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requirements.txt (line 4)) (1.7.6)\n","Requirement already satisfied: scikit-learn==1.2.2 in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 5)) (1.2.2)\n","Requirement already satisfied: wordcloud==1.8.2.2 in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 6)) (1.8.2.2)\n","Requirement already satisfied: autopep8 in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 7)) (2.3.1)\n","Requirement already satisfied: nltk in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 8)) (3.8.1)\n","Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 9)) (4.66.5)\n","Requirement already satisfied: click in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 10)) (8.1.7)\n","Requirement already satisfied: regex in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 11)) (2024.5.15)\n","Requirement already satisfied: imblearn in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 12)) (0.0)\n","Requirement already satisfied: seaborn in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 13)) (0.13.1)\n","Requirement already satisfied: openpyxl in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 14)) (3.1.5)\n","Requirement already satisfied: numpy>=1.16.5 in /usr/local/lib/python3.10/dist-packages (from mealpy==2.5.1->-r requirements.txt (line 3)) (1.26.4)\n","Requirement already satisfied: matplotlib>=3.1.3 in /usr/local/lib/python3.10/dist-packages (from mealpy==2.5.1->-r requirements.txt (line 3)) (3.7.1)\n","Requirement already satisfied: scipy>=1.7.1 in /usr/local/lib/python3.10/dist-packages (from mealpy==2.5.1->-r requirements.txt (line 3)) (1.13.1)\n","Requirement already satisfied: pandas>=1.2.0 in /usr/local/lib/python3.10/dist-packages (from mealpy==2.5.1->-r requirements.txt (line 3)) (2.1.4)\n","Requirement 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openpyxl->-r requirements.txt (line 14)) (1.1.0)\n","Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.1.3->mealpy==2.5.1->-r requirements.txt (line 3)) (1.2.1)\n","Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.1.3->mealpy==2.5.1->-r requirements.txt (line 3)) (0.12.1)\n","Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.1.3->mealpy==2.5.1->-r requirements.txt (line 3)) (1.4.5)\n","Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.1.3->mealpy==2.5.1->-r requirements.txt (line 3)) (24.1)\n","Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.1.3->mealpy==2.5.1->-r requirements.txt (line 3)) (3.1.2)\n","Requirement already satisfied: python-dateutil>=2.7 in 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(3.3.2)\n","Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.27.0->opfunu>=1.0.0->mealpy==2.5.1->-r requirements.txt (line 3)) (3.7)\n","Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.27.0->opfunu>=1.0.0->mealpy==2.5.1->-r requirements.txt (line 3)) (2.0.7)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.27.0->opfunu>=1.0.0->mealpy==2.5.1->-r requirements.txt (line 3)) (2024.7.4)\n"]}]},{"cell_type":"code","source":["## Major\n","import numpy as np\n","import pandas as pd\n","pd.set_option(\"display.max_colwidth\", 200)\n","import re\n","import string\n","from tqdm import tqdm\n","import joblib\n","\n","## plotting\n","import matplotlib.pyplot as plt\n","import seaborn as sns\n","from wordcloud import WordCloud\n","\n","## nltk -- for text processing\n","import nltk\n","from nltk.stem import WordNetLemmatizer\n","from nltk.tokenize import RegexpTokenizer\n","from nltk import word_tokenize\n","from nltk import PorterStemmer, WordNetLemmatizer\n","from nltk.corpus import stopwords\n","\n","## sklearn -- for processing and models\n","from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer\n","from sklearn.svm import SVC\n","from sklearn.linear_model import LogisticRegression\n","from sklearn.neighbors import KNeighborsClassifier\n","from sklearn.ensemble import RandomForestClassifier\n","from sklearn.tree import DecisionTreeClassifier\n","from sklearn.naive_bayes import GaussianNB\n","from xgboost import XGBClassifier\n","from sklearn.cluster import KMeans\n","from sklearn.preprocessing import LabelEncoder, StandardScaler\n","from sklearn.model_selection import train_test_split\n","from sklearn.metrics import accuracy_score\n","\n","## SMOTE for imblanced dataset\n","from imblearn.over_sampling import SMOTE\n","\n","## Optimization Algorithm using Jaya Optimizer\n","from mealpy.swarm_based.JA import BaseJA, OriginalJA, LevyJA\n","\n","## Filter Warnings\n","import warnings\n","warnings.filterwarnings('ignore')"],"metadata":{"id":"csJzsZu6Oh1P","executionInfo":{"status":"ok","timestamp":1724148909812,"user_tz":-180,"elapsed":2344,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}}},"execution_count":2,"outputs":[]},{"cell_type":"markdown","source":["**Load the dataset**"],"metadata":{"id":"6VTIEBOxPour"}},{"cell_type":"code","source":["df = pd.read_csv(\"twitter-sanders-apple2.csv\",\n","                 encoding='ISO-8859-1')\n","df.head()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"NNlQMHJOOoKU","executionInfo":{"status":"ok","timestamp":1724148909813,"user_tz":-180,"elapsed":27,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"2b29eaa4-989b-410f-f688-db131912b4c1"},"execution_count":3,"outputs":[{"output_type":"execute_result","data":{"text/plain":["  class  \\\n","0   Pos   \n","1   Pos   \n","2   Pos   \n","3   Pos   \n","4   Pos   \n","\n","                                                                                                                        text  \n","0                                   Now all @Apple has to do is get swype on the iphone and it will be crack. Iphone that is  \n","1                                               @Apple will be adding more carrier support to the iPhone 4S (just announced)  \n","2  Hilarious @youtube video - guy does a duet with @apple 's Siri. Pretty much sums up the love affair! http://t.co/8ExbnQjY  \n","3                                                       @RIM you made it too easy for me to switch to @Apple iPhone. See ya!  \n","4                                                  I just realized that the reason I got into twitter was ios5 thanks @apple  "],"text/html":["\n","  <div id=\"df-f6850a1b-c0c3-4f5f-8ba4-bd4dee5af7de\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>class</th>\n","      <th>text</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>Pos</td>\n","      <td>Now all @Apple has to do is get swype on the iphone and it will be crack. Iphone that is</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>Pos</td>\n","      <td>@Apple will be adding more carrier support to the iPhone 4S (just announced)</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>Pos</td>\n","      <td>Hilarious @youtube video - guy does a duet with @apple 's Siri. Pretty much sums up the love affair! http://t.co/8ExbnQjY</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>Pos</td>\n","      <td>@RIM you made it too easy for me to switch to @Apple iPhone. See ya!</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>Pos</td>\n","      <td>I just realized that the reason I got into twitter was ios5 thanks @apple</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f6850a1b-c0c3-4f5f-8ba4-bd4dee5af7de')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    .colab-df-buttons div {\n","      margin-bottom: 4px;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","    <script>\n","      const buttonEl =\n","        document.querySelector('#df-f6850a1b-c0c3-4f5f-8ba4-bd4dee5af7de button.colab-df-convert');\n","      buttonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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She can't connect to your network!!!!!!!\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":3}]},{"cell_type":"code","source":["print('The Shape of the Dataset is: ', df.shape)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Oa7iObF-QB_P","executionInfo":{"status":"ok","timestamp":1724148909813,"user_tz":-180,"elapsed":24,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"1ff52e7a-e0b7-4572-8a2c-8b005177bfe6"},"execution_count":4,"outputs":[{"output_type":"stream","name":"stdout","text":["The Shape of the Dataset is:  (479, 2)\n"]}]},{"cell_type":"code","source":["df.info()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ab-Pgdh0QkTt","executionInfo":{"status":"ok","timestamp":1724148909813,"user_tz":-180,"elapsed":22,"user":{"displayName":"marcel 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object</label>"]},"metadata":{},"execution_count":6}]},{"cell_type":"code","source":["df.isnull().sum(axis=0)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":147},"id":"DCjxwc0yQ0yU","executionInfo":{"status":"ok","timestamp":1724148909814,"user_tz":-180,"elapsed":19,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"2f714a90-bd97-435b-81bd-85c1fd8ba780"},"execution_count":7,"outputs":[{"output_type":"execute_result","data":{"text/plain":["class    0\n","text     0\n","dtype: int64"],"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>0</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>class</th>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>text</th>\n","      <td>0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div><br><label><b>dtype:</b> int64</label>"]},"metadata":{},"execution_count":7}]},{"cell_type":"code","source":["df['class'].unique()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"qX8iupKaQ55r","executionInfo":{"status":"ok","timestamp":1724148909814,"user_tz":-180,"elapsed":19,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"50a79a29-24bc-4436-a729-28a24d2cc7fe"},"execution_count":8,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array(['Pos', 'Neg'], 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Iphone that is  \n","1                                                                 @Apple will be adding more carrier support to the iPhone 4S (just announced)  \n","2                    Hilarious @youtube video - guy does a duet with @apple 's Siri. Pretty much sums up the love affair! http://t.co/8ExbnQjY  \n","3                                                                         @RIM you made it too easy for me to switch to @Apple iPhone. See ya!  \n","4                                                                    I just realized that the reason I got into twitter was ios5 thanks @apple  \n","..                                                                                                                                         ...  \n","474                 Houston we have a problem!! My iPad has been restoring for 12+ hours after installing @apple IOS5. This can't be right....  \n","475                                      #Siri went down for a little while last night. Come on @apple! Get your shit together on this launch!  \n","476     @ford should have teamed up with @Apple instead of @microsoft to make this SYNC system in my new focus. Car is sweet SYNC is #EpicFail  \n","477  RT @gdcurry: Really @Apple?  What have you done to my iTunes now?  I can't click on Music Movies TV Shows or any playlists. I get a l ...  \n","478                                                                                                                        DAMN YOU !!! @apple  \n","\n","[479 rows x 2 columns]"],"text/html":["\n","  <div id=\"df-eb5065a1-1115-4d5b-83b9-69b56b654849\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>class</th>\n","      <th>text</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>Pos</td>\n","      <td>Now all @Apple has to do is get swype on the iphone and it will be crack. Iphone that is</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>Pos</td>\n","      <td>@Apple will be adding more carrier support to the iPhone 4S (just announced)</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>Pos</td>\n","      <td>Hilarious @youtube video - guy does a duet with @apple 's Siri. Pretty much sums up the love affair! http://t.co/8ExbnQjY</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>Pos</td>\n","      <td>@RIM you made it too easy for me to switch to @Apple iPhone. See ya!</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>Pos</td>\n","      <td>I just realized that the reason I got into twitter was ios5 thanks @apple</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>474</th>\n","      <td>Neg</td>\n","      <td>Houston we have a problem!! My iPad has been restoring for 12+ hours after installing @apple IOS5. This can't be right....</td>\n","    </tr>\n","    <tr>\n","      <th>475</th>\n","      <td>Neg</td>\n","      <td>#Siri went down for a little while last night. Come on @apple! Get your shit together on this launch!</td>\n","    </tr>\n","    <tr>\n","      <th>476</th>\n","      <td>Neg</td>\n","      <td>@ford should have teamed up with @Apple instead of @microsoft to make this SYNC system in my new focus. Car is sweet SYNC is #EpicFail</td>\n","    </tr>\n","    <tr>\n","      <th>477</th>\n","      <td>Neg</td>\n","      <td>RT @gdcurry: Really @Apple?  What have you done to my iTunes now?  I can't click on Music Movies TV Shows or any playlists. I get a l ...