Twitter-exploratory-data-analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Twitter Sentiment Analysis (Parte 1)\n",
    "\n",
    "A construção da rede neural, que vou utilizar na parte 2, foi baseada em uma aula que tive da Udacity, do \"PyThorch Scholarship Challenge\", no qual aprendi sobre redes neurais profundas (CNNs, LSTMs, etc.). \n",
    "\n",
    "O meu objetivo nessa primeira parte vai fazer uma análise exploratória dos dados pra então treinar um algoritmo, na parte 2, capaz de classificar os sentimentos desses twittes, que são dividos em três categorias, sendo elas:\n",
    "\n",
    "1 - Negativos: qualquer tuíte relacionado com algum sentimento ruim, negativo, de estresse, ou que sejam contra a quarentena;\n",
    "\n",
    "2 - Neutros: caem nessa categoria os tts de propaganda, os que tem um sentimento neutro em relação a quarentena, relatos de atividades cotidianas;\n",
    "\n",
    "3 - Positivos: expressam um sentimento positivo em relação a quarentena, ou piadas, brincadeiras, dicas, etc.\n",
    "\n",
    "Também influenciou a minha nota quando um determinado tuíte aparentava que seu autor poderia vir logo a aparentar sintomas negativos, relacionados ao tédio de ter que ficar em casa."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import re\n",
    "from baseuf import ufbr\n",
    "from collections import Counter\n",
    "import csv\n",
    "import seaborn as sns; sns.set()\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Informações básicas sobre os dados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ">>> Enter file name: quarentenaBR.csv\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/laisouzalves/anaconda3/lib/python3.7/site-packages/IPython/core/interactiveshell.py:3057: DtypeWarning: Columns (4) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  interactivity=interactivity, compiler=compiler, result=result)\n"
     ]
    }
   ],
   "source": [
    "# Abrindo os arquivos:\n",
    "csvFile = str(input(\">>> Enter file name: \"))\n",
    "data = pd.read_csv(csvFile)\n",
    "data.drop(columns=['Unnamed: 0'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>geo</th>\n",
       "      <th>hashtags</th>\n",
       "      <th>id</th>\n",
       "      <th>place</th>\n",
       "      <th>text</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Thu Apr 02 20:45:17 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>quarentena, personalidade, engracado</td>\n",
       "      <td>1245814582364516355</td>\n",
       "      <td>Falha na localização 🚫</td>\n",
       "      <td>Eu tirei: Anti-social🙂! E você? https://t.co/s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Thu Apr 02 20:45:14 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>animalhouse, quarentena, movietime</td>\n",
       "      <td>1245814571559989258</td>\n",
       "      <td>Portugal</td>\n",
       "      <td>Bute ver um filme? #animalhouse #quarentena #m...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Thu Apr 02 20:45:12 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>isolamentosocial</td>\n",
       "      <td>1245814563741798401</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Hoje voltei a meditar... Tá foda. #isolamentos...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Thu Apr 02 20:45:12 +0000 2020</td>\n",
       "      <td>[[-35.815834, -9.711808], [-35.558391, -9.7118...</td>\n",
       "      <td>quarentena, TikTok</td>\n",
       "      <td>1245814560851931136</td>\n",
       "      <td>Maceió, Alagoas</td>\n",
       "      <td>A minha #quarentena está resumida nesse vídeo....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Thu Apr 02 20:45:09 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>humor, comedia, quarentena</td>\n",
       "      <td>1245814550630486017</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @Vamosrirsualou1: Eu estou iguaizinho kkk\\n...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             date  \\\n",
       "0  Thu Apr 02 20:45:17 +0000 2020   \n",
       "1  Thu Apr 02 20:45:14 +0000 2020   \n",
       "2  Thu Apr 02 20:45:12 +0000 2020   \n",
       "3  Thu Apr 02 20:45:12 +0000 2020   \n",
       "4  Thu Apr 02 20:45:09 +0000 2020   \n",
       "\n",
       "                                                 geo  \\\n",
       "0                                                NaN   \n",
       "1                                                NaN   \n",
       "2                                                NaN   \n",
       "3  [[-35.815834, -9.711808], [-35.558391, -9.7118...   \n",
       "4                                                NaN   \n",
       "\n",
       "                               hashtags                   id  \\\n",
       "0  quarentena, personalidade, engracado  1245814582364516355   \n",
       "1    animalhouse, quarentena, movietime  1245814571559989258   \n",
       "2                      isolamentosocial  1245814563741798401   \n",
       "3                    quarentena, TikTok  1245814560851931136   \n",
       "4            humor, comedia, quarentena  1245814550630486017   \n",
       "\n",
       "                    place                                               text  \n",
       "0  Falha na localização 🚫  Eu tirei: Anti-social🙂! E você? https://t.co/s...  \n",
       "1                Portugal  Bute ver um filme? #animalhouse #quarentena #m...  \n",
       "2                     NaN  Hoje voltei a meditar... Tá foda. #isolamentos...  \n",
       "3         Maceió, Alagoas  A minha #quarentena está resumida nesse vídeo....  \n",
       "4                     NaN  RT @Vamosrirsualou1: Eu estou iguaizinho kkk\\n...  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>geo</th>\n",
       "      <th>hashtags</th>\n",
       "      <th>id</th>\n",
       "      <th>place</th>\n",
       "      <th>text</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>614751</th>\n",
       "      <td>2020-03-18 22:22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,24044859183722E+018</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Anitta, rainha brasileira! Proporcionando bem ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>614752</th>\n",
       "      <td>2020-03-18 22:22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,24044845673451E+018</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Esse vídeo mostra como podemos ajudar a diminu...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>614753</th>\n",
       "      <td>2020-03-18 22:22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,24044843663541E+018</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Me deem dicas de não engordar 20 kgs nessas fé...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>614754</th>\n",
       "      <td>2020-03-18 22:22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,24044840409179E+018</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ponto alto do meu 2º dia de # quarentena : liv...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>614755</th>\n",
       "      <td>2020-03-18 22:21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,24044836615006E+018</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ai gente eu pensei que ia estudar mais nessa #...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    date  geo hashtags                     id place  \\\n",
       "614751  2020-03-18 22:22  NaN      NaN  1,24044859183722E+018   NaN   \n",
       "614752  2020-03-18 22:22  NaN      NaN  1,24044845673451E+018   NaN   \n",
       "614753  2020-03-18 22:22  NaN      NaN  1,24044843663541E+018   NaN   \n",
       "614754  2020-03-18 22:22  NaN      NaN  1,24044840409179E+018   NaN   \n",
       "614755  2020-03-18 22:21  NaN      NaN  1,24044836615006E+018   NaN   \n",
       "\n",
       "                                                     text  \n",
       "614751  Anitta, rainha brasileira! Proporcionando bem ...  \n",
       "614752  Esse vídeo mostra como podemos ajudar a diminu...  \n",
       "614753  Me deem dicas de não engordar 20 kgs nessas fé...  \n",
       "614754  Ponto alto do meu 2º dia de # quarentena : liv...  \n",
       "614755  Ai gente eu pensei que ia estudar mais nessa #...  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# df = data[['id', 'date', 'text', 'geo', 'hashtags', 'place']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# \"Little\" Exploratory Data Analysis (EDA)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "O total de twittes é de 614756.\n"
     ]
    }
   ],
   "source": [
    "total_twittes = data.shape[0]\n",
    "print(\"O total de twittes é de {}.\".format(total_twittes))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quantas coordenadas preenchidas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total de twittes com Coordenadas não-nulas: 25046\n",
      "Isso equivale à 4.07% do número total de twittes.\n"
     ]
    }
   ],
   "source": [
    "num_coord = data['geo'].notnull().sum()\n",
    "print('Total de twittes com Coordenadas não-nulas: {}\\nIsso equivale à {:.2f}% do número total de twittes.'.format(num_coord, num_coord/total_twittes*100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Salvando as coordenadas em uma lista\n",
    "mask1 = data['geo'].notnull()\n",
    "geo_coord = data[mask1]\n",
    "\n",
    "# mask2 = geo_coord['has_place'] == False\n",
    "# geo_and_local = geo_coord[mask2]\n",
    "\n",
    "geo_coord_list = pd.DataFrame(geo_coord['geo'])\n",
    "# geo_coord_list.to_csv('coordenadas_tts.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>geo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>[[-35.815834, -9.711808], [-35.558391, -9.7118...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>[[-46.826039, -24.008814], [-46.365052, -24.00...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>[[-40.969461, -9.482947], [-40.208561, -9.4829...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>[[-49.3916434, -25.6447517], [-49.1852775, -25...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>[[-8.916355, 42.1293801], [-8.6267592, 42.1293...</td>\n",
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      "text/plain": [
       "                                                  geo\n",
       "3   [[-35.815834, -9.711808], [-35.558391, -9.7118...\n",
       "25  [[-46.826039, -24.008814], [-46.365052, -24.00...\n",
       "32  [[-40.969461, -9.482947], [-40.208561, -9.4829...\n",
       "46  [[-49.3916434, -25.6447517], [-49.1852775, -25...\n",
       "68  [[-8.916355, 42.1293801], [-8.6267592, 42.1293..."
      ]
     },
     "execution_count": 8,
     "metadata": {},
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    }
   ],
   "source": [
    "geo_coord_list.head()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "geo_coord_list.to_csv('coordenadas_tts.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quantos Locais válidos únicos existem"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "accent_map = {u'\\u00c0': u'A', u'\\u00c1': u'A', u'\\u00c2': u'A', u'\\u00c3': u'A', u'\\u00c4': u'A', u'\\u00c5': u'A', u'\\u00c6': u'A', u'\\u00c7': u'C', u'\\u00c8': u'E', u'\\u00c9': u'E', u'\\u00ca': u'E', u'\\u00cb': u'E', u'\\u00cc': u'I', u'\\u00cd': u'I', u'\\u00ce': u'I', u'\\u00cf': u'I', u'\\u00d0': u'D', u'\\u00d1': u'N', u'\\u00d2': u'O', u'\\u00d3': u'O', u'\\u00d4': u'O', u'\\u00d5': u'O', u'\\u00d6': u'O', u'\\u00d7': u'x', u'\\u00d8': u'0', u'\\u00d9': u'U', u'\\u00da': u'U', u'\\u00db': u'U', u'\\u00dc': u'U', U'\\u00dd': u'Y', u'\\u00df': u'B', u'\\u00e0': u'a', u'\\u00e1': u'a', u'\\u00e2': u'a', u'\\u00e3': u'a', u'\\u00e4': u'a', u'\\u00e5': u'a', u'\\u00e6': u'a', u'\\u00e7': u'c', u'\\u00e8': u'e', u'\\u00e9': u'e', u'\\u00ea': u'e', u'\\u00eb': u'e', u'\\u00ec': u'i', u'\\u00ed': u'i', u'\\u00ee': u'i', u'\\u00ef': u'i', u'\\u00f1': u'n', u'\\u00f2': u'o', u'\\u00f3': u'o', u'\\u00f4': u'o', u'\\u00f5': u'o', u'\\u00f6': u'o', u'\\u00f8': u'0', u'\\u00f9': u'u', u'\\u00fa': u'u', u'\\u00fb': u'u', u'\\u00fc': u'u'}\n",
    "\n",
    "\n",
    "def accent_remove(m):\n",
    "    return accent_map[m.group(0)]\n",
    "\n",
    "\n",
    "def clean_list(list_to_clean):\n",
    "    for idx, item in enumerate(list_to_clean):\n",
    "        list_to_clean[idx] = str(item)\n",
    "        string = list_to_clean[idx]\n",
    "        list_to_clean[idx] = re.sub('[÷ð]', '', string)\n",
    "        string = list_to_clean[idx]\n",
    "        list_to_clean[idx] = re.sub(u'([\\u00C0-\\u00FC])', accent_remove, string.encode().decode('utf-8'))\n",
    "        list_to_clean[idx] = list_to_clean[idx].lower()\n",
    "        string = list_to_clean[idx]\n",
    "        list_to_clean[idx] = re.sub('\\W\\s-', '', string)\n",
    "        string = list_to_clean[idx]\n",
    "        list_to_clean[idx] = re.sub('[…•\\(\\)\\&]', ' ', string)\n",
    "    return list_to_clean\n",
    "\n",
    "\n",
    "def remove_emoji(string):\n",
    "    emoji_pattern = re.compile(\"[\"\n",
    "                           u\"\\U0001F600-\\U0001F64F\"  # emoticons\n",
    "                           u\"\\U0001F300-\\U0001F5FF\"  # symbols & pictographs\n",
    "                           u\"\\U0001F680-\\U0001F6FF\"  # transport & map symbols\n",
    "                           u\"\\U0001F1E0-\\U0001F1FF\"  # flags (iOS)\n",
    "                           u\"\\U00002702-\\U000027B0\"\n",
    "                           u\"\\U000024C2-\\U0001F251\"\n",
    "                           \"]+\", flags=re.UNICODE)\n",
    "    return emoji_pattern.sub(r'', string)\n",
    "\n",
    "\n",
    "def clean_tts(list_to_clean):\n",
    "    for idx, item in enumerate(list_to_clean):\n",
    "        # transforma tudo para str\n",
    "        list_to_clean[idx] = str(item)\n",
    "        # retira todo o link https:// do tuite\n",
    "        list_str = list_to_clean[idx].split()\n",
    "        string = ' '.join([word for word in list_str if not re.search('https://t.co', word)])\n",
    "        #remove acentos\n",
    "        list_to_clean[idx] = re.sub(u'([\\u00C0-\\u00FC])', accent_remove, string.encode().decode('utf-8'))\n",
    "        # remove emojis\n",
    "        string = list_to_clean[idx].encode('ascii', 'ignore').decode('ascii')\n",
    "        list_to_clean[idx] = remove_emoji(string)\n",
    "        # deixa tudo em caixa baixa\n",
    "        list_to_clean[idx] = list_to_clean[idx].lower()\n",
