COVID_19(Sentiment_Analysis).ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "TGE98L2JuUed"
   },
   "source": [
    "# **COVID-19 Sentiment Analysis (INDIA)**\n",
    "**Context :**\n",
    "\n",
    "This dataset contains the Tweets of users who have applied the following hashtags: #coronavirus, #coronavirusoutbreak, #coronavirusPandemic, #covid19, #covid_19, #epitwitter, #ihavecorona, etc.\n",
    "\n",
    "From about 29th March till 30th April, the dataset also included the following additional hashtags: #StayHomeStaySafe, #TestTraceIsolate, etc.\n",
    "\n",
    "\n",
    "**Content :**\n",
    "\n",
    "The dataset contains variables associated with Twitter and other Social Media platform: the text of various tweets and the accounts that tweeted them, the hashtags used and the locations of the accounts.\n",
    "\n",
    "The retweets argument has been set to FALSE, so this dataset does not include retweets (although a count of retweets is provided as a variable).\n",
    "\n",
    "**Acknowledgements :**\n",
    "\n",
    "This dataset would not be possible without the creators of the rtweet package on CRAN.\n",
    "\n",
    "**Made by :**\n",
    "1. Vedaant Singh (1830207) \n",
    "2. Vedant Tibrewal (1830208)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ghFMJtofO6vj"
   },
   "source": [
    "### **Imporing the Libraries**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "ZTWF_6Fg54ms",
    "outputId": "eca0759f-f53e-448e-f53e-a450c43c39e3"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
      "[nltk_data]   Package stopwords is already up-to-date!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 85,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import nltk\n",
    "nltk.download('stopwords')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "ykrC49MLmuQv"
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import os\n",
    "import re\n",
    "from nltk.corpus import stopwords\n",
    "from nltk.stem.porter import PorterStemmer\n",
    "from sklearn.metrics import confusion_matrix, accuracy_score, classification_report"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "1we8qk7Zpa1R"
   },
   "source": [
    "## **Merging all the 33 datasets together**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "1tyUWuD0nDAo",
    "outputId": "5ea824ad-a2d2-4850-d6e6-30d946ece45d"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-03-29 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-03-30 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-03-31 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-01 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-02 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-03 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-04 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-05 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-06 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-07 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-08 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-09 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-10 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-11 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-12 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-13 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-14 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-15 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-16 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-17 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-18 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-19 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-20 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-21 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-22 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-23 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-24 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-25 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-26 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-27 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-28 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-29 Coronavirus Tweets.CSV\n",
      "/content/drive/MyDrive/COVID 19 - Sentiment Analysis/2020-04-30 Coronavirus Tweets.CSV\n",
      "\n",
      "\n",
      "9658     -1st world leader to call a regional conferenc...\n",
      "31605    When nothing works, #HOPE does! #stayhomestays...\n",
      "4909     Research Fellow Dr. @amritajash writes on #COV...\n",
      "12282    Good news: \\nKulwant Nirmal Kaur, 81 year old ...\n",
      "6225     #Alert  #CoronaVirusNews\\n3 more #COVID19 posi...\n",
      "Name: text, dtype: object\n",
      "\n",
      "\n",
      "Index(['created_at', 'text', 'source', 'favourites_count', 'retweet_count',\n",
      "       'country_code', 'lang', 'date_of_tweet'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "tweets = []\n",
    "for dirname, _, filenames in os.walk('/content/drive/MyDrive/COVID 19 - Sentiment Analysis'):\n",
    "    for filename in filenames:\n",
    "        print(os.path.join(dirname, filename))\n",
    "        df = pd.read_csv(os.path.join(dirname, filename), index_col=None, header=0)\n",
    "        df = df[(df['lang']=='en') & (df['country_code'] == 'IN')]\n",
    "        row, cols = df.shape\n",
    "        date = [filename[0:10]]*row\n",
    "        df['date_of_tweet'] = date\n",
    "        tweets.append(df)\n",
    "        \n",
    "data = pd.concat(tweets, axis=0, ignore_index=True)\n",
    "del tweets\n",
    "\n",
    "# random samples of tweets \n",
    "print(\"\\n\")\n",
    "print(data.text.sample(5))\n",
    "\n",
    "# print columns of dataframe\n",
    "# print(tweets_en_US.columns)\n",
    "\n",
    "# drop columns with user sensitive information \n",
    "data_set = data.copy()\n",
    "data_set.drop(['status_id','user_id','screen_name','reply_to_status_id',\n",
    "                                    'reply_to_user_id','is_retweet','place_full_name','place_type',\n",
    "                                    'reply_to_screen_name','is_quote','followers_count','friends_count',\n",
    "                                    'account_lang','account_created_at','verified'],axis=1, inplace = True)\n",
    "print(\"\\n\")\n",
    "print(data_set.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "4dp31gn2pmML"
   },
   "source": [
    "## **Data Wrangling**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 195
    },
    "id": "mswK87x5ziHW",
    "outputId": "8ecf06e7-340a-47d6-d620-8970f4a3fdbb"
   },
   "outputs": [
    {
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>created_at</th>\n",
       "      <th>text</th>\n",
       "      <th>source</th>\n",
       "      <th>favourites_count</th>\n",
       "      <th>retweet_count</th>\n",
       "      <th>country_code</th>\n",
       "      <th>lang</th>\n",
       "      <th>date_of_tweet</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-03-29T00:04:06Z</td>\n",
       "      <td>\"#Covid19: #SocialDistancing the Indian way\"  ...</td>\n",
       "      <td>Twitter for Android</td>\n",
       "      <td>10374</td>\n",
       "      <td>0</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-03-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-03-29T00:04:55Z</td>\n",
       "      <td>Possible case of human to animal transmission ...</td>\n",
       "      <td>Twitter for Android</td>\n",
       "      <td>22880</td>\n",
       "      <td>0</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-03-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-03-29T00:07:20Z</td>\n",
       "      <td>#Coronavirus: #US eclipses 120,000 confirmed c...</td>\n",
       "      <td>Twitter for Android</td>\n",
       "      <td>12968</td>\n",
       "      <td>6</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-03-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-03-29T00:09:14Z</td>\n",
       "      <td>The bitter truth 😔\\n#covid_19 #covid19india #l...</td>\n",
       "      <td>Instagram</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-03-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-03-29T00:13:20Z</td>\n",
       "      <td>#CoronavirusOutbreak  All Churches shd realize...</td>\n",
       "      <td>Twitter for Android</td>\n",
       "      <td>38</td>\n",
       "      <td>0</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-03-29</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             created_at  ... date_of_tweet\n",
       "0  2020-03-29T00:04:06Z  ...    2020-03-29\n",
       "1  2020-03-29T00:04:55Z  ...    2020-03-29\n",
       "2  2020-03-29T00:07:20Z  ...    2020-03-29\n",
       "3  2020-03-29T00:09:14Z  ...    2020-03-29\n",
       "4  2020-03-29T00:13:20Z  ...    2020-03-29\n",
       "\n",
       "[5 rows x 8 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_set.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "cXLEy7_Knoon",
    "outputId": "2b2063a1-5ba1-44ce-8932-9584dedda698"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(41618, 8)"
      ]
     },
     "execution_count": 5,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_set.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 284
    },
    "id": "he9ZiPLwpKmV",
    "outputId": "1060602c-dffd-46cd-c569-a4016ac92857"
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>favourites_count</th>\n",
       "      <th>retweet_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>41618.000000</td>\n",
       "      <td>41618.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>8357.006728</td>\n",
       "      <td>2.349584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>23384.337234</td>\n",
       "      <td>30.280830</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>170.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1221.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>5942.750000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>684015.000000</td>\n",
       "      <td>3818.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       favourites_count  retweet_count\n",
       "count      41618.000000   41618.000000\n",
       "mean        8357.006728       2.349584\n",
       "std        23384.337234      30.280830\n",
       "min            0.000000       0.000000\n",
       "25%          170.000000       0.000000\n",
       "50%         1221.000000       0.000000\n",
       "75%         5942.750000       1.000000\n",
       "max       684015.000000    3818.000000"
      ]
     },
     "execution_count": 6,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_set.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "7dbO-zctpPKz",
    "outputId": "d99dfd36-3b99-42bb-8a0a-b8abeebd219b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 41618 entries, 0 to 41617\n",
      "Data columns (total 8 columns):\n",
      " #   Column            Non-Null Count  Dtype \n",
      "---  ------            --------------  ----- \n",
      " 0   created_at        41618 non-null  object\n",
      " 1   text              41618 non-null  object\n",
      " 2   source            41618 non-null  object\n",
      " 3   favourites_count  41618 non-null  int64 \n",
      " 4   retweet_count     41618 non-null  int64 \n",
      " 5   country_code      41618 non-null  object\n",
      " 6   lang              41618 non-null  object\n",
      " 7   date_of_tweet     41618 non-null  object\n",
      "dtypes: int64(2), object(6)\n",
      "memory usage: 2.5+ MB\n"
     ]
    }
   ],
   "source": [
    "data_set.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "DoazZcV4pQ-L",
    "outputId": "288d442c-751a-4c49-be17-65ad7ef8b68e"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "created_at          0\n",
       "text                0\n",
       "source              0\n",
       "favourites_count    0\n",
       "retweet_count       0\n",
       "country_code        0\n",
       "lang                0\n",
       "date_of_tweet       0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_set.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 402
    },
    "id": "O9ugytFPpXHI",
    "outputId": "20d3e5d3-27e4-4e91-88ff-89347d9fa127"
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Text</th>\n",
       "      <th>Source</th>\n",
       "      <th>Favourites_Count</th>\n",
       "      <th>Retweet_count</th>\n",
       "      <th>Country_code</th>\n",
       "      <th>Lang</th>\n",
       "      <th>Date_of_tweet</th>\n",
       "      <th>Text_length</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>\"#Covid19: #SocialDistancing the Indian way\"  ...</td>\n",
       "      <td>Twitter for Android</td>\n",
       "      <td>10374</td>\n",
       "      <td>0</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-03-29</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Possible case of human to animal transmission ...</td>\n",
       "      <td>Twitter for Android</td>\n",
       "      <td>22880</td>\n",
       "      <td>0</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-03-29</td>\n",
       "      <td>253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>#Coronavirus: #US eclipses 120,000 confirmed c...</td>\n",
       "      <td>Twitter for Android</td>\n",
       "      <td>12968</td>\n",
       "      <td>6</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-03-29</td>\n",
       "      <td>224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>The bitter truth 😔\\n#covid_19 #covid19india #l...</td>\n",
       "      <td>Instagram</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-03-29</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>#CoronavirusOutbreak  All Churches shd realize...</td>\n",
       "      <td>Twitter for Android</td>\n",
       "      <td>38</td>\n",
       "      <td>0</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-03-29</td>\n",
       "      <td>280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41613</th>\n",
       "      <td>How/ Is @CMODelhi #DelhiGovt or @DelhiPolice u...</td>\n",
       "      <td>Twitter for Android</td>\n",
       "      <td>1499</td>\n",
       "      <td>1</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-04-30</td>\n",
       "      <td>258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41614</th>\n",
       "      <td>#Emotional:\\nWelcome ceremony of the 82 year o...</td>\n",
       "      <td>Twitter for Android</td>\n",
       "      <td>2198</td>\n",
       "      <td>0</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-04-30</td>\n",
       "      <td>295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41615</th>\n",
       "      <td>#ramdan's first #JumahMubarak.\\n\\nMay God prot...</td>\n",
       "      <td>Twitter for Android</td>\n",
       "      <td>2325</td>\n",
       "      <td>0</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-04-30</td>\n",
       "      <td>191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41616</th>\n",
       "      <td>It is not easy to transport them Gov need to a...</td>\n",
