_16.md
new file mode 100644
index 0000000..f704831
--- /dev/null
+++ b/slides/chapter4_16.md
@@ -0,0 +1,162 @@
+---
+type: slides
+---
+
+# You made it! 💪
+
+Notes: Congratulations! You finished our fourth and final case study in this course on case studies in supervised machine learning.
+
+---
+
+# Predicting age
+
+
+```out
+── Model ──────────────────────────────────────────────────────────────────────
+n= 14460 
+
+node), split, n, deviance, yval
+      * denotes terminal node
+
+ 1) root 14460 3691121.000 48.11134  
+   2) PC1< 1.744274 10223 1988405.000 43.87362  
+     4) PC1< -0.3827951 7068 1163392.000 41.99774  
+       8) PC3< 1.289199 5743  864820.600 41.02037  
+        16) PC2>=-6.154196 5715  840659.100 40.90114 *
+        17) PC2< -6.154196 28    7496.429 65.35714 *
+       9) PC3>=1.289199 1325  269307.500 46.23396  
+        18) PC3< 2.638801 1079  211851.500 45.33828 *
+        19) PC3>=2.638801 246   52793.500 50.16260 *
+     5) PC1>=-0.3827951 3155  744421.700 48.07607  
+      10) PC3< 0.2146542 1643  342640.400 45.51430  
+        20) PC4>=-3.03208 1629  332107.700 45.36525 *
+        21) PC4< -3.03208 14    6285.714 62.85714 *
+      11) PC3>=0.2146542 1512  379282.300 50.85979  
+        22) PC1< 0.5623101 693  160369.100 48.51371 *
+        23) PC1>=0.5623101 819  211871.300 52.84493 *
+   3) PC1>=1.744274 4237 1076169.000 58.33609  
+     6) PC1< 4.98542 3009  761850.300 55.43702  
+      12) PC3< 0.09750898 1621  396508.800 53.01049  
+        24) PC1< 3.348799 902  210185.400 50.48780 *
+        25) PC1>=3.348799 719  173381.900 56.17524 *
+      13) PC3>=0.09750898 1388  344650.100 58.27089  
+        26) PC4>=-1.117264 1088  272870.200 57.04044 *
+        27) PC4< -1.117264 300   64158.670 62.73333 *
+     7) PC1>=4.98542 1228  227062.500 65.43974  
+      14) PC4>=-1.213035 750  143755.900 63.21333  
+        28) PC3< -1.338169 120   26320.000 58.00000 *
+        29) PC3>=-1.338169 630  113553.200 64.20635 *
+      15) PC4< -1.213035 478   73755.860 68.93305  
+        30) PC1< 7.248641 297   52855.220 67.44108 *
+        31) PC1>=7.248641 181   19154.700 71.38122 *
+```
+
+Notes: You tuned model hyperparameters for a decision tree (cost complexity and tree depth) along with the number of components to use in PCA for data preprocessing. The resulting decision tree (shown here) exhibits some sensible behavior, with the first principal component being the variable for the first split, etc.
+
+---
+
+# Predicting age
+
+```r
+final_tree <- final_wf %>%
+  last_fit(sisters_split) 
+
+final_tree %>%
+  collect_metrics()
+```
+
+```out
+# A tibble: 2 x 3
+  .metric .estimator .estimate
+  <chr>   <chr>          <dbl>
+1 rmse    standard      14.0  
+2 rsq     standard       0.236
+```
+
+Notes: The performance metrics you achieved on the testing set indicate that you did not overfit during the tuning process.
+
+---
+
+# Predicting age
+
+- **Build** your model with your training data
+- **Choose** your model and model hyperparameters with your validation data
+- **Evaluate** your model with your testing data
+
+Notes: You divided your data into three subsets: a training set to train your model, a validation set to tune hyperparameters, and then a testing set to evaluate the performance of your model and estimate how it will do with new data.
+
+You can also use a validation set to choose between different models.
+
+---
+
+# Diverse data, powerful tools
+
+- Fuel efficiency of cars 🚗
+- Developers working remotely in the Stack Overflow survey 💻
+- Voter turnout in 2016 🗳
+- Catholic nuns' ages based on beliefs and attitudes ⛪
+
+Notes: This analysis was just the final example in the series of predictive projects you approached in this course. 