    "        # substitui o restante dos caracteres desnecessarios\n",
    "        string = list_to_clean[idx]\n",
    "        list_to_clean[idx] = re.sub('[…•\\(\\)\\&]', '', string)\n",
    "        string = list_to_clean[idx]\n",
    "        list_to_clean[idx] = re.sub('\\W\\s-', '', string)\n",
    "        string = list_to_clean[idx]\n",
    "        list_to_clean[idx] = re.sub('[\"º°/_]', ' ', string)\n",
    "        # remove espaços desnecessarios\n",
    "        string_list = list_to_clean[idx].split()\n",
    "        list_to_clean[idx] = ' '.join(string_list)\n",
    "\n",
    "    return list_to_clean\n",
    "\n",
    "def filter_count(principal_list, filter1):\n",
    "    count_filter = 0\n",
    "    bool_list = []\n",
    "    for idx, item in enumerate(principal_list):\n",
    "        frase = item\n",
    "        if ' - ' in frase:\n",
    "            frase = frase.split(' - ')\n",
    "        elif ' -' in frase:\n",
    "            frase = frase.split(' -')\n",
    "        elif '- ' in frase:\n",
    "            frase = frase.split('- ')\n",
    "        elif '-' in frase:\n",
    "            frase = frase.split('-')\n",
    "        elif ' / ' in frase:\n",
    "            frase = frase.split(' / ')\n",
    "        elif ' /' in frase:\n",
    "            frase = frase.split(' /')\n",
    "        elif '/ ' in frase:\n",
    "            frase = frase.split('/ ')\n",
    "        elif '/' in frase:\n",
    "            frase = frase.split('/')\n",
    "        elif ' , ' in frase:\n",
    "            frase = frase.split(' , ')\n",
    "        elif ', ' in frase:\n",
    "            frase = frase.split(', ')\n",
    "        elif ' ,' in frase:\n",
    "            frase = frase.split(' ,')\n",
    "        elif ',' in frase:\n",
    "            frase = frase.split(',')\n",
    "        elif ' | ' in frase:\n",
    "            frase = frase.split(' | ')\n",
    "        elif ' |' in frase:\n",
    "            frase = frase.split(' |')\n",
    "        elif '| ' in frase:\n",
    "            frase = frase.split('| ')\n",
    "        elif '|' in frase:\n",
    "            frase = frase.split('|')\n",
    "        \n",
    "        if type(frase) != list:\n",
    "            frase = [frase]\n",
    "            \n",
    "        for idx, item in enumerate(filter1):\n",
    "            if item in frase:\n",
    "                count_filter += 1\n",
    "                bool_list.append(True)\n",
    "                break\n",
    "            if item == filter1[-1]:\n",
    "                bool_list.append(False)\n",
    "\n",
    "    return count_filter, bool_list\n",
    "\n",
    "\n",
    "# def cities_tolist(city_list):\n",
    "#     cities = []\n",
    "#     for idx, item in enumerate(city_list):\n",
    "#         city = item.lower()\n",
    "#         cities.append(city)\n",
    "#     return cities\n",
    "\n",
    "\n",
    "estados = [['acre', 'ac'], ['alagoas', 'al'], ['amazonas', 'am'], ['amapa', 'ap'], ['bahia', 'bahea', 'ba'],  ['ceara', 'ce'], ['distrito federal', 'de-efe', 'brasolia', 'df', 'taguatinga', 'asa sul', 'sobradinho', 'ceilandia', 'samambaia', 'asa norte', 'guara', 'aguas claras', 'parkway', 'vicente pires'], ['espirito santo', 'es'], ['goias', 'gyn', 'go'], ['maranhao', 'terehell', 'ma'], ['minas gerais', 'mg'], ['mato grosso do sul', 'ms'], ['mato grosso', 'mt'], ['para', 'pa'], ['paraiba', 'pb'], ['pernambuco', 'pe'], ['piaui', 'pi'], ['parana', 'pr'], ['rio de janeiro', 'rj'], ['rio grande do norte', 'rn'], ['rondonia', 'ro'], ['roraima', 'rr'], ['rio grande do sul', 'rs'], ['santa catarina', 'sc'], ['sergipe', 'se'], ['sao paulo', 'sampa', 'sp'], ['tocantins', 'to']]\n",
    "\n",
    "def separar_estados(lista_locais, csvFile_):\n",
    "    c_lista_locais = clean_list(lista_locais)\n",
    "    dataframe = pd.DataFrame(columns=['state', 'tts_count'])\n",
    "    # ufbr.list_uf = ['AC', 'AL', 'AM', 'AP', 'BA', 'CE', 'DF', 'ES', 'GO', 'MA', 'MG', 'MS', 'MT', 'PA', 'PB', 'PE', 'PI', 'PR', 'RJ', 'RN', 'RO', 'RR', 'RS', 'SC', 'SE', 'SP', 'TO']\n",
    "    for idx, item in enumerate(ufbr.list_uf):\n",
    "        # Example: cidades_sp = ufbr.list_cidades('SP')\n",
    "        # cities_tolist() limpa a lista de cidades (set lower)\n",
    "        # cities = cities_tolist(ufbr.list_cidades(item)) + estados[idx]\n",
    "        cities = [x.lower() for x in ufbr.list_cidades(item)] + estados[idx]\n",
    "        # c_cities contains the list of cities without any pontuation\n",
    "        c_cities = clean_list(cities)\n",
    "        # cities_count(states_list) é o numero de tweets na lista states_list\n",
    "        cities_count, has_place_list = filter_count(c_lista_locais, c_cities)\n",
    "        row_to_append = [str(item), cities_count]\n",
    "        row = pd.DataFrame([row_to_append], columns=['state', 'tts_count'])\n",
    "        dataframe = dataframe.append(row, ignore_index=True)\n",
    "\n",
    "    dataframe.to_csv(csvFile_, mode='a', columns=['state', 'tts_count'], header=True, index=False, encoding=\"utf-8\")\n"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "# lista_teste = ['carrao, sao paulo', 'banana, sp/brasil', 'brasil - bsb/sp', 'moto nada a ver']\n",
    "filtro_teste = ['sao paulo', 'brasil', 'bsb', 'sp']\n",
    "filter_count(lista_teste, filtro_teste)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Colecting all cities in Brasil...\n",
      "Done colecting all cities.\n",
      "\n",
      "Cleaning lists...\n",
      "Done cleaning lists.\n",
      "\n",
      "Colecting 'has_place' column...\n",
      "Done colecting 'has_place' column.\n",
      "Número total de tweets com local preenchido 406726.\n",
      "Isso equivale a 66.16 % dos tweets.\n",
      "\n",
      "Número total de twittes que possuem local válido: 300470.\n",
      "Isso equivale à 73.88% do total de twittes.\n"
     ]
    }
   ],
   "source": [
    "estados_list = ['acre', 'ac', 'alagoas', 'al', 'amapa', 'ap', 'amazonas', 'am', 'bahia', 'ba', 'ceara', 'ce', 'distrito federal', 'df', 'espirito santo', 'es', 'goias', 'go', 'maranhao', 'ma', 'mato grosso', 'mt', 'mato grosso do sul', 'ms', 'minas gerais', 'mg', 'para', 'pa', 'paraiba', 'pb', 'parana', 'pr', 'pernambuco', 'pe', 'piaui', 'pi', 'rio de janeiro', 'rj', 'rio grande do norte', 'rn', 'sul', 'rs', 'rondonia', 'ro', 'roraima', 'rr', 'santa catarina', 'sc', 'sao paulo', 'sp', 'sergipe', 'se', 'tocantins', 'to']\n",
    "\n",
    "capitais = ['rio branco', 'maceio', 'macapa', 'manaus', 'salvador', 'fortaleza', 'brasilia', 'bsb', 'vitoria', 'goiania', 'gyn', 'sao luis', 'cuiaba', 'campo grande', 'belo horizonte', 'bh', 'belem', 'joao pessoa', 'jp', 'curitiba', 'recife', 'teresina', 'terehell', 'rio de janeiro', 'rj', 'natal', 'porto alegre', 'poa', 'porto velho', 'boa vista', 'florianopolis', 'floripa', 'sao paulo', 'sampa', 'aracaju', 'palmas']\n",
    "\n",
    "print(\"Colecting all cities in Brasil...\")\n",
    "all_cities = []\n",
    "for item in ufbr.list_uf:\n",
    "    city_list = [x.lower() for x in ufbr.list_cidades(item)]\n",
    "    all_cities += city_list\n",
    "print(\"Done colecting all cities.\\n\")\n",
    "\n",
    "# all_cities = []    \n",
    "# for idx, item in enumerate(ufbr.list_uf):\n",
    "#     city_list = cities_tolist(ufbr.list_cidades(item))\n",
    "#     for idx, item in enumerate(city_list):\n",
    "#         all_cities.append(item)\n",
    "\n",
    "print(\"Cleaning lists...\")\n",
    "locais_br = all_cities + estados_list + ['brasil', 'brazil']\n",
    "c_locais_br = clean_list(locais_br)\n",
    "\n",
    "places = data['place'].to_list()\n",
    "c_places = clean_list(places)\n",
    "print(\"Done cleaning lists.\\n\")\n",
    "\n",
    "# places_idx = []\n",
    "# places_bool = []\n",
    "# for idx, item in enumerate(c_places):\n",
    "#     string = str(item)\n",
    "#     for i, j in enumerate(string.split()): \n",
    "#         if j in c_locais_br:\n",
    "#             places_bool.append(True)\n",
    "#             places_idx.append(idx)\n",
    "#             break\n",
    "#         else: \n",
    "#             places_bool.append(False)\n",
    "#\n",
    "# OU ESSA VERSÃO ABAIXO QUE É MAIS EFICIENTE\n",
    "#\n",
    "# print(\"Colecting 'has_place' column...\")\n",
    "# places_bool = [True if item in c_locais_br else False for item in c_places]\n",
    "# print(\"Done colecting 'has_place' column. /nNow colecting places indexes...\")\n",
    "# places_idx = [idx for idx, item in enumerate(c_places) if item in c_locais_br]\n",
    "# print(\"Done colecting places indexes.\")\n",
    "\n",
    "# Mas melhor ainda é o código abaixo. Eu corrigi a funçao filter_count() pra coletar a coluna True/False\n",
    "print(\"Colecting 'has_place' column...\")\n",
    "num_places_br, has_place = filter_count(c_places, c_locais_br)\n",
    "print(\"Done colecting 'has_place' column.\")\n",
    "\n",
    "mask = data['place'].notnull()\n",
    "data_all_places = data[mask]\n",
    "\n",
    "print(\"Número total de tweets com local preenchido {}.\\nIsso equivale a {:.2f} % dos tweets.\\n\".format(data_all_places.shape[0], data_all_places.shape[0]*100/data.shape[0]))\n",
    "\n",
    "# print(\"Número total de twittes que possuem local válido: {}.\\nIsso equivale à {:.2f}% do total de twittes.\".format(len(places_idx), len(places_idx)*100/len(c_places)))\n",
    "print(\"Número total de twittes que possuem local válido: {}.\\nIsso equivale à {:.2f}% do total de twittes.\".format(num_places_br, num_places_br*100/data.shape[0]))"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "c_places[:50]"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "str_teste = 'sao paulo  ,    brasil'\n",
    "print(str_teste)\n",
    "str_arrumada = str_teste.split()\n",
    "print(str_arrumada)\n",
    "str_arrumada = ' '.join(str_arrumada)\n",
    "print(str_arrumada)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ">>> New column 'has_place' has been concatenated\n"
     ]
    }
   ],
   "source": [
    "# O código abaixo já não é mais necessário pq essa funcionalidade foi inserida na função filter_count()\n",
    "# has_place = list(range(0, len(data['place'])))\n",
    "# for idx,item in enumerate(data['place']):\n",
    "#     if idx in places_idx:\n",
    "#         has_place[idx] = True\n",
    "#     else:\n",
    "#         has_place[idx] = False\n",
    "\n",
    "\n",
    "has_place = pd.DataFrame(has_place, columns=['has_place'])\n",
    "new_data = pd.concat([data, has_place], axis=1)\n",
    "print(\">>> New column 'has_place' has been concatenated\")\n",
    "try:\n",
    "    if new_data['Unnamed: 0'].any():\n",
    "        print('---------------------------------------------------------')\n",
    "        print(\"Droping column 'Unnamed: 0'\")\n",
    "        new_data.drop(columns=['Unnamed: 0'], inplace=True)\n",
    "except KeyError:\n",
    "    pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>geo</th>\n",
       "      <th>hashtags</th>\n",
       "      <th>id</th>\n",
       "      <th>place</th>\n",
       "      <th>text</th>\n",
       "      <th>has_place</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Thu Apr 02 20:45:17 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>quarentena, personalidade, engracado</td>\n",
       "      <td>1245814582364516355</td>\n",
       "      <td>Falha na localização 🚫</td>\n",
       "      <td>Eu tirei: Anti-social🙂! E você? https://t.co/s...</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Thu Apr 02 20:45:14 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>animalhouse, quarentena, movietime</td>\n",
       "      <td>1245814571559989258</td>\n",
       "      <td>Portugal</td>\n",
       "      <td>Bute ver um filme? #animalhouse #quarentena #m...</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Thu Apr 02 20:45:12 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>isolamentosocial</td>\n",
       "      <td>1245814563741798401</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Hoje voltei a meditar... Tá foda. #isolamentos...</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Thu Apr 02 20:45:12 +0000 2020</td>\n",
       "      <td>[[-35.815834, -9.711808], [-35.558391, -9.7118...</td>\n",
       "      <td>quarentena, TikTok</td>\n",
       "      <td>1245814560851931136</td>\n",
       "      <td>Maceió, Alagoas</td>\n",
       "      <td>A minha #quarentena está resumida nesse vídeo....</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Thu Apr 02 20:45:09 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>humor, comedia, quarentena</td>\n",
       "      <td>1245814550630486017</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @Vamosrirsualou1: Eu estou iguaizinho kkk\\n...</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Thu Apr 02 20:45:09 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245814549346955271</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @jorgeemateus: Vamos de spoiler? Essas já e...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Thu Apr 02 20:45:07 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sunshine, raiodesol, vsco, vscofilters, Quaren...</td>\n",
       "      <td>1245814540127940608</td>\n",
       "      <td>se eu soubesse eu falava</td>\n",
       "      <td>Eh O prisioneiro saiu pra pegar um banho de so...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Thu Apr 02 20:45:07 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>coronavirusnomundo, quarentena, covid19</td>\n",
       "      <td>1245814539842715648</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @Francischini_: Previsão da OMS se confirmo...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Thu Apr 02 20:45:06 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>EcuadorEnEmergencia, COVID19Pandemic, quarente...</td>\n",
       "      <td>1245814536235560961</td>\n",
       "      <td>Brasil</td>\n",
       "      <td>Ver a situação do Equador neste momento acabou...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Thu Apr 02 20:44:50 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245814472146595842</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @JL2edicao: Corpo de homem que foi desenter...</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Thu Apr 02 20:44:48 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>COVID19Pandemic</td>\n",
