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Analiza sentymentu - World Cup 2022.ipynb
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Analiza sentymentu - World Cup 2022.ipynb
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{
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"cells": [
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{
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"metadata": {},
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"cell_type": "markdown",
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"source": "### Importy",
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"id": "7a1e7d26143b0471"
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-01-19T11:01:47.450Z",
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"start_time": "2025-01-19T11:01:46.692135Z"
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}
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},
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"cell_type": "code",
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"source": "import pandas as pd",
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"id": "1691b104789b8a60",
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"outputs": [],
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"execution_count": 1
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},
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{
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"metadata": {},
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"cell_type": "markdown",
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"source": "### Zbiór danych",
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"id": "bf04fbdb243e5742"
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},
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{
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"metadata": {},
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"cell_type": "markdown",
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"source": [
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"Zbiór danych zawiera tweety związne z *Mistrzostwami Świata w Piłce Nożnej* w Katarze, które odbyły się w *2022 roku*. \n",
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"\n",
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"Tweety pochodzą z dnia otwarcia turnieju, tj. *20 listopada 2022 roku*, kiedy to mecz otwarcia rozegrali gospodarze turnieju - Katar przeciwko reprezentacji Ekwadoru. Mecz rozpoczął się o godzinie *16:00 UTC*, a finalny gwizdek sędziego zabrzmiał o godzinie *18:00 UTC*. \n",
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"\n",
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"Zbiór zawiera *22524* tweetów. Każdy tweet zawiera następujące kolumny:\n",
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"\n",
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"- `Date Created` - data napisania tweeta\n",
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"- `Number of Likes` - liczba polubień tweeta\n",
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"- `Source of Tweet` - źródło tweeta (np. Twitter for iPhone)\n",
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"- `Tweet` - treść tweeta\n",
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"- `Sentiment` - sentyment tweeta (`positive`, `negative`, `neutral`)"
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],
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"id": "139728685fbfc7cc"
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-01-19T11:13:14.897578Z",
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"start_time": "2025-01-19T11:13:14.637111Z"
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}
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},
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"cell_type": "code",
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"outputs": [
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{
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"data": {
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"text/plain": [
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" Date Created Number of Likes Source of Tweet \\\n",
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"0 2022-11-20 23:59:21+00:00 4 Twitter Web App \n",
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"1 2022-11-20 23:59:01+00:00 3 Twitter for iPhone \n",
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"2 2022-11-20 23:58:41+00:00 1 Twitter for iPhone \n",
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"3 2022-11-20 23:58:33+00:00 1 Twitter Web App \n",
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"4 2022-11-20 23:58:28+00:00 0 Twitter for Android \n",
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"\n",
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" Tweet Sentiment \n",
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"0 What are we drinking today @TucanTribe \\n@MadB... neutral \n",
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"1 Amazing @CanadaSoccerEN #WorldCup2022 launch ... positive \n",
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"2 Worth reading while watching #WorldCup2022 htt... positive \n",
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"3 Golden Maknae shinning bright\\n\\nhttps://t.co/... positive \n",
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"4 If the BBC cares so much about human rights, h... negative "
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],
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>Date Created</th>\n",
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" <th>Number of Likes</th>\n",
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" <th>Source of Tweet</th>\n",
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" <th>Tweet</th>\n",
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" <th>Sentiment</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>2022-11-20 23:59:21+00:00</td>\n",
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" <td>4</td>\n",
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" <td>Twitter Web App</td>\n",
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" <td>What are we drinking today @TucanTribe \\n@MadB...</td>\n",
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" <td>neutral</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>2022-11-20 23:59:01+00:00</td>\n",
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" <td>3</td>\n",
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" <td>Twitter for iPhone</td>\n",
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" <td>Amazing @CanadaSoccerEN #WorldCup2022 launch ...</td>\n",
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" <td>positive</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>2022-11-20 23:58:41+00:00</td>\n",
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" <td>1</td>\n",
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" <td>Twitter for iPhone</td>\n",
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" <td>Worth reading while watching #WorldCup2022 htt...</td>\n",
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" <td>positive</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>2022-11-20 23:58:33+00:00</td>\n",
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" <td>1</td>\n",
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" <td>Twitter Web App</td>\n",
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" <td>Golden Maknae shinning bright\\n\\nhttps://t.co/...</td>\n",
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" <td>positive</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>2022-11-20 23:58:28+00:00</td>\n",
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" <td>0</td>\n",
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" <td>Twitter for Android</td>\n",
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" <td>If the BBC cares so much about human rights, h...</td>\n",
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" <td>negative</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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]
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},
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"execution_count": 10,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"execution_count": 10,
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"source": [
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"df = pd.read_csv('dataset/fifa_world_cup_2022_tweets.csv', index_col=0)\n",
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"df['Date Created'] = pd.to_datetime(df['Date Created'])\n",
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"df.head()"
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],
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"id": "e760d702af7f88"
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-01-19T11:19:14.426885Z",
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"start_time": "2025-01-19T11:19:14.415327Z"
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}
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},
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"cell_type": "code",
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"source": [
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"df_before_match = df[df['Date Created'].dt.hour < 16]\n",
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"df_during_match = df[(df['Date Created'].dt.hour >= 16) & (df['Date Created'].dt.hour < 18)]\n",
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"df_after_match = df[df['Date Created'].dt.hour >= 18]"
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],
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"id": "c7424dd463db584e",
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"outputs": [],
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"execution_count": 12
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},
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{
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"metadata": {},
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"cell_type": "markdown",
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"source": "### Analiza sentymentu",
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"id": "6b277da32554cb66"
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-01-19T11:19:17.763717Z",
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"start_time": "2025-01-19T11:19:17.759353Z"
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}
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},
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"cell_type": "code",
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"source": "# TODO",
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"id": "e7201b91b120968e",
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"outputs": [],
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"execution_count": 13
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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58878
dataset/fifa_world_cup_2022_tweets.csv
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58878
dataset/fifa_world_cup_2022_tweets.csv
Normal file
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