</td>\n","    </tr>\n","    <tr>\n","      <th>478</th>\n","      <td>Neg</td>\n","      <td>DAMN YOU !!! @apple</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>479 rows × 2 columns</p>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-eb5065a1-1115-4d5b-83b9-69b56b654849')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    .colab-df-buttons div {\n","      margin-bottom: 4px;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","    <script>\n","      const buttonEl =\n","        document.querySelector('#df-eb5065a1-1115-4d5b-83b9-69b56b654849 button.colab-df-convert');\n","      buttonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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'block' : 'none';\n","    })();\n","  </script>\n","</div>\n","\n","    </div>\n","  </div>\n"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"dataframe","summary":"{\n  \"name\": \"df[df['class']!='class']\",\n  \"rows\": 479,\n  \"fields\": [\n    {\n      \"column\": \"class\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Neg\",\n          \"Pos\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 479,\n        \"samples\": [\n          \"@apple your simply the best.\",\n          \"+1  RT @Doug_Newton: @apple PLEASE FIX #Siri!!!! She can't connect to your network!!!!!!!\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":10}]},{"cell_type":"code","source":["df['class'].value_counts()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":178},"id":"dA7Q34l4RnPh","executionInfo":{"status":"ok","timestamp":1724148910316,"user_tz":-180,"elapsed":14,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"55e3d040-b688-4488-d3e7-30e365e1018a"},"execution_count":11,"outputs":[{"output_type":"execute_result","data":{"text/plain":["class\n","Neg    316\n","Pos    163\n","Name: count, dtype: int64"],"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>count</th>\n","    </tr>\n","    <tr>\n","      <th>class</th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>Neg</th>\n","      <td>316</td>\n","    </tr>\n","    <tr>\n","      <th>Pos</th>\n","      <td>163</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div><br><label><b>dtype:</b> int64</label>"]},"metadata":{},"execution_count":11}]},{"cell_type":"code","source":["## countplot of target\n","plt.figure(figsize=(10, 6))\n","sns.countplot(data=df, x='class')\n","plt.title('Distr. of target in Dataset', fontsize=14, c='k')\n","plt.xlabel('Target', c='k', fontsize=12)\n","plt.ylabel('Count', c='k', fontsize=12)\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":569},"id":"DhM_h9rYRvnR","executionInfo":{"status":"ok","timestamp":1724148910316,"user_tz":-180,"elapsed":14,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"fc539ee7-2a42-4d05-f68c-84a691743984"},"execution_count":12,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x600 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["for i in range(len(df['class'])):\n","  if df['class'][i] == 'Pos':\n","    df['class'][i] = 1\n","  else:\n","    df['class'][i] = 0\n","\n","\n","print(df['class'].unique())"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"MEwCfsBNRz9x","executionInfo":{"status":"ok","timestamp":1724148910687,"user_tz":-180,"elapsed":383,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"f97d02a2-e92c-450a-a8cf-94b5f2d7709e"},"execution_count":13,"outputs":[{"output_type":"stream","name":"stdout","text":["[1 0]\n"]}]},{"cell_type":"code","source":["## Check Length of Tweets\n","length_tweets = df['text'].str.len()\n","## Plotting\n","plt.figure(figsize=(10, 6))\n","plt.hist(length_tweets, bins=50)\n","plt.title('Length of Tweets')\n","plt.xlabel('Tweets Length')\n","plt.ylabel('Frequency')\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":564},"id":"jAhzLXQPSh89","executionInfo":{"status":"ok","timestamp":1724148911245,"user_tz":-180,"elapsed":560,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"b2f9fc03-2d25-44c7-fe60-2ccee9be4ecc"},"execution_count":14,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x600 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["## Hashtags\n","def hashtag_extract(x):\n","    hashtags = []\n","    ## Loop over the words in the tweet\n","    for i in x:\n","        ht = re.findall(r\"#(\\w+)\", i)\n","        hashtags.append(ht)\n","\n","    return hashtags\n","\n","## Extracting hashtags from non racist tweets\n","hash_neg = hashtag_extract(df['text'][df['class'] == 0])  ## Negative\n","hash_pos = hashtag_extract(df['text'][df['class'] == 1])  ## Positive\n","\n","\n","## Unnesting list\n","hash_neg = sum(hash_neg, [])\n","hash_pos = sum(hash_pos, [])\n","\n","print(hash_pos)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"R-4HSWhGTQKj","executionInfo":{"status":"ok","timestamp":1724148911245,"user_tz":-180,"elapsed":9,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"b51ee097-7531-4e50-b0c8-dc9fa75c5d1f"},"execution_count":15,"outputs":[{"output_type":"stream","name":"stdout","text":["['iPad', 'BlackBerry', 'BlackBerry', 'smallvictory', 'thievingbastards', 'GeniusBar', 'yourdaysarenumbered', 'iPhone4S', 'notjustaboutthephone', 'ios5', 'iPhone4S', 'iPhone4S', 'iPad', 'iPad', 'iphone', 'RVA', 'iphone4s', 'HP', 'iPhone', 'lol', 'backchannel', 'ios5', 'Siri', 'need4s', 'sweet', 'apple', 'probono', 'IPhones', 'smartphone', 'sm', 'technology', 'mack', 'iCloud', 'iOS5', 'geek', 'iphone', 'iphone4S', 'smartphone', 'stevejobs', 'iphone4s', 'fb', 'iOS5', 'readinglists', 'nowicanspendevenmoretimeonmyphone', '10twitterpeopleiwouldliketomeet', 'MacOSC', 'iphone', 'iPhone4S', 'android', 'CardsApp', 'appletv', 'PrincessOfChina', 'wow', 'ios5', 'ios5', 'ios5', 'lovemyiphone', 'iPhone', 'iPhone', 'MakeMeProud', '365daysofgratefulness', 'hypo', 'D', 'tri', 'hypo', 'D', 'tri', 'iPhone4S', 'ios5', 'genius', 'magic', 'Siri', 'imamac', 'iOS5', 'awesome', 'addicted', 'iOS5', 'Blackberry', 'iPhone', 'creative', 'siri', 'ipod4s', 'iOS5', 'newfeature', 'iOS5', 'iOS5', 'iphone4s', 'iOs5', 'Bellevue', 'thankyou', 'coolness']\n"]}]},{"cell_type":"code","source":["## Hashtags in Tweets\n","a_neg = nltk.FreqDist(hash_neg)\n","a_pos = nltk.FreqDist(hash_pos)\n","\n","print(a_pos)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"lkRQoIuHUvMp","executionInfo":{"status":"ok","timestamp":1724148911246,"user_tz":-180,"elapsed":7,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"b2d2db0d-a2aa-414e-d1ea-8d3cb69b6bdf"},"execution_count":16,"outputs":[{"output_type":"stream","name":"stdout","text":["<FreqDist with 61 samples and 91 outcomes>\n"]}]},{"cell_type":"code","source":["\n","## Negative Tweets\n","df_neg = pd.DataFrame({'Hashtag': list(a_neg.keys()),\n","                  'Count': list(a_neg.values())})\n","\n","## Positive Tweets\n","df_pos = pd.DataFrame({'Hashtag': list(a_pos.keys()),\n","                  'Count': list(a_pos.values())})\n","\n","# selecting top 15 most frequent hashtags\n","df_neg = df_neg.nlargest(columns='Count', n=15)\n","df_pos = df_pos.nlargest(columns='Count', n=15)\n","\n","## Plotting\n","fig, ax = plt.subplots(2, 1, figsize=(16, 10))\n","fig.tight_layout(pad=5)\n","plt.sca(ax[0])\n","sns.barplot(data=df_neg, x='Hashtag', y='Count')\n","plt.xticks(rotation=30)\n","plt.title('Distr. of Most Frequent Hastags in Negative Tweets', fontsize=14, c='k')\n","plt.xlabel('')\n","##\n","plt.sca(ax[1])\n","sns.barplot(data=df_pos, x='Hashtag', y='Count')\n","plt.xticks(rotation=30)\n","plt.title('Distr. of Most Frequent Hastags in Positive Tweets', fontsize=14, c='k')\n","plt.xlabel('')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":710},"id":"2p9JMwCWTYuz","executionInfo":{"status":"ok","timestamp":1724148913231,"user_tz":-180,"elapsed":1990,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"1cca6577-fcb7-44bf-91e4-35e544eb9528"},"execution_count":17,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0.5, 80.7222222222222, '')"]},"metadata":{},"execution_count":17},{"output_type":"display_data","data":{"text/plain":["<Figure size 1600x1000 with 2 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wcNBt27ap6r/P0alTp2r27Nn5fH0JREVFGf9/5513tEmTJhoYGKiqqleuXNFSpUrpxYsXdfz48erk5KTNmjXTY8eOpXgdhPAvic2bN2vVqlV1z549ceY9/Ybx7AfetWvX9LXXXtNJkyZZvcb07LffflN3d3ctX768Dhw4UFevXq2qqr/88ouaTCZdv3690bZ169ZVX19fixe5qmpQUJBmz55dR44cmdrlvxKe/VKoqrp9+3bNlSuXTpgwQWNjYzUkJETz5ctn/Fg1BwIHDx7UjBkz6tixYzU8PDzVa09LoqOj9cMPP1R3d3ddtWqVMX3z5s1aokQJLVasmJYrV05z586tO3bsMOZ36dJFy5QpY3wRP3DggGbPnl1nz56tqnzZtqan2/bgwYPq6uqqRYsW1WzZsumYMWM0JCREHz58qH5+fpo5c2b97bffLNZfsmSJfv3113EOuOBfZ86c0Tp16mi+fPl0yJAhum/fPuP9I773jEmTJmmJEiWMH1BIvtjY2AR73K1atUpz5sypP/30k6o++VFlMpl0yJAhFstdvHhRe/XqZfGehuR5+jtlVFSUzpo1SwMDA/X69euq+uS9v1atWurv76/ZsmXT7t2766VLl1T1yWN56NAhm9Sd1sXGxlq07eHDh/XEiRPG+0xUVJS2bNlS3333XQ0LCzOWu379unp6emq1atWMXsV83qae0NBQHThwoPbu3Vvnzp2rf//9t6o+6fTRrFkzffTokbZv317t7e01f/78Wrdu3Vf27DPz83LZsmVGZ4AlS5boiBEj1MPDQ/Pmzauff/65qj5p1+3bt+u1a9c0LCxMIyMjVVX15MmT6ubmZnHGMWxj165dWqlSJa1YsaIWKVJEv/76a713754GBARo6dKldfHixRbLjxo1Sk0mk3bv3l1VeZ962rPh7p07d9RkMumIESM0PDxcHzx4oNWrV9ePPvpIVf9tuzNnzqiTk5P279/feI0gfuY2M7f1rVu3tF+/furh4WEcLF2xYoW6ubkZZ1Sa1zl16pS6uLjor7/+aoPKkVKefs85fvy4zp07VytVqqQDBgzQBw8eqKpq9erV1WQyabVq1Sx+M1y7dk2XLl1qcXDxRRDCpyNPh4zPBo5t27bVJk2aWCx/48YNjYqK0vv37xvTnn2T3759uxYvXlz37dtnxcrTt23btmn58uV17Nix+s8//8TpydW4cWOtU6eOXrlyRVWffCmxs7PTX375xWK50NBQnThxom7YsCHVan8VPfslpHPnztqkSRM9dOiQRkZG6vvvv6+VKlWyGFZowYIF6uDgoCaTSQ8ePJjaJac5NWvWNE5vvHTpkv7xxx9apUoV41Q8VdXWrVtrzZo19cSJE6r65Ohx9uzZ9euvv1bVJ2H+O++8o1WqVOGLdiq4evWqLl68WPv372/8EPr888/Vw8PDONVuxowZmjdvXv3ll1+M97GNGzdq1apVdeDAgYTw/9+zz9eYmBht06aNtm7d+rl78vbo0UPbtWtnjfJeKU9/Z7l06ZIOHTpUf/75Z+OspTt37ug777yjRYsWNZarVq2a1q9fXxcuXKiXLl3SrVu3as2aNdXHx8fiDB68mKCgIM2ZM6cWK1ZMixQpotWrVzfmeXt7a44cOXT9+vUW62zcuFHffffdV/6MhMR60x07dkxr1aqlJUqUUFdXV+3cubNx4GLixIlaqFAhizM8VJ8MCZcxY0Z97733rFo3LJkPAvr6+mrfvn21SZMm6uHhoY8fP9Zjx45p5syZ1WQyqZeXl548eVKPHTumJpNJ58yZ80oNU/Z0aBEWFqaNGzfWMWPGWCxz48YNbdu2rdrb2xtDGcb3Otm5c6e6ublZdAKB9T37fA0ICNDXXntNhw4dqsHBwbps2TKtVKmS9uzZU1VVmzZtqv7+/hZnZH700Uf6xhtvaPHixV/5z4DEmL+Dfvrpp1qyZEndv3+/Pn78WAcPHqze3t4Wbbpz5051dnZWk8mkW7ZssVXJaV5CZ+5t3rxZa9WqpX379lXVJyNLvP/++1q7dm3dv3+/sdzWrVs1b968xlmwSL+uXbumdevW1cKFC2vHjh01T548WrhwYWMUi++++04dHBzidBiZNGmStm3bVi9evJgidRDCpxMpOX5eeHi4hoSE6K+//qrlypXT7t27v/K9fxMzePBgbdy4cbztrvrk9CWTyaSzZs0yer936dJFK1asmOA6sI5vvvlG33vvPYsv/MeOHdPSpUvrsGHDNDo6Wnft2qVly5bVVq1a6b59+/T8+fP69ttv65YtW3TmzJk2rD5tiIyM1GHDhmnZsmW1e/fu6uTkpD/88IPRoyUqKkoHDhyoWbNmVZPJpJ988olx9Hjs2LHq7OysZ86cUVW1OD0VKcf8efB0WPzpp59qrly51MPDw+iRqqr6/vvva7169fTgwYMaERGhH3/8sWbOnFkrVaqkDRo0UEdHR4uDK6+yhEKRv//+WytXrmwM53bkyBE9duyYBgQEGENbqT4JES5duqT9+/dXd3d3I4DkINSLW7VqlTo4OGi1atX0tdde01y5cum6detUVXX//v3q5uamn376qao+ec9/77331MHBQWvXrq05c+bUDz/80Jblv1SOHTumvXv31lmzZukPP/ygjx8/1t9++00LFCig/fr1U1XV9evXa9asWfXLL7/UM2fO6J07d/S7777TkiVL6rBhw/Thw4c23gvbeDpUfPjwoa5cuVJ37txpdJZZu3atlilTRnv37q3Xrl3Tbdu2aevWrbVhw4bGeuXKldNWrVoZp8tv375dW7ZsqaNHj47T8xQpI6FrH7Rt2zbeax8sWLBAz58/rwMGDNAVK1ZYBEAtW7bUnj17xjlb9mU1cOBA7d69u3H2xsKFCzVTpkzG2TGq/3727t69W8uWLateXl4W2/jnn380MjJSt2zZolWrVtVOnTrx/dJGzM/bUaNGaevWrY3pEydOVDs7O6MH8Y4dO9THx0cLFy6sn3/+uXbo0EE9PDx03759fCeKR0BAgLZp0yZOL1t3d3d99913NTo6Wg8cOKCNGzfW2rVr64kTJzQkJESHDBmi06dP1+nTp3Ng4zmY22rFihWq+uQ37xdffKGlSpUyDm4HBARolSpVtHLlyrp+/Xr966+/tG3btlq9enUNCQmxZflIARMmTNAKFSro7du39cGDB3rq1Cl1d3fXt99+W2/evKm3b9/WJk2aaNGiRXXo0KG6YsUK9fX11QIFCujChQtTrA5C+HQkuePn+fv7G+PnPX78WL///nutU6eO5syZ0+LCE4hf06ZNLXo0bty4UadMmaIDBgzQL7/8Uh89eqSjR49WFxcXPXnypKo+6RVsMpn0iy++sFXZL7WYmJh4v8R98803WrBgQV26dKnF9KFDh2qlSpX0999/V1XVPXv2GEOrZM2aVRs1amRxeverrn///moymdTV1VVv3Lihqk++eP/5559atWpVrVu3rp48eVKnTJmiOXLkMHotRUREaP78+V/5i45Zy7PP+6fP5rh165Y2bNhQS5UqZfElcf/+/erl5aV9+vQxfjxt2rRJFy5cqBMnTjQuGmfe/qvk6R87T7drUFCQLlmyxOgFERsbq9WrV9f69etrxYoV1c/PT8uWLav58+fXxo0ba0REhB4/flwHDBigBQoU0OrVq1uMt4/k27Ztm77xxhs6fPhwXbZsmao+eZ956623tHbt2rp9+3ZVfdIRIWfOnMZjGhkZqWfOnNHdu3dbvB5epd6nKSG+9tqyZYuaTCYtUKCAxTi0CxYsUHt7ez169Kiqqn7++edavnx5LVSokFaqVEnz5s3LZ8P/Z+44U758ebW3t9e33npLg4ODNSgoyOIie5MnTzZ6Oc6YMUNVn7wmmjVrplmzZtX69etrxowZddy4cVxY3koSu/ZBsWLFEr32wdPrmj9fX7X3oEuXLll8vx4+fLi6urpanKX9tMGDB2vBggWNXqgBAQHarVs3ffPNNzVbtmw6bNiwVKkb/4qNjdW///5ba9SoYXTyaNiwoS5dulQ3b96shQoVUk9Pzzhnel+7dk0HDBigr7/+uvr6+urZs2eNea/a68AsoeH1/vzzTzWZTDp//nyL+QsXLlRnZ2ejbQ8cOKAVK1ZUNzc3zZUrl5YsWdIq41W/bLZt26Zubm5avnx5bdeunTo5OengwYP1xo0beubMGePMDbMxY8aos7Ozenp6aqtWrbRWrVrG9eWQ9iV0bZ2oqCjt0KGDtm3bVmNiYozP5Tlz5mipUqX0u+++U9UnnST69u2rDRs21Fq1amnnzp0T/MxKLkL4NC6p4+cFBQX95/h5hw8f1h9++IHe789p8+bNajKZtH79+uru7q6lSpXSxo0ba8WKFbVo0aLq4eGhqqr58+fXwYMHG72Cf/zxR4IYK3g6KDx16pQeOHDAYhiNBg0a6Jtvvmkx7EB4eLjmzZtXe/ToYYQ0N2/e1MOHD1uc1ocnpwq3atVK33rrLXVzczOGWVJ90tv69ddfN4L55cuXq8lk0g4dOhhBF2d/WN/mzZvV19dXW7VqpTNnzjTGMvzhhx+0fPnyOmvWLIvlx4wZo3Xr1k3wCP7jx49fuZ5Jz/bOU31ycdpGjRppjhw51MPDQx0dHXXgwIEaFRWlwcHB+sUXX+jYsWN1zZo1euLECf3ll1/Uzc1Nt27dquHh4bpy5UrdtGmTDfcq/Uroh+nWrVvV3t5enZ2djaGvVFUvXLigVatW1cGDB+vjx4/15MmTWqtWLW3RokW8238Vn+Mv4tkDcuHh4cbjYx4DO0+ePBY92h89eqR169Y1hkaMiYnRK1eu6M6dO+MMz/eqMX+O7tu3T0uWLKlubm76+++/69WrV3X69OkWZxGEh4fr6dOntVatWlq2bFn94YcftFevXuri4mJ817l165auWLFCP//8c77DWMmLXPsgJiaGax88Y9OmTRoSEqIzZszQHDlyxAm0zO8vq1evVnt7e+P30/79+3XYsGE6atQoevqmkvg6ZNy4cUMzZ86sQUFBqmrZWWfatGnGgSfzGT7mg7GqavwuTmjbr4qn9z00NFT//PNPjYiIMA7W9ezZU0uUKGFcV8LMw8ND/fz8jGEw7t27p4cOHWJ88ng8Haw+7a233tIPPvjA+Hvq1KmaMWNGI3SdO3euli5dWn/++WdVfTJeePPmzbVjx47G2d3m7SNte/oxOnHihJ49e9ZiWrNmzbRVq1aqanmR1pIlS2qDBg2MIYfMvxnMF5JWTdmDh4TwaZQ1xs8zf3Ai6dauXauDBw/WsWPH6q5du4yj+UFBQZo3b14NCgrSH3/8UU0mk8UYYngxd+/ejfcI/71797Rly5aaN29edXd3V29vb2OoiO3bt6uLi4tOnz7d4s21Zs2aWqxYMYaceU4nT57UunXraocOHVT1yQdPiRIldNCgQcYyY8aM0Y4dO2rBggWNIBjWExsbqyNHjtRs2bLpJ598op07d9YyZcpo5cqVjWVatmypzZs3txi38PLly1qtWjXt3bt3nDHNX9Vg8tneeapPxiv19vbWO3fuGCFXgQIF9Msvv4x3LPiVK1dqzZo1CQZe0NPPwdDQUL18+bIRNoaHh+uQIUPU2dnZGPrH/IP1s88+0/Lly6vqk57vs2bN0iJFihgHCfHizD9MGzRooK1btzbC5FOnTmmuXLmMsynNj+H27ds1U6ZMxlkL+PeAX2xsrI4fP17z5ctn/NA3a9asmVarVs04mN2/f39t37698bn61Vdfqclksvj8Rerg2gcv7u7du1qoUCEdOnSo7tmzR7Nnz25cq+ZZv/76qzo6Olp893/ea7Eg5URFRVm0+99//621atUyLoIeFBSkBQsW1AkTJlist2HDBvXz84tz3QrVV6/3u/lA0rPZzLBhwzR37txatmxZrVmzps6ePVtVnxzIzpIliw4bNsyic1mnTp3U2dlZp0+fzsVXnxEdHa0zZszQgIAAi+lPP9eOHDmipUuX1n/++Ufv3bun3bp10+zZs2v//v315s2bqvqkY0e3bt20Ro0aRttPnz5da9Sood9//72qxr3mHNKu4OBgbdSokbq6umqRIkW0c+fORj5nPtBr/owxvz59fHw0f/78OnDgQItrcJr/TekDMITwaRDj56UfgYGBmjNnTuM0senTp9u4opdLhw4d1M3NzeKsjcePH2u3bt20bt26evr0ad28ebP269dP7ezsjB5hPXr00Dp16hg/jI4cOaJdu3bV2rVrG2eEIHHR0dE6Z84cLVSokG7cuFFVVYcMGaKOjo46ePBgbd++vRYtWpTAy0oS6olUvXp1nTt3rjHt6NGjmjt3bh0+fLiqPultVqlSJf38888twk16S8Zvy5Yt+ueff2psbKxWqlQpzqnuH3/8sXp5eRk/KPfv36979uzRQYMGaY4cOXTYsGH0sk4hI0aMUCcnJy1fvrzWqVPH6Pl+7tw5zZcvnw4dOtRi+YULF2quXLmMoOv+/fuv3I98azCflTBkyBAtXLiwTp8+Xb/55hstXry41q9fXwMDA1VV9YsvvtCsWbNaBI2xsbHq7++vb731lo2qT3suXbpknCH24MEDff3117Vt27bGxYVVVd977z2tW7euqj4JYtzc3HTkyJHG/EGDBmmdOnU0d+7cFkOIwXq49kHKmjZtmjZu3Fh//vln7dOnj+bIkUP37dsXZ7lu3bpxUfNU9uz3zd27d6u3t3ecz9zSpUvr2LFjVVX19u3b+umnn2qmTJl04MCB+vPPP+t7772nzs7O+tlnn73yw2NNmjRJTSaT8fvV/B3xq6++0hIlSuj69et1+/bt+v7772uuXLmM63l8/fXXmitXLv3tt99U9UnHhN69e2vVqlWNMzPxr0ePHmnRokW1X79+Rht/+eWX2rRpU+3Xr59euXJFr1y5orly5dLBgwdr3rx5tVGjRhZnKpkPfv/vf//TUqVKGZnO7du3tVOnTlq9enUNDg5O9X3D83n2e//WrVu1ZMmS2q1bNz19+rTu379fGzdurG3btjUOuvj4+Gi1atWMM3aOHDmiHTt21A4dOsQZ0thaCOHTIMbPSx8ePnyogwYN0saNG1tcnA/JE99RxrNnz6qTk5PF8Bpnz57V3Llz6+rVq41pERER6ufnp97e3qr65EySRo0aqYuLi7Zt21Zz5Mihs2bNsjglEv/t3Llz2qZNG61du7YxrV+/ftq4cWNt3ry5nj9/3obVvVxWrlypR44c0djY2AQD3YsXL6rJZIoTqE+dOlWzZs1qvH769Omjnp6e8Q6NwqmU/7p79666urrqp59+qo8fP9bixYvrlClTVFWNnjAhISGaK1cu40vZ1KlTtWrVqhbjkePF7Nu3T7ds2aJeXl66atUqXbt2rdHG5ufwxIkTNVOmTLp27Vq9ceOGxsTEaIsWLbRTp05xtkcQ//xiYmLivdDzo0eP1NPTUydPnmxMO336tDZp0kS7du2qDx8+1Dt37hgX8H56fa6vEr+NGzdqSEiIbtq0SStUqKDffvutqj7pvGFnZ2e899y7d0979OihJUuW1M2bN+vHH3+sderU0T179vAdxkq49oH1RUREaO3atbVPnz66Y8cOrVy5shYuXFgnTZqkx44d05MnT+rbb7+tbm5uRgjGwW3rSmgYuNDQUJ00aZI6OTnp0KFDjeFR+vXrp35+fhbLfvXVV9q0aVP19vbWxo0b65EjR1Kl9rQuODhYS5Qoof379zemPXjwQMuUKWMMI6z6pPNA3759tWDBgsa0+vXra7FixbRjx45aunRpff/993nvT8SaNWu0Ro0aunjxYh0xYoSWKVNGR4wYoblz59YWLVro2rVrtVu3bmpvbx/nrKXly5frl19+qbGxsRoeHh7nwquLFy+26DGPtOPZ965Vq1bp33//rfv379fPPvvMmL506VLNmjWrurm56VdffaWqqtevX9fy5ctr4cKF1dvbWzNmzKhffvllqp7tQAifhjF+Xtpz/vx5XbRokc6ZM0dfe+01LVeuXLw9OZA0TweDly9f1r///tv4wBs6dKjmz5/fOC371q1bWrBgQeOD1Pw62LFjh5pMJuML4IkTJ3T27NnapUsXXbNmTWruzkvll19+0ZIlS+rEiRNV9ckpqnwZTHnZsmXTt956y+g5t3PnTu3evbuOHz/e6IFx4sQJ9fT01EmTJlms+9dff6mLi4sxPuSxY8e0a9euHCR5DtOnT1dvb28NDAzU4cOHq5ubmzHP/N5SrFgxHTVqlKo+CSf5kZl8z35pNh9YKlCggE6bNs2YHhwcrK+//rp26tRJw8LC9N69e1qnTh3jGhSenp5apEiReE95R+Lmz59vjIP69OPxdOB18OBBLVSokNHr3Wzy5MlaqVIl3b17t6o++XHDMHz/zTwch/mHYdeuXbVatWparFgxfe2113TFihUWy+/du1f9/Py0RIkSWr58ed2zZ48tyn7pce2D1LVp0yatXr26rlixQi9fvqytW7dWe3t7LVu2rLq5uWnDhg3pcWoDp06d0j59+ui4ceMsOhesXLlSa9eurfXr19fbt2/r8OHDtXXr1hoaGhrns/zpkDKhcblfBU8f1J43b57a2dkZB/HCwsK0evXqFkP4xMbG6uHDh7Vw4cLGsCfnz5/X2bNnq7+/f5zhfhBXTEyM+vn5adu2bbVNmzbGkMH79+9Xb29vfffdd3XChAnq5uamS5YsMYLWLVu2aPXq1fWDDz6w+F2b0MEppE0PHjzQ5s2bq5ubm+7fv1/DwsI0PDxcL1++bBzQ+uabb7Rdu3ZarVo1Iy89d+6crl27VocMGaI7duwwtpdYZ7iURAifRjF+Xtq0du1arVGjhtauXVtnzJhh63JeKuHh4dqzZ0/19PTUN954Q9u0aWNMd3V1NU7/PXfunPr4+OgHH3xgMWbe0aNH1d3dXdetW2eT+l9WN2/e1C5dumjVqlVf+dNLrcHcphs3bjR6aXz77beaL18+bdasmRYvXlyLFy+uZ8+eNa7q/tZbb1n0zNu0aZPmy5dPT548aavdSLee7p23ceNGLVq0qA4YMMD4DN25c6eWKlWKi+y9oKd/0ERGRlr8iB81apSaTKY4QeT06dO1YsWKRgC5bt06tbe310WLFhkhMJLm1q1b2r59ey1XrpwxROHChQvV29tbu3XrZnGGmbOzs3799deq+u/Fq+7evasODg7GY3Lv3j0dM2YMZwM+h+nTp2vdunX10KFDeurUKS1ZsqTWqVPHGNLt8ePHFp+xMTExcS7QB+vg2gepwzxcVZs2bYwL3P7999967NixeK//BOsbO3asOjg46BtvvKE1atTQ3Llz65AhQ4wQ/ejRo+rt7a0tWrTQbt26WXRUUI17tsKrGl4+u9/mntV169bVhg0bquqTEL5Bgwb63nvvGc9/1Se9csuVK2dc28zsVT2QkRxHjx7VPHnyaM2aNS2mjxkzRhs2bKhTpkzRCRMmqIODg3p6emrDhg3V0dFRR4wYYaOKkRxPv85iYmK0W7du+vHHH2vv3r3jnMUwYMAA9ff3NzqkzZgxQ7NkyaJ9+vSJd9upffCQED4NY/y8tOmvv/4ijEwh5je7NWvWaKFChbRRo0a6Z88e/fPPPy3eTH/66Se1t7c3grBhw4apl5eXxfjuGzZs0GLFihlXj0fKOXfuHOMQWpH5R4yPj4/6+Pjo//3f/+nWrVtV9d/xgXv06KExMTEaEBCgNWvW1CZNmujBgwf1zJkz2qFDB23atKkx7rAZX+Cfz8aNG7VWrVq6YMECXbdunWbLlk09PT21U6dOmj17du3atavFAT8k37hx47RMmTLq7e2t7du318jISKPTQZ8+fSy+YN+5c0czZsxoBL6hoaHasmVLiwsR81mcuPjeAzZu3KjVq1fXwYMHa2BgoLq7u+uIESO0Zs2aWqFCBeOiocOGDdO8efNaBOz79u3TwoULcwZCMkRERGitWrX0/fffNy6yXbt2beMMJobeSF1c+8A2Tp8+rRUqVNDRo0fbupRXSnzvLxcuXNAKFSrokiVLjGlffPGFVq1aVWfOnGlMCw8P1169emnx4sXVZDLpzp07U6XmtOzq1avG/59u2/Xr1+t7771nDKUXEBCgGTJkMM6SmTFjhlaoUME4G031yTCrbm5uumXLllSq/uXUr18/rVy5skWnmatXr+rrr7+u7du31wcPHujevXt1/vz5OnHixDhnbyDtevbxMf9W6NOnj5pMJu3WrZsxLzY2Vu/evau1atUyOnCqqn7wwQdaoUIFrVu3rkVHtvi2nxoI4dMwxs/Dy+rpLy8RERHatGlT7d+/f6JBr5eXl3H675UrV7Rr167q7Oys7733ng4bNkzz5cunvXv31kePHvE6QJqW0NH28+fPG0NzXLhwwZi+dOlSzZEjhzGsUmBgoHp6emqJEiU0T5486uXlxSncL8AcqLRr107v3bunBw8e1K+//lp79uypmzdvtnV5L4WLFy9qo0aNtEyZMvrjjz/qsmXLtGzZstqxY0d9+PChzps3Tx0cHCyGP9m1a5e6ubnp3r17jWkHDhzQ7NmzG9cJ4b0+fk+/vzx8+FBXrlypQUFB+s8//2hkZKSOGDFCy5Urp35+fsbZY+fPn9f3339fy5UrpxERERoZGamlS5dWLy8vnTJliu7fv1/r1aunTZo0YUiyZDJfOHvNmjV6584drVu3rr777rtxenAhZXHtg7Tlgw8+MK6JAOuKb2gN83P4999/1/z58+vBgweNedeuXdPevXtro0aN9M6dO8b08PBwXbRokdrb22tQUFDqFJ9GDRw4ULt3727xHnD79m1988031dnZWT/55BNdt26dRkVF6T///KM9evTQokWLGst27NhRS5YsqR07dtS5c+dqhQoVtFGjRsZZUUiemzdvauXKlXXkyJEW34EWLFigpUuXNsYDf9rjx4/5HpmGPXu9wFOnTmnlypWNzjl3795Vd3d37dKli0WnnEePHmnr1q21YcOGunz5ch03bpw2atRIN2zYoHfv3k31/YgPIXwax/h5eNk8++VlyZIlajKZ9NSpU4mut3v3brWzs9Ply5er6pNgYcqUKdqxY0f18vLSn376yeq1Ay/i2XHmzp07p/v27dPw8HBj+kcffaQ5c+aMM+64j4+P+vr6GuH8/fv39a+//rL48URPjuQ7ffq0litXTr/44gtbl/JS2rZtm3788cfGj8zbt29rjRo11NHRURcsWKCRkZFap04dLViwoA4cOFCXLl1qDA/x9A/dqKgo7dWrl1apUoUfTs9hzJgxmiNHDi1fvrza29tr69atNTg4WE+fPq0NGzbUPHnyWBz8/v3337VcuXI6ZMgQVX0yVETXrl2N75zt27fX8PBwW+1Oumc+4Ne2bVsNDw/X7777TgsVKmQxDBBSBtc+SLv4rpI6nr3e1rhx4zQwMNA46LdmzRrNmzevMUay+bUxb948rVixol6+fNmYZv63XLlyRpj5qn4GX7p0Kc5BuAkTJmidOnUsOtCYHT9+XHPmzGl8vwwJCdFFixZp06ZNtWrVqjp06NBUqftVMG3aNPX29tbffvvNmBYZGal9+vQx3ufNr4tX9fmbHu3fv1+7deum33//vZpMJh08eLBx9ve3336rjo6OxsXSzY/rb7/9pq1atVJXV1ctVaqURaeqtPAZRAifxjF+Hl42z355GTVqlLq6uhrTnv1QfPrvbt26aYUKFSyOYqaFN1IgPlFRUTp69Gjdtm2bxfTIyEh99913NVOmTFqsWDGtVq2aMbRSTEyM/j/27js6irJ94/i1SSAECL2GLlV6L4L0IkUBUUClCKiIIAIir/hKCaiIAlJEVBQQFAEpCii9Ix1fQJAuvYtAqAlJ7t8fnJ0fS4LSNhuS7+ecnJOdnZ2959md2d1rnnkmVapU1qtXL48hULZu3WrJkye3jz/+ONartyfWcTgfJHfvvLi6KE9icvz4cdu7d69FR0dbnz59LE2aNPbaa69Z48aNrWDBgnbo0CFbu3atuVwue+qpp6xDhw7ORSxv5R7LHDG5x7Jev369FShQwHLmzGmLFy+2Y8eO2ciRIy1LlizOeJiff/65BQcH26xZs5zHX7x40QYMGGC5c+e23bt3m9mNIX+OHz/uLBv3x33A76OPPrKoqCiPsAAPBtc+AP7f1KlTLWnSpFa8eHHLnj27NWjQwLkve/bs1rVrV4/vlbNnz7YkSZLEus+vV6+ex5kjidmiRYucDjMVKlSw1157zeN+9/fyyMhIe//99y116tQeZxeEh4fb1atX467gRODatWv2+OOP22uvvebR1nh4jRs3zpInT27du3e3ESNGWLVq1SwoKMjju1Pp0qWtWbNmsf4WvnXomfjy+44Q/iHA+HlIiObPn28nT560UaNGWZo0aWz//v23nde9Uz127Ji5XC56q+KhcOXKFXv11Vc9TjFdvHixjRgxwpo0aWKbNm2ydevWWatWrSxfvnw2Y8YMM7txAb8UKVI44y67vzC0adPGPvjgg3jzBSKh4YCe902YMMFKlSrljJe6fv16CwgIsMGDB9vVq1etVatWVqFCBY/rGzDu+51xn2UWHR1tgwcPtkyZMjnju7s1bNjQypQpY2FhYbZ//35r2bKlVa9e3eO9/7///c8qVapktWvXjutVSDTeeOMNGzNmjK/LSDC49gEQ05IlS6xVq1b2/vvvO71Ap06datmzZ7c+ffqYmdl3331nSZIksTFjxtihQ4fs8uXL1qpVK3v++edjdPj44osvzOVyMXa53ThQlyNHDuvdu7dFRkZagQIFbPDgwWZmsXaUOXXqlGXPnt2aNm0a16UmOnPmzLGCBQvaypUrPabzHT9+uzVAj4qKsujoaGvRooW1bt3amR4dHW3lypWz2rVrOx2UlyxZYkmTJnWG53bP90/L9zVC+IcE4+chIXFfiK937962du1aCw4OtkGDBjn337zj/Pvvv61Zs2a2ePFiM7vRm8l96iTwsPj777/t8OHD5ufnZxkzZrRRo0Y59x08eNDatWtnpUqVcqYVLlzYWrRoYX/99ZczjfAdD7Nr165ZrVq1rEOHDnbt2jUzMxsyZIilSpXKXC6X7dmzx/bv328pU6Z0xnzHnTt8+LBz8OLSpUvWoEEDa968ucdQbx07drTHH3/cuT1lyhQrVqyYR8/GyMhIGzt2LK+BFxEGPBhc+wCIfdz3qKgo+/LLLy0wMNCKFy/ufDaEh4fboEGDLEmSJM7Fht944w0rUKCAFSxY0HLnzm0FCxb0uLil2Y3P71GjRnmEXIndyJEjrWrVqrZ06VJ7++23LWfOnDHm2bZtmzOs1cyZM23y5MlxXWaiEx0dbTt27PB1GbgLN3+W33wWuJlZzpw5bejQoWb2/2erbdiwwVwul40fP96ZVr9+fcuTJ89Dc3YJIfxDgi/sSGhGjBhhderUscmTJ1uXLl0sTZo0sY63OXnyZHv22We5cBkeWqGhodaoUSO7du2aDRkyxFwuV4yA68cff7RHH33UOU1+6dKl5nK5bN68eTGWx+cBHlZNmza1SpUq2ebNm23dunXWoEED+/33352AzMysd+/e5nK5GPrhHs2bN89Onjxp8+fPt2LFijkdOEaOHGl+fn72ySefOIHNmTNnrFu3blaqVCmPoQc44IeHCdc+QGJ18746LCzMjh075oRQBw4csFatWsUIhw8cOGDFixe3p59+2szMrl69avv27bNJkybZ9OnT4674h9y1a9fsscces86dO9ucOXMsd+7c1qVLF2cIrIMHD9pzzz1nw4YN44w+IBY3/57dsWOHNW3a1J555hmbMmWKnT9/3sxuXMi4cuXKMR5TokQJq1Kliu3cudPMbnREcZ9l+zAghAfgEzd/eVm1apWVLl3asmfPbkOGDLFVq1bZ6tWr7bnnnrPs2bNzFggeaps2bbISJUrYhAkT7Nq1a1aoUCFr3769R8i4c+dOy5Qpk8cF4tzD0wAJxaFDhywkJMQeeeQRS5Ysmb3xxhsx5rl48aLT6wV3x32WmXs8/bZt21q5cuXskUcesXz58sUasCxYsMAKFixon3zySRxXC9wbrn0AeOrXr5+lSZPGSpYs6THkyaJFiyxdunQeZ19GRUU5FxtetWpVrMsjNL4z8+bNs0qVKtnEiRNt/vz5li5dOsubN681bdrUUqdObfXr17fTp0/7ukwg3oqMjLTly5db6dKlrVWrVta8eXPLlCmTffzxx2ZmNn36dMuXL5998803zmMOHjxoZcqUMT8/P2cYqIeNy8xMAOADCxYsUN++fdWrVy9VrFhRb775pmbPnq0sWbIoICBAefPm1ZgxY5Q7d25flwrcl9dee01//vmnJk6cqAULFuidd95R79699dprr0mS1q1bp+bNm2vmzJkqW7asx2PNTC6XyxdlAw/c8ePHtX//fj3yyCPKli2br8tJcEaNGqUffvhBw4cPV4oUKfTUU08pY8aMmjlzpjJlyqSoqCi5XC7nLyIiQnv37lWRIkV8XTrwr958802dO3dOX3/9tT7++GMNHTpUn3zyiZ5//nlnnkaNGunkyZNatmyZzpw5o//+9786efKklixZIj8/P0nSli1b9NprrylFihRatGiRr1YHuC8bN27U1atXNXDgQHXt2lUnTpzQO++8o+bNm+uzzz7TpUuX1K9fP33//ffav3+/goKCJElnzpxR8+bNVaJECQ0fPty3K/EQMzM9/fTTCgwM1JgxY3Tq1CmtXLlS+/fvV7169VSzZk1flwjEKzf/pt2xY4f+85//KDo6WrVq1dKbb74pSerevbs2btyoAQMG6LHHHtNbb72lSZMmadSoUSpevLgmTpyoTJky6eLFi5o8ebL+/PNPX67SPSGEB+Az7i8vSZIk0YgRI5Q1a1YdOHBAUVFRioqKUsGCBX1dIvBAnDlzRnXq1FGzZs3Up08f1alTR2vWrFHz5s316KOPasiQIXr88cc1YcIEBQcH+7pcIE5ERUXJz8+Pg0wPUHh4uGr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\n"},"metadata":{}}]},{"cell_type":"code","source":["## Remove unwanted text patterns from the tweets\n","def remove_pattern(input_txt: str, pattern: str):\n","    ''' This Function takes the input and pattern you want to remove\n","\n","    Args:\n","    *****\n","        (input_text: str) --> The text you want to apply the function to it.\n","        (pattern: str) --> The pattern you want to remove from the text.\n","    '''\n","\n","    input_txt = re.sub(pattern, '', input_txt)\n","    return input_txt"],"metadata":{"id":"S7F8-ZQvT5ov","executionInfo":{"status":"ok","timestamp":1724148913231,"user_tz":-180,"elapsed":50,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}}},"execution_count":18,"outputs":[]},{"cell_type":"code","source":["## Removing @user in tweets, and apply the function\n","df['text'] = df['text'].apply(remove_pattern, pattern=r'@[\\w]*')\n","df.head()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"L8YYyVlhVxUy","executionInfo":{"status":"ok","timestamp":1724148913232,"user_tz":-180,"elapsed":49,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"5a394b1b-b264-4e85-f3b5-c3cc9d29ac94"},"execution_count":19,"outputs":[{"output_type":"execute_result","data":{"text/plain":["  class  \\\n","0     1   \n","1     1   \n","2     1   \n","3     1   \n","4     1   \n","\n","                                                                                                          text  \n","0                           Now all  has to do is get swype on the iphone and it will be crack. Iphone that is  \n","1                                        will be adding more carrier support to the iPhone 4S (just announced)  \n","2  Hilarious  video - guy does a duet with  's Siri. Pretty much sums up the love affair! http://t.co/8ExbnQjY  \n","3                                                    you made it too easy for me to switch to  iPhone. See ya!  \n","4                                          I just realized that the reason I got into twitter was ios5 thanks   "],"text/html":["\n","  <div id=\"df-7d12342e-9ab9-4217-acf3-9db58615cf35\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>class</th>\n","      <th>text</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1</td>\n","      <td>Now all  has to do is get swype on the iphone and it will be crack. Iphone that is</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>will be adding more carrier support to the iPhone 4S (just announced)</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>1</td>\n","      <td>Hilarious  video - guy does a duet with  's Siri. Pretty much sums up the love affair! http://t.co/8ExbnQjY</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1</td>\n","      <td>you made it too easy for me to switch to  iPhone. See ya!