       "      <td>1245814463145574401</td>\n",
       "      <td>Brasil, de Bananas e Bundas</td>\n",
       "      <td>RT @BlogDoTato67: #COVID19Pandemic \\n\\nNúmeros...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Thu Apr 02 20:44:47 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RAVEDADIVA</td>\n",
       "      <td>1245814457525309440</td>\n",
       "      <td>Eroda -  Sacred Hearts Club</td>\n",
       "      <td>RT @DivaDepressao: Vcs acharam q a gente não i...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Thu Apr 02 20:44:41 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245814432611041280</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @jnascim: 🇧🇷 No cemitério da Vila Formosa, ...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Thu Apr 02 20:44:41 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245814430711066626</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @Corinthians: Não afrouxe as medidas preven...</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Thu Apr 02 20:44:21 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FiqueEmCasa</td>\n",
       "      <td>1245814346829234176</td>\n",
       "      <td>Imbituba, Brasil</td>\n",
       "      <td>A vida é igual matemática, se tá fácil então t...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Thu Apr 02 20:44:17 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245814330676961282</td>\n",
       "      <td>Hogwarts</td>\n",
       "      <td>RT @YaraKings: Amados, vocês que estão fazendo...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Thu Apr 02 20:44:16 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>COVID19Pandemic, FiqueEmCasa</td>\n",
       "      <td>1245814328940531712</td>\n",
       "      <td>Brasil, de Bananas e Bundas</td>\n",
       "      <td>#COVID19Pandemic \\n\\nNúmeros atualizados do @m...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Thu Apr 02 20:44:03 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FiqueEmCasa</td>\n",
       "      <td>1245814274951393283</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @softpowers_: O Ceará saltou de 9 mortes on...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Thu Apr 02 20:44:02 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245814270350241794</td>\n",
       "      <td>São Paulo, Brasil</td>\n",
       "      <td>RT @delucca: Moisés Borowicz, 93 anos, sobrevi...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Thu Apr 02 20:44:01 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245814265124196352</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @jorgeemateus: Vamos de spoiler? Essas já e...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Thu Apr 02 20:43:54 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>quarentena</td>\n",
       "      <td>1245814235072008195</td>\n",
       "      <td>Pará, Brasil</td>\n",
       "      <td>Pelo visto só eu tô de quarentena!\\n#quarentena</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Thu Apr 02 20:43:52 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>homeoffice, indeotecnologia, tech, covid19, co...</td>\n",
       "      <td>1245814226817560579</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Como trabalhamos mudou, você está pronto mesmo...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Thu Apr 02 20:43:51 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>covıd19, ficaemcasa, pandemia, quarentena, Dis...</td>\n",
       "      <td>1245814223160193025</td>\n",
       "      <td>Brasil</td>\n",
       "      <td>E você, o que tem feito nesses dias de isolame...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Thu Apr 02 20:43:50 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FiqueEmCasa, MudadeCanal, CuidadaSaúdeMental</td>\n",
       "      <td>1245814216780582914</td>\n",
       "      <td>Sirinhaém, Brasil</td>\n",
       "      <td>RT @ednandof: Se você assistir 2x ao dia o Jor...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Thu Apr 02 20:43:47 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245814206093500416</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @_Goalpoint: 📅 JÁ HÁ PLANO PARA A LIGA NOS\\...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Thu Apr 02 20:43:37 +0000 2020</td>\n",
       "      <td>[[-46.826039, -24.008814], [-46.365052, -24.00...</td>\n",
       "      <td>quarentena, HomeOffice</td>\n",
       "      <td>1245814164020506624</td>\n",
       "      <td>Carrão, São Paulo</td>\n",
       "      <td>Tá ligado ??? \\nNão!?\\nEntão se conecta!\\n#qua...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Thu Apr 02 20:43:27 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245814120701669382</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @cbmerjoficial: Nossa missão é salvar vidas...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Thu Apr 02 20:43:24 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>HomeOffice</td>\n",
       "      <td>1245814111310622721</td>\n",
       "      <td>Uruguaiana, Brasil</td>\n",
       "      <td>Quem quiser algumas dicas básicas, clica no ví...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Thu Apr 02 20:43:23 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245814103676989450</td>\n",
       "      <td>Porto Alegre, Brasil</td>\n",
       "      <td>RT @lariir1909: Quarentena e as idéias surgira...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Thu Apr 02 20:43:18 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FiqueEmCasa</td>\n",
       "      <td>1245814082579636224</td>\n",
       "      <td>Brasil</td>\n",
       "      <td>Carlos e Alexa criaram uma conta no Tik Tok e ...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Thu Apr 02 20:43:08 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245814044189175814</td>\n",
       "      <td>Santa Catarina, Brasil</td>\n",
       "      <td>RT @delucca: Moisés Borowicz, 93 anos, sobrevi...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Thu Apr 02 20:43:07 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245814036769452036</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @indiedadepre: Outra coisa importante: Não ...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Thu Apr 02 20:42:59 +0000 2020</td>\n",
       "      <td>[[-40.969461, -9.482947], [-40.208561, -9.4829...</td>\n",
       "      <td>tbt, quarentena, pequenasnotaveis, rose, rosa,...</td>\n",
       "      <td>1245814006058758149</td>\n",
       "      <td>Petrolina-PE</td>\n",
       "      <td>Em dia de #tbt, um registro de um dos últimos ...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Thu Apr 02 20:42:44 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NovaYork, isolamento</td>\n",
       "      <td>1245813939780358144</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @ReutersLatam: #NovaYork vira cidade fantas...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Thu Apr 02 20:42:42 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FiqueEmCasa</td>\n",
       "      <td>1245813931811241984</td>\n",
       "      <td>Fortaleza, Brasil</td>\n",
       "      <td>RT @softpowers_: O Ceará saltou de 9 mortes on...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Thu Apr 02 20:42:41 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245813930892636179</td>\n",
       "      <td>Brasil</td>\n",
       "      <td>RT @Corinthians: Não afrouxe as medidas preven...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Thu Apr 02 20:42:37 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PensandoEmTodos, FiqueEmCasa</td>\n",
       "      <td>1245813910407708672</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Massa, estamos passando por um momento difícil...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Thu Apr 02 20:42:36 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245813908935491584</td>\n",
       "      <td>na róça em botucatu/sp</td>\n",
       "      <td>RT @jnascim: 🇧🇷 No cemitério da Vila Formosa, ...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Thu Apr 02 20:42:35 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245813904820879360</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @jorgeemateus: Vamos de spoiler? Essas já e...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>Thu Apr 02 20:42:32 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ficaemcasa, quarentena</td>\n",
       "      <td>1245813890568650753</td>\n",
       "      <td>RJ • BSB • SLZ</td>\n",
       "      <td>[vai aqui tmb]\\n\\nquarentena né, minha filha\\n...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Thu Apr 02 20:42:29 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>gurideuruguaiana, jairkobe, riograndedosul, hu...</td>\n",
       "      <td>1245813878585470981</td>\n",
       "      <td>Berço da revolução Farroupilha</td>\n",
       "      <td>RT @jairkobe: E por aí chê! Como estão?\\n\\n#gu...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Thu Apr 02 20:42:27 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>quarentena</td>\n",
       "      <td>1245813870385651713</td>\n",
       "      <td>Condado - Faria Lima</td>\n",
       "      <td>Mais um pôr do sol durante a #quarentena, espe...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Thu Apr 02 20:42:27 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245813869026689025</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @recifeordinario: E aí, já tá com saudade d...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Thu Apr 02 20:42:22 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245813848822743040</td>\n",
       "      <td>Brasil</td>\n",
       "      <td>RT @SCCPFutFeminino: O futebol feminino do Cor...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Thu Apr 02 20:42:21 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245813843768508417</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @indiedadepre: Outra coisa importante: Não ...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Thu Apr 02 20:42:18 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245813834838876160</td>\n",
       "      <td>EDUÇÃO FÍSICA 📔✏</td>\n",
       "      <td>RT @jorgeemateus: Vamos de spoiler? Essas já e...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Thu Apr 02 20:42:14 +0000 2020</td>\n",
       "      <td>[[-49.3916434, -25.6447517], [-49.1852775, -25...</td>\n",
       "      <td>QuintaLiberdadeNoSDV, Quintadetremutasdv, LaCa...</td>\n",
       "      <td>1245813817617068036</td>\n",
       "      <td>Brasil</td>\n",
       "      <td>https://t.co/mjRMmw9OeU galera, temos um grupo...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>Thu Apr 02 20:42:09 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245813793453637633</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @delucca: Moisés Borowicz, 93 anos, sobrevi...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>Thu Apr 02 20:42:06 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245813782691094528</td>\n",
       "      <td>027</td>\n",
       "      <td>RT @thegeekguia: Feel Good vai além do comum p...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>Thu Apr 02 20:42:02 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>frases, amor, love, love, quarentena, words, c...</td>\n",
       "      <td>1245813764861112325</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>RT @versosdojm: Concordam ? 💛🌹\\n.\\n. @versosdo...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              date  \\\n",
       "0   Thu Apr 02 20:45:17 +0000 2020   \n",
       "1   Thu Apr 02 20:45:14 +0000 2020   \n",
       "2   Thu Apr 02 20:45:12 +0000 2020   \n",
       "3   Thu Apr 02 20:45:12 +0000 2020   \n",
       "4   Thu Apr 02 20:45:09 +0000 2020   \n",
       "5   Thu Apr 02 20:45:09 +0000 2020   \n",
       "6   Thu Apr 02 20:45:07 +0000 2020   \n",
       "7   Thu Apr 02 20:45:07 +0000 2020   \n",
       "8   Thu Apr 02 20:45:06 +0000 2020   \n",
       "9   Thu Apr 02 20:44:50 +0000 2020   \n",
       "10  Thu Apr 02 20:44:48 +0000 2020   \n",
       "11  Thu Apr 02 20:44:47 +0000 2020   \n",
       "12  Thu Apr 02 20:44:41 +0000 2020   \n",
       "13  Thu Apr 02 20:44:41 +0000 2020   \n",
       "14  Thu Apr 02 20:44:21 +0000 2020   \n",
       "15  Thu Apr 02 20:44:17 +0000 2020   \n",
       "16  Thu Apr 02 20:44:16 +0000 2020   \n",
       "17  Thu Apr 02 20:44:03 +0000 2020   \n",
       "18  Thu Apr 02 20:44:02 +0000 2020   \n",
       "19  Thu Apr 02 20:44:01 +0000 2020   \n",
       "20  Thu Apr 02 20:43:54 +0000 2020   \n",
       "21  Thu Apr 02 20:43:52 +0000 2020   \n",
       "22  Thu Apr 02 20:43:51 +0000 2020   \n",
       "23  Thu Apr 02 20:43:50 +0000 2020   \n",
       "24  Thu Apr 02 20:43:47 +0000 2020   \n",
       "25  Thu Apr 02 20:43:37 +0000 2020   \n",
       "26  Thu Apr 02 20:43:27 +0000 2020   \n",
       "27  Thu Apr 02 20:43:24 +0000 2020   \n",
       "28  Thu Apr 02 20:43:23 +0000 2020   \n",
       "29  Thu Apr 02 20:43:18 +0000 2020   \n",
       "30  Thu Apr 02 20:43:08 +0000 2020   \n",
       "31  Thu Apr 02 20:43:07 +0000 2020   \n",
       "32  Thu Apr 02 20:42:59 +0000 2020   \n",
       "33  Thu Apr 02 20:42:44 +0000 2020   \n",
       "34  Thu Apr 02 20:42:42 +0000 2020   \n",
       "35  Thu Apr 02 20:42:41 +0000 2020   \n",
       "36  Thu Apr 02 20:42:37 +0000 2020   \n",
       "37  Thu Apr 02 20:42:36 +0000 2020   \n",
       "38  Thu Apr 02 20:42:35 +0000 2020   \n",
       "39  Thu Apr 02 20:42:32 +0000 2020   \n",
       "40  Thu Apr 02 20:42:29 +0000 2020   \n",
       "41  Thu Apr 02 20:42:27 +0000 2020   \n",
       "42  Thu Apr 02 20:42:27 +0000 2020   \n",
       "43  Thu Apr 02 20:42:22 +0000 2020   \n",
       "44  Thu Apr 02 20:42:21 +0000 2020   \n",
       "45  Thu Apr 02 20:42:18 +0000 2020   \n",
       "46  Thu Apr 02 20:42:14 +0000 2020   \n",
       "47  Thu Apr 02 20:42:09 +0000 2020   \n",
       "48  Thu Apr 02 20:42:06 +0000 2020   \n",
       "49  Thu Apr 02 20:42:02 +0000 2020   \n",
       "\n",
       "                                                  geo  \\\n",
       "0                                                 NaN   \n",
       "1                                                 NaN   \n",
       "2                                                 NaN   \n",
       "3   [[-35.815834, -9.711808], [-35.558391, -9.7118...   \n",
