src/twitter-search_v2_GetOldTweets3.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>\n",
    "<h1 style=\"font-family:sans-serif; text-align:center\"> \n",
    "<!--     <span style='color: pink'> Twitter analysis of </span> -->\n",
    "    <span style='color: white; font-size:100%; text-shadow: 0px 0px 15px black'> Twitter analysis of </span>\n",
    "<!--     <span style='color:#00acee'> Twitter analysis of </span> -->\n",
    "<!--     <span style=\"-webkit-text-stroke\"> Twitter analysis of</span> -->\n",
    "<!--     <span class=\"hr3\" style='color:#e40843; letter-spacing: 4px; font-size:105%'> Canada</span> -->\n",
    "    <span class=\"hr3\" style='color:#e40843; font-size:120%; text-shadow: 0px 0px 30px pink'>Canada </span> <span class=\"hr3\" style='color:gray; font-size:100%; text-shadow: 0px 0px 30px pink'>response to Covid-19</span><br>\n",
    "</h1>\n",
    "\n",
    "#### — _Using GetOldTweets3_ —\n",
    "\n",
    "### ⚠️ Due the changes in Twitter's API in late 2020, __GetOldTweets3__ is no longer functioning.\n",
    "\n",
    "The aim of this notebook is to retrieve the tweets from March 1st until April 30th, to analyze the difference in sentiment analysis of tweets from people before and after Trudeau's [announcement of government policies facing impact of Covid-19](https://www.youtube.com/watch?v=1o-tV0A87l8&feature=youtu.be) to support small businesses and their employees.\n",
    "\n",
    "For the original Jupyter notebook, made by Leo Cuspinera (alias _[cuspime](https://github.com/cuspime)_) [click here](https://github.com/cuspime/Projects/blob/master/Canada_Twitter.ipynb).\n",
    "\n",
    "_Authors: Leo Cuspinera ([cuspime](https://github.com/cuspime)) and Victor Cuspinera ([vcuspinera](https://github.com/vcuspinera))_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "# !pip install GetOldTweets3 #If you need to install this package, uncomment this line and run it\n",
    "import GetOldTweets3 as got \n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns; sns.set()\n",
    "import re \n",
    "from datetime import timedelta\n",
    "import datetime, time\n",
    "import pytz\n",
    "\n",
    "# WordCloud:\n",
    "from textblob import TextBlob\n",
    "from PIL import Image\n",
    "from wordcloud import WordCloud, STOPWORDS, ImageColorGenerator\n",
    "\n",
    "# Necessary to plot timeseries:\n",
    "pd.plotting.register_matplotlib_converters()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "hidden": true
   },
   "source": [
    "The **GetOldTweets3** package is really nice because it allows you to look for very old tweets (as opposed to the free version of the API from twitter). However, the downside is that it has less functionality.\n",
    "\n",
    "Nonetheless, as we shall see, this package provides enough functionality to make a nice analysis about a specific topic.\n",
    "\n",
    "GOT3 allows some criteria one can make use of to search on the Twit-sphere \n",
    "<img src='https://miro.medium.com/max/576/1*xVu-oaDRWW4yWF7yZ8W4Xw.png'>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:root:Internal Python error in the inspect module.\n",
      "Below is the traceback from this internal error.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "An error occured during an HTTP request: HTTP Error 404: Not Found\n",
      "Try to open in browser: https://twitter.com/search?q=%20from%3Abarackobama&src=typd\n",
      "Traceback (most recent call last):\n",
      "  File \"/opt/anaconda3/lib/python3.7/site-packages/GetOldTweets3/manager/TweetManager.py\", line 343, in getJsonResponse\n",
      "    response = opener.open(url)\n",
      "  File \"/opt/anaconda3/lib/python3.7/urllib/request.py\", line 531, in open\n",
      "    response = meth(req, response)\n",
      "  File \"/opt/anaconda3/lib/python3.7/urllib/request.py\", line 641, in http_response\n",
      "    'http', request, response, code, msg, hdrs)\n",
      "  File \"/opt/anaconda3/lib/python3.7/urllib/request.py\", line 569, in error\n",
      "    return self._call_chain(*args)\n",
      "  File \"/opt/anaconda3/lib/python3.7/urllib/request.py\", line 503, in _call_chain\n",
      "    result = func(*args)\n",
      "  File \"/opt/anaconda3/lib/python3.7/urllib/request.py\", line 649, in http_error_default\n",
      "    raise HTTPError(req.full_url, code, msg, hdrs, fp)\n",
      "urllib.error.HTTPError: HTTP Error 404: Not Found\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"/opt/anaconda3/lib/python3.7/site-packages/IPython/core/interactiveshell.py\", line 3418, in run_code\n",
      "    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "  File \"<ipython-input-2-5a7a148bd652>\", line 4, in <module>\n",
      "    tweet = got.manager.TweetManager.getTweets(tweetCriteria)[0]\n",
      "  File \"/opt/anaconda3/lib/python3.7/site-packages/GetOldTweets3/manager/TweetManager.py\", line 65, in getTweets\n",
      "    json = TweetManager.getJsonResponse(tweetCriteria, refreshCursor, cookieJar, proxy, user_agent, debug=debug)\n",
      "  File \"/opt/anaconda3/lib/python3.7/site-packages/GetOldTweets3/manager/TweetManager.py\", line 348, in getJsonResponse\n",
      "    sys.exit()\n",
      "SystemExit\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"/opt/anaconda3/lib/python3.7/site-packages/IPython/core/ultratb.py\", line 1170, in get_records\n",
      "    return _fixed_getinnerframes(etb, number_of_lines_of_context, tb_offset)\n",
      "  File \"/opt/anaconda3/lib/python3.7/site-packages/IPython/core/ultratb.py\", line 316, in wrapped\n",
      "    return f(*args, **kwargs)\n",
      "  File \"/opt/anaconda3/lib/python3.7/site-packages/IPython/core/ultratb.py\", line 350, in _fixed_getinnerframes\n",
      "    records = fix_frame_records_filenames(inspect.getinnerframes(etb, context))\n",
      "  File \"/opt/anaconda3/lib/python3.7/inspect.py\", line 1502, in getinnerframes\n",
      "    frameinfo = (tb.tb_frame,) + getframeinfo(tb, context)\n",
      "AttributeError: 'tuple' object has no attribute 'tb_frame'\n"
     ]
    },
    {
     "ename": "TypeError",
     "evalue": "object of type 'NoneType' has no len()",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mHTTPError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/GetOldTweets3/manager/TweetManager.py\u001b[0m in \u001b[0;36mgetJsonResponse\u001b[0;34m(tweetCriteria, refreshCursor, cookieJar, proxy, useragent, debug)\u001b[0m\n\u001b[1;32m    342\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 343\u001b[0;31m             \u001b[0mresponse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mopener\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    344\u001b[0m             \u001b[0mjsonResponse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/urllib/request.py\u001b[0m in \u001b[0;36mopen\u001b[0;34m(self, fullurl, data, timeout)\u001b[0m\n\u001b[1;32m    530\u001b[0m             \u001b[0mmeth\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprocessor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmeth_name\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 531\u001b[0;31m             \u001b[0mresponse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmeth\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreq\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    532\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/urllib/request.py\u001b[0m in \u001b[0;36mhttp_response\u001b[0;34m(self, request, response)\u001b[0m\n\u001b[1;32m    640\u001b[0m             response = self.parent.error(\n\u001b[0;32m--> 641\u001b[0;31m                 'http', request, response, code, msg, hdrs)\n\u001b[0m\u001b[1;32m    642\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/urllib/request.py\u001b[0m in \u001b[0;36merror\u001b[0;34m(self, proto, *args)\u001b[0m\n\u001b[1;32m    568\u001b[0m             \u001b[0margs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mdict\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'default'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'http_error_default'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0morig_args\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 569\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_call_chain\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    570\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/urllib/request.py\u001b[0m in \u001b[0;36m_call_chain\u001b[0;34m(self, chain, kind, meth_name, *args)\u001b[0m\n\u001b[1;32m    502\u001b[0m             \u001b[0mfunc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhandler\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmeth_name\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 503\u001b[0;31m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    504\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mresult\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/urllib/request.py\u001b[0m in \u001b[0;36mhttp_error_default\u001b[0;34m(self, req, fp, code, msg, hdrs)\u001b[0m\n\u001b[1;32m    648\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mhttp_error_default\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreq\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcode\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmsg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhdrs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 649\u001b[0;31m         \u001b[0;32mraise\u001b[0m \u001b[0mHTTPError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreq\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfull_url\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcode\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmsg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhdrs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfp\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    650\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mHTTPError\u001b[0m: HTTP Error 404: Not Found",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mSystemExit\u001b[0m                                Traceback (most recent call last)",
      "    \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n",
      "\u001b[0;32m<ipython-input-2-5a7a148bd652>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      3\u001b[0m                                            \u001b[0;34m.\u001b[0m\u001b[0msetMaxTweets\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mtweet\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgot\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmanager\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTweetManager\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetTweets\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtweetCriteria\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m \u001b[0;31m# print(tweet.text)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/GetOldTweets3/manager/TweetManager.py\u001b[0m in \u001b[0;36mgetTweets\u001b[0;34m(tweetCriteria, receiveBuffer, bufferLength, proxy, debug)\u001b[0m\n\u001b[1;32m     64\u001b[0m             \u001b[0;32mwhile\u001b[0m \u001b[0mactive\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 65\u001b[0;31m                 \u001b[0mjson\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTweetManager\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetJsonResponse\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtweetCriteria\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrefreshCursor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcookieJar\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mproxy\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0muser_agent\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdebug\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdebug\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     66\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mjson\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'items_html'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstrip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/GetOldTweets3/manager/TweetManager.py\u001b[0m in \u001b[0;36mgetJsonResponse\u001b[0;34m(tweetCriteria, refreshCursor, cookieJar, proxy, useragent, debug)\u001b[0m\n\u001b[1;32m    347\u001b[0m             \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Try to open in browser: https://twitter.com/search?q=%s&src=typd\"\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0murllib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mparse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mquote\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murlGetData\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 348\u001b[0;31m             \u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    349\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mSystemExit\u001b[0m: ",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "    \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/IPython/core/interactiveshell.py\u001b[0m in \u001b[0;36mshowtraceback\u001b[0;34m(self, exc_tuple, filename, tb_offset, exception_only, running_compiled_code)\u001b[0m\n\u001b[1;32m   2037\u001b[0m                            'the full traceback.\\n']\n\u001b[1;32m   2038\u001b[0m                     stb.extend(self.InteractiveTB.get_exception_only(etype,\n\u001b[0;32m-> 2039\u001b[0;31m                                                                      value))\n\u001b[0m\u001b[1;32m   2040\u001b[0m                 \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2041\u001b[0m                     \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/IPython/core/ultratb.py\u001b[0m in \u001b[0;36mget_exception_only\u001b[0;34m(self, etype, value)\u001b[0m\n\u001b[1;32m    821\u001b[0m         \u001b[0mvalue\u001b[0m \u001b[0;34m:\u001b[0m \u001b[0mexception\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    822\u001b[0m         \"\"\"\n\u001b[0;32m--> 823\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mListTB\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstructured_traceback\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0metype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    824\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    