</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>1</td>\n","      <td>I just realized that the reason I got into twitter was ios5 thanks</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7d12342e-9ab9-4217-acf3-9db58615cf35')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    .colab-df-buttons div {\n","      margin-bottom: 4px;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","    <script>\n","      const buttonEl =\n","        document.querySelector('#df-7d12342e-9ab9-4217-acf3-9db58615cf35 button.colab-df-convert');\n","      buttonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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Visit the ' +\n","          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n","          + ' to learn more about interactive tables.';\n","        element.innerHTML = '';\n","        dataTable['output_type'] = 'display_data';\n","        await google.colab.output.renderOutput(dataTable, element);\n","        const docLink = document.createElement('div');\n","        docLink.innerHTML = docLinkHtml;\n","        element.appendChild(docLink);\n","      }\n","    </script>\n","  </div>\n","\n","\n","<div id=\"df-f23b2ff4-e04c-4259-bf47-2e295a3af10a\">\n","  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-f23b2ff4-e04c-4259-bf47-2e295a3af10a')\"\n","            title=\"Suggest charts\"\n","            style=\"display:none;\">\n","\n","<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","     width=\"24px\">\n","    <g>\n","        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n","    </g>\n","</svg>\n","  </button>\n","\n","<style>\n","  .colab-df-quickchart {\n","      --bg-color: #E8F0FE;\n","      --fill-color: #1967D2;\n","      --hover-bg-color: #E2EBFA;\n","      --hover-fill-color: #174EA6;\n","      --disabled-fill-color: #AAA;\n","      --disabled-bg-color: #DDD;\n","  }\n","\n","  [theme=dark] .colab-df-quickchart {\n","      --bg-color: #3B4455;\n","      --fill-color: #D2E3FC;\n","      --hover-bg-color: #434B5C;\n","      --hover-fill-color: #FFFFFF;\n","      --disabled-bg-color: #3B4455;\n","      --disabled-fill-color: #666;\n","  }\n","\n","  .colab-df-quickchart {\n","    background-color: var(--bg-color);\n","    border: none;\n","    border-radius: 50%;\n","    cursor: pointer;\n","    display: none;\n","    fill: var(--fill-color);\n","    height: 32px;\n","    padding: 0;\n","    width: 32px;\n","  }\n","\n","  .colab-df-quickchart:hover {\n","    background-color: var(--hover-bg-color);\n","    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n","    fill: var(--button-hover-fill-color);\n","  }\n","\n","  .colab-df-quickchart-complete:disabled,\n","  .colab-df-quickchart-complete:disabled:hover {\n","    background-color: var(--disabled-bg-color);\n","    fill: var(--disabled-fill-color);\n","    box-shadow: none;\n","  }\n","\n","  .colab-df-spinner {\n","    border: 2px solid var(--fill-color);\n","    border-color: transparent;\n","    border-bottom-color: var(--fill-color);\n","    animation:\n","      spin 1s steps(1) infinite;\n","  }\n","\n","  @keyframes spin {\n","    0% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","      border-left-color: var(--fill-color);\n","    }\n","    20% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    30% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","      border-right-color: var(--fill-color);\n","    }\n","    40% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    60% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","    }\n","    80% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-bottom-color: var(--fill-color);\n","    }\n","    90% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","    }\n","  }\n","</style>\n","\n","  <script>\n","    async function quickchart(key) {\n","      const quickchartButtonEl =\n","        document.querySelector('#' + key + ' button');\n","      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n","      quickchartButtonEl.classList.add('colab-df-spinner');\n","      try {\n","        const charts = await google.colab.kernel.invokeFunction(\n","            'suggestCharts', [key], {});\n","      } catch (error) {\n","        console.error('Error during call to suggestCharts:', error);\n","      }\n","      quickchartButtonEl.classList.remove('colab-df-spinner');\n","      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n","    }\n","    (() => {\n","      let quickchartButtonEl =\n","        document.querySelector('#df-f23b2ff4-e04c-4259-bf47-2e295a3af10a button');\n","      quickchartButtonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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She can't connect to your network!!!!!!!\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":19}]},{"cell_type":"code","source":["## An exmaple before removing links\n","df['text'].iloc[400]"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":35},"id":"6D6NjN0CV0nC","executionInfo":{"status":"ok","timestamp":1724148913232,"user_tz":-180,"elapsed":48,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"3f3c531f-da70-4125-bb60-a7e8a4b18233"},"execution_count":20,"outputs":[{"output_type":"execute_result","data":{"text/plain":["\"Dear  how convenient/handy/thoughtful/smart that after iPhone #ios5 update you're apps won't work anymore! (none!!!) :( #gr%\\\\mbl^.%)\""],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":20}]},{"cell_type":"code","source":["## Define a regular expression pattern to match URLs\n","## Apply the above function\n","df['text'] = df['text'].apply(remove_pattern, pattern=r'https?://\\S+|www\\.\\S+')\n","df.head()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"JSqwWMNJV4YB","executionInfo":{"status":"ok","timestamp":1724148913232,"user_tz":-180,"elapsed":47,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"100fb7da-b6a8-4edd-fa4e-cc62d7cd70ff"},"execution_count":21,"outputs":[{"output_type":"execute_result","data":{"text/plain":["  class  \\\n","0     1   \n","1     1   \n","2     1   \n","3     1   \n","4     1   \n","\n","                                                                                      text  \n","0       Now all  has to do is get swype on the iphone and it will be crack. Iphone that is  \n","1                    will be adding more carrier support to the iPhone 4S (just announced)  \n","2  Hilarious  video - guy does a duet with  's Siri. Pretty much sums up the love affair!   \n","3                                you made it too easy for me to switch to  iPhone. See ya!  \n","4                      I just realized that the reason I got into twitter was ios5 thanks   "],"text/html":["\n","  <div id=\"df-d52572c1-5c78-4257-a6df-b440f49712e1\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>class</th>\n","      <th>text</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1</td>\n","      <td>Now all  has to do is get swype on the iphone and it will be crack. Iphone that is</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>will be adding more carrier support to the iPhone 4S (just announced)</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>1</td>\n","      <td>Hilarious  video - guy does a duet with  's Siri. Pretty much sums up the love affair!</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1</td>\n","      <td>you made it too easy for me to switch to  iPhone. See ya!</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>1</td>\n","      <td>I just realized that the reason I got into twitter was ios5 thanks</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d52572c1-5c78-4257-a6df-b440f49712e1')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    .colab-df-buttons div {\n","      margin-bottom: 4px;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","    <script>\n","      const buttonEl =\n","        document.querySelector('#df-d52572c1-5c78-4257-a6df-b440f49712e1 button.colab-df-convert');\n","      buttonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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She can't connect to your network!!!!!!!\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":21}]},{"cell_type":"code","source":["## An exmaple before removing repeated chars\n","df['text'].iloc[0]"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":35},"id":"PzaIkFUxWFEp","executionInfo":{"status":"ok","timestamp":1724148913233,"user_tz":-180,"elapsed":46,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"f6822361-8219-4cea-d994-c398696a7c9c"},"execution_count":22,"outputs":[{"output_type":"execute_result","data":{"text/plain":["'Now all  has to do is get swype on the iphone and it will be crack. Iphone that is'"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":22}]},{"cell_type":"code","source":["## A Function to remove excessive repeated chars while preserving correct words\n","def remove_excessive_repeated_characters(input_string, max_repeats=2):\n","    ## Define a regular expression pattern to match consecutive repeated characters\n","    pattern = f\"(\\\\w)\\\\1{{{max_repeats},}}\"\n","    ## Replace the matched pattern with a single occurrence of the character\n","    cleaned_string = re.sub(pattern, r\"\\1\", input_string)\n","\n","    return cleaned_string\n","\n","## Apply the above function\n","df['text'] = df['text'].apply(remove_excessive_repeated_characters)\n","df.head()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"0QS_5Ui-WjkH","executionInfo":{"status":"ok","timestamp":1724148913233,"user_tz":-180,"elapsed":45,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"8f868dc5-acf2-4273-ee44-f8efe758457e"},"execution_count":23,"outputs":[{"output_type":"execute_result","data":{"text/plain":["  class  \\\n","0     1   \n","1     1   \n","2     1   \n","3     1   \n","4     1   \n","\n","                                                                                      text  \n","0       Now all  has to do is get swype on the iphone and it will be crack. Iphone that is  \n","1                    will be adding more carrier support to the iPhone 4S (just announced)  \n","2  Hilarious  video - guy does a duet with  's Siri. Pretty much sums up the love affair!   \n","3                                you made it too easy for me to switch to  iPhone. See ya!  \n","4                      I just realized that the reason I got into twitter was ios5 thanks   "],"text/html":["\n","  <div id=\"df-7e2e7b83-2978-4b36-85a8-96586c49be48\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>class</th>\n","      <th>text</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1</td>\n","      <td>Now all  has to do is get swype on the iphone and it will be crack. Iphone that is</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>will be adding more carrier support to the iPhone 4S (just announced)</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>1</td>\n","      <td>Hilarious  video - guy does a duet with  's Siri. Pretty much sums up the love affair!</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1</td>\n","      <td>you made it too easy for me to switch to  iPhone. See ya!</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>1</td>\n","      <td>I just realized that the reason I got into twitter was ios5 thanks</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7e2e7b83-2978-4b36-85a8-96586c49be48')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    .colab-df-buttons div {\n","      margin-bottom: 4px;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","    <script>\n","      const buttonEl =\n","        document.querySelector('#df-7e2e7b83-2978-4b36-85a8-96586c49be48 button.colab-df-convert');\n","      buttonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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'block' : 'none';\n","    })();\n","  </script>\n","</div>\n","\n","    </div>\n","  </div>\n"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"dataframe","variable_name":"df","summary":"{\n  \"name\": \"df\",\n  \"rows\": 479,\n  \"fields\": [\n    {\n      \"column\": \"class\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 479,\n        \"samples\": [\n          \" your simply the best.\",\n          \"+1  RT :  PLEASE FIX #Siri!!!! She can't connect to your network!!!!!!!\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":23}]},{"cell_type":"code","source":["## The same exmaple after removing repeated chars\n","df['text'].iloc[0]"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":35},"id":"-fqeNQFNWtUP","executionInfo":{"status":"ok","timestamp":1724148913234,"user_tz":-180,"elapsed":44,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"1f38c834-2bb0-45b4-f537-dfb673641c2b"},"execution_count":24,"outputs":[{"output_type":"execute_result","data":{"text/plain":["'Now all  has to do is get swype on the iphone and it will be crack. Iphone that is'"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":24}]},{"cell_type":"code","source":["## Check on sample before mapping emoticons\n","df['text'].iloc[73]"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":35},"id":"is464-KmWy1e","executionInfo":{"status":"ok","timestamp":1724148913234,"user_tz":-180,"elapsed":43,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"61b766c5-7f29-469a-d575-47e51e4c1fb2"},"execution_count":25,"outputs":[{"output_type":"execute_result","data":{"text/plain":["'Apple sells 4 million iPhones in 3 days  keep doing what you are doing because you are doing it well! '"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":25}]},{"cell_type":"code","source":["## Convert Emojis to Text : example 😀 to Happy , 😢 Sad\n","## This Dataset doesn't contains emojis, but it contains emotioncons like that :D, :)\n","## So, We can't demojize, but we will map the moticons to its meaning.\n","\n","emoticon_meanings = {\n","    \":)\": \"Happy\",\n","    \":(\": \"Sad\",\n","    \":D\": \"Very Happy\",\n","    \":|\": \"Neutral\",\n","    \":O\": \"Surprised\",\n","    \"<3\": \"Love\",\n","    \";)\": \"Wink\",\n","    \":P\": \"Playful\",\n","    \":/\": \"Confused\",\n","    \":*\": \"Kiss\",\n","    \":')\": \"Touched\",\n","    \"XD\": \"Laughing\",\n","    \":3\": \"Cute\",\n","    \">:(\": \"Angry\",\n","    \":-O\": \"Shocked\",\n","    \":|]\": \"Robot\",\n","    \":>\": \"Sly\",\n","    \"^_^\": \"Happy\",\n","    \"O_o\": \"Confused\",\n","    \":-|\": \"Straight Face\",\n","    \":X\": \"Silent\",\n","    \"B-)\": \"Cool\",\n","    \"<(‘.'