       "4                                                 NaN   \n",
       "5                                                 NaN   \n",
       "6                                                 NaN   \n",
       "7                                                 NaN   \n",
       "8                                                 NaN   \n",
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       "10                                                NaN   \n",
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       "19                                                NaN   \n",
       "20                                                NaN   \n",
       "21                                                NaN   \n",
       "22                                                NaN   \n",
       "23                                                NaN   \n",
       "24                                                NaN   \n",
       "25  [[-46.826039, -24.008814], [-46.365052, -24.00...   \n",
       "26                                                NaN   \n",
       "27                                                NaN   \n",
       "28                                                NaN   \n",
       "29                                                NaN   \n",
       "30                                                NaN   \n",
       "31                                                NaN   \n",
       "32  [[-40.969461, -9.482947], [-40.208561, -9.4829...   \n",
       "33                                                NaN   \n",
       "34                                                NaN   \n",
       "35                                                NaN   \n",
       "36                                                NaN   \n",
       "37                                                NaN   \n",
       "38                                                NaN   \n",
       "39                                                NaN   \n",
       "40                                                NaN   \n",
       "41                                                NaN   \n",
       "42                                                NaN   \n",
       "43                                                NaN   \n",
       "44                                                NaN   \n",
       "45                                                NaN   \n",
       "46  [[-49.3916434, -25.6447517], [-49.1852775, -25...   \n",
       "47                                                NaN   \n",
       "48                                                NaN   \n",
       "49                                                NaN   \n",
       "\n",
       "                                             hashtags                   id  \\\n",
       "0                quarentena, personalidade, engracado  1245814582364516355   \n",
       "1                  animalhouse, quarentena, movietime  1245814571559989258   \n",
       "2                                    isolamentosocial  1245814563741798401   \n",
       "3                                  quarentena, TikTok  1245814560851931136   \n",
       "4                          humor, comedia, quarentena  1245814550630486017   \n",
       "5                                                 NaN  1245814549346955271   \n",
       "6   sunshine, raiodesol, vsco, vscofilters, Quaren...  1245814540127940608   \n",
       "7             coronavirusnomundo, quarentena, covid19  1245814539842715648   \n",
       "8   EcuadorEnEmergencia, COVID19Pandemic, quarente...  1245814536235560961   \n",
       "9                                                 NaN  1245814472146595842   \n",
       "10                                    COVID19Pandemic  1245814463145574401   \n",
       "11                                         RAVEDADIVA  1245814457525309440   \n",
       "12                                                NaN  1245814432611041280   \n",
       "13                                                NaN  1245814430711066626   \n",
       "14                                        FiqueEmCasa  1245814346829234176   \n",
       "15                                                NaN  1245814330676961282   \n",
       "16                       COVID19Pandemic, FiqueEmCasa  1245814328940531712   \n",
       "17                                        FiqueEmCasa  1245814274951393283   \n",
       "18                                                NaN  1245814270350241794   \n",
       "19                                                NaN  1245814265124196352   \n",
       "20                                         quarentena  1245814235072008195   \n",
       "21  homeoffice, indeotecnologia, tech, covid19, co...  1245814226817560579   \n",
       "22  covıd19, ficaemcasa, pandemia, quarentena, Dis...  1245814223160193025   \n",
       "23       FiqueEmCasa, MudadeCanal, CuidadaSaúdeMental  1245814216780582914   \n",
       "24                                                NaN  1245814206093500416   \n",
       "25                             quarentena, HomeOffice  1245814164020506624   \n",
       "26                                                NaN  1245814120701669382   \n",
       "27                                         HomeOffice  1245814111310622721   \n",
       "28                                                NaN  1245814103676989450   \n",
       "29                                        FiqueEmCasa  1245814082579636224   \n",
       "30                                                NaN  1245814044189175814   \n",
       "31                                                NaN  1245814036769452036   \n",
       "32  tbt, quarentena, pequenasnotaveis, rose, rosa,...  1245814006058758149   \n",
       "33                               NovaYork, isolamento  1245813939780358144   \n",
       "34                                        FiqueEmCasa  1245813931811241984   \n",
       "35                                                NaN  1245813930892636179   \n",
       "36                       PensandoEmTodos, FiqueEmCasa  1245813910407708672   \n",
       "37                                                NaN  1245813908935491584   \n",
       "38                                                NaN  1245813904820879360   \n",
       "39                             ficaemcasa, quarentena  1245813890568650753   \n",
       "40  gurideuruguaiana, jairkobe, riograndedosul, hu...  1245813878585470981   \n",
       "41                                         quarentena  1245813870385651713   \n",
       "42                                                NaN  1245813869026689025   \n",
       "43                                                NaN  1245813848822743040   \n",
       "44                                                NaN  1245813843768508417   \n",
       "45                                                NaN  1245813834838876160   \n",
       "46  QuintaLiberdadeNoSDV, Quintadetremutasdv, LaCa...  1245813817617068036   \n",
       "47                                                NaN  1245813793453637633   \n",
       "48                                                NaN  1245813782691094528   \n",
       "49  frases, amor, love, love, quarentena, words, c...  1245813764861112325   \n",
       "\n",
       "                             place  \\\n",
       "0           Falha na localização 🚫   \n",
       "1                         Portugal   \n",
       "2                              NaN   \n",
       "3                  Maceió, Alagoas   \n",
       "4                              NaN   \n",
       "5                              NaN   \n",
       "6         se eu soubesse eu falava   \n",
       "7                              NaN   \n",
       "8                           Brasil   \n",
       "9                              NaN   \n",
       "10    Brasil, de Bananas e Bundas    \n",
       "11     Eroda -  Sacred Hearts Club   \n",
       "12                             NaN   \n",
       "13                             NaN   \n",
       "14                Imbituba, Brasil   \n",
       "15                        Hogwarts   \n",
       "16    Brasil, de Bananas e Bundas    \n",
       "17                             NaN   \n",
       "18               São Paulo, Brasil   \n",
       "19                             NaN   \n",
       "20                    Pará, Brasil   \n",
       "21                             NaN   \n",
       "22                          Brasil   \n",
       "23               Sirinhaém, Brasil   \n",
       "24                             NaN   \n",
       "25               Carrão, São Paulo   \n",
       "26                             NaN   \n",
       "27              Uruguaiana, Brasil   \n",
       "28            Porto Alegre, Brasil   \n",
       "29                          Brasil   \n",
       "30          Santa Catarina, Brasil   \n",
       "31                             NaN   \n",
       "32                    Petrolina-PE   \n",
       "33                             NaN   \n",
       "34               Fortaleza, Brasil   \n",
       "35                          Brasil   \n",
       "36                             NaN   \n",
       "37          na róça em botucatu/sp   \n",
       "38                             NaN   \n",
       "39                  RJ • BSB • SLZ   \n",
       "40  Berço da revolução Farroupilha   \n",
       "41            Condado - Faria Lima   \n",
       "42                             NaN   \n",
       "43                          Brasil   \n",
       "44                             NaN   \n",
       "45             EDUÇÃO FÍSICA 📔✏      \n",
       "46                          Brasil   \n",
       "47                             NaN   \n",
       "48                             027   \n",
       "49                          Brazil   \n",
       "\n",
       "                                                 text  has_place  \n",
       "0   Eu tirei: Anti-social🙂! E você? https://t.co/s...      False  \n",
       "1   Bute ver um filme? #animalhouse #quarentena #m...      False  \n",
       "2   Hoje voltei a meditar... Tá foda. #isolamentos...      False  \n",
       "3   A minha #quarentena está resumida nesse vídeo....       True  \n",
       "4   RT @Vamosrirsualou1: Eu estou iguaizinho kkk\\n...      False  \n",
       "5   RT @jorgeemateus: Vamos de spoiler? Essas já e...      False  \n",
       "6   Eh O prisioneiro saiu pra pegar um banho de so...      False  \n",
       "7   RT @Francischini_: Previsão da OMS se confirmo...      False  \n",
       "8   Ver a situação do Equador neste momento acabou...       True  \n",
       "9   RT @JL2edicao: Corpo de homem que foi desenter...      False  \n",
       "10  RT @BlogDoTato67: #COVID19Pandemic \\n\\nNúmeros...       True  \n",
       "11  RT @DivaDepressao: Vcs acharam q a gente não i...      False  \n",
       "12  RT @jnascim: 🇧🇷 No cemitério da Vila Formosa, ...      False  \n",
       "13  RT @Corinthians: Não afrouxe as medidas preven...      False  \n",
       "14  A vida é igual matemática, se tá fácil então t...       True  \n",
       "15  RT @YaraKings: Amados, vocês que estão fazendo...      False  \n",
       "16  #COVID19Pandemic \\n\\nNúmeros atualizados do @m...       True  \n",
       "17  RT @softpowers_: O Ceará saltou de 9 mortes on...      False  \n",
       "18  RT @delucca: Moisés Borowicz, 93 anos, sobrevi...       True  \n",
       "19  RT @jorgeemateus: Vamos de spoiler? Essas já e...      False  \n",
       "20    Pelo visto só eu tô de quarentena!\\n#quarentena       True  \n",
       "21  Como trabalhamos mudou, você está pronto mesmo...      False  \n",
       "22  E você, o que tem feito nesses dias de isolame...       True  \n",
       "23  RT @ednandof: Se você assistir 2x ao dia o Jor...       True  \n",
       "24  RT @_Goalpoint: 📅 JÁ HÁ PLANO PARA A LIGA NOS\\...      False  \n",
       "25  Tá ligado ??? \\nNão!?\\nEntão se conecta!\\n#qua...       True  \n",
       "26  RT @cbmerjoficial: Nossa missão é salvar vidas...      False  \n",
       "27  Quem quiser algumas dicas básicas, clica no ví...       True  \n",
       "28  RT @lariir1909: Quarentena e as idéias surgira...       True  \n",
       "29  Carlos e Alexa criaram uma conta no Tik Tok e ...       True  \n",
       "30  RT @delucca: Moisés Borowicz, 93 anos, sobrevi...       True  \n",
       "31  RT @indiedadepre: Outra coisa importante: Não ...      False  \n",
       "32  Em dia de #tbt, um registro de um dos últimos ...       True  \n",
       "33  RT @ReutersLatam: #NovaYork vira cidade fantas...      False  \n",
       "34  RT @softpowers_: O Ceará saltou de 9 mortes on...       True  \n",
       "35  RT @Corinthians: Não afrouxe as medidas preven...       True  \n",
       "36  Massa, estamos passando por um momento difícil...      False  \n",
       "37  RT @jnascim: 🇧🇷 No cemitério da Vila Formosa, ...       True  \n",
       "38  RT @jorgeemateus: Vamos de spoiler? Essas já e...      False  \n",
       "39  [vai aqui tmb]\\n\\nquarentena né, minha filha\\n...      False  \n",
       "40  RT @jairkobe: E por aí chê! Como estão?\\n\\n#gu...      False  \n",
       "41  Mais um pôr do sol durante a #quarentena, espe...       True  \n",
       "42  RT @recifeordinario: E aí, já tá com saudade d...      False  \n",
       "43  RT @SCCPFutFeminino: O futebol feminino do Cor...       True  \n",
       "44  RT @indiedadepre: Outra coisa importante: Não ...      False  \n",
       "45  RT @jorgeemateus: Vamos de spoiler? Essas já e...      False  \n",
       "46  https://t.co/mjRMmw9OeU galera, temos um grupo...       True  \n",
       "47  RT @delucca: Moisés Borowicz, 93 anos, sobrevi...      False  \n",
       "48  RT @thegeekguia: Feel Good vai além do comum p...      False  \n",
       "49  RT @versosdojm: Concordam ? 💛🌹\\n.\\n. @versosdo...       True  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_data.head(50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "---------------------------------------------------------\n",
      "\n",
      "Total de tweets com 'place' do Brasil: 284760\n"
     ]
    }
   ],
   "source": [
    "# DataFrame with all the valid places:\n",
    "mask = new_data['has_place'] == True\n",
    "data_valid_places = new_data[mask]\n",
    "\n",
    "# List with all valid places:\n",
    "places_list = data_valid_places['place'].to_list()\n",
    "\n",
    "# csvFile_places = str(input(\">>> Enter name for the output csv file for the number of tweets per state (ex.: tweets-per-state.csv): \"))\n",