825\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mshow_exception_only\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0metype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mevalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/IPython/core/ultratb.py\u001b[0m in \u001b[0;36mstructured_traceback\u001b[0;34m(self, etype, evalue, etb, tb_offset, context)\u001b[0m\n\u001b[1;32m    700\u001b[0m                     chained_exceptions_tb_offset, context)\n\u001b[1;32m    701\u001b[0m                 \u001b[0;34m+\u001b[0m \u001b[0mchained_exception_message\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 702\u001b[0;31m                 + out_list)\n\u001b[0m\u001b[1;32m    703\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    704\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mout_list\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/IPython/core/ultratb.py\u001b[0m in \u001b[0;36mstructured_traceback\u001b[0;34m(self, etype, value, tb, tb_offset, number_of_lines_of_context)\u001b[0m\n\u001b[1;32m   1435\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtb\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1436\u001b[0m         return FormattedTB.structured_traceback(\n\u001b[0;32m-> 1437\u001b[0;31m             self, etype, value, tb, tb_offset, number_of_lines_of_context)\n\u001b[0m\u001b[1;32m   1438\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1439\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/IPython/core/ultratb.py\u001b[0m in \u001b[0;36mstructured_traceback\u001b[0;34m(self, etype, value, tb, tb_offset, number_of_lines_of_context)\u001b[0m\n\u001b[1;32m   1335\u001b[0m             \u001b[0;31m# Verbose modes need a full traceback\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1336\u001b[0m             return VerboseTB.structured_traceback(\n\u001b[0;32m-> 1337\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0metype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtb\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtb_offset\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnumber_of_lines_of_context\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1338\u001b[0m             )\n\u001b[1;32m   1339\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0mmode\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'Minimal'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/IPython/core/ultratb.py\u001b[0m in \u001b[0;36mstructured_traceback\u001b[0;34m(self, etype, evalue, etb, tb_offset, number_of_lines_of_context)\u001b[0m\n\u001b[1;32m   1192\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1193\u001b[0m         formatted_exception = self.format_exception_as_a_whole(etype, evalue, etb, number_of_lines_of_context,\n\u001b[0;32m-> 1194\u001b[0;31m                                                                tb_offset)\n\u001b[0m\u001b[1;32m   1195\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1196\u001b[0m         \u001b[0mcolors\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mColors\u001b[0m  \u001b[0;31m# just a shorthand + quicker name lookup\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/IPython/core/ultratb.py\u001b[0m in \u001b[0;36mformat_exception_as_a_whole\u001b[0;34m(self, etype, evalue, etb, number_of_lines_of_context, tb_offset)\u001b[0m\n\u001b[1;32m   1149\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1150\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1151\u001b[0;31m         \u001b[0mlast_unique\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrecursion_repeat\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfind_recursion\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0morig_etype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mevalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrecords\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1152\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1153\u001b[0m         \u001b[0mframes\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat_records\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrecords\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlast_unique\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrecursion_repeat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/IPython/core/ultratb.py\u001b[0m in \u001b[0;36mfind_recursion\u001b[0;34m(etype, value, records)\u001b[0m\n\u001b[1;32m    449\u001b[0m     \u001b[0;31m# first frame (from in to out) that looks different.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    450\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mis_recursion_error\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0metype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrecords\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 451\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrecords\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    452\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    453\u001b[0m     \u001b[0;31m# Select filename, lineno, func_name to track frames with\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mTypeError\u001b[0m: object of type 'NoneType' has no len()"
     ]
    }
   ],
   "source": [
    "# THIS CODE CHUNK IS ONLY TO TEST IF `GetOldTweets3` IS WORKING\n",
    "tweetCriteria = got.manager.TweetCriteria().setUsername(\"barackobama\")\\\n",
    "                                           .setTopTweets(True)\\\n",
    "                                           .setMaxTweets(10)\n",
    "tweet = got.manager.TweetManager.getTweets(tweetCriteria)[0]\n",
    "# print(tweet.text)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Creating a dataframe from tweets\n",
    "\n",
    "We have a list of twitter objects and would like now to create lists which will enable us to put a dataframe together. \n",
    "\n",
    "We will define a function that translates a list of tweet objects into a friendly, understandable pandas dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 5 µs, sys: 0 ns, total: 5 µs\n",
      "Wall time: 8.34 µs\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "def TweetDataframe(tweets):\n",
    "    \"\"\"\n",
    "    Function that translates a list of tweet objects into a friendly, \n",
    "    understandable pandas dataframe.\n",
    "    \n",
    "    Parameters:\n",
    "    -----------\n",
    "    tweets (pd.DataFrame):\n",
    "        pandas dataframe con columnas 'tipo_operacion_gral', 'year',\n",
    "        'month', 'fecha', 'importe'.\n",
    "        \n",
    "    text (str):\n",
    "        texto que se usará en el nombre de las gráficas.\n",
    "    ancho (int; default=300): \n",
    "        ancho de la gráfica en caso de limitar el tamaño.\n",
    "    alto (int; default=250): \n",
    "        alto de la gráfica en caso de limitar el tamaño.\n",
    "    tipo (str; opciones: 'sucursal', 'atm', 'ambos'):\n",
    "        texto para identificar el límite a usar para la gráfica.\n",
    "    limitar (bool):\n",
    "        bandera para idenitificar si se desea cambiar el tamaño de \n",
    "        las gráficas.\n",
    "    \n",
    "    Returns:\n",
    "    --------\n",
    "    Pandas dataframe.\n",
    "    \n",
    "    Example:\n",
    "    --------\n",
    "    TweetDataframe(tweet_01)\n",
    "    \"\"\"\n",
    "    text = []\n",