<)\": \"Dance\",\n","    \"(-_-)\": \"Bored\",\n","    \"(>_<)\": \"Upset\",\n","    \"(¬‿¬)\": \"Sarcastic\",\n","    \"(o_o)\": \"Surprised\",\n","    \"(o.O)\": \"Shocked\",\n","    \":0\": \"Shocked\",\n","    \":*(\": \"Crying\",\n","    \":v\": \"Pac-Man\",\n","    \"(^_^)v\": \"Double Victory\",\n","    \":-D\": \"Big Grin\",\n","    \":-*\": \"Blowing a Kiss\",\n","    \":^)\": \"Nosey\",\n","    \":-((\": \"Very Sad\",\n","    \":-(\": \"Frowning\",\n","}\n","\n","\n","## Function to replace emoticons with their meanings\n","def convert_emoticons(text: str):\n","    ''' This Function is to replace the emoticons with thier meaning instead\n","    '''\n","    for emoticon, meaning in emoticon_meanings.items():\n","        text = text.replace(emoticon, meaning)\n","    return text\n","\n","## Apply the function on our dataset\n","df['text'] = df['text'].apply(convert_emoticons)\n","df.head()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"j2ZqX043W3Ym","executionInfo":{"status":"ok","timestamp":1724148913234,"user_tz":-180,"elapsed":42,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"c02fbc0e-17a2-49fd-f74a-50dce8526e3c"},"execution_count":26,"outputs":[{"output_type":"execute_result","data":{"text/plain":["  class  \\\n","0     1   \n","1     1   \n","2     1   \n","3     1   \n","4     1   \n","\n","                                                                                      text  \n","0       Now all  has to do is get swype on the iphone and it will be crack. Iphone that is  \n","1                    will be adding more carrier support to the iPhone 4S (just announced)  \n","2  Hilarious  video - guy does a duet with  's Siri. Pretty much sums up the love affair!   \n","3                                you made it too easy for me to switch to  iPhone. See ya!  \n","4                      I just realized that the reason I got into twitter was ios5 thanks   "],"text/html":["\n","  <div id=\"df-f6def599-c90e-4827-8965-617cda13ec56\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>class</th>\n","      <th>text</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1</td>\n","      <td>Now all  has to do is get swype on the iphone and it will be crack. Iphone that is</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>will be adding more carrier support to the iPhone 4S (just announced)</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>1</td>\n","      <td>Hilarious  video - guy does a duet with  's Siri. Pretty much sums up the love affair!</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1</td>\n","      <td>you made it too easy for me to switch to  iPhone. See ya!</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>1</td>\n","      <td>I just realized that the reason I got into twitter was ios5 thanks</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f6def599-c90e-4827-8965-617cda13ec56')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    .colab-df-buttons div {\n","      margin-bottom: 4px;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","    <script>\n","      const buttonEl =\n","        document.querySelector('#df-f6def599-c90e-4827-8965-617cda13ec56 button.colab-df-convert');\n","      buttonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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Visit the ' +\n","          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n","          + ' to learn more about interactive tables.';\n","        element.innerHTML = '';\n","        dataTable['output_type'] = 'display_data';\n","        await google.colab.output.renderOutput(dataTable, element);\n","        const docLink = document.createElement('div');\n","        docLink.innerHTML = docLinkHtml;\n","        element.appendChild(docLink);\n","      }\n","    </script>\n","  </div>\n","\n","\n","<div id=\"df-de21bf93-4dde-4520-89ef-d651432ec13c\">\n","  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-de21bf93-4dde-4520-89ef-d651432ec13c')\"\n","            title=\"Suggest charts\"\n","            style=\"display:none;\">\n","\n","<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","     width=\"24px\">\n","    <g>\n","        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n","    </g>\n","</svg>\n","  </button>\n","\n","<style>\n","  .colab-df-quickchart {\n","      --bg-color: #E8F0FE;\n","      --fill-color: #1967D2;\n","      --hover-bg-color: #E2EBFA;\n","      --hover-fill-color: #174EA6;\n","      --disabled-fill-color: #AAA;\n","      --disabled-bg-color: #DDD;\n","  }\n","\n","  [theme=dark] .colab-df-quickchart {\n","      --bg-color: #3B4455;\n","      --fill-color: #D2E3FC;\n","      --hover-bg-color: #434B5C;\n","      --hover-fill-color: #FFFFFF;\n","      --disabled-bg-color: #3B4455;\n","      --disabled-fill-color: #666;\n","  }\n","\n","  .colab-df-quickchart {\n","    background-color: var(--bg-color);\n","    border: none;\n","    border-radius: 50%;\n","    cursor: pointer;\n","    display: none;\n","    fill: var(--fill-color);\n","    height: 32px;\n","    padding: 0;\n","    width: 32px;\n","  }\n","\n","  .colab-df-quickchart:hover {\n","    background-color: var(--hover-bg-color);\n","    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n","    fill: var(--button-hover-fill-color);\n","  }\n","\n","  .colab-df-quickchart-complete:disabled,\n","  .colab-df-quickchart-complete:disabled:hover {\n","    background-color: var(--disabled-bg-color);\n","    fill: var(--disabled-fill-color);\n","    box-shadow: none;\n","  }\n","\n","  .colab-df-spinner {\n","    border: 2px solid var(--fill-color);\n","    border-color: transparent;\n","    border-bottom-color: var(--fill-color);\n","    animation:\n","      spin 1s steps(1) infinite;\n","  }\n","\n","  @keyframes spin {\n","    0% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","      border-left-color: var(--fill-color);\n","    }\n","    20% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    30% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","      border-right-color: var(--fill-color);\n","    }\n","    40% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    60% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","    }\n","    80% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-bottom-color: var(--fill-color);\n","    }\n","    90% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","    }\n","  }\n","</style>\n","\n","  <script>\n","    async function quickchart(key) {\n","      const quickchartButtonEl =\n","        document.querySelector('#' + key + ' button');\n","      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n","      quickchartButtonEl.classList.add('colab-df-spinner');\n","      try {\n","        const charts = await google.colab.kernel.invokeFunction(\n","            'suggestCharts', [key], {});\n","      } catch (error) {\n","        console.error('Error during call to suggestCharts:', error);\n","      }\n","      quickchartButtonEl.classList.remove('colab-df-spinner');\n","      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n","    }\n","    (() => {\n","      let quickchartButtonEl =\n","        document.querySelector('#df-de21bf93-4dde-4520-89ef-d651432ec13c button');\n","      quickchartButtonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 'block' : 'none';\n","    })();\n","  </script>\n","</div>\n","\n","    </div>\n","  </div>\n"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"dataframe","variable_name":"df","summary":"{\n  \"name\": \"df\",\n  \"rows\": 479,\n  \"fields\": [\n    {\n      \"column\": \"class\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 479,\n        \"samples\": [\n          \" your simply the best.\",\n          \"+1  RT :  PLEASE FIX #Siri!!!! She can't connect to your network!!!!!!!\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":26}]},{"cell_type":"code","source":["## The same exmaple after mapping emoticons\n","df['text'].iloc[73]"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":35},"id":"t54gv9XnW9IG","executionInfo":{"status":"ok","timestamp":1724148913234,"user_tz":-180,"elapsed":41,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"d366f9c6-13d9-440a-8100-c4f4e57e8dae"},"execution_count":27,"outputs":[{"output_type":"execute_result","data":{"text/plain":["'Apple sells 4 million iPhones in 3 days  keep doing what you are doing because you are doing it well! '"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":27}]},{"cell_type":"code","source":["## Removing Punctuations, Numbers, and Special Characters\n","df['text'] = df['text'].str.replace('[^a-zA-Z#]', ' ')\n","df.head()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"l4sZj2XtXBKW","executionInfo":{"status":"ok","timestamp":1724148913235,"user_tz":-180,"elapsed":42,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"273e6202-2a3e-49f6-db22-0c10141d5def"},"execution_count":28,"outputs":[{"output_type":"execute_result","data":{"text/plain":["  class  \\\n","0     1   \n","1     1   \n","2     1   \n","3     1   \n","4     1   \n","\n","                                                                                      text  \n","0       Now all  has to do is get swype on the iphone and it will be crack. Iphone that is  \n","1                    will be adding more carrier support to the iPhone 4S (just announced)  \n","2  Hilarious  video - guy does a duet with  's Siri. Pretty much sums up the love affair!   \n","3                                you made it too easy for me to switch to  iPhone. See ya!  \n","4                      I just realized that the reason I got into twitter was ios5 thanks   "],"text/html":["\n","  <div id=\"df-d627efb2-8e9f-4d34-81ce-0cb66032b2a2\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>class</th>\n","      <th>text</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1</td>\n","      <td>Now all  has to do is get swype on the iphone and it will be crack. Iphone that is</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>will be adding more carrier support to the iPhone 4S (just announced)</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>1</td>\n","      <td>Hilarious  video - guy does a duet with  's Siri. Pretty much sums up the love affair!</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1</td>\n","      <td>you made it too easy for me to switch to  iPhone. See ya!</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>1</td>\n","      <td>I just realized that the reason I got into twitter was ios5 thanks</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d627efb2-8e9f-4d34-81ce-0cb66032b2a2')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    .colab-df-buttons div {\n","      margin-bottom: 4px;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","    <script>\n","      const buttonEl =\n","        document.querySelector('#df-d627efb2-8e9f-4d34-81ce-0cb66032b2a2 button.colab-df-convert');\n","      buttonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 'block' : 'none';\n","\n","      async function convertToInteractive(key) {\n","        const element = document.querySelector('#df-d627efb2-8e9f-4d34-81ce-0cb66032b2a2');\n","        const dataTable =\n","          await google.colab.kernel.invokeFunction('convertToInteractive',\n","                                                    [key], {});\n","        if (!dataTable) return;\n","\n","        const docLinkHtml = 'Like what you see? Visit the ' +\n","          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n","          + ' to learn more about interactive tables.';\n","        element.innerHTML = '';\n","        dataTable['output_type'] = 'display_data';\n","        await google.colab.output.renderOutput(dataTable, element);\n","        const docLink = document.createElement('div');\n","        docLink.innerHTML = docLinkHtml;\n","        element.appendChild(docLink);\n","      }\n","    </script>\n","  </div>\n","\n","\n","<div id=\"df-7266440f-0985-440b-a0a3-b091e1e7d7d4\">\n","  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-7266440f-0985-440b-a0a3-b091e1e7d7d4')\"\n","            title=\"Suggest charts\"\n","            style=\"display:none;\">\n","\n","<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","     width=\"24px\">\n","    <g>\n","        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n","    </g>\n","</svg>\n","  </button>\n","\n","<style>\n","  .colab-df-quickchart {\n","      --bg-color: #E8F0FE;\n","      --fill-color: #1967D2;\n","      --hover-bg-color: #E2EBFA;\n","      --hover-fill-color: #174EA6;\n","      --disabled-fill-color: #AAA;\n","      --disabled-bg-color: #DDD;\n","  }\n","\n","  [theme=dark] .colab-df-quickchart {\n","      --bg-color: #3B4455;\n","      --fill-color: #D2E3FC;\n","      --hover-bg-color: #434B5C;\n","      --hover-fill-color: #FFFFFF;\n","      --disabled-bg-color: #3B4455;\n","      --disabled-fill-color: #666;\n","  }\n","\n","  .colab-df-quickchart {\n","    background-color: var(--bg-color);\n","    border: none;\n","    border-radius: 50%;\n","    cursor: pointer;\n","    display: none;\n","    fill: var(--fill-color);\n","    height: 32px;\n","    padding: 0;\n","    width: 32px;\n","  }\n","\n","  .colab-df-quickchart:hover {\n","    background-color: var(--hover-bg-color);\n","    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n","    fill: var(--button-hover-fill-color);\n","  }\n","\n","  .colab-df-quickchart-complete:disabled,\n","  .colab-df-quickchart-complete:disabled:hover {\n","    background-color: var(--disabled-bg-color);\n","    fill: var(--disabled-fill-color);\n","    box-shadow: none;\n","  }\n","\n","  .colab-df-spinner {\n","    border: 2px solid var(--fill-color);\n","    border-color: transparent;\n","    border-bottom-color: var(--fill-color);\n","    animation:\n","      spin 1s steps(1) infinite;\n","  }\n","\n","  @keyframes spin {\n","    0% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","      border-left-color: var(--fill-color);\n","    }\n","    20% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    30% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","      border-right-color: var(--fill-color);\n","    }\n","    40% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    60% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","    }\n","    80% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-bottom-color: var(--fill-color);\n","    }\n","    90% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","    }\n","  }\n","</style>\n","\n","  <script>\n","    async function quickchart(key) {\n","      const quickchartButtonEl =\n","        document.querySelector('#' + key + ' button');\n","      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n","      quickchartButtonEl.classList.add('colab-df-spinner');\n","      try {\n","        const charts = await google.colab.kernel.invokeFunction(\n","            'suggestCharts', [key], {});\n","      } catch (error) {\n","        console.error('Error during call to suggestCharts:', error);\n","      }\n","      quickchartButtonEl.classList.remove('colab-df-spinner');\n","      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n","    }\n","    (() => {\n","      let quickchartButtonEl =\n","        document.querySelector('#df-7266440f-0985-440b-a0a3-b091e1e7d7d4 button');\n","      quickchartButtonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 'block' : 'none';\n","    })();\n","  </script>\n","</div>\n","\n","    </div>\n","  </div>\n"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"dataframe","variable_name":"df","summary":"{\n  \"name\": \"df\",\n  \"rows\": 479,\n  \"fields\": [\n    {\n      \"column\": \"class\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 479,\n        \"samples\": [\n          \" your simply the best.