    "csvFile_places = 'tts-por-estado.csv'\n",
    "separar_estados(places_list, csvFile_places)\n",
    "\n",
    "count = pd.read_csv(csvFile_places) # tts-por-estado.csv\n",
    "number_of_tts = count['tts_count'].sum()\n",
    "\n",
    "print(\"Total de tweets com 'place' do Brasil: {}\".format(number_of_tts))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "300470"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_valid_places.shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Análise de RTs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total de RTs : 363424\n",
      "Isso equivale a 59.12% do número total de tweets.\n",
      "---------------------------------------------------------\n",
      ">>> New column 'is_rt' has been concatenated\n"
     ]
    }
   ],
   "source": [
    "tweets = new_data['text'].tolist()\n",
    "tweets = [str(x) for x in tweets]\n",
    "\n",
    "tweets_RT = sum(1 for x in tweets if x.count('RT @'))\n",
    "\n",
    "print(\"Total de RTs : {}\".format(tweets_RT))\n",
    "print(\"Isso equivale a {:.2f}% do número total de tweets.\".format(tweets_RT*100/len(tweets)))\n",
    "print('---------------------------------------------------------')\n",
    "\n",
    "\n",
    "is_rt = []\n",
    "rt_pattern = 'RT @'\n",
    "original_tts = new_data['text'].tolist()\n",
    "for idx, item in enumerate(original_tts):\n",
    "    string = str(item)\n",
    "    if string.find(rt_pattern) == 0:\n",
    "        is_rt.append(True)\n",
    "    else:\n",
    "        is_rt.append(False)\n",
    "\n",
    "is_rt = pd.DataFrame(is_rt, columns=['is_rt'])\n",
    "new_data_rt = pd.concat([new_data, is_rt], axis=1)\n",
    "print(\">>> New column 'is_rt' has been concatenated\")\n",
    "try:\n",
    "    if new_data_rt['Unnamed: 0'].any():\n",
    "        print('---------------------------------------------------------')\n",
    "        print(\">>> Droping column 'Unnamed: 0'\")\n",
    "        new_data_rt.drop(columns=['Unnamed: 0'], inplace=True)\n",
    "except KeyError:\n",
    "    pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ">>> New file 'quarentenaBR_new.csv' has been created.\n"
     ]
    }
   ],
   "source": [
    "fileName = str(csvFile[:-4]+'_new.csv')\n",
    "new_data_rt.to_csv(fileName)\n",
    "print(\">>> New file '{}' has been created.\".format(fileName))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(614756, 8)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_data_rt.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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>geo</th>\n",
       "      <th>hashtags</th>\n",
       "      <th>id</th>\n",
       "      <th>place</th>\n",
       "      <th>text</th>\n",
       "      <th>has_place</th>\n",
       "      <th>is_rt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Thu Apr 02 20:45:17 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>quarentena, personalidade, engracado</td>\n",
       "      <td>1245814582364516355</td>\n",
       "      <td>Falha na localização 🚫</td>\n",
       "      <td>Eu tirei: Anti-social🙂! E você? https://t.co/s...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Thu Apr 02 20:45:14 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>animalhouse, quarentena, movietime</td>\n",
       "      <td>1245814571559989258</td>\n",
       "      <td>Portugal</td>\n",
       "      <td>Bute ver um filme? #animalhouse #quarentena #m...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Thu Apr 02 20:45:12 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>isolamentosocial</td>\n",
       "      <td>1245814563741798401</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Hoje voltei a meditar... Tá foda. #isolamentos...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Thu Apr 02 20:45:12 +0000 2020</td>\n",
       "      <td>[[-35.815834, -9.711808], [-35.558391, -9.7118...</td>\n",
       "      <td>quarentena, TikTok</td>\n",
       "      <td>1245814560851931136</td>\n",
       "      <td>Maceió, Alagoas</td>\n",
       "      <td>A minha #quarentena está resumida nesse vídeo....</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Thu Apr 02 20:45:09 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>humor, comedia, quarentena</td>\n",
       "      <td>1245814550630486017</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @Vamosrirsualou1: Eu estou iguaizinho kkk\\n...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Thu Apr 02 20:45:09 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245814549346955271</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @jorgeemateus: Vamos de spoiler? Essas já e...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Thu Apr 02 20:45:07 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sunshine, raiodesol, vsco, vscofilters, Quaren...</td>\n",
       "      <td>1245814540127940608</td>\n",
       "      <td>se eu soubesse eu falava</td>\n",
       "      <td>Eh O prisioneiro saiu pra pegar um banho de so...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Thu Apr 02 20:45:07 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>coronavirusnomundo, quarentena, covid19</td>\n",
       "      <td>1245814539842715648</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @Francischini_: Previsão da OMS se confirmo...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Thu Apr 02 20:45:06 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>EcuadorEnEmergencia, COVID19Pandemic, quarente...</td>\n",
       "      <td>1245814536235560961</td>\n",
       "      <td>Brasil</td>\n",
       "      <td>Ver a situação do Equador neste momento acabou...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Thu Apr 02 20:44:50 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245814472146595842</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @JL2edicao: Corpo de homem que foi desenter...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Thu Apr 02 20:44:48 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>COVID19Pandemic</td>\n",
       "      <td>1245814463145574401</td>\n",
       "      <td>Brasil, de Bananas e Bundas</td>\n",
       "      <td>RT @BlogDoTato67: #COVID19Pandemic \\n\\nNúmeros...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Thu Apr 02 20:44:47 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RAVEDADIVA</td>\n",
       "      <td>1245814457525309440</td>\n",
       "      <td>Eroda -  Sacred Hearts Club</td>\n",
       "      <td>RT @DivaDepressao: Vcs acharam q a gente não i...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Thu Apr 02 20:44:41 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245814432611041280</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @jnascim: 🇧🇷 No cemitério da Vila Formosa, ...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Thu Apr 02 20:44:41 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245814430711066626</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @Corinthians: Não afrouxe as medidas preven...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Thu Apr 02 20:44:21 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FiqueEmCasa</td>\n",
       "      <td>1245814346829234176</td>\n",
       "      <td>Imbituba, Brasil</td>\n",
       "      <td>A vida é igual matemática, se tá fácil então t...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Thu Apr 02 20:44:17 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245814330676961282</td>\n",
       "      <td>Hogwarts</td>\n",
       "      <td>RT @YaraKings: Amados, vocês que estão fazendo...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Thu Apr 02 20:44:16 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>COVID19Pandemic, FiqueEmCasa</td>\n",
       "      <td>1245814328940531712</td>\n",
       "      <td>Brasil, de Bananas e Bundas</td>\n",
       "      <td>#COVID19Pandemic \\n\\nNúmeros atualizados do @m...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Thu Apr 02 20:44:03 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FiqueEmCasa</td>\n",
       "      <td>1245814274951393283</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @softpowers_: O Ceará saltou de 9 mortes on...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Thu Apr 02 20:44:02 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245814270350241794</td>\n",
       "      <td>São Paulo, Brasil</td>\n",
       "      <td>RT @delucca: Moisés Borowicz, 93 anos, sobrevi...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Thu Apr 02 20:44:01 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245814265124196352</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @jorgeemateus: Vamos de spoiler? Essas já e...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Thu Apr 02 20:43:54 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>quarentena</td>\n",
       "      <td>1245814235072008195</td>\n",
       "      <td>Pará, Brasil</td>\n",
       "      <td>Pelo visto só eu tô de quarentena!\\n#quarentena</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Thu Apr 02 20:43:52 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>homeoffice, indeotecnologia, tech, covid19, co...</td>\n",
       "      <td>1245814226817560579</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Como trabalhamos mudou, você está pronto mesmo...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Thu Apr 02 20:43:51 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>covıd19, ficaemcasa, pandemia, quarentena, Dis...</td>\n",
       "      <td>1245814223160193025</td>\n",
       "      <td>Brasil</td>\n",
       "      <td>E você, o que tem feito nesses dias de isolame...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Thu Apr 02 20:43:50 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FiqueEmCasa, MudadeCanal, CuidadaSaúdeMental</td>\n",
       "      <td>1245814216780582914</td>\n",
       "      <td>Sirinhaém, Brasil</td>\n",
       "      <td>RT @ednandof: Se você assistir 2x ao dia o Jor...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Thu Apr 02 20:43:47 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245814206093500416</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @_Goalpoint: 📅 JÁ HÁ PLANO PARA A LIGA NOS\\...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Thu Apr 02 20:43:37 +0000 2020</td>\n",
       "      <td>[[-46.826039, -24.008814], [-46.365052, -24.00...</td>\n",
       "      <td>quarentena, HomeOffice</td>\n",
       "      <td>1245814164020506624</td>\n",
       "      <td>Carrão, São Paulo</td>\n",
       "      <td>Tá ligado ??? \\nNão!?\\nEntão se conecta!\\n#qua...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Thu Apr 02 20:43:27 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245814120701669382</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @cbmerjoficial: Nossa missão é salvar vidas...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Thu Apr 02 20:43:24 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>HomeOffice</td>\n",
       "      <td>1245814111310622721</td>\n",
       "      <td>Uruguaiana, Brasil</td>\n",
       "      <td>Quem quiser algumas dicas básicas, clica no ví...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Thu Apr 02 20:43:23 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245814103676989450</td>\n",
       "      <td>Porto Alegre, Brasil</td>\n",
       "      <td>RT @lariir1909: Quarentena e as idéias surgira...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Thu Apr 02 20:43:18 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FiqueEmCasa</td>\n",
       "      <td>1245814082579636224</td>\n",
       "      <td>Brasil</td>\n",
       "      <td>Carlos e Alexa criaram uma conta no Tik Tok e ...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Thu Apr 02 20:43:08 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245814044189175814</td>\n",
       "      <td>Santa Catarina, Brasil</td>\n",
       "      <td>RT @delucca: Moisés Borowicz, 93 anos, sobrevi...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Thu Apr 02 20:43:07 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245814036769452036</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @indiedadepre: Outra coisa importante: Não ...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Thu Apr 02 20:42:59 +0000 2020</td>\n",
       "      <td>[[-40.969461, -9.482947], [-40.208561, -9.4829...</td>\n",
       "      <td>tbt, quarentena, pequenasnotaveis, rose, rosa,...</td>\n",
       "      <td>1245814006058758149</td>\n",
       "      <td>Petrolina-PE</td>\n",
       "      <td>Em dia de #tbt, um registro de um dos últimos ...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Thu Apr 02 20:42:44 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NovaYork, isolamento</td>\n",
       "      <td>1245813939780358144</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @ReutersLatam: #NovaYork vira cidade fantas...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Thu Apr 02 20:42:42 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FiqueEmCasa</td>\n",
       "      <td>1245813931811241984</td>\n",
       "      <td>Fortaleza, Brasil</td>\n",
       "      <td>RT @softpowers_: O Ceará saltou de 9 mortes on...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Thu Apr 02 20:42:41 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245813930892636179</td>\n",
       "      <td>Brasil</td>\n",
       "      <td>RT @Corinthians: Não afrouxe as medidas preven...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Thu Apr 02 20:42:37 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PensandoEmTodos, FiqueEmCasa</td>\n",
       "      <td>1245813910407708672</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Massa, estamos passando por um momento difícil...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Thu Apr 02 20:42:36 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245813908935491584</td>\n",
       "      <td>na róça em botucatu/sp</td>\n",
       "      <td>RT @jnascim: 🇧🇷 No cemitério da Vila Formosa, ...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Thu Apr 02 20:42:35 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245813904820879360</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @jorgeemateus: Vamos de spoiler? Essas já e...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>Thu Apr 02 20:42:32 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ficaemcasa, quarentena</td>\n",