    "    usr = []\n",
    "    rt=[]\n",
    "    fav=[]\n",
    "    ht=[]\n",
    "    mentions=[]\n",
    "    id_ = []\n",
    "    date=[]\n",
    "    geo=[]\n",
    "    for i in range(len(tweets)):\n",
    "    #     print('{} \\n '.format(got.manager.TweetManager.getTweets(tweetCriteria)[i].text ) )\n",
    "        id_.append( tweets[i].id )\n",
    "        text.append( tweets[i].text )\n",
    "        usr.append(  tweets[i].username )\n",
    "        rt.append( tweets[i].retweets )\n",
    "        ht.append( tweets[i].hashtags )\n",
    "        mentions.append( tweets[i].mentions )\n",
    "        fav.append( tweets[i].favorites )\n",
    "        date.append(tweets[i].date)\n",
    "        geo.append( tweets[i].geo )\n",
    "\n",
    "    # Create dataframe\n",
    "    df = pd.DataFrame.from_dict({'date':date, 'usr':usr, 'ht':ht, \n",
    "                                 'mentions':mentions, 'rt':rt, \n",
    "                                 'fav':fav, 'text':text, 'ind':id_ } )\n",
    "    df = df.set_index('ind')\n",
    "    \n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Downloading tweets analysis\n",
    "\n",
    "Now, this is where things gets interesting. We will first define a search criteria that we will mantain throughout our search.\n",
    "\n",
    "We will be looking into:\n",
    "* Tweets addressed to any of the following accounts: **@CanadianPM, @Canada, @GovCanHealth, @JustinTrudeau**\n",
    "* The search will start on the *first second of March* and will end on *April 30th at midnight*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Creation of database"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 2 µs, sys: 1 µs, total: 3 µs\n",
      "Wall time: 4.77 µs\n"
     ]
    }
   ],
   "source": [
    "# RUNNING THIS CELL WILL DELETE df!\n",
    "%time\n",
    "# Create empty dataframe\n",
    "df = pd.DataFrame(columns = ['date', 'usr', 'ht', 'mentions', 'rt', 'fav', 'text', 'top_usr', 'geo', 'ind'])\n",
    "df = df.set_index('ind')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Search criteria"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 🔥 Search Criteria. This is the place to change the topic, hashtag or so\n",
    "interesting_text='@Canada' #'@JustinTrudeau'#'@GovCanHealth'#'@Canada'#'@CanadianPM'# OR  OR @GovCanHealth OR @JustinTrudeau'# AND text'\n",
    "today = datetime.datetime.today()\n",
    "last_update = pd.to_datetime('2020-03-01')\n",
    "finishing_date = pd.to_datetime('2020-05-01')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import database and update\n",
    "Let's now import the previously saved dataframe:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 209 µs, sys: 340 µs, total: 549 µs\n",
      "Wall time: 2.27 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# En Windows, el path se tiene que escribir con \"\\\\\" en lugar del usual \"/\"\n",
    "# df = pd.read_csv(\"C:\\\\Users\\\\cuspi\\\\Documents\\\\Databases\\\\Twitter\\\\twitter_lint_bulk.csv\", parse_dates=['date']) #Usa este si quieres comenzar desde el update que llegó hasta el 17 de Agosto\n",
    "# path_to_file = \"C:\\\\Users\\\\cuspi\\\\Documents\\\\Databases\\\\Canada_Twitter\\\\main.csv\"\n",
    "path_to_file = \"../tweets/historic/main.csv\"\n",
    "\n",
    "try:\n",
    "    df = pd.read_csv(path_to_file, parse_dates=['date'])\n",
    "    df = df.set_index('ind')\n",
    "except:\n",
    "    next"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <span style='color:red'>Update</span>\n",
    "This is the main funciton that has to be run several times"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "last update: 2020-Mar-01 \n",
      "len(df):     0\n"
     ]
    }
   ],
   "source": [
    "#Let's check where we were left last time:\n",
    "print('last update:', last_update.strftime('%Y-%b-%d'), '\\nlen(df):    ',len(df))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "An error occured during an HTTP request: HTTP Error 404: Not Found\n",
      "Try to open in browser: https://twitter.com/search?q=%40Canada%20since%3A2020-03-01%20until%3A2020-03-02&src=typd\n"
     ]
    },
    {
     "ename": "SystemExit",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mHTTPError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/GetOldTweets3/manager/TweetManager.py\u001b[0m in \u001b[0;36mgetJsonResponse\u001b[0;34m(tweetCriteria, refreshCursor, cookieJar, proxy, useragent, debug)\u001b[0m\n\u001b[1;32m    342\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 343\u001b[0;31m             \u001b[0mresponse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mopener\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    344\u001b[0m             \u001b[0mjsonResponse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/urllib/request.py\u001b[0m in \u001b[0;36mopen\u001b[0;34m(self, fullurl, data, timeout)\u001b[0m\n\u001b[1;32m    530\u001b[0m             \u001b[0mmeth\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprocessor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmeth_name\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 531\u001b[0;31m             \u001b[0mresponse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmeth\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreq\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    532\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/urllib/request.py\u001b[0m in \u001b[0;36mhttp_response\u001b[0;34m(self, request, response)\u001b[0m\n\u001b[1;32m    640\u001b[0m             response = self.parent.error(\n\u001b[0;32m--> 641\u001b[0;31m                 'http', request, response, code, msg, hdrs)\n\u001b[0m\u001b[1;32m    642\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/urllib/request.py\u001b[0m in \u001b[0;36merror\u001b[0;34m(self, proto, *args)\u001b[0m\n\u001b[1;32m    568\u001b[0m             \u001b[0margs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mdict\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'default'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'http_error_default'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0morig_args\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 569\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_call_chain\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    570\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/urllib/request.py\u001b[0m in \u001b[0;36m_call_chain\u001b[0;34m(self, chain, kind, meth_name, *args)\u001b[0m\n\u001b[1;32m    502\u001b[0m             \u001b[0mfunc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhandler\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmeth_name\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 503\u001b[0;31m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    504\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mresult\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/urllib/request.py\u001b[0m in \u001b[0;36mhttp_error_default\u001b[0;34m(self, req, fp, code, msg, hdrs)\u001b[0m\n\u001b[1;32m    