       "      <td>Twitter for Android</td>\n",
       "      <td>22327</td>\n",
       "      <td>0</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-04-30</td>\n",
       "      <td>269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41617</th>\n",
       "      <td>Look at this and ask yourselves does #PMCARES ...</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>32419</td>\n",
       "      <td>0</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-04-30</td>\n",
       "      <td>228</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>41618 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Text  ... Text_length\n",
       "0      \"#Covid19: #SocialDistancing the Indian way\"  ...  ...          69\n",
       "1      Possible case of human to animal transmission ...  ...         253\n",
       "2      #Coronavirus: #US eclipses 120,000 confirmed c...  ...         224\n",
       "3      The bitter truth 😔\\n#covid_19 #covid19india #l...  ...          84\n",
       "4      #CoronavirusOutbreak  All Churches shd realize...  ...         280\n",
       "...                                                  ...  ...         ...\n",
       "41613  How/ Is @CMODelhi #DelhiGovt or @DelhiPolice u...  ...         258\n",
       "41614  #Emotional:\\nWelcome ceremony of the 82 year o...  ...         295\n",
       "41615  #ramdan's first #JumahMubarak.\\n\\nMay God prot...  ...         191\n",
       "41616  It is not easy to transport them Gov need to a...  ...         269\n",
       "41617  Look at this and ask yourselves does #PMCARES ...  ...         228\n",
       "\n",
       "[41618 rows x 8 columns]"
      ]
     },
     "execution_count": 88,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset = pd.DataFrame({\"Text\": data_set['text'], \"Source\": data_set['source'], \"Favourites_Count\": data_set['favourites_count'], \n",
    "                        \"Retweet_count\": data_set['retweet_count'], \"Country_code\": data_set['country_code'], \"Lang\": data_set['lang'], \n",
    "                        \"Date_of_tweet\": data_set['date_of_tweet'], \"Text_length\": data_set['text'].apply(len)})\n",
    "\n",
    "dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "2xR8FUbwujaY"
   },
   "source": [
    "## **Exploratory Data Analysis - I (Without including the Sentiment Column)**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "60qIh6p9Zw51"
   },
   "source": [
    "#### **Source vs. Count**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 603
    },
    "id": "5zQ6yWkMujIP",
    "outputId": "eb264e03-1fa5-4ba0-902d-30acd0a08261"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (25, 10))\n",
    "sns.countplot(x = dataset['Source'], data = dataset)\n",
    "plt.title('Source Vs Count', fontdict = {'fontsize' : 15})\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Y2RgUKzG33ES"
   },
   "source": [
    "**Most Tweets were made from Twitter for Android devices, followed by Twitter for iPhone devices followed by Instagram**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "VPiUwN44EnbU"
   },
   "source": [
    "#### **Tweets per Day**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 515
    },
    "id": "KSsSfvuWz2jg",
    "outputId": "7d552f8e-8409-4a97-8638-b33fed43d06a"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (12, 8))\n",
    "dataset.sort_values('Date_of_tweet', inplace = True)\n",
    "sns.countplot(y = dataset['Date_of_tweet'], data = dataset)\n",
    "plt.title(\"Tweets per Day\", fontdict = {'fontsize' : 15})\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "0vZPQ_-90xnh"
   },
   "source": [
    "**Most number of Tweets were made on the 5th April, 2020**\n",
    "\n",
    "**Least number of tweets were made on the 12th April, 2020**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_WS8mjf4Eo4x"
   },
   "source": [
    "#### **Pair Plot to find relation between the features**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 567
    },
    "id": "7VCgehx30NnW",
    "outputId": "1460071b-ee35-469a-fdfb-c793b141e53d"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1080x1080 with 0 Axes>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x540 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (15, 15))\n",
    "sns.pairplot(dataset)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "rWdbulq0CEga"
   },
   "source": [
    "#### **HeatMap to check the Correlation (if any)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 500
    },
    "id": "nb8Vsxoi0TnA",
    "outputId": "5744db36-dd23-417c-db99-c1859dc96a2a"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (12, 8))\n",
    "dataset_cor = dataset[['Favourites_Count', 'Retweet_count', 'Text_length']].corr()\n",
    "axes = sns.heatmap(dataset_cor, linecolor = 'white', linewidths = 1, cmap = 'coolwarm', annot = True)\n",
    "axes.set_title('Heat Map of Variables')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "sdqPPQKTBvGA"
   },
   "source": [
    "#### **Most Mentions on Twitter**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "RPCrnAfa82Hw",
    "outputId": "0c43c02e-1bce-499f-cadf-8071e2a3e5f9"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['@BNODesk',\n",
       " '@JyotiPa65122202',\n",
       " '@KaushikDesai16',\n",
       " '@AnitaSi67735735',\n",
       " '@sanjeevsg52',\n",
       " '@PriyeshAdvocate',\n",
       " '@USATODAY',\n",
       " '@kerrywashington',\n",
       " '@ayush4bharat',\n",
       " '@narendramodi',\n",
       " '@AmitShah',\n",
       " '@ArvindKejriwal',\n",
       " '@Gurmeetramrahim',\n",
       " '@WHO',\n",
       " '@odisha_mining',\n",
       " '@tatatrusts',\n",
       " '@RNTata2000',\n",
       " '@rvineel_krishna',\n",
       " '@IMQuotes_Videos',\n",
       " '@CNNBusiness',\n",
       " '@JokeBot6000',\n",
       " '@sarcasm_box',\n",
       " '@911well',\n",
       " '@Gurmeetramrahim',\n",
       " '@safaindia',\n",
       " '@KTRTRS',\n",
       " '@jayesh_ranjan',\n",
       " '@cpcybd',\n",
       " '@HiHyderabad',\n",
       " '@ShantaThoutam',\n",
       " '@TiEHyderabad',\n",
       " '@narendramodi',\n",
       " '@PawanKalyan',\n",
       " '@narendramodi',\n",
       " '@AmitShah',\n",
       " '@CMOfficeUP',\n",
       " '@look',\n",
       " '@MoHFW_INDIA',\n",
       " '@PMOIndia',\n",
       " '@myogiadityanath',\n",
       " '@narendramodi',\n",
       " '@AprajitaSarangi',\n",
       " '@narendramodi',\n",
       " '@deepakwhynot',\n",
       " '@narendramodi',\n",
       " '@PMOIndia',\n",
       " '@sardanarohit',\n",
       " '@CMOTamilNadu',\n",
       " '@CM_tamilnadu',\n",
       " '@Vijayabaskarofl',\n",
       " '@TNGOVDIPR',\n",
       " '@KPAnbalaganoffl',\n",
       " '@RanchiPIB',\n",
       " '@MoHFW_INDIA',\n",
       " '@narendramodi',\n",
       " '@franciscus',\n",
       " '@narendramodi',\n",
       " '@jay21sep',\n",
       " '@naval',\n",
       " '@Mastikapaath',\n",
       " '@Ram87343952',\n",
       " '@ashu2424',\n",
       " '@narendramodi',\n",
       " '@PraphullRai',\n",
       " '@PMOIndia',\n",
       " '@WHO',\n",
       " '@PMOIndia',\n",
       " '@narendramodi',\n",
       " '@PMOIndia',\n",
       " '@dr_maheshsharma',\n",
       " '@RajCMO',\n",
       " '@RajGovOfficial',\n",
       " '@sbi',\n",
       " '@ashokgehlot51',\n",
       " '@RajSampark',\n",
       " '@SachinPilot',\n",
       " '@PMOIndia',\n",
       " '@myogiadityanath',\n",
       " '@ArvindKejriwal',\n",
       " '@narendramodi',\n",
       " '@mannkibaat',\n",
       " '@toi_john_sarkar',\n",
       " '@nirav440',\n",
       " '@narendramodi',\n",
       " '@narendramodi',\n",
       " '@himantabiswa',\n",
       " '@sarbanandsonwal',\n",
       " '@BeingSalmanKhan',\n",
       " '@SrBachchan',\n",
       " '@iHrithik',\n",
       " '@priyankachopra',\n",
       " '@aliaa08',\n",
       " '@iamsrk',\n",
       " '@TheAaryanKartik',\n",
       " '@imVkohli',\n",
       " '@ChouhanShivraj',\n",
       " '@CMMadhyaPradesh',\n",
       " '@narendramodi',\n",
       " '@RahulGandhi',\n",
       " '@ICMRDELHI',\n",
       " '@ProfBhargava',\n",
       " '@PMOIndia',\n",
       " '@WhiteHouse',\n",
       " '@WHO',\n",
       " '@EU_Commission',\n",
       " '@IvankaTrump',\n",
       " '@HemantSorenJMM',\n",
       " '@JharkhandCMO',\n",
       " '@DCseraikella',\n",
       " '@myogiadityanath',\n",
       " '@anuragkashyap72',\n",
       " '@ReallySwara',\n",
       " '@PMOIndia',\n",
       " '@narendramodi',\n",
       " '@narendramodi',\n",
       " '@rajeshtope11',\n",
       " '@uddhavthackeray',\n",
       " '@PriyankaJShukla',\n",
       " '@ChhattisgarhCMO',\n",
       " '@DPRChhattisgarh',\n",
       " '@narendramodi',\n",
       " '@PMOIndia',\n",
       " '@narendramodi',\n",
       " '@blacksheeptamil',\n",
       " '@ShivAroor',\n",
       " '@narendramodi',\n",
       " '@ShashiTharoor',\n",
       " '@narendramodi',\n",
       " '@PMOIndia',\n",
       " '@DDNational',\n",
       " '@PrakashJavdekar',\n",
       " '@Begin_Humor',\n",
       " '@DDNational',\n",
       " '@UpendrraRai',\n",
       " '@DelhiAirport',\n",
       " '@DCPSouthBCP',\n",
       " '@BBMPCOMM',\n",
       " '@deepolice12',\n",
       " '@BBMP_MAYOR',\n",
       " '@DCPSouthBCP',\n",
       " '@BBMPCOMM',\n",
       " '@deepolice12',\n",
       " '@BBMP_MAYOR',\n",
       " '@ShalluKapoor2',\n",
       " '@ArvindKejriwal',\n",
       " '@navikakumar',\n",
       " '@sudhirchaudhary',\n",
       " '@sardanarohit',\n",
       " '@DCPSouthBCP',\n",
       " '@BBMPCOMM',\n",
       " '@deepolice12',\n",
       " '@BBMP_MAYOR',\n",
       " '@narendramodi',\n",
       " '@akshaykumar',\n",
       " '@AlokTiwari9335',\n",
       " '@badri_dk',\n",
       " '@Bittu_Tufani',\n",
       " '@TheAnujBajpai',\n",
       " '@Yogehooda2',\n",
       " '@Sandosh75189169',\n",
       " '@narendramodi',\n",
       " '@PMOIndia',\n",
       " '@SGanguly99',\n",
       " '@BCCI',\n",
       " '@narendramodi',\n",
       " '@sardesairajdeep',\n",
       " '@Chshekhar2010',\n",
       " '@DM_Muzaffarpur',\n",
       " '@IPRD_Bihar',\n",
       " '@mfpcity',\n",
       " '@WHOAFRO',\n",
       " '@Sayed_8818',\n",
       " '@rashtrapatibhvn',\n",
       " '@VPSecretariat',\n",
       " '@narendramodi',\n",
       " '@jagdishmukhi',\n",
       " '@sarbanandsonwal',\n",
       " '@PrakashJavdekar',\n",
       " '@realDonaldTrump',\n",
       " '@StratNewsGlobal',\n",
       " '@PiyushGoyalOffc',\n",
       " '@RailMinIndia',\n",
       " '@WesternRly',\n",
       " '@Gmwrly',\n",
       " '@DRM_BVP',\n",
       " '@adrm_bvp',\n",
       " '@MazdoorSangh',\n",
       " '@brmsunion',\n",
       " '@SrBachchan',\n",
       " '@DrMNPandeyMP',\n",
       " '@anjanaomkashyap',\n",
       " '@narendramodi',\n",
       " '@Swamy39',\n",
       " '@vhsindia',\n",
       " '@jagdishshetty',\n",
       " '@MaheshJoshi_MJ',\n",
       " '@narendramodi',\n",
       " '@GooglePay',\n",
       " '@Paytm',\n",
       " '@PhonePe_',\n",
       " '@abhi_thakur3271',\n",
       " '@myogiadityanath',\n",
       " '@TOINoida',\n",
       " '@ANI',\n",
       " '@DDNewslive',\n",
       " '@PTI_News',\n",
       " '@SP_BERHAMPUR',\n",
       " '@DGPOdisha',\n",
       " '@igpsr',\n",
       " '@CMO_Odisha',\n",
       " '@nokia',\n",
       " '@corona',\n",
       " '@NokiaMobile',\n",
       " '@NokiamobileIN',\n",
       " '@nokianetworks',\n",
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       " '@WHO',\n",
       " '@PiyushGoyal',\n",
       " '@SureshAngadi_',\n",
       " '@RailMinIndia',\n",
       " '@narendramodi',\n",
       " '@PMOIndia',\n",
       " '@RahulGandhi',\n",
       " '@narendramodi',\n",
       " '@MahaCyber1',\n",
       " '@CMOMaharashtra',\n",
       " '@DGPMaharashtra',\n",
       " '@MahaDGIPR',\n",
       " '@MahaPolice',\n",
       " '@rajputbalsing',\n",
       " '@Brijeshbsingh',\n",
       " '@BharatkaSanjay',\n",
       " '@narendramodi',\n",
       " '@vnehra',\n",
       " '@vijayrupanibjp',\n",
       " '@IshuGupta11',\n",
       " '@Shamsher_IPS',\n",
       " '@ibijalpatel',\n",
       " '@MadhishParikh',\n",
       " '@kumarmanish9',\n",
       " '@KrunalShah225',\n",
       " '@urbanvoicesin',\n",
       " '@UCD_AMC',\n",
       " '@Amc_Gujarat',\n",
       " '@joan_cm',\n",
       " '@ashokgehlot51',\n",
       " '@GauravPandhi',\n",
       " '@kidliberty',\n",
       " '@AjaySingh_SG',\n",
       " '@BFI_official',\n",
       " '@Media_SAI',\n",
       " '@satyam3vedi',\n",
       " '@Fortunegiants',\n",
       " '@hiteshcoach',\n",
       " '@boxerachaudhary',\n",
       " '@boxerpooja',\n",
       " '@Boxernjhajhria',\n",
       " '@boxersanjeet91',\n",
       " '@boxersehrawat',\n",
       " '@boxerdabas',\n",
       " '@boxerdhankhar',\n",
       " '@rajmayna',\n",
       " '@WHO',\n",
       " '@ArvindKejriwal',\n",
       " '@SanjayAzadSln',\n",
       " '@dilipkpandey',\n",
       " '@AAPDelhi',\n",
       " '@narendramodi',\n",
       " '@BJP4India',\n",
       " '@nuts2406',\n",
       " '@SaniaAhmad1111',\n",
       " '@LiberalMantri',\n",
       " '@narendramodi',\n",
       " '@narendramodi',\n",
       " '@who',\n",
       " '@unicef',\n",
       " '@corona_india',\n",
       " '@coronavid19official',\n",
       " '@flyspicejet',\n",
       " '@Samanthaprabhu2',\n",
       " '@DeccanHerald',\n",
       " '@CMofKarnataka',\n",
       " '@BSYBJP',\n",
       " '@FcZoya',\n",
       " '@nehaaaa__me',\n",
       " '@nehaaaa__me',\n",
       " '@hammada_23',\n",
       " '@narendramodi',\n",
       " '@HPCL',\n",
       " '@dpradhanbjp',\n",
       " '@SwapanSamirEkka',\n",
       " '@myogiadityanath',\n",
       " '@PMOIndia',\n",
       " '@StarMoviesIndia',\n",
       " '@SonyPIX',\n",
       " '@HBO',\n",
       " '@NagpurTOI',\n",
       " '@TOIsarfaraz',\n",
       " '@PiyushGoyal',\n",
       " '@PiyushGoyalOffc',\n",
       " '@ICMRDELHI',\n",
       " '@RailMinIndia',\n",
       " '@CMofKarnataka',\n",
       " '@BSYBJP',\n",
       " '@siddaramaiah',\n",
       " '@jdsindia',\n",
       " '@hd_kumaraswamy',\n",
       " '@siddaramaiah',\n",
       " '@sriramulubjp',\n",
       " '@IndiaFi36606467',\n",
       " '@PraveenOmUniyal',\n",
       " '@alok_ajay',\n",
       " '@NitishKumar',\n",
       " '@PraveenOmUniyal',\n",
       " '@OnePlus_IN',\n",
       " '@oneplus',\n",
       " '@dchopra78',\n",
       " '@Sarcastic_homan',\n",
       " '@ShashiTharoor',\n",
       " '@INCIndia',\n",
       " '@CMOMaharashtra',\n",
       " '@ashoswai',\n",
       " '@PMOIndia',\n",
       " '@BeingSalmanKhan',\n",
       " '@kunalkamra88',\n",
       " '@narendramodi',\n",
       " '@timesofindia',\n",
       " '@CMOMaharashtra',\n",
       " '@OfficeofUT',\n",
       " '@AUThackeray',\n",
       " '@CMOMaharashtra',\n",
       " '@PMOIndia',\n",
       " '@capt_amarinder',\n",
       " '@mygovindia',\n",
       " '@narendramodi',\n",
       " '@jdjsindore',\n",
       " '@IndoreCollector',\n",
       " '@CESCLimited',\n",
       " '@narendramodi',\n",
       " '@INCIndia',\n",
       " ...]"