       "      <td>1245813890568650753</td>\n",
       "      <td>RJ • BSB • SLZ</td>\n",
       "      <td>[vai aqui tmb]\\n\\nquarentena né, minha filha\\n...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Thu Apr 02 20:42:29 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>gurideuruguaiana, jairkobe, riograndedosul, hu...</td>\n",
       "      <td>1245813878585470981</td>\n",
       "      <td>Berço da revolução Farroupilha</td>\n",
       "      <td>RT @jairkobe: E por aí chê! Como estão?\\n\\n#gu...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Thu Apr 02 20:42:27 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>quarentena</td>\n",
       "      <td>1245813870385651713</td>\n",
       "      <td>Condado - Faria Lima</td>\n",
       "      <td>Mais um pôr do sol durante a #quarentena, espe...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Thu Apr 02 20:42:27 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245813869026689025</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @recifeordinario: E aí, já tá com saudade d...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Thu Apr 02 20:42:22 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245813848822743040</td>\n",
       "      <td>Brasil</td>\n",
       "      <td>RT @SCCPFutFeminino: O futebol feminino do Cor...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Thu Apr 02 20:42:21 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245813843768508417</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @indiedadepre: Outra coisa importante: Não ...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Thu Apr 02 20:42:18 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245813834838876160</td>\n",
       "      <td>EDUÇÃO FÍSICA 📔✏</td>\n",
       "      <td>RT @jorgeemateus: Vamos de spoiler? Essas já e...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Thu Apr 02 20:42:14 +0000 2020</td>\n",
       "      <td>[[-49.3916434, -25.6447517], [-49.1852775, -25...</td>\n",
       "      <td>QuintaLiberdadeNoSDV, Quintadetremutasdv, LaCa...</td>\n",
       "      <td>1245813817617068036</td>\n",
       "      <td>Brasil</td>\n",
       "      <td>https://t.co/mjRMmw9OeU galera, temos um grupo...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>Thu Apr 02 20:42:09 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245813793453637633</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @delucca: Moisés Borowicz, 93 anos, sobrevi...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>Thu Apr 02 20:42:06 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1245813782691094528</td>\n",
       "      <td>027</td>\n",
       "      <td>RT @thegeekguia: Feel Good vai além do comum p...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>Thu Apr 02 20:42:02 +0000 2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>frases, amor, love, love, quarentena, words, c...</td>\n",
       "      <td>1245813764861112325</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>RT @versosdojm: Concordam ? 💛🌹\\n.\\n. @versosdo...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              date  \\\n",
       "0   Thu Apr 02 20:45:17 +0000 2020   \n",
       "1   Thu Apr 02 20:45:14 +0000 2020   \n",
       "2   Thu Apr 02 20:45:12 +0000 2020   \n",
       "3   Thu Apr 02 20:45:12 +0000 2020   \n",
       "4   Thu Apr 02 20:45:09 +0000 2020   \n",
       "5   Thu Apr 02 20:45:09 +0000 2020   \n",
       "6   Thu Apr 02 20:45:07 +0000 2020   \n",
       "7   Thu Apr 02 20:45:07 +0000 2020   \n",
       "8   Thu Apr 02 20:45:06 +0000 2020   \n",
       "9   Thu Apr 02 20:44:50 +0000 2020   \n",
       "10  Thu Apr 02 20:44:48 +0000 2020   \n",
       "11  Thu Apr 02 20:44:47 +0000 2020   \n",
       "12  Thu Apr 02 20:44:41 +0000 2020   \n",
       "13  Thu Apr 02 20:44:41 +0000 2020   \n",
       "14  Thu Apr 02 20:44:21 +0000 2020   \n",
       "15  Thu Apr 02 20:44:17 +0000 2020   \n",
       "16  Thu Apr 02 20:44:16 +0000 2020   \n",
       "17  Thu Apr 02 20:44:03 +0000 2020   \n",
       "18  Thu Apr 02 20:44:02 +0000 2020   \n",
       "19  Thu Apr 02 20:44:01 +0000 2020   \n",
       "20  Thu Apr 02 20:43:54 +0000 2020   \n",
       "21  Thu Apr 02 20:43:52 +0000 2020   \n",
       "22  Thu Apr 02 20:43:51 +0000 2020   \n",
       "23  Thu Apr 02 20:43:50 +0000 2020   \n",
       "24  Thu Apr 02 20:43:47 +0000 2020   \n",
       "25  Thu Apr 02 20:43:37 +0000 2020   \n",
       "26  Thu Apr 02 20:43:27 +0000 2020   \n",
       "27  Thu Apr 02 20:43:24 +0000 2020   \n",
       "28  Thu Apr 02 20:43:23 +0000 2020   \n",
       "29  Thu Apr 02 20:43:18 +0000 2020   \n",
       "30  Thu Apr 02 20:43:08 +0000 2020   \n",
       "31  Thu Apr 02 20:43:07 +0000 2020   \n",
       "32  Thu Apr 02 20:42:59 +0000 2020   \n",
       "33  Thu Apr 02 20:42:44 +0000 2020   \n",
       "34  Thu Apr 02 20:42:42 +0000 2020   \n",
       "35  Thu Apr 02 20:42:41 +0000 2020   \n",
       "36  Thu Apr 02 20:42:37 +0000 2020   \n",
       "37  Thu Apr 02 20:42:36 +0000 2020   \n",
       "38  Thu Apr 02 20:42:35 +0000 2020   \n",
       "39  Thu Apr 02 20:42:32 +0000 2020   \n",
       "40  Thu Apr 02 20:42:29 +0000 2020   \n",
       "41  Thu Apr 02 20:42:27 +0000 2020   \n",
       "42  Thu Apr 02 20:42:27 +0000 2020   \n",
       "43  Thu Apr 02 20:42:22 +0000 2020   \n",
       "44  Thu Apr 02 20:42:21 +0000 2020   \n",
       "45  Thu Apr 02 20:42:18 +0000 2020   \n",
       "46  Thu Apr 02 20:42:14 +0000 2020   \n",
       "47  Thu Apr 02 20:42:09 +0000 2020   \n",
       "48  Thu Apr 02 20:42:06 +0000 2020   \n",
       "49  Thu Apr 02 20:42:02 +0000 2020   \n",
       "\n",
       "                                                  geo  \\\n",
       "0                                                 NaN   \n",
       "1                                                 NaN   \n",
       "2                                                 NaN   \n",
       "3   [[-35.815834, -9.711808], [-35.558391, -9.7118...   \n",
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       "25  [[-46.826039, -24.008814], [-46.365052, -24.00...   \n",
       "26                                                NaN   \n",
       "27                                                NaN   \n",
       "28                                                NaN   \n",
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       "31                                                NaN   \n",
       "32  [[-40.969461, -9.482947], [-40.208561, -9.4829...   \n",
       "33                                                NaN   \n",
       "34                                                NaN   \n",
       "35                                                NaN   \n",
       "36                                                NaN   \n",
       "37                                                NaN   \n",
       "38                                                NaN   \n",
       "39                                                NaN   \n",
       "40                                                NaN   \n",
       "41                                                NaN   \n",
       "42                                                NaN   \n",
       "43                                                NaN   \n",
       "44                                                NaN   \n",
       "45                                                NaN   \n",
       "46  [[-49.3916434, -25.6447517], [-49.1852775, -25...   \n",
       "47                                                NaN   \n",
       "48                                                NaN   \n",
       "49                                                NaN   \n",
       "\n",
       "                                             hashtags                   id  \\\n",
       "0                quarentena, personalidade, engracado  1245814582364516355   \n",
       "1                  animalhouse, quarentena, movietime  1245814571559989258   \n",
       "2                                    isolamentosocial  1245814563741798401   \n",
       "3                                  quarentena, TikTok  1245814560851931136   \n",
       "4                          humor, comedia, quarentena  1245814550630486017   \n",
       "5                                                 NaN  1245814549346955271   \n",
       "6   sunshine, raiodesol, vsco, vscofilters, Quaren...  1245814540127940608   \n",
       "7             coronavirusnomundo, quarentena, covid19  1245814539842715648   \n",
       "8   EcuadorEnEmergencia, COVID19Pandemic, quarente...  1245814536235560961   \n",
       "9                                                 NaN  1245814472146595842   \n",
       "10                                    COVID19Pandemic  1245814463145574401   \n",
       "11                                         RAVEDADIVA  1245814457525309440   \n",
       "12                                                NaN  1245814432611041280   \n",
       "13                                                NaN  1245814430711066626   \n",
       "14                                        FiqueEmCasa  1245814346829234176   \n",
       "15                                                NaN  1245814330676961282   \n",
       "16                       COVID19Pandemic, FiqueEmCasa  1245814328940531712   \n",
       "17                                        FiqueEmCasa  1245814274951393283   \n",
       "18                                                NaN  1245814270350241794   \n",
       "19                                                NaN  1245814265124196352   \n",
       "20                                         quarentena  1245814235072008195   \n",
       "21  homeoffice, indeotecnologia, tech, covid19, co...  1245814226817560579   \n",
       "22  covıd19, ficaemcasa, pandemia, quarentena, Dis...  1245814223160193025   \n",
       "23       FiqueEmCasa, MudadeCanal, CuidadaSaúdeMental  1245814216780582914   \n",
       "24                                                NaN  1245814206093500416   \n",
       "25                             quarentena, HomeOffice  1245814164020506624   \n",
       "26                                                NaN  1245814120701669382   \n",
       "27                                         HomeOffice  1245814111310622721   \n",
       "28                                                NaN  1245814103676989450   \n",
       "29                                        FiqueEmCasa  1245814082579636224   \n",
       "30                                                NaN  1245814044189175814   \n",
       "31                                                NaN  1245814036769452036   \n",
       "32  tbt, quarentena, pequenasnotaveis, rose, rosa,...  1245814006058758149   \n",
       "33                               NovaYork, isolamento  1245813939780358144   \n",
       "34                                        FiqueEmCasa  1245813931811241984   \n",
       "35                                                NaN  1245813930892636179   \n",
       "36                       PensandoEmTodos, FiqueEmCasa  1245813910407708672   \n",
       "37                                                NaN  1245813908935491584   \n",
       "38                                                NaN  1245813904820879360   \n",
       "39                             ficaemcasa, quarentena  1245813890568650753   \n",
       "40  gurideuruguaiana, jairkobe, riograndedosul, hu...  1245813878585470981   \n",
       "41                                         quarentena  1245813870385651713   \n",
       "42                                                NaN  1245813869026689025   \n",
       "43                                                NaN  1245813848822743040   \n",
       "44                                                NaN  1245813843768508417   \n",
       "45                                                NaN  1245813834838876160   \n",
       "46  QuintaLiberdadeNoSDV, Quintadetremutasdv, LaCa...  1245813817617068036   \n",
       "47                                                NaN  1245813793453637633   \n",
       "48                                                NaN  1245813782691094528   \n",
       "49  frases, amor, love, love, quarentena, words, c...  1245813764861112325   \n",
       "\n",
       "                             place  \\\n",
       "0           Falha na localização 🚫   \n",
       "1                         Portugal   \n",
       "2                              NaN   \n",
       "3                  Maceió, Alagoas   \n",
       "4                              NaN   \n",
       "5                              NaN   \n",
       "6         se eu soubesse eu falava   \n",
       "7                              NaN   \n",
       "8                           Brasil   \n",
       "9                              NaN   \n",
       "10    Brasil, de Bananas e Bundas    \n",
       "11     Eroda -  Sacred Hearts Club   \n",
       "12                             NaN   \n",
       "13                             NaN   \n",
       "14                Imbituba, Brasil   \n",
       "15                        Hogwarts   \n",
       "16    Brasil, de Bananas e Bundas    \n",
       "17                             NaN   \n",
       "18               São Paulo, Brasil   \n",
       "19                             NaN   \n",
       "20                    Pará, Brasil   \n",
       "21                             NaN   \n",
       "22                          Brasil   \n",
       "23               Sirinhaém, Brasil   \n",
       "24                             NaN   \n",
       "25               Carrão, São Paulo   \n",
       "26                             NaN   \n",
       "27              Uruguaiana, Brasil   \n",
       "28            Porto Alegre, Brasil   \n",
       "29                          Brasil   \n",
       "30          Santa Catarina, Brasil   \n",
       "31                             NaN   \n",
       "32                    Petrolina-PE   \n",
       "33                             NaN   \n",
       "34               Fortaleza, Brasil   \n",
       "35                          Brasil   \n",
       "36                             NaN   \n",
       "37          na róça em botucatu/sp   \n",
       "38                             NaN   \n",
       "39                  RJ • BSB • SLZ   \n",