648\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mhttp_error_default\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreq\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcode\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmsg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhdrs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 649\u001b[0;31m         \u001b[0;32mraise\u001b[0m \u001b[0mHTTPError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreq\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfull_url\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcode\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmsg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhdrs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfp\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    650\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mHTTPError\u001b[0m: HTTP Error 404: Not Found",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mSystemExit\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<timed exec>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/GetOldTweets3/manager/TweetManager.py\u001b[0m in \u001b[0;36mgetTweets\u001b[0;34m(tweetCriteria, receiveBuffer, bufferLength, proxy, debug)\u001b[0m\n\u001b[1;32m     63\u001b[0m             \u001b[0mactive\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     64\u001b[0m             \u001b[0;32mwhile\u001b[0m \u001b[0mactive\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 65\u001b[0;31m                 \u001b[0mjson\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTweetManager\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetJsonResponse\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtweetCriteria\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrefreshCursor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcookieJar\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mproxy\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0muser_agent\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdebug\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdebug\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     66\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mjson\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'items_html'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstrip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     67\u001b[0m                     \u001b[0;32mbreak\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/GetOldTweets3/manager/TweetManager.py\u001b[0m in \u001b[0;36mgetJsonResponse\u001b[0;34m(tweetCriteria, refreshCursor, cookieJar, proxy, useragent, debug)\u001b[0m\n\u001b[1;32m    346\u001b[0m             \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"An error occured during an HTTP request:\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    347\u001b[0m             \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Try to open in browser: https://twitter.com/search?q=%s&src=typd\"\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0murllib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mparse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mquote\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murlGetData\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 348\u001b[0;31m             \u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    349\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    350\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mSystemExit\u001b[0m: "
     ]
    }
   ],
   "source": [
    "%%time\n",
    "count=1.1e4\n",
    "\n",
    "# Let's now update this database 😎\n",
    "\n",
    "# time.sleep(60*5)\n",
    "\n",
    "while (pd.to_datetime(finishing_date).replace(tzinfo=pytz.UTC) - last_update.replace(tzinfo=pytz.UTC) ) > timedelta(seconds=1) :\n",
    "    start_date_string = last_update.strftime('%Y-%m-%d')\n",
    "    end_date_string = (last_update + timedelta(1) ).strftime('%Y-%m-%d')\n",
    "    \n",
    "    # This is how to make a search on Twitter with GetOldTweets3\n",
    "    tweetCriteria = got.manager.TweetCriteria()\\\n",
    "                    .setQuerySearch(interesting_text)\\\n",
    "                    .setEmoji(\"unicode\")\\\n",
    "                    .setMaxTweets(count)\\\n",
    "                    .setSince(start_date_string)\\\n",
    "                    .setUntil(end_date_string)\n",
    "\n",
    "    # List of twits \n",
    "    tweets = got.manager.TweetManager.getTweets(tweetCriteria)\n",
    "    # Create DataFrame with previously defined function\n",
    "    current_df = TweetDataframe(tweets)\n",
    "    # Remove tweets without text \n",
    "    current_df = current_df[~current_df.text.isna()]\n",
    "    # Remove known ads\n",
    "    ads_usr = ['MovistarMX','MatthewASwift','overbags','FarandWidecom','AiseStampa','roomtour_house', 'danielchayau','AlcoveVR','JLCPCB','ExcelEasy', 'BUZZNET','hotelpricedrops', 'GamesRedDeer', 'sergistack', 'robersperanza', 'k_colonialism', 'VOANoticias','MasayukiTsuda2','POLITICOEurope']\n",
    "    current_df = current_df[ ~current_df.usr.isin(ads_usr) ]\n",
    "    \n",
    "    # Append current_df to df\n",
    "    df = pd.concat([df,current_df])\n",
    "    \n",
    "    #     # Check we're getting something\n",
    "    print(\"Last update:{} \\nDataFrame length:{}\\n\".format(last_update.strftime('%Y-%m-%d'), len(df)) )\n",
    "    \n",
    "    # Move one day \n",
    "    last_update = pd.to_datetime(df.iloc[-1].date+timedelta(1))\n",
    "    # Pull an all nighter\n",
    "#     time.sleep(60*8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "ename": "IndexError",
     "evalue": "single positional indexer is out-of-bounds",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-11-725a3f917813>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# Compare with the previous maximum date:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'last update:'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0miloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdate\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstrftime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'%Y-%b-%d  %h'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'\\nlen(df):    '\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   1766\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1767\u001b[0m             \u001b[0mmaybe_callable\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcom\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply_if_callable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1768\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmaybe_callable\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1769\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1770\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_is_scalar_access\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mTuple\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_getitem_axis\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m   2136\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2137\u001b[0m             \u001b[0;31m# validate the location\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2138\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_integer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2139\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2140\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_validate_integer\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m   2061\u001b[0m         \u001b[0mlen_axis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2062\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;34m>=\u001b[0m \u001b[0mlen_axis\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0mlen_axis\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2063\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mIndexError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"single positional indexer is out-of-bounds\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2064\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2065\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_getitem_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtup\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mTuple\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mIndexError\u001b[0m: single positional indexer is out-of-bounds"