      ]
     },
     "execution_count": 14,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mention = []\n",
    "for i in range(0, len(dataset)):\n",
    "  review1 = dataset['Text'][i]\n",
    "  review1 = re.findall('@[a-zA-Z0-9_]+', review1)\n",
    "  for j in review1:\n",
    "    mention.append(j)\n",
    "\n",
    "mention"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "Pg2w3VGd4fyg",
    "outputId": "9e718494-d37c-4b69-c4ae-3429ec659b2e"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "FreqDist({1: 9714,\n",
       "          2: 1992,\n",
       "          3: 851,\n",
       "          4: 452,\n",
       "          5: 282,\n",
       "          6: 220,\n",
       "          7: 147,\n",
       "          8: 113,\n",
       "          9: 93,\n",
       "          10: 70,\n",
       "          11: 61,\n",
       "          12: 66,\n",
       "          13: 43,\n",
       "          14: 39,\n",
       "          15: 32,\n",
       "          16: 28,\n",
       "          17: 19,\n",
       "          18: 25,\n",
       "          19: 19,\n",
       "          20: 18,\n",
       "          21: 20,\n",
       "          22: 13,\n",
       "          23: 8,\n",
       "          24: 13,\n",
       "          25: 13,\n",
       "          26: 10,\n",
       "          27: 16,\n",
       "          28: 10,\n",
       "          29: 11,\n",
       "          30: 7,\n",
       "          31: 8,\n",
       "          32: 4,\n",
       "          33: 5,\n",
       "          34: 8,\n",
       "          35: 5,\n",
       "          36: 4,\n",
       "          37: 5,\n",
       "          38: 1,\n",
       "          39: 4,\n",
       "          40: 4,\n",
       "          41: 5,\n",
       "          42: 5,\n",
       "          43: 4,\n",
       "          44: 4,\n",
       "          45: 2,\n",
       "          46: 4,\n",
       "          47: 1,\n",
       "          48: 2,\n",
       "          49: 2,\n",
       "          50: 2,\n",
       "          51: 1,\n",
       "          52: 2,\n",
       "          53: 5,\n",
       "          55: 3,\n",
       "          56: 1,\n",
       "          57: 1,\n",
       "          59: 2,\n",
       "          60: 2,\n",
       "          61: 3,\n",
       "          62: 1,\n",
       "          63: 1,\n",
       "          66: 1,\n",
       "          67: 1,\n",
       "          68: 2,\n",
       "          70: 1,\n",
       "          71: 2,\n",
       "          73: 1,\n",
       "          75: 2,\n",
       "          76: 1,\n",
       "          77: 2,\n",
       "          78: 1,\n",
       "          79: 2,\n",
       "          80: 1,\n",
       "          81: 3,\n",
       "          83: 1,\n",
       "          84: 1,\n",
       "          85: 2,\n",
       "          86: 2,\n",
       "          87: 1,\n",
       "          88: 1,\n",
       "          91: 2,\n",
       "          92: 1,\n",
       "          95: 2,\n",
       "          96: 1,\n",
       "          97: 2,\n",
       "          98: 3,\n",
       "          101: 1,\n",
       "          103: 1,\n",
       "          104: 1,\n",
       "          108: 1,\n",
       "          117: 1,\n",
       "          127: 1,\n",
       "          131: 1,\n",
       "          132: 1,\n",
       "          133: 1,\n",
       "          136: 1,\n",
       "          137: 1,\n",
       "          139: 1,\n",
       "          141: 1,\n",
       "          143: 1,\n",
       "          149: 1,\n",
       "          153: 2,\n",
       "          156: 2,\n",
       "          162: 1,\n",
       "          177: 1,\n",
       "          184: 1,\n",
       "          187: 1,\n",
       "          194: 1,\n",
       "          199: 1,\n",
       "          220: 1,\n",
       "          243: 1,\n",
       "          247: 1,\n",
       "          264: 1,\n",
       "          267: 1,\n",
       "          274: 1,\n",
       "          278: 1,\n",
       "          288: 1,\n",
       "          292: 1,\n",
       "          294: 1,\n",
       "          301: 1,\n",
       "          362: 1,\n",
       "          363: 1,\n",
       "          383: 1,\n",
       "          505: 1,\n",
       "          587: 1,\n",
       "          831: 1,\n",
       "          2417: 1,\n",
       "          3645: 1})"
      ]
     },
     "execution_count": 15,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(mention)\n",
    "df = df[0].value_counts()\n",
    "\n",
    "from nltk.probability import FreqDist\n",
    "freqdist = FreqDist()\n",
    "\n",
    "for words in df:\n",
    "  freqdist[words] += 1\n",
    "\n",
    "freqdist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 569
    },
    "id": "PMwLJ4OU4gIQ",
    "outputId": "44da1ef3-de16-4e21-8b00-9247f04a7441"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  FutureWarning\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = df[:20, ]\n",
    "plt.figure(figsize = (12, 8))\n",
    "sns.barplot(df.values, df.index, alpha = 0.8)\n",
    "plt.title(\"Most @(mention)\", fontdict = {'fontsize' : 15})\n",
    "plt.ylabel(\"Account Name\")\n",
    "plt.xlabel(\"Count\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "LG8quWKyGEaq"
   },
   "source": [
    "**Most mentioned twitter account : @narendramodi**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "v8BVdWv0B7XZ"
   },
   "source": [
    "#### **Top Hashtags Used**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "VDGZXnFf3DMG",
    "outputId": "761f3e80-4638-42e2-b92a-b8a52718136d"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['#Covid19',\n",
       " '#SocialDistancing',\n",
       " '#COVID19',\n",
       " '#Coronavirus',\n",
       " '#US',\n",
       " '#Coronavirus',\n",
       " '#covid_19',\n",
       " '#covid19india',\n",
       " '#lockdown',\n",
       " '#CoronavirusOutbreak',\n",
       " '#CoronaUpdate',\n",
       " '#Italy',\n",
       " '#USA',\n",
       " '#Worldwide',\n",
       " '#DeathCount',\n",
       " '#COVID19',\n",
       " '#FollowMePlz',\n",
       " '#News',\n",
       " '#SaveIndia',\n",
       " '#COVID19INDIA',\n",
       " '#IndiaVsCorona',\n",
       " '#IndiaFightCorona',\n",
       " '#IndiaFightsCOVID19',\n",
       " '#IndiaFightsCorona',\n",
       " '#modi',\n",
       " '#Delhi',\n",
       " '#StayAwareStaySafe',\n",
       " '#StayHome',\n",
       " '#StayHomeStaySafe',\n",
       " '#SaveLives',\n",
       " '#CoronaPandemic',\n",
       " '#StayHomeSaveLives',\n",
       " '#Covid_19',\n",
       " '#COVID19',\n",
       " '#CoronaUpdate',\n",
       " '#CoronaLockdown',\n",
       " '#coronavirus',\n",
       " '#CoronavirusOutbreak',\n",
       " '#SuratReadyToFight',\n",
       " '#Surat',\n",
       " '#COVID2019india',\n",
       " '#CoronaUpdate',\n",
       " '#CoronaLockdown',\n",
       " '#IndiaFightsCornona',\n",
       " '#Covid_19',\n",
       " '#SundayMorning',\n",
       " '#SundayThoughts',\n",
       " '#SundayMotivation',\n",
       " '#StayAtHomeAndStaySafe',\n",
       " '#StayAtHomeSaveLives',\n",
       " '#SundayFunday',\n",
       " '#COVID19',\n",
       " '#Coronavirus',\n",
       " '#Drones',\n",
       " '#FeedTheNeedy',\n",
       " '#FeedingTheNation',\n",
       " '#coronavirus',\n",
       " '#coronavirusindia',\n",
       " '#CoronaLockdown',\n",
       " '#CoronaWarrior',\n",
       " '#CoronaUpdate',\n",
       " '#CoronavirusOutbreak',\n",
       " '#COVID19',\n",
       " '#CoronavirusPandemic',\n",
       " '#CoronaLockdown',\n",
       " '#coronavirus',\n",
       " '#Coronavirus',\n",
       " '#CoronaUpdate',\n",
       " '#CoronaLockdown',\n",
       " '#CoronavirusPandemic',\n",
       " '#LabourleftDelhi',\n",
       " '#God',\n",
       " '#JustAsking',\n",
       " '#CoronaUpdate',\n",
       " '#CoronaLockdown',\n",
       " '#CoronavirusOutbreak',\n",
       " '#CoronaAlert',\n",
       " '#janathacurfew',\n",
       " '#IndiaFightsCorona',\n",
       " '#Covid_19',\n",
       " '#IndiaFightsCorona',\n",
       " '#Covid_19',\n",
       " '#IndiaFightsCorona',\n",
       " '#Covid_19',\n",
       " '#Covid_19',\n",
       " '#Corona',\n",
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       " '#lockdown',\n",
       " '#stayhome',\n",
       " '#staysafe',\n",
       " '#corona',\n",
       " '#covid_19',\n",
       " '#shame',\n",
       " '#lockdown',\n",
       " '#coronavirus',\n",
       " '#COVID2019india',\n",
       " '#AndhraPradesh',\n",
       " '#COVID19',\n",
       " '#IndiaFightsCorona',\n",
       " '#Hyderabad',\n",
       " '#police',\n",
       " '#lockdown',\n",
       " '#coronavirus',\n",
       " '#CoronavirusOutbreak',\n",
       " '#sanitization',\n",
       " '#garbage',\n",
       " '#CoronaLockdown',\n",
       " '#ThankYou',\n",
       " '#future',\n",
       " '#BigBazar',\n",
       " '#kishorebiyani',\n",
       " '#coronavirus',\n",
       " '#21daylockdown',\n",
       " '#coronafightindia',\n",
       " '#coronavirusindia',\n",
       " '#CoronaLockdown',\n",
       " '#COVID19',\n",
       " '#Day4lockdown',\n",
       " '#COVID19',\n",
       " '#Telangana',\n",
       " '#COVID19',\n",
       " '#Tweets',\n",
       " '#post',\n",
       " '#news',\n",
       " '#COVID19',\n",
       " '#stayhome',\n",
       " '#Telangana',\n",
       " '#COVID19',\n",
       " '#Kargil',\n",
       " '#Ladakh',\n",
       " '#COVID19',\n",
       " '#PMCaresFund',\n",
       " '#LetsFightCorona',\n",
       " '#Covid_19',\n",
       " '#coronavirus',\n",
       " '#narendramodi',\n",
       " '#coronavirus',\n",
       " '#corona',\n",
       " '#covid19',\n",
       " '#COVID19',\n",
       " '#COVID2019india',\n",
       " '#CoronaInMaharashtra',\n",
       " '#COVID19outbreak',\n",
       " '#Covid19India',\n",
       " '#CoronavirusOutbreak',\n",
       " '#CoronaInMaharashtra',\n",
       " '#ShameOnKejriwal',\n",
       " '#lockdown',\n",
       " '#CoronavirusOutbreak',\n",
       " '#Covid_19',\n",
       " '#StayAtHomeAndStaySafe',\n",
       " '#COVID19',\n",
       " '#Coronavirus',\n",
       " '#AndhraPradesh',\n",
       " '#Corona',\n",
       " '#Coronaindia',\n",
       " '#coronavirus',\n",
       " '#COVID19',\n",
       " '#lockdownindia',\n",
       " '#Assam',\n",
       " '#nature',\n",
       " '#Healing',\n",
       " '#CoronaVirus',\n",
       " '#coronavirus',\n",
       " '#coronavirus',\n",
       " '#21dayslockdown',\n",
       " '#coronavirus',\n",
       " '#EndSpeciesism',\n",
       " '#CrueltyFree',\n",
       " '#Nature',\n",
       " '#CoronavirusOutbreak',\n",
       " '#StayHome',\n",
       " '#COVID19',\n",
       " '#COVID19',\n",
       " '#Covid_19',\n",
       " '#StayAtHomeAndStaySafe',\n",
       " '#CoronavirusOutbreak',\n",
       " '#CoronaUpdate',\n",
       " '#COVID19',\n",
       " '#CoronavirusLockdown',\n",
       " '#EndSpeciesism',\n",
       " '#CrueltyFree',\n",
       " '#CoronavirusOutbreak',\n",
       " '#PMCaresFund',\n",
       " '#COVID19',\n",
       " '#coronavirus',\n",
       " '#lockdownindia',\n",
       " '#COVID19',\n",
       " '#IndiaFightsCorona',\n",
       " '#HandHygiene',\n",
       " '#SocialDistancingNow',\n",
       " '#lockdownindia',\n",
       " '#CoronaUpdatesInIndia',\n",
       " '#CoronaUpdate',\n",
       " '#Covid19India',\n",
       " '#COVID2019',\n",
       " '#Covid_19',\n",
       " '#Covid_19india',\n",
       " '#Coronavirus',\n",
       " '#CautionYesPanicNo',\n",
       " '#CoronavirusOutbreak',\n",
       " '#Covid19India',\n",
       " '#IndiaFightsCorona',\n",
       " '#StayHomeIndia',\n",
       " '#StayHome',\n",
       " '#American',\n",
       " '#AmericaFirst',\n",
       " '#coronavirus',\n",
       " '#COVID19',\n",
       " '#India',\n",
       " '#CoronavirusOutbreak',\n",
       " '#CoronaUpdate',\n",
       " '#CoronaUpdatesInIndia',\n",
       " '#CoronaStopKaroNa',\n",
       " '#COVID19',\n",
       " '#coronavirus',\n",
       " '#COVID2019india',\n",
       " '#COVID19outbreak',\n",
       " '#COVID19',\n",
       " '#AmitShah',\n",
       " '#COVID19',\n",
       " '#Corona',\n",
       " '#PMCARE',\n",
       " '#CORONA',\n",
       " '#COVID19',\n",
       " '#DONATE',\n",
       " '#CyberPeace',\n",
       " '#PMCaresFund',\n",
       " '#IndiaFightsCorona',\n",
       " '#FakeNews',\n",
       " '#cybercrimes',\n",
       " '#COVID19',\n",
       " '#BreakTheChain',\n",
       " '#coronavirus',\n",
       " '#coronavirus',\n",
       " '#coronaquiz',\n",
       " '#Lockdown21',\n",
       " '#Deaths',\n",
       " '#Coronavirus',\n",
       " '#COVID19',\n",
       " '#COVID',\n",
       " '#COVID19',\n",
       " '#corona',\n",
       " '#MannKiBaat',\n",
       " '#CoronaUpdate',\n",
       " '#COVID19',\n",
       " '#CoronaUpdate',\n",
       " '#EarthHour2020',\n",
       " '#EarthHour',\n",
       " '#IndiaFightsCornona',\n",
       " '#StayAtHomeAndStaySafe',\n",
       " '#COVID19',\n",
       " '#FightCorona',\n",
       " '#lockdown21days',\n",
       " '#FightCOVID19',\n",
       " '#StayHomeSaveLives',\n",
       " '#COVID19',\n",
       " '#report',\n",
       " '#IndiaFightsCornona',\n",
       " '#CoronaUpdate',\n",
       " '#hospitals',\n",
       " '#ambala',\n",
       " '#NewsAlert',\n",
       " '#Coronavirustruth',\n",
       " '#coronavirus',\n",
       " '#assamarogyanidhi',\n",
       " '#IndiaFightsCorona',\n",
       " '#IndiaFightsCoronavirus',\n",
       " '#centralgovernmentdecisions',\n",
       " '#COVID19',\n",
       " '#COVID_19',\n",
       " '#I_nominate_u',\n",
       " '#COVID19',\n",
       " '#HimachalPradesh',\n",
       " '#coronavirushimachal',\n",
       " '#coronavirus',\n",
       " '#2019nCoV',\n",
       " '#CoronaVirusUpdates',\n",
       " '#Covid_19',\n",
       " '#CoronaLockdown',\n",
       " '#CoronaVirus',\n",
       " '#CoronaVirusIndia',\n",
       " '#India',\n",
       " '#Lockdown21',\n",
       " '#Corona',\n",
       " '#Virus',\n",
       " '#PMCARES',\n",
       " '#Covid19',\n",
       " '#IndiaFightAgainstCorona',\n",
       " '#Coronavirus',\n",
       " '#StayHome',\n",
       " '#StayHomeSaveLives',\n",
       " '#COVID19',\n",
       " '#India',\n",
       " '#Sakal',\n",
       " '#SakalNews',\n",
       " '#viral',\n",
       " '#ViralNews',\n",
       " '#SakalTimes',\n",
       " '#news',\n",
       " '#Corona',\n",
       " '#CoronavirusOutbreak',\n",
       " '#COVID2019',\n",
       " '#PeopleOnStreets',\n",
       " '#LabourersExodus',\n",
       " '#CoronavirusOutbreak',\n",
       " '#Corona',\n",
       " ...]"