       "40  Berço da revolução Farroupilha   \n",
       "41            Condado - Faria Lima   \n",
       "42                             NaN   \n",
       "43                          Brasil   \n",
       "44                             NaN   \n",
       "45             EDUÇÃO FÍSICA 📔✏      \n",
       "46                          Brasil   \n",
       "47                             NaN   \n",
       "48                             027   \n",
       "49                          Brazil   \n",
       "\n",
       "                                                 text  has_place  is_rt  \n",
       "0   Eu tirei: Anti-social🙂! E você? https://t.co/s...      False  False  \n",
       "1   Bute ver um filme? #animalhouse #quarentena #m...      False  False  \n",
       "2   Hoje voltei a meditar... Tá foda. #isolamentos...      False  False  \n",
       "3   A minha #quarentena está resumida nesse vídeo....       True  False  \n",
       "4   RT @Vamosrirsualou1: Eu estou iguaizinho kkk\\n...      False   True  \n",
       "5   RT @jorgeemateus: Vamos de spoiler? Essas já e...      False   True  \n",
       "6   Eh O prisioneiro saiu pra pegar um banho de so...      False  False  \n",
       "7   RT @Francischini_: Previsão da OMS se confirmo...      False   True  \n",
       "8   Ver a situação do Equador neste momento acabou...       True  False  \n",
       "9   RT @JL2edicao: Corpo de homem que foi desenter...      False   True  \n",
       "10  RT @BlogDoTato67: #COVID19Pandemic \\n\\nNúmeros...       True   True  \n",
       "11  RT @DivaDepressao: Vcs acharam q a gente não i...      False   True  \n",
       "12  RT @jnascim: 🇧🇷 No cemitério da Vila Formosa, ...      False   True  \n",
       "13  RT @Corinthians: Não afrouxe as medidas preven...      False   True  \n",
       "14  A vida é igual matemática, se tá fácil então t...       True  False  \n",
       "15  RT @YaraKings: Amados, vocês que estão fazendo...      False   True  \n",
       "16  #COVID19Pandemic \\n\\nNúmeros atualizados do @m...       True  False  \n",
       "17  RT @softpowers_: O Ceará saltou de 9 mortes on...      False   True  \n",
       "18  RT @delucca: Moisés Borowicz, 93 anos, sobrevi...       True   True  \n",
       "19  RT @jorgeemateus: Vamos de spoiler? Essas já e...      False   True  \n",
       "20    Pelo visto só eu tô de quarentena!\\n#quarentena       True  False  \n",
       "21  Como trabalhamos mudou, você está pronto mesmo...      False  False  \n",
       "22  E você, o que tem feito nesses dias de isolame...       True  False  \n",
       "23  RT @ednandof: Se você assistir 2x ao dia o Jor...       True   True  \n",
       "24  RT @_Goalpoint: 📅 JÁ HÁ PLANO PARA A LIGA NOS\\...      False   True  \n",
       "25  Tá ligado ??? \\nNão!?\\nEntão se conecta!\\n#qua...       True  False  \n",
       "26  RT @cbmerjoficial: Nossa missão é salvar vidas...      False   True  \n",
       "27  Quem quiser algumas dicas básicas, clica no ví...       True  False  \n",
       "28  RT @lariir1909: Quarentena e as idéias surgira...       True   True  \n",
       "29  Carlos e Alexa criaram uma conta no Tik Tok e ...       True  False  \n",
       "30  RT @delucca: Moisés Borowicz, 93 anos, sobrevi...       True   True  \n",
       "31  RT @indiedadepre: Outra coisa importante: Não ...      False   True  \n",
       "32  Em dia de #tbt, um registro de um dos últimos ...       True  False  \n",
       "33  RT @ReutersLatam: #NovaYork vira cidade fantas...      False   True  \n",
       "34  RT @softpowers_: O Ceará saltou de 9 mortes on...       True   True  \n",
       "35  RT @Corinthians: Não afrouxe as medidas preven...       True   True  \n",
       "36  Massa, estamos passando por um momento difícil...      False  False  \n",
       "37  RT @jnascim: 🇧🇷 No cemitério da Vila Formosa, ...       True   True  \n",
       "38  RT @jorgeemateus: Vamos de spoiler? Essas já e...      False   True  \n",
       "39  [vai aqui tmb]\\n\\nquarentena né, minha filha\\n...      False  False  \n",
       "40  RT @jairkobe: E por aí chê! Como estão?\\n\\n#gu...      False   True  \n",
       "41  Mais um pôr do sol durante a #quarentena, espe...       True  False  \n",
       "42  RT @recifeordinario: E aí, já tá com saudade d...      False   True  \n",
       "43  RT @SCCPFutFeminino: O futebol feminino do Cor...       True   True  \n",
       "44  RT @indiedadepre: Outra coisa importante: Não ...      False   True  \n",
       "45  RT @jorgeemateus: Vamos de spoiler? Essas já e...      False   True  \n",
       "46  https://t.co/mjRMmw9OeU galera, temos um grupo...       True  False  \n",
       "47  RT @delucca: Moisés Borowicz, 93 anos, sobrevi...      False   True  \n",
       "48  RT @thegeekguia: Feel Good vai além do comum p...      False   True  \n",
       "49  RT @versosdojm: Concordam ? 💛🌹\\n.\\n. @versosdo...       True   True  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_data_rt.head(50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Lista para nuvem de palavras"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ">>> Saving file 'nuvem_palavras.txt'...\n",
      ">>> Saving file 'words_count.csv'...\n"
     ]
    }
   ],
   "source": [
    "mask = new_data_rt['is_rt'] == False\n",
    "cloud_data = new_data_rt[mask]\n",
    "mask = cloud_data['has_place'] == True\n",
    "cloud_data = cloud_data[mask]\n",
    "\n",
    "clean_tuites = cloud_data['text'].to_list()\n",
    "clean_tuites = clean_tts(clean_tuites)\n",
    "\n",
    "word_list = []\n",
    "stop_words = ['e', 'de', 'a', 'as', 'da', 'das', 'o', 'os', 'aos', 'do', 'dos', 'que', 'em', 'com', 'para', 'n', 'no', 'na', 'um', 'se', 'pra', 'este', 'esta', 'pro', 'me', 'ao', 'ou', 'esse', 'essa', 'q', 'p', 'nas', 'pq', 'tao', 'entao', 'te', 'porque', '1', '2', '3', '4', '5', '7', '10', '...', '.', ',', '?', '!', '|', ':', '#', '@']\n",
    "print(\">>> Saving file 'nuvem_palavras.txt'...\")\n",
    "with open('nuvem_palavras.txt', 'w') as wf:\n",
    "    for phrase in clean_tuites:\n",
    "        for word in phrase.split():\n",
    "            if word not in stop_words:\n",
    "                if word[-1] == '.' or word[-1] == ',':\n",
    "                    word_list.append(str(word[:-1]))\n",
    "                else:\n",
    "                    word_list.append(str(word))\n",
    "                wf.write(word + ' ')\n",
    "\n",
    "words_count = Counter(word_list)\n",
    "df_words_count = pd.DataFrame(words_count.items(), columns=['word', 'count'])\n",
    "df_words_count = df_words_count.sort_values(by=['count'], ascending=False).reset_index(drop=True)\n",
    "print(\">>> Saving file 'words_count.csv'...\")\n",
    "df_words_count.to_csv('words_count.csv')"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "writer = pd.ExcelWriter('twitter_data.xlsx') \n",
    "twitter_data.to_excel(writer, 'DataFrame') \n",
    "writer.save()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting number of tweets per day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dates = new_data_rt['date'].to_list()\n",
    "\n",
    "clean_datas = []\n",
    "for idx, item in enumerate(dates):\n",
    "    string = str(item)\n",
    "    day = string[8:10]\n",
    "    month = string[4:7]\n",
    "    if month == 'Apr':\n",
    "        month = '04'\n",
    "        clean_datas.append('{}-{}'.format(day, month))\n",
    "    else:\n",
    "        month = '03'\n",
    "        clean_datas.append('{}-{}'.format(day, month))\n",
    "\n",
    "counts = Counter(clean_datas)\n",
    "df_num_tts = pd.DataFrame(counts.items(), columns=['date', 'num_tts'])\n",
    "df_num_tts.drop([0, 36], axis=0, inplace=True)\n",
    "df_num_tts = df_num_tts.sort_values(by=['date']).reset_index(drop=True)\n",
    "\n",
    "sns_plot = sns.lineplot(x=\"date\", y=\"num_tts\", data=df_num_tts)\n",
    "sns_plot.set(xticks=[4, 9, 14, 19, 24, 29, 34])\n",
    "sns_plot.set(xlabel=\"Data\", ylabel = \"Número de tweets\")\n",
    "fig = sns_plot.get_figure()\n",
    "fig.savefig(\"tweets_per_day.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "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>num_tts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-03</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>01-04</td>\n",
       "      <td>2666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>03-04</td>\n",
       "      <td>17999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>04-04</td>\n",
       "      <td>45797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>05-04</td>\n",
       "      <td>43100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>06-04</td>\n",
       "      <td>15862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>07-04</td>\n",
       "      <td>15304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>08-04</td>\n",
       "      <td>21821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>09-04</td>\n",
       "      <td>20111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10-04</td>\n",
       "      <td>11228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11-03</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11-04</td>\n",
       "      <td>4632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12-03</td>\n",
       "      <td>147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>12-04</td>\n",
       "      <td>23191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>13-03</td>\n",
       "      <td>334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>13-04</td>\n",
       "      <td>16875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>14-03</td>\n",
       "      <td>1933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>14-04</td>\n",
       "      <td>14870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>15-03</td>\n",
       "      <td>2337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>15-04</td>\n",
       "      <td>7244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>16-03</td>\n",
       "      <td>5310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>17-03</td>\n",
       "      <td>28828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>18-03</td>\n",
       "      <td>19731</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>19-03</td>\n",
       "      <td>22183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>20-03</td>\n",
       "      <td>9522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>22-03</td>\n",
       "      <td>13006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>23-03</td>\n",
       "      <td>31503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>24-03</td>\n",
       "      <td>24539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>25-03</td>\n",
       "      <td>45305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>26-03</td>\n",
       "      <td>21953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>27-03</td>\n",
       "      <td>36773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>28-03</td>\n",
       "      <td>30404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>29-03</td>\n",
       "      <td>24191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>30-03</td>\n",
       "      <td>7202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>re-03</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     date  num_tts\n",
       "0     -03        3\n",
       "1   01-04     2666\n",
       "2   03-04    17999\n",
       "3   04-04    45797\n",
       "4   05-04    43100\n",
       "5   06-04    15862\n",
       "6   07-04    15304\n",
       "7   08-04    21821\n",
       "8   09-04    20111\n",
       "9   10-04    11228\n",
       "10  11-03       30\n",
       "11  11-04     4632\n",
       "12  12-03      147\n",
       "13  12-04    23191\n",
       "14  13-03      334\n",
       "15  13-04    16875\n",
       "16  14-03     1933\n",
       "17  14-04    14870\n",
       "18  15-03     2337\n",
       "19  15-04     7244\n",
       "20  16-03     5310\n",
       "21  17-03    28828\n",
       "22  18-03    19731\n",
       "23  19-03    22183\n",
       "24  20-03     9522\n",
       "25  22-03    13006\n",
       "26  23-03    31503\n",
       "27  24-03    24539\n",
       "28  25-03    45305\n",
       "29  26-03    21953\n",
       "30  27-03    36773\n",
       "31  28-03    30404\n",
       "32  29-03    24191\n",
       "33  30-03     7202\n",
       "34  re-03        3"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_num_tts.head(50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "date = ['03-11', '03-12', '03-13', '03-14', '03-15', '03-16', '03-17', '03-18', '03-19', '03-20', '03-22', '03-23', '03-24', '03-25', '03-26', '03-27', '03-28', '03-29', '03-30', '04-01', '04-02', '04-03', '04-04', '04-05', '04-06', '04-07', '04-08', '04-09', '04-10', '04-11', '04-12', '04-13', '04-14', '04-15']\n",
    "num_tts = [30, 147, 334, 1933, 2337, 5310, 28828, 19731, 22183, 9522, 12798, 13006, 31503, 24539, 45305, 21953, 36773, 30404, 24191, 7202, 2666, 16021, 17999, 45797, 43100, 15862, 15304, 21821, 20111, 11228, 4632, 23191, 14870, 7244]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "34 34\n"
     ]
    }
   ],
   "source": [
    "print(len(date), len(num_tts))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "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>num_tts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>03-11</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>03-12</td>\n",
       "      <td>147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>03-13</td>\n",
       "      <td>334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>03-14</td>\n",
       "      <td>1933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>03-15</td>\n",
       "      <td>2337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>03-16</td>\n",
       "      <td>5310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>03-17</td>\n",
       "      <td>28828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>03-18</td>\n",
       "      <td>19731</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>03-19</td>\n",
       "      <td>22183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>03-20</td>\n",
       "      <td>9522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>03-22</td>\n",
       "      <td>12798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>03-23</td>\n",
       "      <td>13006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>03-24</td>\n",