     ]
    }
   ],
   "source": [
    "# Compare with the previous maximum date:\n",
    "print('last update:', df.iloc[-1].date.strftime('%Y-%b-%d  %h'), '\\nlen(df):    ',len(df))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Remove ads\n",
    "\n",
    "In order to analyse our data and make sure that we are not double counting tweets and that we have no adverstisements (very common when looking at Twitter from several countries). Also while importing tweets we might have imported one of them more than once by calling the function on crossing dates or searches (we made independent searches that are highly correlated). \n",
    "\n",
    "To ensure this is not a problem for the following analysis, we will remove these duplicates by selecting repeated indices and removing them:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 326,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>date</th>\n",
       "      <th>usr</th>\n",
       "      <th>ht</th>\n",
       "      <th>mentions</th>\n",
       "      <th>rt</th>\n",
       "      <th>fav</th>\n",
       "      <th>text</th>\n",
       "      <th>top_usr</th>\n",
       "      <th>geo</th>\n",
       "      <th>interactions</th>\n",
       "      <th>subjectivity</th>\n",
       "      <th>polarity</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ind</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [date, usr, ht, mentions, rt, fav, text, top_usr, geo, interactions, subjectivity, polarity]\n",
       "Index: []"
      ]
     },
     "execution_count": 326,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#This helps checking if there are ads:\n",
    "df[df.index.duplicated()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 327,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This removes any entry with a duplicated index 🔥\n",
    "df = df[(~df.index.duplicated(keep='first'))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 999 µs\n"
     ]
    }
   ],
   "source": [
    "%%time \n",
    "# Remove known ads (this depends more on the IP address from where you run these queries and  )\n",
    "ads_usr = ['MovistarMX','FarandWidecom','overbags','MatthewASwift','AiseStampa','roomtour_house', 'danielchayau','AlcoveVR','JLCPCB','ExcelEasy', 'BUZZNET','hotelpricedrops', 'GamesRedDeer', 'sergistack', 'robersperanza', 'k_colonialism', 'VOANoticias','MasayukiTsuda2','POLITICOEurope']\n",
    "df = df[ ~df.usr.isin(ads_usr) ]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Top users"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 294,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 1.49 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# Select top users\n",
    "df['interactions'] = df.rt + df.fav\n",
    "\n",
    "top_number=23\n",
    "top_users = df.sort_values(by=['interactions','rt', 'fav'], ascending=False).usr.unique()[:top_number].tolist()\n",
    "df['top_usr'] = df['usr'].apply(lambda x: top_users.index(x)+1 if (x in top_users) else 0)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Time Series Plots\n",
    "Let's take a look at the time behaviour of tweets discussing **#LoveIsNotTourism**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 265,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,7))\n",
    "\n",
    "# sns.set()\n",
    "# Colours\n",
    "sns.set_palette(\"husl\")\n",
    "\n",
    "\n",
    "sns.scatterplot(x='date', y='fav', hue='top_usr', size=df.rt.astype('float'), size_norm=(5,50), data=df, \n",
    "                palette='Dark2_r', alpha=.4, legend=False)\n",
    "plt.ylabel('# of favorites', size=14);\n",
    "plt.xlabel('')\n",
    "plt.title('{:.0f} tweets talking about {}'.format(len(df), interesting_text), \n",
    "          size=14);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tweets per day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 331,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# df.resample('H', on='timestamps').mean()\n",
    "sns.set()\n",
    "plt.figure(figsize=(15,7))\n",
    "plt.title('Number of twits over time', size=15)\n",
    "\n",
    "# Plotting hist without kde\n",
    "ax = sns.lineplot(x=df.resample('d', on='date').count().index, y=df[df.text.str.contains('Trudeau')].resample('d', on='date').count().usr);\n",
    "ax.set_xlabel('');\n",
    "ax.set_ylabel('Number of tweets per day mentioning Trudeau');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 267,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# df.resample('H', on='timestamps').mean()\n",
    "plt.figure(figsize=(15,7))\n",
    "plt.title('Distribution')\n",
    "\n",
    "# Plotting hist without kde\n",
    "ax = sns.distplot( df.resample('d', on='date').count().usr ,label='Count', kde=False);\n",
    "# Creating another Y axis\n",
    "second_ax = ax.twinx()\n",
    "\n",
    "#Plotting kde without hist on the second Y axis\n",
    "sns.distplot( df.resample('d', on='date').count().usr , ax=second_ax, rug=True, kde=True, hist=False);\n",
    "#Removing Y ticks from the second axis\n",
    "second_ax.set_yticks([]);\n",
    "ax.set_xlabel('Days distribution');\n",
    "ax.set_xlabel('Number of tweets per day');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Most engaging Tweets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 323,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "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>date</th>\n",
       "      <th>usr</th>\n",
       "      <th>rt</th>\n",
       "      <th>fav</th>\n",
       "      <th>text</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ind</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1243681744294948865</th>\n",
       "      <td>2020-03-27 23:30:08+00:00</td>\n",
       "      <td>JustinTrudeau</td>\n",
       "      <td>24634</td>\n",
       "      <td>85506</td>\n",
       "      <td>Stay home. It doesn’t matter that the weekend’s almost here - if you choose to gather in groups or hang out with your friends, you’re putting yourself, those around you, and our health care workers at risk. So take this seriously. Do the right thing and stay home this weekend.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1238904264908582914</th>\n",