+
+You learned how to go from raw data to exploring that data to training models to evaluating those models using the [tidymodels](https://www.tidymodels.org/) metapackage and important tools for exploratory data analysis from the [tidyverse](https://www.tidyverse.org/) ecosystem, like dplyr and ggplot2.
+
+---
+
+#  Practical machine learning
+
+- Dealing with class imbalance
+- Measuring performance with resampling (bootstrap, cross-validation)
+- Tuning hyperparameters
+
+Notes: In this course, I've chosen to spend our energy and time on some of the issues that I have found to be the most important and most impactful from my real world, practical predictive modeling experience. These include knowing what to do when you are faced with class imbalance, having some options in your toolkit for resampling approaches, and optimizing model hyperparametrs. 
+
+---
+
+#  Practical machine learning
+
+![tidymodels](https://github.com/juliasilge/course-ML-tidymodels/blob/master/img/tidymodels_small.png?raw=true)
+
+Notes: To keep going in your machine learning journey, check out the resources at [`tidymodels.org`](https://www.tidymodels.org/). This site is a central location for resources and documentation for tidymodels packages, and there is a ton to explore and learn. 🚀
+
+There are five articles at [**Get Started**](https://www.tidymodels.org/start/) that guide you through what you need to know to use tidymodels, and many more resources at [**Learn**](https://www.tidymodels.org/learn/).
+
+---
+
+# Practical machine learning
+
+- Try out multiple modeling approaches for each new problem 
+- Overall, [gradient tree boosting and random forest](https://arxiv.org/abs/1708.05070v1) 🌳 perform well
+
+Notes: The high level takeaways that you should remember from this course are first, that each time you have a new predictive modeling problem you are working on, you need to try out multiple different kinds of models. You don't know ahead of time which kind of model is going to perform best. This paper linked on this slide uses some super interesting analysis to show that most often, the two kinds of models that perform best are gradient tree boosting and random forest. 
+
+However, depending on how much data you have and the specifics of your problem, that may not be true, so you have to try it for yourself. Also, start with a **simple model** to compare to. 
+
+---
+
+# Never skip exploratory data analysis ✅
+
+
+
+Notes: And perhaps most importantly, never skip exploratory data analysis when you build machine learning models. It is time well spent, because when you understand a data set better, you can do a better job of building accurate models that perform better.
+
+---
+
+# Go train some models!
+
+Notes: And that's our ultimate goal here! Thanks for spending time with me on this course. Now it's time for you to take what you've been practicing here and go apply it in the real world.
+
+If this course has been helpful to you, you can [buy me a coffee](https://ko-fi.com/U7U4WG9B) or chip in for hosting costs.
+
+[![ko-fi](https://www.ko-fi.com/img/githubbutton_sm.svg)](https://ko-fi.com/U7U4WG9B)
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/src/pages/index.js b/src/pages/index.js
index 482785e..b412b37 100644
--- a/src/pages/index.js
+++ b/src/pages/index.js
@@ -21,7 +21,7 @@ export default ({ data }) => {
                 <h1 className={classes.subtitle}>A Free, Interactive Course Using Tidy Tools</h1>
                 <div className={classes.introduction}>
                 <p>
-                    Predictive modeling, or supervised machine learning, is a powerful tool for using data to make predictions about the world around us. Once you understand the basic ideas of supervised machine learning, the next step is to practice your skills so you know how to apply these techniques wisely and appropriately. In this course, you will work through four case studies using data from the real world; you will gain experience in exploratory data analysis, preparing data so it is ready for predictive modeling, training supervised machine learning models, and evaluating those models.
+                    Predictive modeling, or supervised machine learning, is a powerful tool for using data to make predictions about the world around us. Once you understand the basic ideas of supervised machine learning, the next step is to practice your skills so you know how to apply these techniques wisely and appropriately. In this course, you will work through four case studies using data from the real world; you will gain experience in exploratory data analysis, preparing data so it is ready for predictive modeling, training supervised machine learning models using tidymodels, and evaluating those models.
                 </p>
                 <p>
                     To take this course, you need some familiarity with tidyverse packages like <strong>dplyr</strong> and <strong>ggplot2</strong> and exposure to machine learning basics. Now let's get started!