       "      <td>31503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>03-25</td>\n",
       "      <td>24539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>03-26</td>\n",
       "      <td>45305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>03-27</td>\n",
       "      <td>21953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>03-28</td>\n",
       "      <td>36773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>03-29</td>\n",
       "      <td>30404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>03-30</td>\n",
       "      <td>24191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>04-01</td>\n",
       "      <td>7202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>04-02</td>\n",
       "      <td>2666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>04-03</td>\n",
       "      <td>16021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>04-04</td>\n",
       "      <td>17999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>04-05</td>\n",
       "      <td>45797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>04-06</td>\n",
       "      <td>43100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>04-07</td>\n",
       "      <td>15862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>04-08</td>\n",
       "      <td>15304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>04-09</td>\n",
       "      <td>21821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>04-10</td>\n",
       "      <td>20111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>04-11</td>\n",
       "      <td>11228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>04-12</td>\n",
       "      <td>4632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>04-13</td>\n",
       "      <td>23191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>04-14</td>\n",
       "      <td>14870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>04-15</td>\n",
       "      <td>7244</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     date num_tts\n",
       "0   03-11      30\n",
       "1   03-12     147\n",
       "2   03-13     334\n",
       "3   03-14    1933\n",
       "4   03-15    2337\n",
       "5   03-16    5310\n",
       "6   03-17   28828\n",
       "7   03-18   19731\n",
       "8   03-19   22183\n",
       "9   03-20    9522\n",
       "10  03-22   12798\n",
       "11  03-23   13006\n",
       "12  03-24   31503\n",
       "13  03-25   24539\n",
       "14  03-26   45305\n",
       "15  03-27   21953\n",
       "16  03-28   36773\n",
       "17  03-29   30404\n",
       "18  03-30   24191\n",
       "19  04-01    7202\n",
       "20  04-02    2666\n",
       "21  04-03   16021\n",
       "22  04-04   17999\n",
       "23  04-05   45797\n",
       "24  04-06   43100\n",
       "25  04-07   15862\n",
       "26  04-08   15304\n",
       "27  04-09   21821\n",
       "28  04-10   20111\n",
       "29  04-11   11228\n",
       "30  04-12    4632\n",
       "31  04-13   23191\n",
       "32  04-14   14870\n",
       "33  04-15    7244"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_num_tts = pd.DataFrame(columns=['date', 'num_tts'])\n",
    "for i, j in zip(date, num_tts):\n",
    "    row_to_app = [str(i), int(j)]\n",
    "    row = pd.DataFrame([row_to_app], columns=['date', 'num_tts'])\n",
    "    df_num_tts = df_num_tts.append(row, ignore_index=True)\n",
    "df_num_tts.head(50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns_plot = sns.lineplot(x=date, y=num_tts)\n",
    "sns_plot.set(xticks=[0, 5, 10, 15, 20, 25, 30, 35])\n",
    "sns_plot.set(xlabel=\"Data\", ylabel = \"Número de tweets\")\n",
    "fig = sns_plot.get_figure()\n",
    "fig.savefig(\"tweets_per_day.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Twittes com local e originais (não sao RTs)"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "twitter_data = new_data_rt\n",
    "twitter_data.head()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "is_rt = []\n",
    "rt_pattern = 'RT @'\n",
    "original_tts = twitter_data['text'].tolist()\n",
    "for idx, item in enumerate(original_tts):\n",
    "    string = str(item)\n",
    "    if string.find(rt_pattern) == 0:\n",
    "        is_rt.append(True)\n",
    "    else:\n",
    "        is_rt.append(False)\n",
    "\n",
    "print(is_rt[:10], len(is_rt))"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "is_rt = pd.DataFrame(is_rt, columns=['is_rt'])\n",
    "twitter_data = pd.concat([data, is_rt], axis=1)\n",
    "twitter_data.head()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "twitter_data.to_csv('quarentenaBR-all.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Rapidamente, vou verificar quais os 'ids' não estão corretos"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "len(twitter_data['id'].unique())"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "twitter_data.shape[0]"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "twitter_data['id'].count()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "ids = twitter_data['id'].to_list()\n",
    "ids = [str(i) for i in ids]\n",
    "not_ids = [i for i in ids if i[0] != '1']"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "twitter_data['id'].apply(lambda x: str(x))\n",
    "mask = twitter_data['id'].isin(not_ids)\n",
    "data = twitter_data[~mask]"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "ids = []\n",
    "duplicated_ids = []\n",
    "count_dup = {}\n",
    "for idx, item in enumerate(data['id'].to_list()):\n",
    "    tt_id = str(item)\n",
    "    if tt_id not in ids:\n",
    "        ids.append(tt_id)\n",
    "    else:\n",
    "        if tt_id in duplicated_ids:\n",
    "            count_dup[tt_id] += 1\n",
    "        else:\n",
    "            count_dup[tt_id] = 1\n",
    "        duplicated_ids.append(tt_id)"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "print(duplicated_ids)\n",
    "twitter_data.shape"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "mask = data['id'] == 'nan'\n",
    "data = data[~mask]\n",
    "print(data.shape[0])\n",
    "mask = data['id'] == '1,24177168919053E+018'\n",
    "data[mask].head()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "data.at[78843,'id'] = '1241771689190530000'\n",
    "data.at[78843,'id'] = '1241771689190530001'"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "# data.to_csv('twitter-local-and-rt.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Selecionando twittes para treino:"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "mask = data['is_rt'] == False\n",
    "train = data[mask]\n",
    "train.shape"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "mask = data['has_place'] == True\n",
    "train_original_place = train[mask]\n",
    "train_original_place.shape"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "train_original_place.head()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "train_original_place.to_csv('twitter_with_local_originals.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Limpando os tuites para a nuvem de palavras"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "tweets = train['text'].to_list()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "def remove_emoji(string):\n",
    "    emoji_pattern = re.compile(\"[\"\n",
    "                           u\"\\U0001F600-\\U0001F64F\"  # emoticons\n",
    "                           u\"\\U0001F300-\\U0001F5FF\"  # symbols & pictographs\n",
    "                           u\"\\U0001F680-\\U0001F6FF\"  # transport & map symbols\n",
    "                           u\"\\U0001F1E0-\\U0001F1FF\"  # flags (iOS)\n",
    "                           u\"\\U00002702-\\U000027B0\"\n",
    "                           u\"\\U000024C2-\\U0001F251\"\n",
    "                           \"]+\", flags=re.UNICODE)\n",
    "    return emoji_pattern.sub(r'', string)"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "def clean_tts(list_to_clean):\n",
    "    for idx, item in enumerate(list_to_clean):\n",
    "        \n",
    "        # transforma tudo para str\n",
    "        list_to_clean[idx] = str(item)\n",
    "        # retira todo o link https:// do tuite\n",
    "        list_str = list_to_clean[idx].split()\n",
    "        string = ' '.join([word for word in list_str if not re.search('https://t.co', word)])\n",
    "        #remove acentos\n",
    "        list_to_clean[idx] = re.sub(u'([\\u00C0-\\u00FC])', accent_remove, string.encode().decode('utf-8'))\n",
    "        # remove emojis\n",
    "        string = list_to_clean[idx].encode('ascii', 'ignore').decode('ascii')\n",
    "        list_to_clean[idx] = remove_emoji(string)\n",
    "        # deixa tudo em caixa baixa\n",
    "        list_to_clean[idx] = list_to_clean[idx].lower()\n",
    "        # substitui o restante dos caracteres desnecessarios\n",
    "        string = list_to_clean[idx]\n",
    "        list_to_clean[idx] = re.sub('[…•\\-\\(\\)\\&]', '', string)\n",
    "        string = list_to_clean[idx]\n",
    "        list_to_clean[idx] = re.sub('\\W\\s-', '', string)\n",
    "        string = list_to_clean[idx]\n",
    "        list_to_clean[idx] = re.sub('[\"º°/_]', ' ', string)\n",
    "        # remove espaços desnecessarios\n",
    "        string_list = list_to_clean[idx].split()\n",
    "        list_to_clean[idx] = ' '.join(string_list)\n",
    "\n",
    "        \n",
    "    return list_to_clean"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "clean_tuites = train['text'].to_list()\n",
    "clean_tuites = clean_tts(clean_tuites)\n",
    "\n",
    "clean_tuites[:100]"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "word_list = []\n",
    "# word_list = ['que', 'pra', 'nao', 'vai', 'estao', 'esta', 'voce', 'dia', 'hoje', 'nos', \n",
    "#              'essa', 'esse', 'voces', 'minha']\n",
    "with open(\"nuvem_palavras.txt\", 'w') as wf:\n",
    "    for phrase in clean_tuites:\n",
    "        for word in phrase.split():\n",
    "            if word not in word_list:\n",
    "                wf.write(word + ' ')"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "clean_tts_df = pd.DataFrame(clean_tuites)"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "clean_tts_df.to_csv('clean_data_tuittes.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Gráfico do número de twittes por dia com a hashtag #quarentena"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "dates = data['date'].to_list()\n",
    "print(dates[:10])\n",
    "print(dates[-10:])\n",
    "print(len(dates))"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "nan_count = sum(1 for i in dates if i == 'nan')\n",
    "print(nan_count)"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "clean_datas = []\n",
    "days = []\n",
    "months = []\n",
    "\n",
    "for idx, item in enumerate(dates):\n",
    "    string = str(item)\n",
    "    \n",
    "    day = string[8:10]\n",
    "    days.append(day)\n",
    "    \n",
    "    if string[5:7] != '03':\n",
    "        month = string[4:7]\n",
    "        if month == 'Fev':\n",
    "            month = '02'\n",
    "            months.append(month)\n",
    "            clean_datas.append('{}-{}'.format(day, month))\n",
    "        elif month == 'Mar':\n",
    "            month = '03'\n",
    "            months.append(month)\n",
    "            clean_datas.append('{}-{}'.format(day, month))\n",
    "        else:\n",
    "            month = '03'\n",
    "            months.append(month)\n",
    "            clean_datas.append('{}-{}'.format(day, month))\n",
    "    else:\n",
    "        month = string[5:7]\n",
    "        clean_datas.append('{}-{}'.format(day, month))\n",
    "        \n",
    "\n",
    "print(clean_datas[0], clean_datas[-1])"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "print(len(clean_datas), len(days), len(months))"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "clean_datas_df = pd.DataFrame(clean_datas, columns=['clean_date'])\n",
    "days_df = pd.DataFrame(days, columns=['day'])\n",
    "months_df = pd.DataFrame(months, columns=['month'])\n",
    "\n",
    "\n",
    "tuites_dates = pd.concat([clean_datas_df, days_df, months_df], axis=1)\n",
    "tuites_dates.tail(100)"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "# tuites_dates['clean_date'].fillna('11-03', inplace=True)\n",
    "# tuites_dates['day'].fillna('11', inplace=True)\n",
    "tuites_dates['month'].fillna('03', inplace=True)\n",
    "\n",
    "tuites_dates.tail(10)"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "result = tuites_dates.groupby(by=['clean_date']).count()\n",
    "result['day']"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "result = tuites_dates.groupby(by=['clean_date']).count()\n",
    "result['day']"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "result = tuites_dates.groupby(by=['clean_date']).count()\n",
    "result['day']"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "import seaborn as sns; sns.set()\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "clean_dates = tuites_dates['clean_date'].unique().tolist()\n",
    "clean_dates.reverse()\n",
    "print(clean_dates, len(clean_dates), '\\n')\n",
    "\n",
    "clean_dates_df = pd.DataFrame(clean_dates, columns=['Date'])\n",
    "\n",
    "\n",
    "tt_counts = result['day'].tolist()\n",
    "print(tt_counts, len(tt_counts))\n",
    "\n",
    "tt_count_df = pd.DataFrame(tt_counts, columns=['Number of tweets'])\n",
    "\n",
    "data_tt_counts = pd.concat([clean_dates_df, tt_count_df], axis=1)\n",
    "data_tt_counts.head(10)"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "sns_plot = sns.lineplot(x=\"Date\", y=\"Number of tweets\", data=data_tt_counts)\n",
    "fig = sns_plot.get_figure()\n",
    "sns_plot.fig.autofmt_xdate()\n",
    "fig.savefig(\"twitter_count1.png\")"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "sns.set(style=\"ticks\")\n",
    "sns_plot = sns.relplot(x=\"Date\", y=\"Number of tweets\", kind=\"line\", data=data_tt_counts)\n",
    "sns_plot.fig.autofmt_xdate()\n",
    "sns_plot.savefig(\"twitter_count2.png\")"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "sns.set(style=\"darkgrid\")\n",
    "sns_plot = sns.relplot(x=\"Date\", y=\"Number of tweets\", kind=\"line\", data=data_tt_counts)\n",
    "sns_plot.fig.autofmt_xdate()\n",
    "sns_plot.savefig(\"twitter_count3.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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