Update meetup data

data/chapters_meetup.json

@@ -2250,7 +2250,7 @@
     "country_acronym": "ca",
     "state": "ON",
     "city": "Toronto",
-    "members": 749,
+    "members": 750,
     "lat": 43.74,
     "lon": -79.36,
     "timezone": "America/Toronto"

data/events.json

@@ -73,7 +73,7 @@
     "id": "305348585",
     "group_urlname": "rladies-rtp",
     "title": "[ONLINE] Tidy Data, Weighted Insights: Analyzing Complex Survey Data in R",
-    "body": "<h6 class='entry-title mt-2' style='font-size: 1.5em !important';>[ONLINE] Tidy Data, Weighted Insights: Analyzing Complex Survey Data in R<\/h6><p><i class='fa fa-users'><\/i>&emsp;3<\/p><p class='text-truncate'>Please join us for our next meetup with co-authors Stephanie Zimmer, Rebecca Powell, and Isabella Velásquez on **Analyzing Complex Survey Data in R**! This meetup is being co-organized with R-Ladies Amsterdam.\n\n**Topic:** Surveys are powerful tools, but to ensure the accurate interpretation of results, they require specific analysis methods. With the \\`srvyr\\` package and \\`tidyverse\\` family of functions, we are able to analyze survey data with weights to derive meaningful results. Our new book, Exploring Complex Survey Data Analysis Using R, goes through how to do this step-by-step. You can view the book here: https://tidy-survey-r.github.io/tidy-survey-book/.\n\n**Agenda:** This webinar will start with an overview of the importance of weighting in survey analysis and the framework for conducting survey analysis in R. We will highlight examples from the book, including how to calculate means and perform t-tests. Knowing that publication-ready tables are important, we will show you how to efficiently create reproducible tables using your final weighted data! We will end with time for Q&A and discussion.\n\n**Prerequisites:** There are no prerequisites. All members are encouraged to attend.\n\n**Code of Conduct:** All events are intended for women as leaders, mentors, members, and attendees. We are emphatically queer and trans friendly. Men are welcomed to attend *as guests* and must be accompanied by the R-Lady who invited them. This group was created so those who identify as women have a comfortable place to learn. If you would like to attend and feel excluded, please introduce yourself to an organizer.\n\n**Contact:** If you have any questions or concerns, please reach out to organizer, Sheila Saia, on meetup.<\/p><center><a href='https://www.meetup.com/rladies-rtp/events/305348585' target='_blank'><button class='btn btn-primary'>Event page<\/button><\/center><\/a>",
+    "body": "<h6 class='entry-title mt-2' style='font-size: 1.5em !important';>[ONLINE] Tidy Data, Weighted Insights: Analyzing Complex Survey Data in R<\/h6><p><i class='fa fa-users'><\/i>&emsp;4<\/p><p class='text-truncate'>Please join us for our next meetup with co-authors Stephanie Zimmer, Rebecca Powell, and Isabella Velásquez on **Analyzing Complex Survey Data in R**! This meetup is being co-organized with R-Ladies Amsterdam.\n\n**Topic:** Surveys are powerful tools, but to ensure the accurate interpretation of results, they require specific analysis methods. With the \\`srvyr\\` package and \\`tidyverse\\` family of functions, we are able to analyze survey data with weights to derive meaningful results. Our new book, Exploring Complex Survey Data Analysis Using R, goes through how to do this step-by-step. You can view the book here: https://tidy-survey-r.github.io/tidy-survey-book/.\n\n**Agenda:** This webinar will start with an overview of the importance of weighting in survey analysis and the framework for conducting survey analysis in R. We will highlight examples from the book, including how to calculate means and perform t-tests. Knowing that publication-ready tables are important, we will show you how to efficiently create reproducible tables using your final weighted data! We will end with time for Q&A and discussion.\n\n**Prerequisites:** There are no prerequisites. All members are encouraged to attend.\n\n**Code of Conduct:** All events are intended for women as leaders, mentors, members, and attendees. We are emphatically queer and trans friendly. Men are welcomed to attend *as guests* and must be accompanied by the R-Lady who invited them. This group was created so those who identify as women have a comfortable place to learn. If you would like to attend and feel excluded, please introduce yourself to an organizer.\n\n**Contact:** If you have any questions or concerns, please reach out to organizer, Sheila Saia, on meetup.<\/p><center><a href='https://www.meetup.com/rladies-rtp/events/305348585' target='_blank'><button class='btn btn-primary'>Event page<\/button><\/center><\/a>",
     "start": "2025-02-25 12:00:05",
     "end": "2025-02-25 13:00:05",
     "date": "2025-02-25",
@@ -129,7 +129,7 @@
     "id": "304199693",
     "group_urlname": "rladies-philly",
     "title": "Lunch&Learn: {targets} with Irena Papst",
-    "body": "<h6 class='entry-title mt-2' style='font-size: 1.5em !important';>Lunch&Learn: {targets} with Irena Papst<\/h6><p><i class='fa fa-users'><\/i>&emsp;31<\/p><p class='text-truncate'>Do you ever find yourself starting with a simple analysis script only to end up wrangling a thousand line behemoth? Are you sick of wasting time re-running long scripts from start to finish, just to make sure everything is up-to-date? Are you (haphazardly?) saving objects to file because they take a long time to generate? There’s got to be a better way!\n\nEnter {targets}, an R package used to build reproducible, efficient, and scalable pipelines. {targets} can free you from many common analysis management tasks so that you can focus on the analysis itself. In this session, I’ll introduce the {targets} package and share how I’ve used it to streamline my work. I'll also highlight some tips and tricks that I've learned from my experience with the package over the last two years.<\/p><center><a href='https://www.meetup.com/rladies-philly/events/304199693' target='_blank'><button class='btn btn-primary'>Event page<\/button><\/center><\/a>",
+    "body": "<h6 class='entry-title mt-2' style='font-size: 1.5em !important';>Lunch&Learn: {targets} with Irena Papst<\/h6><p><i class='fa fa-users'><\/i>&emsp;32<\/p><p class='text-truncate'>Do you ever find yourself starting with a simple analysis script only to end up wrangling a thousand line behemoth? Are you sick of wasting time re-running long scripts from start to finish, just to make sure everything is up-to-date? Are you (haphazardly?) saving objects to file because they take a long time to generate? There’s got to be a better way!\n\nEnter {targets}, an R package used to build reproducible, efficient, and scalable pipelines. {targets} can free you from many common analysis management tasks so that you can focus on the analysis itself. In this session, I’ll introduce the {targets} package and share how I’ve used it to streamline my work. I'll also highlight some tips and tricks that I've learned from my experience with the package over the last two years.<\/p><center><a href='https://www.meetup.com/rladies-philly/events/304199693' target='_blank'><button class='btn btn-primary'>Event page<\/button><\/center><\/a>",
     "start": "2025-01-22 12:00:05",
     "end": "2025-01-22 13:00:05",
     "date": "2025-01-22",

data/events_updated.json

@@ -1,6 +1,6 @@
 [
   {
-    "date": "2025-01-01 00:36:18",
+    "date": "2025-01-01 12:14:09",
     "n_events_past": 3943
   }
 ]