      ]
     },
     "execution_count": 17,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hashtags = []\n",
    "for i in range(0, 41618):\n",
    "  review = dataset['Text'][i]\n",
    "  review = re.findall('#[a-zA-Z0-9_]+', review)\n",
    "  for j in review:\n",
    "    hashtags.append(j)\n",
    "    \n",
    "hashtags"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "HHiOsfOLBHxZ",
    "outputId": "be444f80-e53f-4665-a03d-3c6cb58c0994"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "FreqDist({199: 1,\n",
       "          220: 1,\n",
       "          243: 1,\n",
       "          247: 1,\n",
       "          264: 1,\n",
       "          267: 1,\n",
       "          274: 1,\n",
       "          278: 1,\n",
       "          288: 1,\n",
       "          292: 1,\n",
       "          294: 1,\n",
       "          301: 1,\n",
       "          362: 1,\n",
       "          363: 1,\n",
       "          383: 1,\n",
       "          505: 1,\n",
       "          587: 1,\n",
       "          831: 1,\n",
       "          2417: 1,\n",
       "          3645: 1})"
      ]
     },
     "execution_count": 18,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pd.DataFrame(hashtags)\n",
    "df1 = df1[0].value_counts()\n",
    "\n",
    "from nltk.probability import FreqDist\n",
    "freqdist1 = FreqDist()\n",
    "\n",
    "for words in df:\n",
    "  freqdist1[words] += 1\n",
    "\n",
    "freqdist1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 569
    },
    "id": "1I2QBw3hDU9E",
    "outputId": "a0628a51-1cfa-4515-8d4f-da26b95f4533"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  FutureWarning\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1 = df1[:20, ]\n",
    "plt.figure(figsize = (12, 8))\n",
    "sns.barplot(df1.values, df1.index, alpha = 0.8)\n",
    "plt.title(\"Top Hashtag Used\", fontdict = {'fontsize' : 15})\n",
    "plt.ylabel(\"Hashtags (#)\")\n",
    "plt.xlabel(\"Count\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ltN20sE3GbN9"
   },
   "source": [
    "**Most used hashtag : #COVID19**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_zFezVYdGzRq"
   },
   "source": [
    "## **Data Cleaning**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "X2-QluW4HD07"
   },
   "source": [
    "#### **Applying Sentiments on these tweets**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "I-fh4RCOJCAX"
   },
   "source": [
    "TextBlob is a Python (2 and 3) library for processing textual data. It provides a simple API for diving into common natural language processing (NLP) tasks such as part-of-speech tagging, noun phrase extraction, sentiment analysis, classification, translation, and more"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 402
    },
    "id": "4hFEwhAODgDP",
    "outputId": "49a9c506-f1f4-450c-928d-ba980a3ca5d2"
   },
   "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>Text</th>\n",
       "      <th>Source</th>\n",
       "      <th>Favourites_Count</th>\n",
       "      <th>Retweet_count</th>\n",
       "      <th>Country_code</th>\n",
       "      <th>Lang</th>\n",
       "      <th>Date_of_tweet</th>\n",
       "      <th>Text_length</th>\n",
       "      <th>sentiment</th>\n",
       "      <th>polarity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>\"#Covid19: #SocialDistancing the Indian way\"  ...</td>\n",
       "      <td>Twitter for Android</td>\n",
       "      <td>10374</td>\n",
       "      <td>0</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-03-29</td>\n",
       "      <td>69</td>\n",
       "      <td>positive</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Possible case of human to animal transmission ...</td>\n",
       "      <td>Twitter for Android</td>\n",
       "      <td>22880</td>\n",
       "      <td>0</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-03-29</td>\n",
       "      <td>253</td>\n",
       "      <td>negative</td>\n",
       "      <td>-0.085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>#Coronavirus: #US eclipses 120,000 confirmed c...</td>\n",
       "      <td>Twitter for Android</td>\n",
       "      <td>12968</td>\n",
       "      <td>6</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-03-29</td>\n",
       "      <td>224</td>\n",
       "      <td>positive</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>The bitter truth 😔\\n#covid_19 #covid19india #l...</td>\n",
       "      <td>Instagram</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-03-29</td>\n",
       "      <td>84</td>\n",
       "      <td>negative</td>\n",
       "      <td>-0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>#CoronavirusOutbreak  All Churches shd realize...</td>\n",
       "      <td>Twitter for Android</td>\n",
       "      <td>38</td>\n",
       "      <td>0</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-03-29</td>\n",
       "      <td>280</td>\n",
       "      <td>positive</td>\n",
       "      <td>0.1375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41613</th>\n",
       "      <td>How/ Is @CMODelhi #DelhiGovt or @DelhiPolice u...</td>\n",
       "      <td>Twitter for Android</td>\n",
       "      <td>1499</td>\n",
       "      <td>1</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-04-30</td>\n",
       "      <td>258</td>\n",
       "      <td>positive</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41614</th>\n",
       "      <td>#Emotional:\\nWelcome ceremony of the 82 year o...</td>\n",
       "      <td>Twitter for Android</td>\n",
       "      <td>2198</td>\n",
       "      <td>0</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-04-30</td>\n",
       "      <td>295</td>\n",
       "      <td>positive</td>\n",
       "      <td>0.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41615</th>\n",
       "      <td>#ramdan's first #JumahMubarak.\\n\\nMay God prot...</td>\n",
       "      <td>Twitter for Android</td>\n",
       "      <td>2325</td>\n",
       "      <td>0</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-04-30</td>\n",
       "      <td>191</td>\n",
       "      <td>positive</td>\n",
       "      <td>0.416667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41616</th>\n",
       "      <td>It is not easy to transport them Gov need to a...</td>\n",
       "      <td>Twitter for Android</td>\n",
       "      <td>22327</td>\n",
       "      <td>0</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-04-30</td>\n",
       "      <td>269</td>\n",
       "      <td>negative</td>\n",
       "      <td>-0.216667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41617</th>\n",
       "      <td>Look at this and ask yourselves does #PMCARES ...</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>32419</td>\n",
       "      <td>0</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-04-30</td>\n",
       "      <td>228</td>\n",
       "      <td>positive</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>41618 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Text  ...  polarity\n",
       "0      \"#Covid19: #SocialDistancing the Indian way\"  ...  ...         0\n",
       "1      Possible case of human to animal transmission ...  ...    -0.085\n",
       "2      #Coronavirus: #US eclipses 120,000 confirmed c...  ...       0.4\n",
       "3      The bitter truth 😔\\n#covid_19 #covid19india #l...  ...      -0.1\n",
       "4      #CoronavirusOutbreak  All Churches shd realize...  ...    0.1375\n",
       "...                                                  ...  ...       ...\n",
       "41613  How/ Is @CMODelhi #DelhiGovt or @DelhiPolice u...  ...       0.4\n",
       "41614  #Emotional:\\nWelcome ceremony of the 82 year o...  ...      0.32\n",
       "41615  #ramdan's first #JumahMubarak.\\n\\nMay God prot...  ...  0.416667\n",
       "41616  It is not easy to transport them Gov need to a...  ... -0.216667\n",
       "41617  Look at this and ask yourselves does #PMCARES ...  ...       0.2\n",
       "\n",
       "[41618 rows x 10 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from textblob import TextBlob\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "dataset['sentiment'] = ' '\n",
    "dataset['polarity'] = None\n",
    "for i,j in enumerate(dataset.Text):\n",
    "  blob = TextBlob(j)\n",
    "  dataset['polarity'][i] = blob.sentiment.polarity\n",
    "  if blob.sentiment.polarity >= 0 :\n",
    "    dataset['sentiment'][i] = 'positive'\n",
    "  else:\n",
    "    dataset['sentiment'][i] = 'negative'\n",
    "\n",
    "dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 195
    },
    "id": "2C_YpaB0Idxw",
    "outputId": "14aa3cd4-ac26-4dc7-cd97-6abf38fcaf65"
   },
   "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>Text</th>\n",
       "      <th>Source</th>\n",
       "      <th>Favourites_Count</th>\n",
       "      <th>Retweet_count</th>\n",
       "      <th>Country_code</th>\n",
       "      <th>Lang</th>\n",
       "      <th>Date_of_tweet</th>\n",
       "      <th>Text_length</th>\n",
       "      <th>polarity</th>\n",
       "      <th>positive</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>\"#Covid19: #SocialDistancing the Indian way\"  ...</td>\n",
       "      <td>Twitter for Android</td>\n",
       "      <td>10374</td>\n",
       "      <td>0</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-03-29</td>\n",
       "      <td>69</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Possible case of human to animal transmission ...</td>\n",
       "      <td>Twitter for Android</td>\n",
       "      <td>22880</td>\n",
       "      <td>0</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-03-29</td>\n",
       "      <td>253</td>\n",
       "      <td>-0.085</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>#Coronavirus: #US eclipses 120,000 confirmed c...</td>\n",
       "      <td>Twitter for Android</td>\n",
       "      <td>12968</td>\n",
       "      <td>6</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-03-29</td>\n",
       "      <td>224</td>\n",
       "      <td>0.4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>The bitter truth 😔\\n#covid_19 #covid19india #l...</td>\n",
       "      <td>Instagram</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-03-29</td>\n",
       "      <td>84</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>#CoronavirusOutbreak  All Churches shd realize...</td>\n",
       "      <td>Twitter for Android</td>\n",
       "      <td>38</td>\n",
       "      <td>0</td>\n",
       "      <td>IN</td>\n",
       "      <td>en</td>\n",
       "      <td>2020-03-29</td>\n",
       "      <td>280</td>\n",
       "      <td>0.1375</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                Text  ... positive\n",
       "0  \"#Covid19: #SocialDistancing the Indian way\"  ...  ...        1\n",
       "1  Possible case of human to animal transmission ...  ...        0\n",
       "2  #Coronavirus: #US eclipses 120,000 confirmed c...  ...        1\n",
       "3  The bitter truth 😔\\n#covid_19 #covid19india #l...  ...        0\n",
       "4  #CoronavirusOutbreak  All Churches shd realize...  ...        1\n",
       "\n",
       "[5 rows x 10 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "senti = pd.get_dummies(dataset['sentiment'], drop_first = True)\n",
    "dataset = pd.concat([dataset, senti], axis = 1)\n",
    "dataset = dataset.drop('sentiment', axis = 1)\n",
    "dataset.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "z14cXAsDMCll"
   },
   "source": [
    "### **Creating Corpus**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "v7OdGnSIfFjc",
    "outputId": "9cd754d8-1a2a-4f57-f726-579e1f94bc7b"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['indian way',\n",
       " 'possibl case human anim transmiss way around worri pet look india look stray anim popul look idiot still continu go god help us',\n",
       " 'eclips confirm case death usa',\n",
       " 'bitter truth india',\n",
       " 'church shd realiz mass form worship r import make arrang counter spread infect n treat infect church premis incl palati bp hous allow use isol ward',\n",
       " 'amp reach due',\n",
       " 'death count march th itali death total spain franc caus havoc save famili stay home',\n",
       " 'unfortun see unplan ill intend mayhem add gasolin fire',\n",
       " 'two week ago today',\n",
       " 'made small contribut toward countri pleas contribut even small amount matter ji lot countri let particip save countri epidem',\n",
       " 'strang feel dat lockdown go b extend',\n",
       " 'madurai kavalan app use gp track coronaviru pandem',\n",
       " 'polic deploy monitor movement vehicl peopl',\n",
       " 'appreci true human serv citizen soil time delhi govern',\n",
       " 'thousand infect thousand plu dead death rate itali number danger horribl',\n",
       " 'killer team activist combin journalist urban naxal support china friendli china countri popul non muslim suffer tri fail',\n",
       " 'coronaviru tweet indian author',\n",
       " 'case march u reach itali reach spain reach worldwid case',\n",
       " 'delhi cm aprici central govern advis drink cow urin shame govt fool mindless peopl',\n",
       " 'hide',\n",
       " 'everi articl everi opinion attack lockdown measur ill plan take countri like logist nightmar second instead hurl accus give solut know work',\n",
       " 'need understand india joint famili system live hous defin boundari teach social distanc readi even think distanc issu resist start',\n",
       " 'said migrant worker shoukd put shelter food basic amneti monitor would work better panic fear confus go creat far problem',\n",
       " 'onset commun social era',\n",
       " 'today whole world fight danger diseas everyon worri follow guidelin govern health care tip fight',\n",
       " 'yesterday global case today increas',\n",
       " 'never histori human civilis human face formid challeng role corp sector mission critic fight corp citizen amp lead way amp commit rs cr',\n",
       " 'mani compani compet compani creat good morn sleepi quarantin ask free say',\n",
       " 'true fight corona need go side fight fight insid home',\n",
       " 'anyon interest donat volunt give support daili wage earner across telangana reach amp covid relief',\n",
       " 'dear sir happi pm like u tollywood lot celebr like sir donat money fight plz u recogn n appreci duti one tweet sir thank u',\n",
       " 'asia famou cricket board donat combat rs million nearli lakh taka crore million usd see favourit team stand bcci tri put india',\n",
       " 'case peopl goe',\n",
       " 'start special screen passeng board except symptom unless host state provid food amp shelter amp secur',\n",
       " 'pl grave neglig whoever fight without pay salari need apart pat back',\n",
       " 'know reach amp provid medicin patient get free medicin suppli govern hospit suggest pleas',\n",
       " 'done',\n",
       " 'govt public money contribut govt simpli transfer one pocket anoth nation disast govt need fund soumoto take fund without consent safeguard peopl maam plz correct wrong sincer request',\n",
       " 'wast manag essenti public servic fight beat covid',\n",
       " 'also contribut ji know nation safe fight lead front keep billion citizen safe proud sir god bless bharat mata ki jai',\n",
       " 'know onlin bank transfer account thought would contribut least rs small drop ocean ask best friend fight caus stitch money go',\n",
       " 'click erth new updat world click erth thank',\n",
       " 'time bit help defeat pledg fight tamilnadu cm disast relief fund pleas bit',\n",
       " 'surpris case report jharkhand till date posit report peripher state poor surveil amp report failur fact',\n",
       " 'asantu ame banchiba let live fight covid',\n",
       " 'currenc potenti carrier infect pleas use altern mode payment time readi safe handl money transact use us pleas stay home stay safe',\n",
       " 'avoid situat want disrupt shame rather criticis world best action pm ji led govt someth peopl situat ground',\n",
       " 'bengaluru base dr vishal rao use cytokin target new approach treat',\n",
       " 'pictur worth thousand word sign time pope deliv special urbi et orbi bless step st peter basilica complet empti vatican citi',\n",
       " 'tommorow sunris see corona mortal pray world',\n",
       " 'interferon hamper covid infect therebi reduc immun person',\n",
       " 'big blow come imagin peopl surviv hard time',\n",
       " 'small contribut toward jai hind would urg peopl network pl contribut nation jaan hai jahan hai',\n",