       "      <td>2020-03-14 19:06:09+00:00</td>\n",
       "      <td>realDonaldTrump</td>\n",
       "      <td>14218</td>\n",
       "      <td>89324</td>\n",
       "      <td>Just had a nice conversation with Prime Minister @JustinTrudeau of Canada. Great to hear that his wonderful wife Sophie is doing very well. The United States and Canada will continue to coordinate closely together on COVID-19.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1255155284588158979</th>\n",
       "      <td>2020-04-28 15:21:54+00:00</td>\n",
       "      <td>narendramodi</td>\n",
       "      <td>9111</td>\n",
       "      <td>88226</td>\n",
       "      <td>Had a warm exchange with PM @JustinTrudeau. Thanked him for looking after Indian citizens in Canada in these difficult times. Collaboration and partnership between India and Canada is vital to fighting the pandemic including through medical research and supply chain management.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1242179031438635010</th>\n",
       "      <td>2020-03-23 19:58:54+00:00</td>\n",
       "      <td>JustinTrudeau</td>\n",
       "      <td>23822</td>\n",
       "      <td>66080</td>\n",
       "      <td>To the people who seem to think they’re invincible: You’re not. So go home and stay home. You’re not just putting yourself at risk, you’re putting others at risk too - nurses and doctors, grocery store workers, your grandparents, and so many others. #StayAtHomeSaveLives</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1242234576455585793</th>\n",
       "      <td>2020-03-23 23:39:37+00:00</td>\n",
       "      <td>JustinTrudeau</td>\n",
       "      <td>22496</td>\n",
       "      <td>60348</td>\n",
       "      <td>You need to stay home. And so do your friends and family members. Help spread the word with your own video - and tag your friends to remind them to stay home too. And together, we can #PlankTheCurve. @MichaelBuble and @VancityReynolds - can you help? #StayAtHomeSaveLives</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1253059782300389377</th>\n",
       "      <td>2020-04-22 20:35:07+00:00</td>\n",
       "      <td>JessTherrien17</td>\n",
       "      <td>0</td>\n",
       "      <td>51</td>\n",
       "      <td>This benefit is drastically lower than CERB, and rightfully should be going to students who need it to help their education and their future. Very closed minded to think the next generation doesn’t deserve a little support.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1253453914533486592</th>\n",
       "      <td>2020-04-23 22:41:15+00:00</td>\n",
       "      <td>SupaleeNate</td>\n",
       "      <td>0</td>\n",
       "      <td>51</td>\n",
       "      <td>Christians have called for the deaths of gay and trans people for decades. Don't act like your religion is any better.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1253452408648278016</th>\n",
       "      <td>2020-04-23 22:35:16+00:00</td>\n",
       "      <td>Balajibril1</td>\n",
       "      <td>0</td>\n",
       "      <td>51</td>\n",
       "      <td>You're hate-filled.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1253640735188029440</th>\n",
       "      <td>2020-04-24 11:03:37+00:00</td>\n",
       "      <td>syrencove</td>\n",
       "      <td>0</td>\n",
       "      <td>51</td>\n",
       "      <td>go to horny jail</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1255139418991546377</th>\n",
       "      <td>2020-04-28 14:18:51+00:00</td>\n",
       "      <td>DavidJGoodyear</td>\n",
       "      <td>0</td>\n",
       "      <td>51</td>\n",
       "      <td>I’m glad your mother is okay. Also wanted to say that you and your colleagues are doing a fabulous job in this crisis. Thank you!</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6279 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         date              usr     rt    fav  \\\n",
       "ind                                                                            \n",
       "1243681744294948865 2020-03-27 23:30:08+00:00    JustinTrudeau  24634  85506   \n",
       "1238904264908582914 2020-03-14 19:06:09+00:00  realDonaldTrump  14218  89324   \n",
       "1255155284588158979 2020-04-28 15:21:54+00:00     narendramodi   9111  88226   \n",
       "1242179031438635010 2020-03-23 19:58:54+00:00    JustinTrudeau  23822  66080   \n",
       "1242234576455585793 2020-03-23 23:39:37+00:00    JustinTrudeau  22496  60348   \n",
       "...                                       ...              ...    ...    ...   \n",
       "1253059782300389377 2020-04-22 20:35:07+00:00   JessTherrien17      0     51   \n",
       "1253453914533486592 2020-04-23 22:41:15+00:00      SupaleeNate      0     51   \n",
       "1253452408648278016 2020-04-23 22:35:16+00:00      Balajibril1      0     51   \n",
       "1253640735188029440 2020-04-24 11:03:37+00:00        syrencove      0     51   \n",
       "1255139418991546377 2020-04-28 14:18:51+00:00   DavidJGoodyear      0     51   \n",
       "\n",
       "                                                                                                                                                                                                                                                                                                       text  \n",
       "ind                                                                                                                                                                                                                                                                                                          \n",
       "1243681744294948865   Stay home. It doesn’t matter that the weekend’s almost here - if you choose to gather in groups or hang out with your friends, you’re putting yourself, those around you, and our health care workers at risk. So take this seriously. Do the right thing and stay home this weekend.  \n",
       "1238904264908582914                                                      Just had a nice conversation with Prime Minister @JustinTrudeau of Canada. Great to hear that his wonderful wife Sophie is doing very well. The United States and Canada will continue to coordinate closely together on COVID-19.  \n",
       "1255155284588158979  Had a warm exchange with PM @JustinTrudeau. Thanked him for looking after Indian citizens in Canada in these difficult times. Collaboration and partnership between India and Canada is vital to fighting the pandemic including through medical research and supply chain management.  \n",
       "1242179031438635010          To the people who seem to think they’re invincible: You’re not. So go home and stay home. You’re not just putting yourself at risk, you’re putting others at risk too - nurses and doctors, grocery store workers, your grandparents, and so many others. #StayAtHomeSaveLives  \n",
       "1242234576455585793         You need to stay home. And so do your friends and family members. Help spread the word with your own video - and tag your friends to remind them to stay home too. And together, we can #PlankTheCurve. @MichaelBuble and @VancityReynolds - can you help? #StayAtHomeSaveLives  \n",