\",\n          \"+1  RT :  PLEASE FIX #Siri!!!! She can't connect to your network!!!!!!!\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":28}]},{"cell_type":"code","source":["df['text'].iloc[73]"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":35},"id":"NRkYa-AHZ8mP","executionInfo":{"status":"ok","timestamp":1724148913235,"user_tz":-180,"elapsed":41,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"d188d117-0767-4e52-b79d-e008de0e07e4"},"execution_count":29,"outputs":[{"output_type":"execute_result","data":{"text/plain":["'Apple sells 4 million iPhones in 3 days  keep doing what you are doing because you are doing it well! '"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":29}]},{"cell_type":"code","source":["## Removing Short Words\n","df['text'] = df['text'].apply(lambda x: ' '.join([w for w in x.split() if len(w)>3]))\n","df.head()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"WcafS4LxXGYV","executionInfo":{"status":"ok","timestamp":1724148913236,"user_tz":-180,"elapsed":41,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"d11a1860-af40-40a1-95f2-9d1b1d4ba216"},"execution_count":30,"outputs":[{"output_type":"execute_result","data":{"text/plain":["  class                                                                text\n","0     1                                swype iphone will crack. Iphone that\n","1     1            will adding more carrier support iPhone (just announced)\n","2     1  Hilarious video does duet with Siri. Pretty much sums love affair!\n","3     1                                            made easy switch iPhone.\n","4     1                  just realized that reason into twitter ios5 thanks"],"text/html":["\n","  <div id=\"df-78855cf6-4547-4518-a2fe-1f82a299ba3e\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>class</th>\n","      <th>text</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1</td>\n","      <td>swype iphone will crack. Iphone that</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>will adding more carrier support iPhone (just announced)</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>1</td>\n","      <td>Hilarious video does duet with Siri. Pretty much sums love affair!</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1</td>\n","      <td>made easy switch iPhone.</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>1</td>\n","      <td>just realized that reason into twitter ios5 thanks</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-78855cf6-4547-4518-a2fe-1f82a299ba3e')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    .colab-df-buttons div {\n","      margin-bottom: 4px;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","    <script>\n","      const buttonEl =\n","        document.querySelector('#df-78855cf6-4547-4518-a2fe-1f82a299ba3e button.colab-df-convert');\n","      buttonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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Iphone that\n","1     1            will adding more carrier support iPhone (just announced)\n","2     1  Hilarious video does duet with Siri. Pretty much sums love affair!\n","3     1                                            made easy switch iPhone.\n","4     1                   just realized that reason into twitter ios thanks"],"text/html":["\n","  <div id=\"df-2022556f-c184-4e97-b7a8-f7edc7ac0fb9\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>class</th>\n","      <th>text</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1</td>\n","      <td>swype iphone will crack. 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Pretty much sums love affair!</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1</td>\n","      <td>made easy switch iPhone.</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>1</td>\n","      <td>just realized that reason into twitter ios thanks</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-2022556f-c184-4e97-b7a8-f7edc7ac0fb9')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    .colab-df-buttons div {\n","      margin-bottom: 4px;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","    <script>\n","      const buttonEl =\n","        document.querySelector('#df-2022556f-c184-4e97-b7a8-f7edc7ac0fb9 button.colab-df-convert');\n","      buttonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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Visit the ' +\n","          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n","          + ' to learn more about interactive tables.';\n","        element.innerHTML = '';\n","        dataTable['output_type'] = 'display_data';\n","        await google.colab.output.renderOutput(dataTable, element);\n","        const docLink = document.createElement('div');\n","        docLink.innerHTML = docLinkHtml;\n","        element.appendChild(docLink);\n","      }\n","    </script>\n","  </div>\n","\n","\n","<div id=\"df-7a1debc1-5cd4-4234-98dc-303e1343152f\">\n","  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-7a1debc1-5cd4-4234-98dc-303e1343152f')\"\n","            title=\"Suggest charts\"\n","            style=\"display:none;\">\n","\n","<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","     width=\"24px\">\n","    <g>\n","        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n","    </g>\n","</svg>\n","  </button>\n","\n","<style>\n","  .colab-df-quickchart {\n","      --bg-color: #E8F0FE;\n","      --fill-color: #1967D2;\n","      --hover-bg-color: #E2EBFA;\n","      --hover-fill-color: #174EA6;\n","      --disabled-fill-color: #AAA;\n","      --disabled-bg-color: #DDD;\n","  }\n","\n","  [theme=dark] .colab-df-quickchart {\n","      --bg-color: #3B4455;\n","      --fill-color: #D2E3FC;\n","      --hover-bg-color: #434B5C;\n","      --hover-fill-color: #FFFFFF;\n","      --disabled-bg-color: #3B4455;\n","      --disabled-fill-color: #666;\n","  }\n","\n","  .colab-df-quickchart {\n","    background-color: var(--bg-color);\n","    border: none;\n","    border-radius: 50%;\n","    cursor: pointer;\n","    display: none;\n","    fill: var(--fill-color);\n","    height: 32px;\n","    padding: 0;\n","    width: 32px;\n","  }\n","\n","  .colab-df-quickchart:hover {\n","    background-color: var(--hover-bg-color);\n","    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n","    fill: var(--button-hover-fill-color);\n","  }\n","\n","  .colab-df-quickchart-complete:disabled,\n","  .colab-df-quickchart-complete:disabled:hover {\n","    background-color: var(--disabled-bg-color);\n","    fill: var(--disabled-fill-color);\n","    box-shadow: none;\n","  }\n","\n","  .colab-df-spinner {\n","    border: 2px solid var(--fill-color);\n","    border-color: transparent;\n","    border-bottom-color: var(--fill-color);\n","    animation:\n","      spin 1s steps(1) infinite;\n","  }\n","\n","  @keyframes spin {\n","    0% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","      border-left-color: var(--fill-color);\n","    }\n","    20% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    30% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","      border-right-color: var(--fill-color);\n","    }\n","    40% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    60% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","    }\n","    80% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-bottom-color: var(--fill-color);\n","    }\n","    90% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","    }\n","  }\n","</style>\n","\n","  <script>\n","    async function quickchart(key) {\n","      const quickchartButtonEl =\n","        document.querySelector('#' + key + ' button');\n","      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n","      quickchartButtonEl.classList.add('colab-df-spinner');\n","      try {\n","        const charts = await google.colab.kernel.invokeFunction(\n","            'suggestCharts', [key], {});\n","      } catch (error) {\n","        console.error('Error during call to suggestCharts:', error);\n","      }\n","      quickchartButtonEl.classList.remove('colab-df-spinner');\n","      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n","    }\n","    (() => {\n","      let quickchartButtonEl =\n","        document.querySelector('#df-7a1debc1-5cd4-4234-98dc-303e1343152f button');\n","      quickchartButtonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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Happy\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":32}]},{"cell_type":"code","source":["df['text'] = df['text'].apply(remove_pattern, pattern=r'[!@#$%^&*()_+{}\\[\\]:;<>,.?~\\\\|\\/-]')\n","df.head()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"Tcfi32HiZnnQ","executionInfo":{"status":"ok","timestamp":1724148913669,"user_tz":-180,"elapsed":34,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"7e7c03f3-7b90-420c-d032-2a83a183bc0d"},"execution_count":33,"outputs":[{"output_type":"execute_result","data":{"text/plain":["  class                                                              text\n","0     1                               swype iphone will crack Iphone that\n","1     1            will adding more carrier support iPhone just announced\n","2     1  Hilarious video does duet with Siri Pretty much sums love affair\n","3     1                                           made easy switch iPhone\n","4     1                 just realized that reason into twitter ios thanks"],"text/html":["\n","  <div id=\"df-b3129c84-11ba-4525-b537-469cb61c636c\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>class</th>\n","      <th>text</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1</td>\n","      <td>swype iphone will crack Iphone that</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>will adding more carrier support iPhone just announced</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>1</td>\n","      <td>Hilarious video does duet with Siri Pretty much sums love affair</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1</td>\n","      <td>made easy switch iPhone</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>1</td>\n","      <td>just realized that reason into twitter ios thanks</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b3129c84-11ba-4525-b537-469cb61c636c')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    .colab-df-buttons div {\n","      margin-bottom: 4px;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","    <script>\n","      const buttonEl =\n","        document.querySelector('#df-b3129c84-11ba-4525-b537-469cb61c636c button.colab-df-convert');\n","      buttonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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Visit the ' +\n","          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n","          + ' to learn more about interactive tables.';\n","        element.innerHTML = '';\n","        dataTable['output_type'] = 'display_data';\n","        await google.colab.output.renderOutput(dataTable, element);\n","        const docLink = document.createElement('div');\n","        docLink.innerHTML = docLinkHtml;\n","        element.appendChild(docLink);\n","      }\n","    </script>\n","  </div>\n","\n","\n","<div id=\"df-f3eef596-a5bb-4470-af1a-b0e2c76056d5\">\n","  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-f3eef596-a5bb-4470-af1a-b0e2c76056d5')\"\n","            title=\"Suggest charts\"\n","            style=\"display:none;\">\n","\n","<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","     width=\"24px\">\n","    <g>\n","        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n","    </g>\n","</svg>\n","  </button>\n","\n","<style>\n","  .colab-df-quickchart {\n","      --bg-color: #E8F0FE;\n","      --fill-color: #1967D2;\n","      --hover-bg-color: #E2EBFA;\n","      --hover-fill-color: #174EA6;\n","      --disabled-fill-color: #AAA;\n","      --disabled-bg-color: #DDD;\n","  }\n","\n","  [theme=dark] .colab-df-quickchart {\n","      --bg-color: #3B4455;\n","      --fill-color: #D2E3FC;\n","      --hover-bg-color: #434B5C;\n","      --hover-fill-color: #FFFFFF;\n","      --disabled-bg-color: #3B4455;\n","      --disabled-fill-color: #666;\n","  }\n","\n","  .colab-df-quickchart {\n","    background-color: var(--bg-color);\n","    border: none;\n","    border-radius: 50%;\n","    cursor: pointer;\n","    display: none;\n","    fill: var(--fill-color);\n","    height: 32px;\n","    padding: 0;\n","    width: 32px;\n","  }\n","\n","  .colab-df-quickchart:hover {\n","    background-color: var(--hover-bg-color);\n","    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n","    fill: var(--button-hover-fill-color);\n","  }\n","\n","  .colab-df-quickchart-complete:disabled,\n","  .colab-df-quickchart-complete:disabled:hover {\n","    background-color: var(--disabled-bg-color);\n","    fill: var(--disabled-fill-color);\n","    box-shadow: none;\n","  }\n","\n","  .colab-df-spinner {\n","    border: 2px solid var(--fill-color);\n","    border-color: transparent;\n","    border-bottom-color: var(--fill-color);\n","    animation:\n","      spin 1s steps(1) infinite;\n","  }\n","\n","  @keyframes spin {\n","    0% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","      border-left-color: var(--fill-color);\n","    }\n","    20% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    30% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","      border-right-color: var(--fill-color);\n","    }\n","    40% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    60% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","    }\n","    80% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-bottom-color: var(--fill-color);\n","    }\n","    90% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","    }\n","  }\n","</style>\n","\n","  <script>\n","    async function quickchart(key) {\n","      const quickchartButtonEl =\n","        document.querySelector('#' + key + ' button');\n","      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n","      quickchartButtonEl.classList.add('colab-df-spinner');\n","      try {\n","        const charts = await google.colab.kernel.invokeFunction(\n","            'suggestCharts', [key], {});\n","      } catch (error) {\n","        console.error('Error during call to suggestCharts:', error);\n","      }\n","      quickchartButtonEl.classList.remove('colab-df-spinner');\n","      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n","    }\n","    (() => {\n","      let quickchartButtonEl =\n","        document.querySelector('#df-f3eef596-a5bb-4470-af1a-b0e2c76056d5 button');\n","      quickchartButtonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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]\n}"}},"metadata":{},"execution_count":33}]},{"cell_type":"code","source":["## An exmaple before removing special chars\n","df['text'].iloc[2]"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":35},"id":"Rk0c-tTIXb48","executionInfo":{"status":"ok","timestamp":1724148913669,"user_tz":-180,"elapsed":31,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"7213843d-f9f4-488b-ed14-efce896caa5a"},"execution_count":34,"outputs":[{"output_type":"execute_result","data":{"text/plain":["'Hilarious video does duet with Siri Pretty much sums love affair'"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":34}]},{"cell_type":"code","source":["## Define a regular expression pattern to match special characters\n","## Apply the function to the dataset\n","df['text'] = df['text'].apply(remove_pattern, pattern=r'[!@#$%^&*()_+{}\\[\\]:;<>,.?~\\\\|\\/-]')\n","df.head()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"Wc5dWuAqXkCz","executionInfo":{"status":"ok","timestamp":1724148913669,"user_tz":-180,"elapsed":30,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"6d73ef21-aa1e-4906-8af9-7468d114e9a5"},"execution_count":35,"outputs":[{"output_type":"execute_result","data":{"text/plain":["  class                                                              text\n","0     1                               swype iphone will crack Iphone that\n","1     1            will adding more carrier support iPhone just announced\n","2     1  Hilarious video does duet with Siri Pretty much sums love affair\n","3     1                                           made easy switch iPhone\n","4     1                 just realized that reason into twitter ios thanks"],"text/html":["\n","  <div id=\"df-4ed2486e-ca73-46fc-a782-0774e3d9e698\" 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Visit the ' +\n","          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n","          + ' to learn more about interactive tables.';\n","        element.innerHTML = '';\n","        dataTable['output_type'] = 'display_data';\n","        await google.colab.output.renderOutput(dataTable, element);\n","        const docLink = document.createElement('div');\n","        docLink.innerHTML = docLinkHtml;\n","        element.appendChild(docLink);\n","      }\n","    </script>\n","  </div>\n","\n","\n","<div id=\"df-7df3b836-f594-46e3-866e-d7fb345a29d0\">\n","  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-7df3b836-f594-46e3-866e-d7fb345a29d0')\"\n","            title=\"Suggest charts\"\n","            style=\"display:none;\">\n","\n","<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","     width=\"24px\">\n","    <g>\n","        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n","    </g>\n","</svg>\n","  </button>\n","\n","<style>\n","  .colab-df-quickchart {\n","      --bg-color: #E8F0FE;\n","      --fill-color: #1967D2;\n","      --hover-bg-color: #E2EBFA;\n","      --hover-fill-color: #174EA6;\n","      --disabled-fill-color: #AAA;\n","      --disabled-bg-color: #DDD;\n","  }\n","\n","  [theme=dark] .colab-df-quickchart {\n","      --bg-color: #3B4455;\n","      --fill-color: #D2E3FC;\n","      --hover-bg-color: #434B5C;\n","      --hover-fill-color: #FFFFFF;\n","      --disabled-bg-color: #3B4455;\n","      --disabled-fill-color: #666;\n","  }\n","\n","  .colab-df-quickchart {\n","    background-color: var(--bg-color);\n","    border: none;\n","    border-radius: 50%;\n","    cursor: pointer;\n","    display: none;\n","    fill: var(--fill-color);\n","    height: 32px;\n","    padding: 0;\n","    width: 32px;\n","  }\n","\n","  .colab-df-quickchart:hover {\n","    background-color: var(--hover-bg-color);\n","    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n","    fill: var(--button-hover-fill-color);\n","  }\n","\n","  .colab-df-quickchart-complete:disabled,\n","  .colab-df-quickchart-complete:disabled:hover {\n","    background-color: var(--disabled-bg-color);\n","    fill: var(--disabled-fill-color);\n","    box-shadow: none;\n","  }\n","\n","  .colab-df-spinner {\n","    border: 2px solid var(--fill-color);\n","    border-color: transparent;\n","    border-bottom-color: var(--fill-color);\n","    animation:\n","      spin 1s steps(1) infinite;\n","  }\n","\n","  @keyframes spin {\n","    0% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","      border-left-color: var(--fill-color);\n","    }\n","    20% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    30% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","      border-right-color: var(--fill-color);\n","    }\n","    40% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    60% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","    }\n","    80% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-bottom-color: var(--fill-color);\n","    }\n","    90% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","    }\n","  }\n","</style>\n","\n","  <script>\n","    async function quickchart(key) {\n","      const quickchartButtonEl =\n","        document.querySelector('#' + key + ' button');\n","      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n","      quickchartButtonEl.classList.add('colab-df-spinner');\n","      try {\n","        const charts = await google.colab.kernel.invokeFunction(\n","            'suggestCharts', [key], {});\n","      } catch (error) {\n","        console.error('Error during call to suggestCharts:', error);\n","      }\n","      quickchartButtonEl.classList.remove('colab-df-spinner');\n","      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n","    }\n","    (() => {\n","      let quickchartButtonEl =\n","        document.querySelector('#df-7df3b836-f594-46e3-866e-d7fb345a29d0 button');\n","      quickchartButtonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 'block' : 'none';\n","    })();\n","  </script>\n","</div>\n","\n","    </div>\n","  </div>\n"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"dataframe","variable_name":"df","summary":"{\n  \"name\": \"df\",\n  \"rows\": 479,\n  \"fields\": [\n    {\n      \"column\": \"class\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 459,\n        \"samples\": [\n          \"backside phone impressed with\",\n          \"OVER people bitching about iPhoneS think it's smartest phone I've ever very happy Happy\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":35}]},{"cell_type":"code","source":["## The same exmaple after removing special chars\n","df['text'].iloc[2]"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":35},"id":"gVp7QrJ_XnfL","executionInfo":{"status":"ok","timestamp":1724148913670,"user_tz":-180,"elapsed":29,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"4f54a393-ac9b-41d8-944c-dad359ea3962"},"execution_count":36,"outputs":[{"output_type":"execute_result","data":{"text/plain":["'Hilarious video does duet with Siri Pretty much sums love affair'"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":36}]},{"cell_type":"code","source":["nltk.download('stopwords')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Bbfb9cUcXyab","executionInfo":{"status":"ok","timestamp":1724148913670,"user_tz":-180,"elapsed":28,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"f2d90c42-e3ab-4ac9-9a79-7841940cf870"},"execution_count":37,"outputs":[{"output_type":"stream","name":"stderr","text":["[nltk_data] Downloading package stopwords to /root/nltk_data...\n","[nltk_data]   Package stopwords is already up-to-date!\n"]},{"output_type":"execute_result","data":{"text/plain":["True"]},"metadata":{},"execution_count":37}]},{"cell_type":"code","source":["## An exmaple before solving that\n","df['text'].iloc[3]"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":35},"id":"qdaqR1-VX4WK","executionInfo":{"status":"ok","timestamp":1724148913670,"user_tz":-180,"elapsed":23,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"ba46e6ad-3b8d-4192-c9ae-b015c44e3296"},"execution_count":38,"outputs":[{"output_type":"execute_result","data":{"text/plain":["'made easy switch iPhone'"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":38}]},{"cell_type":"code","source":["## A Function to remove redundant words like (I've, You'll)\n","## Again, It is challenging\n","\n","def remove_redundant_words_extra_spaces(text: str):\n","    ## Remove contractions using regular expressions\n","    contraction_pattern = re.compile(r\"'\\w+|\\w+'\\w+|\\w+'\")\n","    text = contraction_pattern.sub('', text)\n","\n","    ## Define a set of stopwords\n","    stop_words = set(stopwords.words(\"english\"))\n","\n","    ## Remove stopwords and extra spaces\n","    words = text.split()\n","    filtered_words = [word for word in words if word.lower() not in stop_words]\n","    clean_text = ' '.join(filtered_words)\n","\n","    ## Remove extra spaces\n","    clean_text = ' '.join(clean_text.split())\n","\n","    return clean_text\n","\n","\n","## Apply the above function\n","df['text'] = df['text'].apply(remove_redundant_words_extra_spaces)"],"metadata":{"id":"rSQOfszoX71L","executionInfo":{"status":"ok","timestamp":1724148914018,"user_tz":-180,"elapsed":370,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}}},"execution_count":39,"outputs":[]},{"cell_type":"code","source":["## The same exmaple after solving that\n","df['text'].iloc[3]"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":35},"id":"6U_PUA6lYATj","executionInfo":{"status":"ok","timestamp":1724148914019,"user_tz":-180,"elapsed":17,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"cfd95298-ef50-495b-98eb-fa972f779b8f"},"execution_count":40,"outputs":[{"output_type":"execute_result","data":{"text/plain":["'made easy switch iPhone'"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":40}]},{"cell_type":"code","source":["## Call the above function (remove_pattern), We want to remove the numbers from words\n","## We don't remove all numbers on the dataset, The pattern only removes the numbers within the words\n","df['text'] = np.vectorize(remove_pattern)(input_txt=df['text'], pattern='(?<=\\w)\\d+|\\d+(?