       " 'god bless frontlin worker selflessli serv commun crisi thank health care worker first respond nurs groceri store employe truck driver amp step keep us safe unpreced time',\n",
       " 'know key success situat like key failur toward tri pleas everybodi maintain',\n",
       " 'govern doctor best judg handl everyon stay home stay afe',\n",
       " 'one best doctor world dr nageswar reddi garu aig hyd detail analysi telugu corona viru cure vacin prevent must watch',\n",
       " 'come join us worship live god telangana',\n",
       " 'let us drill space live connect world let us fight togeth',\n",
       " 'small contribut toward nation defeat',\n",
       " 'think go day control one time lock help world control rather go part wise countri',\n",
       " 'today mann ki baat episod focu situat prevail due covid',\n",
       " 'awe mumbai deal migrant delhi disast manag crowd news mumbai far',\n",
       " 'dear wish donat cm relief fund googl pay amp onlin mode fight pleas publish rajasthan cm upi id maharashtra cm publish cmrfmahacovid',\n",
       " 'guid social distanc',\n",
       " 'motown india afsar baig captur horrifi scene near delhi border march delhi',\n",
       " 'summari fatal symptomat amp asymptomat patient via age age age age age age age age age',\n",
       " 'dear ji one step evacu peopl delhi ncr home creat situat make better easier arrang workplac keep away vilag denguru',\n",
       " 'railway convert coach isol treatment room',\n",
       " 'pm address nation today today episod focus situat prevail due stay tune live',\n",
       " 'person come back maharashtra amravati four member famili test posit meerut',\n",
       " 'india total case activ case recov death',\n",
       " 'groundswel domest discont xi ccp crisi crown tip anger iceberg',\n",
       " 'prime minist narendra modi address nation radio programm today episod focus situat prevail due',\n",
       " 'doctor help defeat smallpox help explain come thank share',\n",
       " 'nri appreci exemplari action pm ji especi amp appeal citizen india strictli obey stay safe',\n",
       " 'pleas go round fake religi leader sorrow redress take shelter certifi lord kabir saheb rid sorrow must watch sadhana tv even',\n",
       " 'small donat countri pleas capabl jai hind bharat mata ki jay',\n",
       " 'posit case indor last night detect indor new epicentr',\n",
       " 'even darkest cloud silver line vasant kunj',\n",
       " 'world face huge problem indian never go come biggest parti india peopl start abus small state cm even full state rememb peopl go mean realli well',\n",
       " 'let share learn grow togeth fight listen pm shri today',\n",
       " 'current gener moral respons make world better futur gener',\n",
       " 'congress amp alli must voluntarili come forward appropri suggest wayout may precis combat pandem crisi emerg world instead criticis amp make concern unsecur futur need think present',\n",
       " 'million us india us fight',\n",
       " 'fda approv self collect nasal swab test potenti eas pressur requir ppe train personnel pleas implement',\n",
       " 'kind ingenu agil leverag exist resourc solv problem make india special',\n",
       " 'itali death toll cross ten fckn thousand ask contain need move needl stop mess forev',\n",
       " 'china sole respons outbreak corona world shameless nation world',\n",
       " 'basic diseas rel come meet kg pair one',\n",
       " 'god give strength fight crisi',\n",
       " 'respect sir lockdown meant mani peopl allow assembl one place respect wait peopl buy veget jai prakash udyan adityapur',\n",
       " 'raigad civil defenc continu food distribut consecut day daili wage labour',\n",
       " 'st cm dbt trf labour commun kitchen super special ward home deliveri ration veggi basic necess rest cm follow anyon pure polit amp anti hindu',\n",
       " 'apart critic hope also give donat support india fight',\n",
       " 'modi govern total fail protect',\n",
       " 'small contribut littl daughter sudiksha',\n",
       " 'similar infect one patient spread other realis affect difficult time got fight hard fight',\n",
       " 'sir mani homeless ppl walk street carri risk die road govt provid shelter govt set rescu camp flood earthquak affect ppl',\n",
       " 'conduct door door campaign amid lockdown cluster whole villag whole citi pleas arrang care health care provid',\n",
       " 'bewar',\n",
       " 'done bit contribut fight diseas like urg peopl contribut',\n",
       " 'congreg commot ever forgiven done know tag',\n",
       " 'trichi base firm new propel technolog offer robot outbreak help doctor health worker avoid interact patient necessari',\n",
       " 'om sai ram may baba bless protect',\n",
       " 'live updat pm address focu pandem case india',\n",
       " 'current lockdown due coronaviru pandem provid opportun simplifi live get rid necessari life beauti basic',\n",
       " 'support littl donat fight small amount whatev best could sorri amp thank',\n",
       " 'happi covid awar stay home safe break chain coimbator tamil nadu',\n",
       " 'tow side stori',\n",
       " 'forget still work effici',\n",
       " 'fight brave bold decis hindsight need surpris announc govt given suffici notic hour notic enough poor homeless worst hit',\n",
       " 'mani crore collect yesterday pm cm relief fund famili like given high end',\n",
       " 'littl drop water make mighti ocean one flower one make garland god pleas continu liber pm care fund let us fight',\n",
       " 'shri sir ji pleas help other state live peopl food essenti servic',\n",
       " 'andaman gb pant govt hospit refus treat patient question patient physiotherapist homeopathi allopathi hospit clinic forc shut',\n",
       " 'impact migrant exodu would known come day economi never role migrant worker play run citi enorm would face crisi manpow avail',\n",
       " 'aankhen serial passion use watch doordarshan child start telecast lockdown',\n",
       " 'amid spike coronaviru case india boost capac tougher challeng ahead',\n",
       " 'aankhen serial passion use watch doordarshan child start telecast lockdown',\n",
       " 'unplan lockdown made mockeri social distanc',\n",
       " 'someth good due',\n",
       " 'today tell peopl differ irrespect boundari creat us human race noth',\n",
       " 'corona viru put extrem deep introspect never happen forev think mind',\n",
       " 'sh ceo amp editor chief sahara news network emphas best fight econom impact compris compass componennt read',\n",
       " 'day read chennai china carnivor coronaviru ruhan wuhan worldwid affect lung seem mine mind affect',\n",
       " 'case alon surpass number case state hs tough task trend use',\n",
       " 'german wait get evacu carri back home lufthansa',\n",
       " 'disciplin must armi teach lesson indisciplin lot',\n",
       " 'corona soldier south bangalor happi see street vendor shift nr coloni ap ground thank basavanagudi polic inspector staff cooper',\n",
       " 'corona soldier south bangalor happi see street vendor shift nr coloni ap ground thank basavanagudi polic inspector staff cooper',\n",
       " 'hinduism cultur hinduism way life whole world accept fact',\n",
       " 'thru dtc buse dump lakh migrant worker u p bihar delhi border thru machin amp rumour monger thu derail amp risk spread amp million human live',\n",
       " 'corona soldier south bangalor happi see street vendor shift nr coloni ap ground thank basavanagudi polic inspector staff cooper',\n",
       " 'huge respect rs cr amp rs cr real hero',\n",
       " 'precis go outsid kota rajasthan',\n",
       " 'suprem god kabir save us sin mani diseas yajurveda adhyay manta plz must watch ishvartv pm',\n",
       " 'citizen india done small bit donat fight pl everi citizen bit',\n",
       " 'fight',\n",
       " 'would good idea cricket stadium around india provid altern isol facil patient sincer request take advis serious',\n",
       " 'st case detect jan rahul gandhi warn thfeb suffici time plan amp take action poor alway suffer nri children brought back amp poor amp thali taali',\n",
       " 'given small opportun serv nation time crisi believ contribut whatev way possibl thank doctor nurs etc',\n",
       " 'think spread myth believ',\n",
       " 'mayb absolut religi fund divert healthcar educ that sureshot way save further civilis religion matter faith amp solitud gargantuan econom',\n",
       " 'dear kindli sanit medic instrument',\n",
       " 'openli alcohol sell shop bihar lockdown bottl thrown compound everyday new polic line durga mandir sabjimandi mit road plz take action',\n",
       " 'need collect take disciplinari action propaganda callous blackmail poor qualiti product world pay price',\n",
       " 'given small opportun serv nation time crisi believ contribut whatev way possibl thank doctor nurs etc',\n",
       " 'disinfect street coronaviru impress',\n",
       " 'kill patient wrong stori made patient consum die',\n",
       " 'spread dozen countri region today confirm case death govern health author across contin strive limit widespread infect',\n",
       " 'amir khan cr shahrukh khan cr salman khan cr sourc whatsapp forward',\n",
       " 'request everyon contribut per abil prime minist citizen assist relief emerg situat fund pm care fund help fight',\n",
       " 'n think indian china take away freedom enslav brain tiananmen squar',\n",
       " 'get ur fact check fakestori checkmat u trust noon authent govt recogn bodi join ur hand fight crisi',\n",
       " 'justif lockdown despit horrif spread way countri deserv lockdown know new york alon half usa case',\n",
       " 'natur best everi day new day new hope stay posit lock',\n",
       " 'arm forc prepar sinc januari readi emerg india quick reaction team readi go countri success mission',\n",
       " 'call',\n",
       " 'bit side sir help countri corona',\n",
       " 'break one test posit bengal first case north bengal year old resid kalimpong recent return thailand via kerala total case stand',\n",
       " 'pl donat support india pride',\n",
       " 'india declar invis enemi dr subramanian articl mr ji',\n",
       " 'number case gone past death march th total death count new case th case new york state alon frivol take chanc stay home',\n",
       " 'prime minist narendra modi sunday speak day lockdown nation stem spread coronaviru urg peopl listen radio show mann ki baat',\n",
       " 'request provid link applic peopl donat',\n",
       " 'noida day paid leav infect say dm via',\n",
       " 'year old covid patient die ahmedabad take total death talli gujarat second death less hour state live updat',\n",
       " 'year old covid patient die ahmedabad take total death talli gujarat second death less hour state live updat',\n",
       " 'akshay kumar donat kriti sanon r madhavan bollywood celeb prais akshay kumar contribut rs crore pm narendra modi care fund',\n",
       " 'good news today global recoveri year old man itali recov fda approv rapid min test cuomo increas slow ny china eas restrict plasma research donor tom hank amp rita wilson recov back us',\n",
       " 'watch episod show th march indian standard time amp issu expert prof nimesh desai director ihba delhi inform other pleas',\n",
       " 'year old covid patient die ahmedabad take total death talli gujarat second death less hour state live updat',\n",
       " 'yesterday went villag bring back parent vehicl call dsp mr sarthak roy permiss thank fr solicit attent complet realli praiseworthi fr tremend job difficult time',\n",
       " 'peopl',\n",
       " 'updat coronaviru test uk march total test neg posit pm march hospitalis uk sadli die',\n",
       " 'insecur even within gang',\n",
       " 'shortag test kit civil hospit staff use hiv kit',\n",
       " 'bill gate mark zuckerberg collabor find treatment busi insid',\n",
       " 'india succe control spread rais statur intern countri could cope democraci unaccount authoritarian state ex foreign secretari',\n",
       " 'death toll novel coronaviru shot past new death countri civil protect servic',\n",
       " 'one new case report today take total talli bhilwara alon report case',\n",
       " 'sir request kindli allow recycl sector suppli chain oper soon massiv shortag packag materi cardboard tissu paper napkin amp plastic relat item use packag essenti good',\n",
       " 'transmitt human human pleas get back learn chines cpp',\n",
       " 'sever resourc constraint desper need condit preced amp happen adopt low incom countri even develop one present perfect condit happen b adopt',\n",
       " 'idk need hear live alon get get',\n",
       " 'contribut wish contribut share contribut social media encourag peopl fight pandem',\n",
       " 'man tangmarg area north kashmir baramulla district test posit yeaterday die cd hospit srinagar travel histori coronaviru death toll kashmir',\n",
       " 'one posit patient male suffer diabet die today ahmedabad total five death gujarat cumul figur till today sourc gujarat ministri health',\n",
       " 'tata pledg rs crore help fight god bless mr ratan tata set benchmark human kind thank mr',\n",
       " 'elderli peopl maximum risk lower immun show generos leav suppli',\n",
       " 'pleas retweet helplin number state requir immedi help public wake',\n",
       " 'solut help nation fight pleas check video link',\n",
       " 'criticis marriot charg two banana statu doctor cousin current duti seven hill hospit food provid j w marriot',\n",
       " 'dear request make keep women amp child helplin amp women amp child desk polic station activ mitig kind violenc difficult time',\n",
       " 'said given instruct go boon taun leav present necessari follow stay away place found',\n",
       " 'conclus countri malaria common covid spread high',\n",
       " 'life chanc everyon need everyday true motiv ji alway provid true life chang tip facebook get amp improv immun',\n",
       " 'design protect tirunelv',\n",
       " 'request contribut part',\n",
       " 'everyon think day quarantin free pleas set mind day till affect count come minimum till june lock max predict mindset import stay safe stay home',\n",
       " 'cong parti hold regular press confer via video conf wake',\n",
       " 'bit famili hope help',\n",
       " 'hon ble prime minist shri ji address nation radio programm today episod focus situat prevail due',\n",
       " 'china construct bed hospit day india establish bed medic facil overnight fraction cost jai hind',\n",
       " 'corona gonna long',\n",
       " 'keep diari',\n",
       " 'quarantin season advantag read book read list quit',\n",
       " 'ration suppli work peopl gather social distanc among peopl situat continu like andhrapradesh first covid case volunt spot',\n",
       " 'number case gone past take lightli go reduc pressur doctor polic pathologist administr learn mistak other stay home',\n",
       " 'enjoy quarantin time realli u routin sleep jog read book watch movi danc exercis',\n",
       " 'think peopl rich journalist countri think peopl donat',\n",
       " '',\n",
       " 'small edit corona serv u peopl kindli stay home stay safe nallathe nadakum',\n",
       " 'indian muslim world center',\n",
       " 'listen region news bulletin india radio rnu ranchi hr latest updat read uday shankar jha via',\n",
       " 'everyon must follow instruct govern protect keep social distanc present could face big problem upcom time',\n",
       " 'precaut taken fight wash hand frequent soap amp water maintain cover mouth cough sneez',\n",
       " 'creativ fit crazi workout kg ekfa indialockeddown dayslockdown music youtub',\n",
       " 'vulner section societi open viru old peopl children',\n",
       " 'indian muslim world center',\n",
       " 'hbr articl impact economi would impact short term liquid well medium term capit format significantli disrupt financi market also real economi',\n",
       " 'garden best practic day spend leisur time water flower plant amp garden stay away anandapur india',\n",
       " 'act lockdown fuck gov fuck gov rule fuck lockdown fuck covid',\n",
       " 'self help group compris poor women contribut control situat stitch protect mask health polic functionari',\n",
       " 'ghastli road accid rais seriou doubt effect patrol checkpost state day nationwid contain spread',\n",
       " 'pleas help us defend seem happen local also pile local due anyth',\n",
       " 'kishor biyani groceri tycoon race keep india fed compani afloat econom time',\n",
       " 'good morn stay safe stay home',\n",
       " 'omg middl manag problem exist job need kinda monitor need evalu post world',\n",
       " 'contribut cmrf fight one rupe use buy new protect equip frontlin health worker procur new medic infrastructur isol patient feed strand migrant worker',\n",