       "...                                                                                                                                                                                                                                                                                                     ...  \n",
       "1253059782300389377                                                         This benefit is drastically lower than CERB, and rightfully should be going to students who need it to help their education and their future. Very closed minded to think the next generation doesn’t deserve a little support.  \n",
       "1253453914533486592                                                                                                                                                                  Christians have called for the deaths of gay and trans people for decades. Don't act like your religion is any better.  \n",
       "1253452408648278016                                                                                                                                                                                                                                                                     You're hate-filled.  \n",
       "1253640735188029440                                                                                                                                                                                                                                                                        go to horny jail  \n",
       "1255139418991546377                                                                                                                                                       I’m glad your mother is okay. Also wanted to say that you and your colleagues are doing a fabulous job in this crisis. Thank you!  \n",
       "\n",
       "[6279 rows x 5 columns]"
      ]
     },
     "execution_count": 323,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# pd.set_option('display.max_colwidth', None)\n",
    "df[df.fav>50].sort_values(['interactions','rt','fav'], ascending=False).loc[:,['date','usr','rt','fav','text']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <span style='color:red'>Export dataframe </span>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 295,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 11.1 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# Save the dfs to disk so that we can make use of it in Tableau \n",
    "df.to_csv(path_to_file)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Sentiment analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 296,
   "metadata": {},
   "outputs": [],
   "source": [
    "stopwords = set(STOPWORDS)\n",
    "stopwords.update(['lo','u',\"I'm\",\"We'll\", 'Nous', 'di', 'Herr', 'ist','de','die','a','por','https','I', 'noch', 'much', 'uns', 'many', 'day', 'come', 'los', 'eine', 'wie', 'aut', 'les', 'sind','un', 'et','il','le','las','la', 'nos','will', 'dan', 'se', 'au', 'una', 'unas', 'le', 'aut', 'and', 'den', 'ein', 'al', 'des','_','il', 'e', 'en', 'que', 'non', 'da', 'Ich', 'la', 'mit', 'zu', 'es', 'con', 'von', 'und', 'auf', 'auch','sich', 'der', 'hasta', 'das', 'Sie', 'para', 'el', 'per'])\n",
    "\n",
    "def CleanText(txt):\n",
    "    txt = re.sub(r'https?:\\/\\/.*[\\r\\n]*','',txt) # Remove hyperlinks\n",
    "    # Remove some nonsense\n",
    "    txt = re.sub(r'dans le','',txt)\n",
    "    txt = re.sub(r'Sie uns','',txt)\n",
    "    txt = re.sub(r'RT[\\s]+','',txt) # remove retweets\n",
    "    txt = re.sub(r'\\d+','',txt) #remove digits\n",
    "#     txt = re.sub(r' https://twitter.com/AFairGoAUS/status/1297320236253769729', '', txt)\n",
    "    txt = re.sub(' '+' | '.join(stopwords).lstrip(' | ')+' ',' ',txt ) # 🔥 This is the right way to remove stopwords, they're just gone\n",
    "    \n",
    "    return txt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Wordcloud"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 305,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 51.1 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "allwords = ' '.join(df.text.apply(CleanText).values.tolist())\n",
    "# allwords\n",
    "mask = np.array(Image.open('C://Users//cuspi//Documents//Databases//Canada_Twitter//Canadian_Flag.jpg'))\n",
    "\n",
    "wcloud = WordCloud(width=3000, height=1700, random_state=11, max_font_size=211, background_color='white',\n",
    "                max_words=400, collocations=False, mode='RGBA',mask=mask, stopwords=stopwords,\n",
    "                  font_path='C://WINDOWS//FONTS//LATOWEB-LIGHT.TTF').generate(allwords)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 306,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14,8))\n",
    "\n",
    "# create coloring from image\n",
    "image_colors = ImageColorGenerator(mask)\n",
    "plt.imshow(wcloud.recolor(color_func=image_colors), interpolation=\"bilinear\")\n",
    "plt.axis(\"off\")\n",
    "\n",
    "# store to file\n",
    "plt.savefig(\"C:/Users/cuspi/Documents/Databases/Twitter/lint.jpg\", format=\"jpg\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## To export to Tableau \n",
    "We first have to do the same cleaning, remove stopwords like we did and separate by columns so that we can then pivot them in Tableau and count them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 309,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 1min 4s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# Separate the text in columns to make a word counter in Tableau 😎\n",
    "df['text'].map(CleanText).str.split(expand=True).to_csv('C:\\\\Users\\\\cuspi\\\\Documents\\\\Databases\\\\Canada_Twitter\\\\text_in_columns.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Subjectivity and Polarity\n",
    "Let's define a couple of functions that will give us the subjectivity and the polarity of each tweet:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def GetSubjectivity(txt):\n",
    "    return TextBlob(txt).sentiment.subjectivity\n",
    "\n",
    "def GetPolarity(txt):\n",
    "    return TextBlob(txt).sentiment.polaritys\n",
    "\n",
    "# Create new columns:\n",
    "df['subjectivity'] = df.text.apply(GetSubjectivity)\n",
    "df['polarity'] = df.text.apply(GetPolarity)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tableau\n",
    "\n",
    "This project gets much more interesting when one is able to interact with the data. \n",
    "\n",
    "In [this Tableau link](https://public.tableau.com/profile/leocuspinera#!/vizhome/Twitter_15978796836980/Dashboard?publish=yes) one can see why:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<iframe src='https://public.tableau.com/views/Twitter_15978796836980/Dashboard?:language=en-GB&:display_count=y&:showVizHome=no&publish=yes&:origin=viz_share_link'  width=\"100%\" height=\"820 px\" style=\"-webkit-transform:scale(0.8);-moz-transform-scale(0.8);\" scrolling=\"yes\" seamless=\"seamless\" frameborder=\"0\" allowfullscreen>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
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