=\\w)')\n","df.head()\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"2LOJPQBIc-bs","executionInfo":{"status":"ok","timestamp":1724148914019,"user_tz":-180,"elapsed":15,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"542a72dd-ee8a-459f-c7a6-c76cc10ee3a2"},"execution_count":41,"outputs":[{"output_type":"execute_result","data":{"text/plain":["  class                                                    text\n","0     1                               swype iphone crack Iphone\n","1     1                 adding carrier support iPhone announced\n","2     1  Hilarious video duet Siri Pretty much sums love affair\n","3     1                                 made easy switch iPhone\n","4     1                      realized reason twitter ios thanks"],"text/html":["\n","  <div id=\"df-66ea7df1-08e6-4fc4-b207-8218410a4539\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>class</th>\n","      <th>text</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1</td>\n","      <td>swype iphone crack Iphone</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>adding carrier support iPhone announced</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>1</td>\n","      <td>Hilarious video duet Siri Pretty much 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]\n}"}},"metadata":{},"execution_count":41}]},{"cell_type":"code","source":["df['text'].iloc[123]"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":35},"id":"VKwUm2LidAVj","executionInfo":{"status":"ok","timestamp":1724148914020,"user_tz":-180,"elapsed":14,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"6657bfa8-9bcf-4cc6-a957-1dc32266bc44"},"execution_count":42,"outputs":[{"output_type":"execute_result","data":{"text/plain":["'lt'"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":42}]},{"cell_type":"code","source":["## Removing Short Words\n","df['text'] = df['text'].apply(lambda x: ' '.join([w for w in x.split() if len(w)>3]))\n","df.head()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"YAnfyTe8dodc","executionInfo":{"status":"ok","timestamp":1724148914020,"user_tz":-180,"elapsed":13,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"610eef52-f0ff-4da4-a9d5-e3233827a63f"},"execution_count":43,"outputs":[{"output_type":"execute_result","data":{"text/plain":["  class                                                    text\n","0     1                               swype iphone crack Iphone\n","1     1                 adding carrier support iPhone announced\n","2     1  Hilarious video duet Siri Pretty much sums love affair\n","3     1                                 made easy switch iPhone\n","4     1                          realized reason twitter thanks"],"text/html":["\n","  <div id=\"df-ad12473d-3768-450f-9ba7-6cb0fcbc3c17\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table 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]\n}"}},"metadata":{},"execution_count":43}]},{"cell_type":"code","source":["df['text'].iloc[123]"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":35},"id":"be8r96BodqCQ","executionInfo":{"status":"ok","timestamp":1724148914337,"user_tz":-180,"elapsed":329,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"78467b84-6e43-45f5-f531-664c30507e22"},"execution_count":44,"outputs":[{"output_type":"execute_result","data":{"text/plain":["''"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":44}]},{"cell_type":"code","source":["df = df[df['text'] != '']"],"metadata":{"id":"e2tx5pMJXk-v","executionInfo":{"status":"ok","timestamp":1724148914337,"user_tz":-180,"elapsed":6,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}}},"execution_count":45,"outputs":[]},{"cell_type":"code","source":["## Download the dataset here at this step before Stemming or Lemmatizing\n","df.to_excel('twitter-sanders-apple2-after-data-preparation.xlsx', index=False)"],"metadata":{"id":"jFg6OaynYIGS","executionInfo":{"status":"ok","timestamp":1724148914703,"user_tz":-180,"elapsed":371,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}}},"execution_count":46,"outputs":[]},{"cell_type":"code","source":["## Download the dataset here at this step before Stemming or Lemmatizing\n","df.to_csv('twitter-sanders-apple2-after-data-preparation.csv', index=False)"],"metadata":{"id":"tnq86RTxdNnE","executionInfo":{"status":"ok","timestamp":1724148914704,"user_tz":-180,"elapsed":7,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}}},"execution_count":47,"outputs":[]},{"cell_type":"code","source":["df['text'].iloc[29]"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":35},"id":"6hn6gJQ5W4hD","executionInfo":{"status":"ok","timestamp":1724148914704,"user_tz":-180,"elapsed":6,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"d38570b5-384e-46d7-89b1-ec9306897b94"},"execution_count":48,"outputs":[{"output_type":"execute_result","data":{"text/plain":["'question iPhone'"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":48}]},{"cell_type":"markdown","source":["# Transformer"],"metadata":{"id":"OEFZ3bRk4F16"}},{"cell_type":"markdown","source":["## Apply Pipeline of HuggingFace on Twitter database 2"],"metadata":{"id":"J9qdyEbR4Uas"}},{"cell_type":"code","source":["from transformers import pipeline"],"metadata":{"id":"eCysn3Ibf_O_","executionInfo":{"status":"ok","timestamp":1724148936948,"user_tz":-180,"elapsed":22249,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}}},"execution_count":49,"outputs":[]},{"cell_type":"code","source":["classifier = pipeline(\"sentiment-analysis\", model=\"distilbert/distilbert-base-uncased-finetuned-sst-2-english\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":145,"referenced_widgets":["7ce653bda5744dbf90b2c1e4c775f697","bcda0532761d4e62b5ae608c38ff590d","7b9ed7cc70ac49708ddc4a2b443f661b","d1392bd606a747168117117de65f311f","e431d7a6770d418ca7b4e1bf46b97442","e8a4703ab51446a0bb6fe27dfee03823","e598f523e8404d3aa2eba718dd712f89","b649b6b5f3ed483e9253d2f12a2ae23f","ae99f0bcac0b4ff58f0c579097bba71a","3b5529cd6f274c6aba4ca9f71701a876","9b149acbd5a449cfac8920a3ca0f3e2c","6764a7cbb9244911a30b1d811705b8ef","e19b8dbbe49b48d4bc211ca18e2ce8b7","3ee8166fca5a4c428468d2870004f352","eebd7108b6414a639039259e57e6bfdf","96c8b45da5c14ec4accb26412da3ae30","947b1205e1004387808b58e8f23a7c5c","57d54f38b92a416aad377b1c3ba66512","4e8f08c8fc924b9497f88434d6e3e7ee","28ee20448a3b4b6f9bd8380ba53e1178","949596cd99e743378b1dfb8515a5deee","ed168bacd0744a92b4ab87113a9d5d2a","1a004b2665904f9d8c015bf1e77cf6b5","78e158a92ef7433c98fb768308899b2a","e96117b093664217a986de322898c3e9","b0f5128a269447419d2baacb841bfc51","9666e014cfe145da9f4757bf282c7589","fc9a10e4269a47a2b83d237eb83329fd","ea531b2a9a64490789a96ad1b1f52ac4","c4669fef52e542429a58bb669750f91b","4b6a76bfcc234e5b91e0d48edbbc0826","8058419261b54c3da0fe165e02d3ae6e","074a94e25f8c44c6ba44263bb11b03b1","1beb8a4ac2c445d287be796d62a6c1bb","4677b2fa77e244b687d328f95caaae4e","fcc1471340e0487a8aa33401adbcb721","1058644cc0f54286a20a33fa2c93753f","51b03d40b9d242e8b37e0eb51d4610ab","50be78fbbfa34a51b526de5d83ad3eb1","6d82697cafa4429d960588bb999e9a4b","c298966e39ba44feb4ec50712458ec33","226b63062b3b4df89a9fb805b769d23c","4cb72547a2ff4c8d8f4be380ad2e62c2","eff497152404405688a533de60016393"]},"id":"zzZGnUCI4oZa","executionInfo":{"status":"ok","timestamp":1724148943615,"user_tz":-180,"elapsed":6687,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"984dc7b7-dcf2-485b-8925-20125c9ae822"},"execution_count":50,"outputs":[{"output_type":"display_data","data":{"text/plain":["config.json:   0%|          | 0.00/629 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"7ce653bda5744dbf90b2c1e4c775f697"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["model.safetensors:   0%|          | 0.00/268M [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"6764a7cbb9244911a30b1d811705b8ef"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["tokenizer_config.json:   0%|          | 0.00/48.0 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"1a004b2665904f9d8c015bf1e77cf6b5"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["vocab.txt:   0%|          | 0.00/232k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"1beb8a4ac2c445d287be796d62a6c1bb"}},"metadata":{}}]},{"cell_type":"code","source":["# Check the task name and the defualt model\n","classifier.task, classifier.model"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"mzLYA_m77WDR","executionInfo":{"status":"ok","timestamp":1724148943615,"user_tz":-180,"elapsed":20,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"ad6c29a3-7e3b-4c89-942d-18f22d576dc5"},"execution_count":51,"outputs":[{"output_type":"execute_result","data":{"text/plain":["('sentiment-analysis',\n"," DistilBertForSequenceClassification(\n","   (distilbert): DistilBertModel(\n","     (embeddings): Embeddings(\n","       (word_embeddings): Embedding(30522, 768, padding_idx=0)\n","       (position_embeddings): Embedding(512, 768)\n","       (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n","       (dropout): Dropout(p=0.1, inplace=False)\n","     )\n","     (transformer): Transformer(\n","       (layer): ModuleList(\n","         (0-5): 6 x TransformerBlock(\n","           (attention): MultiHeadSelfAttention(\n","             (dropout): Dropout(p=0.1, inplace=False)\n","             (q_lin): Linear(in_features=768, out_features=768, bias=True)\n","             (k_lin): Linear(in_features=768, out_features=768, bias=True)\n","             (v_lin): Linear(in_features=768, out_features=768, bias=True)\n","             (out_lin): Linear(in_features=768, out_features=768, bias=True)\n","           )\n","           (sa_layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n","           (ffn): FFN(\n","             (dropout): Dropout(p=0.1, inplace=False)\n","             (lin1): Linear(in_features=768, out_features=3072, bias=True)\n","             (lin2): Linear(in_features=3072, out_features=768, bias=True)\n","             (activation): GELUActivation()\n","           )\n","           (output_layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n","         )\n","       )\n","     )\n","   )\n","   (pre_classifier): Linear(in_features=768, out_features=768, bias=True)\n","   (classifier): Linear(in_features=768, out_features=2, bias=True)\n","   (dropout): Dropout(p=0.2, inplace=False)\n"," ))"]},"metadata":{},"execution_count":51}]},{"cell_type":"code","source":["# List of examples\n","results = classifier([\"We are very happy to show you the 🤗 Transformers library.\", \"We hope you don't hate it.\"])\n","for result in results:\n","    print(f\"label: {result['label']}, with score: {round(result['score'], 4)}\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"3mUWjSbA7cPn","executionInfo":{"status":"ok","timestamp":1724148944060,"user_tz":-180,"elapsed":462,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}},"outputId":"180b7525-62fb-4fd3-b5d5-039cad002315"},"execution_count":52,"outputs":[{"output_type":"stream","name":"stdout","text":["label: POSITIVE, with score: 0.9998\n","label: NEGATIVE, with score: 0.5309\n"]}]},{"cell_type":"code","source":["# Define a function t0 analyze sentiment\n","def analyze_sentiment(text):\n","    result = classifier(text)[0]\n","    return result['label']\n","    # convert the label to postive/negative\n","    if label == 'POSITIVE':\n","        return 1\n","    else:\n","        return 0"],"metadata":{"id":"BnmB3Vo-8C6I","executionInfo":{"status":"ok","timestamp":1724148944060,"user_tz":-180,"elapsed":3,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}}},"execution_count":53,"outputs":[]},{"cell_type":"code","source":["# Apply the sentiment analysis to each tweet\n","df['sentiment'] = df['text'].apply(analyze_sentiment)"],"metadata":{"id":"XispSaHD-1yy","executionInfo":{"status":"ok","timestamp":1724148973164,"user_tz":-180,"elapsed":29106,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}}},"execution_count":54,"outputs":[]},{"cell_type":"code","source":["# Save the result of the transformer pipeline\n","df.to_csv('twitter-sanders-apple2_pipeline.csv', index=False)"],"metadata":{"id":"vMvVdi1A-8vQ","executionInfo":{"status":"ok","timestamp":1724148973165,"user_tz":-180,"elapsed":21,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}}},"execution_count":55,"outputs":[]},{"cell_type":"markdown","source":["## Apply AutoModel & AutoTokenizer of HuggingFace on Twitter database 2"],"metadata":{"id":"I94G9aQ7_XxO"}},{"cell_type":"code","source":["# Load the model directly\n","from transformers import AutoTokenizer, AutoModelForSequenceClassification\n","import torch\n","\n","tokenizer = AutoTokenizer.from_pretrained(\"distilbert/distilbert-base-uncased-finetuned-sst-2-english\")\n","model = AutoModelForSequenceClassification.from_pretrained(\"distilbert/distilbert-base-uncased-finetuned-sst-2-english\")"],"metadata":{"id":"MGVcuDGd_Iho","executionInfo":{"status":"ok","timestamp":1724148973463,"user_tz":-180,"elapsed":318,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}}},"execution_count":56,"outputs":[]},{"cell_type":"code","source":["# Define a function to analyze sentiment\n","def analyze_sentiment_AT(text):\n","    inputs = tokenizer(text, return_tensors=\"pt\")\n","    with torch.no_grad():\n","      outputs = model(**inputs)\n","    logits = outputs.logits\n","    predicted = logits.argmax().item()\n","    return 'POSITIVE' if predicted == 1 else 'NEGATIVE'"],"metadata":{"id":"XlKggnI6_xNr","executionInfo":{"status":"ok","timestamp":1724148973463,"user_tz":-180,"elapsed":3,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}}},"execution_count":57,"outputs":[]},{"cell_type":"code","source":["# Apply the sentiment analysis to each tweet\n","df['sentiment'] = df['text'].apply(analyze_sentiment_AT)"],"metadata":{"id":"Ea4tKckaAyRQ","executionInfo":{"status":"ok","timestamp":1724148997643,"user_tz":-180,"elapsed":24183,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}}},"execution_count":58,"outputs":[]},{"cell_type":"code","source":["# Save the results to a new CSV file\n","df.to_csv('twitter_sanders-apple2_AutoTokenizer.csv', index=False)"],"metadata":{"id":"YGzJBKOQBKVT","executionInfo":{"status":"ok","timestamp":1724148997643,"user_tz":-180,"elapsed":23,"user":{"displayName":"marcel azmy","userId":"07879121807274242679"}}},"execution_count":59,"outputs":[]}]}