       " 'everi messag reason worri feel helpless despit thing home littl posit faith peopl best keep everyon safe fear',\n",
       " 'let bit strengthen hand state govern extraordinari time',\n",
       " 'innoc littl boy turn wisest counselor fight',\n",
       " 'alreadi donat time pleas contribut pm care fund jai hind save countri',\n",
       " 'happi contribut small amount covid war request show interest donat',\n",
       " 'govt announc peopl share fake inform consid crimin case cyber crime dept monitor record respons citizen',\n",
       " 'report mean clarif suggest clear air',\n",
       " 'maharashtrian worldwid request help follow account',\n",
       " 'dear pl stop dirti polit tri emerg great human be reason life death',\n",
       " 'mega princ donat lakh ccc mana kosam corona crisi chariti committe form provid help cinema daili wage worker crisi great gestur',\n",
       " 'understand mp mla say support caus mplad mlalad fund peopl fund come us case would pocket make sens tri fool peopl',\n",
       " 'next week ap villag volunt invent medicin next year ap villag volunt help isro moon land mission th class pass scientist doctor engin chang futur',\n",
       " 'give corona viru give love break myth',\n",
       " 'posit impact lockdown',\n",
       " 'per fm direct creat new handl provid direct rout custom complaint queri concern bank insur relat issu regard relat relief measur',\n",
       " 'total number case india activ case health ministri',\n",
       " 'wake novel pandem claim live peopl across globe urg take necessari precaut stop spread let break chain togeth',\n",
       " 'ft distanc maintain go soon jatani top list new nonveg market goruhat campu jatani odisha',\n",
       " 'live live strike back balanc begin come human wake',\n",
       " 'studi deal anxieti aris pandem view sunday ht column today',\n",
       " 'delet instal',\n",
       " 'mega princ donat lakh ccc mana kosam corona crisi chariti committe form provid help cinema daili wage worker crisi great gestur',\n",
       " 'world war iii',\n",
       " 'india confirm case march confirm case hr death far patient discharg migrat far',\n",
       " 'also let pledg go begin come human wake',\n",
       " 'hear belov pm ji request student contribut nobel caus',\n",
       " 'amidst lockdown stubborn hawker hardli listen put peopl life risk locat namaskar co op hous societi royal park road opp jai hind bank ambernath east dist thane',\n",
       " 'key control',\n",
       " 'word requir',\n",
       " 'total number case countri rise includ cure discharg death union health ministri live updat toi',\n",
       " 'would like see front let act fast stay first front',\n",
       " 'number death rise',\n",
       " 'togeth fight make sure peopl around follow good respiratori hygien thank share inform help us help societi narend rai choki inch lal bagh',\n",
       " 'death toll due covid climb india total case health ministri sourc pti',\n",
       " 'heard trust close friend polit amit shah suffer isol may god give bhai speedi recoveri god bless ps peopl talk friend nj',\n",
       " 'heart donat earn much contribut cours need govern state n nation unless someth signific right point finger vile word personifi',\n",
       " 'donat relief everyon',\n",
       " 'team decid contribut day salari team also work continu bust relat let',\n",
       " 'let true spirit mother india awaken inner strength fight back room magic belief inner strength abil duti jai hind',\n",
       " 'stop covid wash hand soap sanit cover nose mouth mask handkerchief avoid move outsid follow social distanc',\n",
       " 'coronaviru updat case current case recov updat everi hour',\n",
       " 'respect pm god power infinit rel power much fear corona shown much chant medit name god mani virus like disappear',\n",
       " 'came two stori',\n",
       " 'care safe stay home',\n",
       " 'hello news report social trigger amp chitkara news corona viru report directli shot adesh hospit ambala look',\n",
       " 'great contribut like go long way support fight',\n",
       " 'great appreci someth peopl elimin situat success instead comment oppos politicis time come togeth fight',\n",
       " 'swear r fight pandem st amp nd wala chutiyapa koi rok lo inh',\n",
       " 'wow wow thought china wors creat demand provid suppli provid defect suppli',\n",
       " 'corona updat confirm case activ deceas recov pray god number wont chang anymor',\n",
       " 'privileg liter one like kanika kapoor care public safeti common poor hard work peopl set posit exampl societi',\n",
       " 'today son rachit donat full piggi bank amount rs pm care fund appeal hon prime minist shri modiji proud boy also donat pl make donat',\n",
       " 'hate manutd wash hand thread chant keep safe crisi contribut',\n",
       " 'death toll due climb total case health ministri',\n",
       " 'well street choic let pray rememb film kahan se aat hain yeh log',\n",
       " 'effect',\n",
       " 'okk make extra effort bring back peopl iran uk give galli lash migrant worker decid walk home thing',\n",
       " 'death toll due climb total case health ministri',\n",
       " 'world war sham',\n",
       " 'fund contribut toward covid pandem relief countri pleas contribut pandem situat',\n",
       " 'updat',\n",
       " 'dri cough sneez air pollut cough mucu sneez runni nose common cold cough mucu sneez runni nose bodi ach weak light fever flu dri cough sneez bodi pain weak high fever difficulti breath covid may occur seek medic advic',\n",
       " 'extens gst file due date month februari hindi watch video read articl topic',\n",
       " 'pleas countri pm care fund sir countri',\n",
       " 'quarantin advic play love charger pm day see drop case',\n",
       " 'test everyon help co even test neg chanc develop symptom later within next week later might posit imp test peopl symptom dng right blame',\n",
       " 'migrant daili wage labor make journey respect villag foot follow lockdown amid concern spread delhi jaipur highway saturday',\n",
       " 'sunday breakfast scrambl egg indian style splash tomato ketchup accompani amul chocol banana milkshak',\n",
       " 'pleas help us',\n",
       " 'contribut rs pmcare initi gestur support fight request everyon help gener share one thing lockdown safeti emerg servic r work fine need panic stay safe',\n",
       " 'fast move spread requir ever flexibl time fund alloc quickli need situat evolv learn donat click link',\n",
       " 'request peopl support administr implement lockdown social respons also suggest bring awar peopl maintain social distanc purchas day day commod',\n",
       " 'honor chief minist uttar pradesh time global threat problem intern immigr deepen border state crowd thousand daili wage worker amid lockdown countri',\n",
       " 'pichl moth se chines muslim jharkhand mai hai center govt ne koi dhyan hi nhi diya hai fuck',\n",
       " 'pro tell agre delhi india',\n",
       " 'peopl test posit ahmedabad total peopl test till state gujarat health dept sourc toi',\n",
       " 'sometim wonder amid pandem profit nation seem like china track indirect attack us economi could',\n",
       " 'bed hospit ventil hospit bed set indian armi barmer rajasthan day case must stand salut forc',\n",
       " 'small contribut pm care fund inti prime minist ji thank give opportun serv fellow indian pm sir time bit defeat pleas bit',\n",
       " 'list senior offic govt assign coordin matter strand differ state spread word peopl',\n",
       " 'think happi sinc transport decreas much amid emiss also decreas henc recov contribut solv accept',\n",
       " 'colour bloom resid natur unaffect open sun bright',\n",
       " 'u dream island stay home red skin island',\n",
       " 'meanwhil india southern railway turn coach isol ward sleeper coach need littl chang coach new bed icu wheel may develop',\n",
       " 'follow us',\n",
       " 'saanvi want share tip fight corona fit hoga india tabhi lagega india',\n",
       " 'visual jaipur congress govt rajasthan led shri amp shri properli assist migrant labour want return home due loss job aftermath lockdown',\n",
       " 'correct would final address anticip issu requir phase would complet cr popul ought advers issu pop',\n",
       " 'mega princ donat lakh ccc mana kosam corona crisi chariti committe form provid help cinema daili wage worker crisi great gestur',\n",
       " 'mask amp sanit compani right',\n",
       " 'announc addit rs crore support toward fund addit rs crore announc',\n",
       " 'fulli agre suparno da peopl vote ak last elect elect condit due type cheap polit may enter amp may becom devast',\n",
       " 'realli laud hard work plu innov put bid check spread',\n",
       " 'prime minist seek forgiv countri difficult decis caus hardship peopl especi poor',\n",
       " 'thru dtc buse dump lakh migrant worker u p bihar delhi border thru machin amp rumour monger thu derail amp risk spread amp million human live',\n",
       " 'research came togeth creat set multi lingual resourc explain complex issu launch english konkani odia amp video gujarati haryanvi assames',\n",
       " 'coronaviru bent kill peopl therefor entir human must unit resolv elimin say pm',\n",
       " 'lie lie china play world',\n",
       " 'donat blood maharashtra face shortag blood crisi ahmednagar maharashtra',\n",
       " 'appreci effort tough time receiv order certainli thought feasibl deliv keep good effort serv nation time crisi',\n",
       " 'home remedi ginger juic honey small pinch black pepper lt best flu remedi gt teaspoon thrice daili',\n",
       " 'fight life death battl tough decis necessari say pm modi',\n",
       " 'beat togeth maintain hygien wash hand regularli step outsid save water',\n",
       " 'peopl follow quarantin measur world repent say pm urg peopl mind',\n",
       " 'spanish princess first royal die corona',\n",
       " 'ginger juic honey small pinch black pepper lt best flu remedi gt teaspoon thrice daili',\n",
       " 'indian discrimin indian peopl account call mock name outcast',\n",
       " 'mani soldier fight confin home outsid home front line soldier especi brother sister duti nurs doctor amp paramed staff pm ji',\n",
       " 'pm togeth india defeat lockdown keep well famili safe',\n",
       " 'understand one want break rule deliber peopl say follow difficult protect danger pm modi sourc ani',\n",
       " 'industrialist come across help india fight mohali chandigarh',\n",
       " 'pm invit victim ramagampa teja share experi one one chat teja tell pm nation initi frighten felt reassur doctor hospit staff',\n",
       " 'bit tea cooki watchmen neighborhood',\n",
       " 'happen enough time',\n",
       " 'survivor teja say even get discharg hospit follow hygien includ wash hand',\n",
       " 'take inspir front line soldier fight especi nurs doctor paramed',\n",
       " 'pleas follow rule stay home fight',\n",
       " 'tri make video room whatev think work best way distract mind whatev go plan quarantin time',\n",
       " 'take inspir front line soldier fight especi nurs doctor paramed',\n",
       " 'go live youtub littl bit come part convers',\n",
       " 'stay home stay safe come may vijayanagar india',\n",
       " 'world face worst time ever amp reel challeng situat amp peopl r stay home without work incom irrespons u r ask peopl donat ur driver money u earn till gone',\n",
       " 'guy never chang',\n",
       " 'stage give everi individu home import',\n",
       " 'respect sir small contribut end fight definit overcom situat guidanc sir pleas take care health hope crore peopl countri respect amp love sir',\n",
       " 'total number case countri rise includ cure discharg death union health ministri',\n",
       " 'salut jogind sharma fight famous bowl final india win current work dsp haryana help india fight',\n",
       " 'peopl awar',\n",
       " 'go outsid watch video',\n",
       " 'listen wait speak current press issu concern mass migrat amp step govt take combat',\n",
       " 'ji pay emi also help flight alway nation jai hind',\n",
       " 'given free hand mani serial offend mother earth sign pull show ugli face birthright expect unfair trade practic take strict action',\n",
       " 'coz live street high chanc spread instead make effort help peopl get home safe safe hope messag get mr',\n",
       " 'year old man walk km reach home amid die delhi agra highway saturday morn',\n",
       " 'wish india fight thoroughli ur leadership donat small amount fight',\n",
       " 'year old man walk km reach home amid die delhi agra highway saturday morn',\n",
       " 'govt initi dalla like misplac pr job',\n",
       " 'believ even said dint pass anim human',\n",
       " 'help address',\n",
       " 'azim premiji chairman donat thousand crore corona viru pandem',\n",
       " 'everyth lockdown',\n",
       " 'dr pk mishra princip secretari prime minist form group tackl variou emerg review meet chair dr mishra begin',\n",
       " 'mind power thing fill woth posit thought life start chang',\n",
       " 'spicejet pilot test posit airlin tri find list pilot use apparatu breath analys test despit repeat demand airlin regul suspend ba test',\n",
       " 'thank protect us danger request spray found posit case dharmareddi resid mani hostel pg mani residenti peopl check live track link',\n",
       " 'contrari popular belief small farmer disproportion risk food insecur lack capit invest declin crop divers drive farmer brink event pandem',\n",
       " 'situat unfold us humbl request everyon let get scare number let redoubl effort win battl togeth',\n",
       " 'protect other corona viru covid',\n",
       " 'ladi home compens thing sit home take care also share respons',\n",
       " 'princess maria teresa spain becom first royal die covid',\n",
       " 'take care stretch capabl take care famili neighbour care posit wealth strike everyon feel need worri go read',\n",
       " 'current situat india tackl',\n",
       " 'shhh busi sunday bangalor india',\n",
       " 'littl contribut amp fight need hour everyon pitch beat deadli done bit',\n",
       " 'approxim high networh vvip india minimum donat crore pledg calcul number',\n",
       " 'pm acknowledg contribut bank sector employe test time',\n",
       " 'bank loan provid follow appropri measur onlin facil serv say prepay requir meet custom pleas take due care teach respond tough time',\n",
       " 'public appeal made yr old kid aariv chadha',\n",
       " 'happen delhi loyal politician idiot',\n",
       " 'kunal karmra cannot good peopl instead neg tweet ji think beyond utilis energi good caus',\n",
       " 'mind power thing fill woth posit thought life start chang',\n",
       " 'prevent spread',\n",
       " 'time bit help defeat done part request everyon contribut',\n",
       " 'aspect relat',\n",
       " 'high time stay strong protect pleas stay home stay safe everyon get golden opportun serv nation stay home pleas stay home corona viru die thank',\n",
       " 'stay home stay safe',\n",
       " 'donat small amount assam arogya nidhi fight pandem behalf father jayanta borah narayanpur hs school see hb pin tweet want donat',\n",
       " 'lucki serv nation join defenc forc get opportun never let go chanc let join hand togeth fight',\n",
       " 'live form fight right',\n",
       " 'indian youth congress open nationwid helplin state need form assist pandem wherev need help reach us helplin provid shall overcom',\n",
       " 'peopl plz stop play polit bekar hum log ghar pe baith ke ek dusr ki galtiyan nikal rahe hai prime minist chief minist tri best stop pandem',\n",
       " 'custom network carrier label via vodafoneindia idea cellular aundh road',\n",
       " 'chandigarh villag follow social distanc chandigarh',\n",
       " 'resid odia strand outsid state pleas contact number given immedi support',\n",
       " 'psychologist recommend isol news konw everyth need track death toll crikt look addl info avoid send fatalist note listen music home low game children tell stori',\n",
       " 'india salut forefront fight prime minist',\n",
       " 'small contribut toward cm relief fund let contribut let fight',\n",
       " 'bad idea check strong independ woman women',\n",
       " 'thank ji walon ki yaad aagai urgent sanit atm sanit groceri store give option deadli carrier',\n",
       " 'increas social distanc reduc',\n",
       " 'princess spain becom world royal famili member die covid',\n",
       " 'day quarantin meet new pet',\n",
       " 'littl goe long way',\n",
       " 'worldwid statist confirm case recov death unit state statist confirm case recov death',\n",
       " 'home minist ji museebat ki ghadi aap kahan chale gay countri need word action',\n",
       " 'effort world punjabi organ led ji provid ration kit k needi time highli appreci',\n",
       " 'poor famili small donat ji dhanyavad',\n",
       " 'recoveri near lac anoth week social distanc n restraint avg life span week individu swing battl much avg life span sake amp nation let togeth',\n",
       " 'imagin entir india peac follow curfew nice except delhi like alway surpris bast kejriw',\n",
       " 'good job yogi proud swift effici depend',\n",
       " 'whenev need authent news nashik visit twitter page help time thank nashik news',\n",
       " 'shame kejriw damag everyth modi ji handl well far lesson never let monkey rule',\n",
       " 'surpris disappoint even definit drug treatment author readi tri integr manag lose tri',\n",
       " 'ndtv report first report cr peopl infect india action taken channel',\n",
       " 'knew year go wrong',\n",
       " 'bangalor univers ask examin fee amp fine delay last date th april fine student unabl pay time even get food properli govt think date extens need',\n",
       " 'deadli viru claim peopl across world new zealand report first death due south korea report new case addit death china report new case import',\n",
       " 'wit best moment come day need stay home today stay strong stay aliv',\n",
       " 'sir along india express gratitud philonthrop effort fight',\n",
       " 'u break chain stop v r spread let pleas maintain social distanc p us announc lucki got face p',\n",
       " 'year old posit man travel two train pray mosqu attend wed infect four other',\n",
       " 'shall pass',\n",
       " 'natur reboot',\n",
       " 'may final world war countri fight save dynasti',\n",
       " 'still wonder babi amp',\n",
       " 'midst global covid health crisi earth hour mark moment solidar planet global commun unit organ event digit join us saturday march pm local time',\n",
       " 'mr pm contribut fight request everyon part easiest method upi pmcare',\n",
       " 'let see mani box tick absolut love nomin friend fellow book lover share post see hit bingo',\n",
       " 'put togeth million abandon open patent open use research entrepreneur student solv public problem includ pl use share thank',\n",
       " 'everi one must come forward fight covid',\n",
       " 'sometim mean make good gorg leftov within coconut shell yash farm',\n",
       " 'effect solut pandem anybodi still advis kill peopl ignor',\n",
       " 'place beyond call',\n",
       " 'creativ nephew law',\n",
       " 'small contribut make differ pleas come forward donat contribut rupe inform',\n",
       " 'tell someth convinc tell cabinet go among make believ',\n",
       " 'possibl one best poster explain effect wash hand avoid scienc tell fear cannot',\n",
       " 'xi jipe delhi made disast delhi spread hole india',\n",
       " 'done bit surround today littl bit help go long way speechless soul donor abroad use link support case gpay',\n",
       " 'put togeth million abandon open patent open use research entrepreneur student solv public problem like thank zaigham devika thru bhatnagar fellowshp',\n",
       " 'retweet guy pl goa need help',\n",
       " 'year old girl test resid jaripatka area rel khamla patient condit stabl',\n",
       " 'secunderabad',\n",
       " 'demand time must page otherwis one use viru like tool destroy economi countri believ use throw polici one could friend everi countri food',\n",
       " 'ye',\n",
       " 'thank ji walon ki yaad aagai urgent sanit atm sanit groceri store give option deadli carrier',\n",
       " 'special thank',\n",
       " 'dust settl post corpor landscap industri would chang dramat look cost save would put emphasi impact deepli commerci space',\n",
       " 'pm care donat',\n",
       " 'health care profit industri materi gain everyth compass speech although health profession great servic present time control hope perform continu futur',\n",
       " 'long walk jobless migrant head home bu',\n",
       " 'nashik posit case found take addit precaut veget vehicl return apmc mumbai',\n",
       " 'posit patient check n check free viru seem punish celeb wrongdo recov day',\n",
       " 'alway opportun make differ apprehens onlin class never thought would conduct week come togeth gratitud amp particip',\n",
       " 'vendor carri veget farmer field consum hailakandi district assam initi agricultur depart',\n",
       " 'use inform pass surgeon friend',\n",
       " 'great idea work home stay safe effici',\n",
       " 'gujarat j amp k report new death maharashtra report new case total case cross india',\n",
       " 'hearti congratul brilliant work develop test soon may lord bless famili includ youn daughter',\n",
       " 'ask much hope',\n",
       " 'today aviat team refuel medic rescu flt af oper pawanhan make sure emerg suppli avail need hour',\n",
       " 'major popul stay sane much requir wish stay safe',\n",
       " 'seen homeless strand help reach shelter',\n",
       " 'dont spread hate kind world need polit agenda matter',\n",
       " 'delhi delhi',\n",
       " 'karnataka part india even pakistan would open border request scenario death kerala deni entri karnataka medic emerg shame senseless ppl rule karnataka',\n",
       " 'keep patienc go soon',\n",
       " 'enjoy natur',\n",
       " 'done part contribut everyon right',\n",
       " 'india pm modi announc care fund donat india war covid via namo app',\n",
       " 'thank dr pavithra valuabl inform',\n",
       " 'ip assici decid contribut one day salari cm relief fund one day salari pm relief fund fight anjani kumar ip amp media',\n",
       " 'crpf along goa polic station mapusa kept strict vigil citizen come road ban violat rule',\n",
       " 'namaskar stay home ventur corona lurk place unawar let put effort togeth commun pull brake phase transmiss',\n",
       " 'card pay sin',\n",
       " 'good job anna jan great proud fan',\n",
       " 'person loan emi emi go cut hold due salari hold money emi',\n",
       " 'senior citizen year higher risk sever ill due low immun advis take extra care amp regularli monitor symptom like difficulti breath',\n",
       " 'namaskar stay home ventur corona lurk place unawar let put effort togeth commun pull brake phase transmiss',\n",
       " 'attn emerg medic item purchas pl touch x work pleas dont discuss scam maximum possibl technic whether repli immedi mrep navaskh',\n",
       " 'govern alon india wait disast',\n",
       " 'ms dhone donat lakh fake news also filthi rat countri even donat lakh much guy donat shut fookin mouth anyth broke shithead',\n",
       " 'shop pt get medicin plz help',\n",
       " 'death toll go number case rise week back god save us',\n",
       " 'muslim cremat hindu gentleman whose immedi famili memeb amp hindu neighbor abandon fear die due u call',\n",
       " 'easi time everyon rise polit save human collect prayer help us surviv emerg victori',\n",
       " 'better suspend hand entir spread rather contain know',\n",
       " 'arrang need done destin point bihar fight done serious must ensur complet complianc monitor',\n",
       " 'count thmarch',\n",
       " 'mla organis minut self test kit excel initi rapid test need hour',\n",
       " 'break news burundi african countri without case coronaviru minist health ask secret behind zero case covid say simpl test kit',\n",
       " 'btw say sinc year regardless soon start onlin facil never done thought forc final still want stay believ ineffici process',\n",
       " 'worth read',\n",
       " 'sir mani citi control mani rural amp semi urban maintain social distanc pleas need mani market today sunday huge crowd amp gather',\n",
       " 'think carri deep sens valu critic focu humanis',\n",
       " 'accord wei guixian shrimp seller among first peopl test said would kill fewer peopl govt act sooner',\n",
       " 'leav time smile smile face bring smile face other',\n",
       " 'directli review situat princip secretari dr p k mishra form group tackl variou emerg review meet start pmo meet like continu whole day',\n",
       " 'indian air forc engag support avail critic medic suppli tackl spread transport aircraft includ c c super hercul dornier use suppli medic equip per requir icmr agenc iaf',\n",
       " 'market open judgement chandigarh prove serious bureaucrat polit coz doctor frontlin warrior judg bureaucrat go treat patient',\n",
       " 'one name',\n",
       " 'mask make compani sponsor articl',\n",
       " 'ensur continu print electron media view',\n",
       " 'least labour strand kurnool guntur highway tripuranthakam mandal district saturday prakasam district polic refus let district per guidelin combat',\n",
       " 'canon love',\n",
       " 'wash hand soap water often keep viru bay',\n",
       " 'municip corpor bmc rope deliv qualiti hygien food citizen onlin',\n",
       " 'protect other stay safe share inform help us help',\n",
       " 'n focu health amp remain posit skip gym post ng amp tri garden amp pursu full time amp wil also start video seri soon educ everyon time suit n show wat u perish upgrad',\n",
       " 'doctor nurs seen white cloth hospit protect us danger hour crisi policemen run street form god whenev see hospit staff polic offic clap',\n",
       " 'small contribut nation fight',\n",
       " 'namashkar everyon fight pandem togeth pleas listen share group',\n",
       " 'record lowest pm level month amid expert say improv air qualiti observ',\n",
       " 'media guy freedom speech say',\n",
       " 'big thank senior colleagu congress ji constantli patrol constitu make sure well suppli amp enforc social distanc remain approach total unbias learn lot today',\n",
       " 'record lowest pm level month amid expert say improv air qualiti observ',\n",
       " 'maintain social distanc suffer close one connect us great content',\n",
       " 'fight let chant sutra take water fill bowl dip ur hand chant sutra sprinkl drink world peac amp posit sutra vocal guruji champak mehta speech',\n",
       " 'countri show resolv',\n",
       " 'one mistak china suffer entir world world boycott china time',\n",
       " 'union minist donat one month salari pm relief fund amp also releas rs crore mplad fund help govt contain',\n",
       " 'dear ji support appreci thank help god bless',\n",
       " 'stand togeth support india battl donat inr crore tough time urg defeat unpreced pandem togeth thank',\n",
       " 'sir also done part small donat thank',\n",
       " 'clean hous appear big',\n",
       " 'scenario suffer horrif probabl seem major drift evolut go name crush keep aliv',\n",
       " 'prepar knowledg key beat',\n",
       " 'year old patient pass away mumbai admit yesterday follow sever respiratori complic also hypertens patient seventh corona viru relat death maharashtra',\n",
       " 'confirm case death western pacif region manila time march data region check daili sitrep',\n",
       " 'time peopl push short hand deep pocket pledg herewith bit pleas bit jai hind',\n",
       " '',\n",
       " 'beauti done take away natur natur way take reveng',\n",
       " 'madam strongli believ volunt job grate thank andhra pradesh scare come home check daili health statu normal peopl self quarantin member jagan anna believ good today happen',\n",
       " 'sure long stand unit',\n",
       " 'one geopolit anoth non polit noth draw infer photo speak life memori',\n",
       " 'battl start vs win variou releas number death due simultan',\n",
       " 'financi stimulu also posit outlook problem help recov overcom defeat scenario good job',\n",
       " 'beauti done take away natur natur way take reveng',\n",
       " 'dog fight bone dog two leg bone epic failur',\n",
       " 'g india henc impact corona viru less nation g worst',\n",
       " 'stay home',\n",
       " 'stand firm patient organ blood donat camp doctor employe apollomed hospit particip practic preach friend need friend inde',\n",
       " 'peopl test posit total peopl test till state',\n",
       " 'check pleas fight addit battl',\n",
       " 'viru vs immun trade war capit vs commun domin begin rd ww whatev new collect conscienc requir',\n",
       " 'corona viru make much disast america cross confirm casr itali death increas quickli viru peopl suffer k death',\n",
       " 'birthday celebr lockdown small creativ homemad watermelon cake spend time love one stay home stay safe',\n",
       " 'chines govern',\n",
       " 'accord wei guixian shrimp seller among first peopl test said would kill fewer peopl govt act sooner',\n",
       " 'lot similar fail amp present impos fight amp badli amp hit hard labour work class friend',\n",
       " 'safe healthi stay home',\n",
       " 'stay home stay safe',\n",
       " 'paint year thank corona naitri love awesom creativ daughter thank god doctor thank god polic critic situat',\n",
       " 'despit score labour around delhi flee nativ place intensifi spread henc administr strictli implement section suppli food amp shelter',\n",
       " 'request everi individu pleas stay home safe everi singl contribut save countri',\n",
       " 'secretari gener say idea use diseas weapon view repugn',\n",
       " 'get inform updat',\n",
       " 'deadli viru claim peopl across world new zealand report first death due south korea report new case addit death china report new case import',\n",
       " 'extraordinari time need extraordinari measur enter stage corona time india brave show commit social distanc stay indoor ever collab wth',\n",
       " 'use road traffic drone amp satellit identifi hotspot amp crowd detect provid info polic handl situat deploy militari amp para militari handl tougher situat',\n",
       " 'enjoy famili day',\n",
       " 'situat control everyon togeth fight maintain distanc',\n",
       " 'death itali spain china iran franc us uk netherland germani belgium switzerland south korea brazil sweden turkey indonesia portug austria philippin',\n",
       " 'spare time camera',\n",
       " 'alway appreci person apart member follow wise person type tweet post high time india urg worldwid time',\n",
       " 'contribut bit ji pm care fund let save live fight crisi togeth',\n",
       " 'parti presid mp dr today releas addit amount rs crore srinagar base hospit amount equal distribut among three hospit nation confer',\n",
       " 'total person test today far yr old jaripatka girl brother jaripatka patient empress citi resid came delhi',\n",
       " 'great analysi base lesson black death could impact interest rate wage consum behaviour inflat post world also find repetit manual work could attract premium',\n",
       " 'even lockdown flatten curv spread look migrant road let expect mess plan',\n",
       " 'sme frnd collect money prime minist nation relief fund shld wnt prove citizenship transfer',\n",
       " 'forc ru india',\n",
       " 'engag support avail critic medic suppli tackl spread aircraft includ c c super hercul dornier use suppli medic equip per requir icmr agenc',\n",
       " 'one best footbal fighter fight win amp share experi',\n",
       " 'r favorit small contribut toward nation defeat',\n",
       " 'stay home famili human',\n",
       " 'protect other stay safe share inform help us help',\n",
       " 'watch tv today savlon add say ladeng corona viru ki jung scene goe young school girl kais baba school shut market team project famili fight corona sanit',\n",
       " 'forc ru india',\n",
       " 'know come close contact confirm case share inform help us help togeth fight',\n",
       " 'fever clinic set govt amp across place first contact point case begin oper',\n",
       " 'ke side effect',\n",
       " 'done bit amp made small contribut request everyon pleas donat pm care fund amp encourag other everi contribut valuabl let nation',\n",
       " 'everi biker like',\n",
       " 'earli morn sunday use beauti',\n",
       " 'stay home stop spread shall fight togeth stay awar stay safe care fear stay home stay safe',\n",
       " 'someon gotta tell diy pregnanc test proper lab test test',\n",
       " 'spicejet pilot test posit airlin say pilot last flew march chennai delhi sector quarantin post',\n",
       " 'irdai relax reinsur plan insur co submit fy reinsur programm may instead april',\n",
       " 'sir particularli donat u know bihar control happen',\n",
       " 'success complet cours collabor amp',\n",
       " 'whatev may case noth preciou life understand situat across globe support lockdown save india',\n",
       " 'quarantin day commun guidelin word line',\n",
       " 'stay home follow guidlin issu possibl contribut everi small big contribut count way fight pleas gather name socialwork nobodi know infect',\n",
       " 'indian youth congress open nationwid helplin state need form assist',\n",
       " 'well said',\n",
       " 'dear know u day u saw alkapurtownship',\n",
       " 'hear live bedat pleas ask expert feel ill hear pin insert lung whole bodi true',\n",
       " 'let beat viru stay indoor creat art particip support india fight',\n",
       " 'fool tie rope barricad tri go home got entangl die',\n",
       " 'request everyon contribut per abil citizen assist relief emerg situat fund pm care fund help fight',\n",
       " 'wooow sir kya baat miss miss smile face let togeth fight hum hong kamyab',\n",
       " 'want bring attent one fin sound resid take wrong benefit bpl facil want benefit pass poor time cost',\n",
       " 'case today next week gonna crucial',\n",
       " 'iq bjp',\n",
       " 'juli kanika kapoor test posit th time',\n",
       " 'donat one thousand one rupe pm care fund face covid accord financi situat difficult time stand ji',\n",
       " 'order contain spread staff arrang solut public rythu bazar citi sunday',\n",
       " 'temperatur delhi expect touch c april amp also signific number day lockdown amp still spread get control look sky bcoz beauti thing left world',\n",
       " 'donat littl contribut pm care fund fight',\n",
       " 'want go home time know famili secur without time peopl r migrat disast one say correct make huge risk spread',\n",
       " 'corona viru endgam thano snap need time machin snap back',\n",
       " 'keep good work',\n",
       " 'want dedic song stay away human follow song would dedic corona viru leav comment',\n",
       " 'one highest death ratio mortal rate world corona half popul malnourish balanc nourish',\n",
       " 'street desert also mention hon ble take care amp around retail outlet',\n",
       " 'pm ji request everyon compli lockdown without difficult save scourg via namo app',\n",
       " 'mean make sure understand concern bangalor india',\n",
       " 'challeng pm ji sir sir pleas accept click pictur messag also extend',\n",
       " 'thank lot brother kind gestur share work love soul join us supprt',\n",
       " 'ye gayatri mayb mani senior citizen need help pl tag also helplin',\n",
       " 'ram hyderabad recov share experi listen',\n",
       " 'municip commission tukaram mundh appeal citizen person test far',\n",
       " 'let continu studi access differ platform e studi',\n",
       " 'sampl year old woman die saturday test posit maharashtra toll reach offici',\n",
       " 'would request actor amp actress donat caus instead show cook amp gym etc etc would also request media brother sister show',\n",
       " 'safe happi stay home watch full video youtub',\n",
       " 'also hand check rs lakh month salari anoth check rs thousand month pension wife smti monika bora contribut amount resid commr govt assam fight',\n",
       " 'india democrat socialist secular republ ask peopl donat combat govt explain measur took address issu poor migrant labour daili wager work class etc socialist duti humbl opinion',\n",
       " 'read thought yourquot app',\n",
       " 'issu order district collector municip commission surveil contact trace contain',\n",
       " 'lockdown mean',\n",
       " 'retweet amp send namast belov one spread awar greet everyon namast way go let spread awar fight pandem away',\n",
       " 'miss episod',\n",
       " 'secunderabad',\n",
       " 'precaut covid avoid touch eye nose mouth stay home india stay safe india',\n",
       " 'littl bit amount donat pmnrf defeat',\n",
       " 'dr nitesh share keep mood upbeat combat menac hear view',\n",
       " 'mountain wait monument beach amp safari matter us n famili safe destin happi see pass unpreced time',\n",
       " 'dear',\n",
       " 'also maintain within famili india two benefit case famili member get infect outsid pass member reduct birth rate countri',\n",
       " 'us report death europ death toll shoot past mexico ask citizen stay home month latest',\n",
       " 'first time ji suffer demonet gst jobloss amp need pm apolog',\n",
       " 'keep sir',\n",
       " 'dear indian citizen stuck countri help whole countri appreci peopl stuck countri move toward hometown walk help',\n",
       " 'continu complicit till ban exot wet market consumpt bat continu open one form',\n",
       " 'enjoy sunshin support lockdown let fight',\n",
       " 'lakh railway employe donat rs crore pm care fund help combat exclud minist contribut fund',\n",
       " 'student amount budget jai hindi',\n",
       " 'pleas retweet donat fund',\n",
       " 'wait happen one form jump fruit bat civet next long consum bat form exot creatur like continu suscept variat viru',\n",
       " 'pleas stay home pleas follow avoid thank',\n",
       " 'rest home better rest peac',\n",
       " 'govern respons even public need understand situat amp react tri best protect everi singl citizen india u true leader stand protect everyon frm polit',\n",
       " 'sad om shanti differ young amp old',\n",
       " 'polic regist fir across rumour monger spread',\n",
       " 'ji look current situat india time without make delay demand respons citizen',\n",
       " 'small contribut toward india turn donat pm care fund per strength win jai hind jai bharat',\n",
       " 'hear one benificiari famili near',\n",
       " 'look like test kit use time',\n",
       " 'home made prawn biryani ka tai tai fish eat well',\n",
       " 'prioriti bain amp compani guid respond keep worker connect guard attack fortifi core system increas team engag plan evolv scenario',\n",
       " 'migrant labour given respect buse ensur social distanc jaipur rajasthan cm deserv full credit',\n",
       " 'quit evid violent polic respons across state curb peopl movement came singl sourc order follow command control amp administr acumen expos approach nation emerg spend billion weapon year',\n",
       " 'puppi hand wash video stay home amp stay safe',\n",
       " 'recal sunday today holiday lmao',\n",
       " 'take care health',\n",
       " 'thank sir special thank',\n",
       " 'sirji donat fund richest polit parti world money mla horsetrad amp hq build',\n",
       " 'stay home bring hidden cook tri gobi fri believ tasti',\n",
       " 'hon ble pm sir small contribut fight',\n",
       " 'break germ cycl',\n",
       " 'sing ru chennai india',\n",
       " '',\n",
       " 'term use onset strongli recommend avoid contamin other yet may sound like death knell million daili wage peopl',\n",
       " 'see differ rich amp poor one care poor peopl walk hundr mile reach destin rich rich poor poor',\n",
       " 'first offic spicejet test posit test report came march oper intern flight march last domest flight oper march chennai delhi amp sinc quarantin home',\n",
       " 'day day',\n",
       " 'import disciplin',\n",
       " 'peopl stand queue adher rule buy famou mysuru road sunday',\n",
       " 'day watch malayalam movi viru well direct true depict today time',\n",
       " 'much money pour fight epidem need oversight money spent otherwis year line sure look unravel',\n",
       " 'break chain let us practic social distanc avoid crowd place take precaut protect societi',\n",
       " 'u get benefit retweet',\n",
       " 'worri noth gonna happen affect immun eat shit go hell rest safe check tweet god bless',\n",
       " 'full video insta',\n",
       " 'isol coach prepar indian railway fight pandem',\n",
       " 'understand one want break rule deliber peopl say follow difficult protect danger pm',\n",
       " 'happi whatev situat',\n",
       " 'deliveryman mr shyam narayan gupta ravindra hp ga centr lalganj mirzapur uttar pradesh fulli commit time deliveri lpg custom even lockdown period',\n",
       " 'get wors aveng infin war follow antman wasp captain marvel justic leagu follow batman v superman dawn justic aquaman movi kill spare',\n",
       " 'patient test posit confirm div commsr one yr daughter jaripatka resid amp male brother paralyt rd one empress citi tower travel delhi march',\n",
       " 'everi indian n n b like',\n",
       " 'friend given phone repair lockdown',\n",
       " 'introvert feel suffoc quarantin declar',\n",
       " '',\n",
       " 'call parti meet attend leader amp leader pic courtesi',\n",
       " 'ji copi past save time ab ki kon samjaay',\n",
       " 'fail yet think time use polit tool compromis like everytim big word low strategi',\n",
       " 'world',\n",
       " 'small busi due corona',\n",
       " 'could possibl citi like wuhan becam secur well sanitis citi within day realli question part antidot yet anyon answer pleas',\n",
       " 'way govern found fight play antakshari telecast ramayana taali thaali',\n",
       " 'mani foreign return spread viru pleas look matter',\n",
       " 'least peopl india surviv lockdown unlik sweden peopl still parti mood would tough swain like u',\n",
       " 'part pleas even small donat count ss motiv peopl help',\n",
       " 'dear cm may god give courag offic work relentlessli peopl maharashtra fight devast outbreak pl accept tini gestur',\n",
       " 'togeth time understand crucial fight human race adapt grow gibot would like share experi abl maintain product team',\n",
       " 'small contribut fight',\n",
       " 'air india pilot associ ask suspens breath analys test light spicejet pilot found droplet aerosol infect pilot may hamper health healthi time',\n",
       " 'air condition enhanc air qualiti filter air impur give safer breathabl air home',\n",
       " 'sir difficult time govern unabl give support industri electr bill waiver ang option pay later april end current domest connect pl need earliest',\n",
       " 'god great take time annihil everyth matter power',\n",
       " 'china broke lookdown impos govern china vaccin cure covid countri ask china disclos although china must disclos',\n",
       " 'join fight taken stay home save live pledg commint toward keep countri safe also take pledg',\n",
       " 'corona viru outbreak mani us money pay bill request pleas need us peopl know pay onlin even suffer shortag food',\n",
       " 'violat sent day quarantin govt',\n",
       " 'u r biggest deadli bad loan bank lakh crore year ur rule went lakh crore still blame weak indian bank system kitna neech giraavog india ko',\n",
       " 'awar video follow guidelin watch',\n",
       " 'also maintain within famili india two benefit case famili member get infect outsid pass member reduct birth rate countri',\n",
       " 'amaz respons amp bit fine empti street amp activ help line elderli continu compli lockdown norm like entir day way ahead war',\n",
       " 'india alreadi phase heal hope money reach right hand right person right work hope health care amp educ get prioriti india upcom budget futur',\n",
       " 'covid aur episod fazeelat us shaikh jave usman rabbani must watch circul video amp lectur subscrib youtub channel',\n",
       " 'abl leadership sir tri best protect citizen known anti social element unknown kudo entir forc tri best save us sastanga pranam',\n",
       " 'singl import action take fight order protect india save live',\n",
       " 'one side side incompet govern',\n",
       " 'maintain physic distanc',\n",
       " 'well done',\n",
       " 'team set feed uncondit one day call duti seek bless support amp kind today team amtmindia support case gpay',\n",
       " 'peopl like safe problem let come outsid break spread plse asshol home live life love fuck migrant',\n",
       " 'sad death cross cross life',\n",
       " 'complain get bore wholesom serv truth tri digest',\n",
       " 'main stream media tell truth corona q dr biswaroop roy chowdhuri via checkout think logic',\n",
       " 'time understand countri suppress voic citizen control inform bane entir world',\n",
       " 'privat co shut amp staff bound feel brunt paycut amp layoff firm ask employe wfh amp feel distress healthcar sector toe expos risk',\n",
       " 'disinfect spray road clean variou locat bengaluru',\n",
       " 'stay home friend',\n",
       " '',\n",
       " 'spread',\n",
       " 'bro donat lack tfi chariti regard lead garu',\n",
       " 'om chant power beez mantra travel marudhar chakra mouth transit kind like etc lose power',\n",
       " 'mumbai citi bought standstil coronaviru covid photo courtesi palava citi opportun',\n",
       " 'forecast epidem india plot suggest three week lockdown start th march enough prevent resurg wherea singl day lockdown reduc case number',\n",
       " 'miss ride tour wheel',\n",
       " 'forens pathologist bewar covid live blood death',\n",
       " 'nd phase jaiswal yuva munch dimapur distribut homeless needi fli bridg',\n",
       " 'time practic social econom distanc',\n",
       " 'thread fake home remedi inhal steam sea salt orang peel prevent remedi covid yet claim post social media user scientif proof',\n",
       " 'turn backslid children saith lord jeremiah',\n",
       " 'good work team sanitis residenti area koramangala th block',\n",
       " 'great initi',\n",
       " 'end',\n",
       " 'still crucial time ignor peopl stuck religi hatr shame',\n",
       " 'stay home stay healthi dayslockdown day india fight corona hometown sundhiyamau ram nagar barabanki popul k crowd road zero',\n",
       " 'pleas consid donat amount help need',\n",
       " 'want seen like ladi pictur way keep away',\n",
       " 'let fight togeth',\n",
       " 'imagin famili member ventil even see meet imagin love breath anyth imagin even cri viru much pain even imagin plz plz stay home',\n",
       " 'one person done absolut stellar work help feed rescu coordin crisi india tajind bhai brilliant bhai aapko bahut dua mili hain stay bless',\n",
       " 'hey want learn host regular session channel click link',\n",
       " 'temperatur degre celsiu chanc increas temperatur degre celsiu chanc accord univers',\n",
       " 'real life',\n",
       " 'scene held respons peopl india failur bureaucraci system collaps far medic servic effect seriou',\n",
       " 'import valid whatsapp content forward',\n",
       " 'found interest articl',\n",
       " 'pleas vir u break chain',\n",
       " 'meaning messag much relat current situat',\n",
       " 'great see innoc small kid come forward difficult time ji everi contribut count',\n",
       " 'full form',\n",
       " 'think peopl arrogantli dismiss covid seriou danger ponder arrogantli dismiss judgment day',\n",
       " 'definit conclud gone rogu attack brain',\n",
       " 'chines conspiraci world leadership true deal',\n",
       " 'punjab haryana hc upheld ut administr decis open shop essenti item pm dispos pil file ut decis',\n",
       " 'join openwho free multilingu open access learn platform health emerg learn public health expert topic includ risk commun infect prevent amp much join us today free great opportun',\n",
       " 'pleas give month free electr discount bill month help poor genuin request',\n",
       " 'prevent better cure prevent spread step',\n",
       " 'world reel chines busi amp run take countri busi',\n",
       " 'india jitega stay home safe life',\n",
       " 'answer quora june',\n",
       " 'engin student creat india first district wise covid tracker read articl sourc india today',\n",
       " 'akhya varshney stsonginworldwidewith beautifulmessagebi yearoldgirlshar',\n",
       " 'happi give lend hand deserv famili pannimadai needi famili anaikatti tribal villag groceri support',\n",
       " 'want bring attent one fin sound resid take wrong benefit bpl facil want benefit pass poor time cost',\n",
       " 'akhya varshney stsonginworldwidewith beautifulmessagebi yearoldgirlshar',\n",
       " 'case increas india',\n",
       " 'abvp kolhapur distribut free food student live citi area affect due',\n",
       " 'support stay home help maa household chore said import',\n",
       " 'perman time spot develop place year ago becom place',\n",
       " 'heart give',\n",
       " 'littl contribut side accord capabl',\n",
       " 'care guest worker kerala host larg number worker indian state state consid guest worker measur taken ensur secur well senior ia offici assign coordin effort cm',\n",
       " 'r edg destruct',\n",
       " 'direct hour late quick respons essenti govt increas risk commun spread',\n",
       " 'name pawan da address bagpat road merrut uttar pradesh',\n",
       " 'shri write hon ble pm regard amp issu entail extend support fight',\n",
       " 'inspir stori minal bhosal deliv india first test kit cost rs per test rs import one hour later deliv babi salut',\n",
       " 'social distanc ki chu di padi h yaha toh prompt action necessari help reach destin make countri safer',\n",
       " 'confirm case outsid china look scari usa watch anim video',\n",
       " 'patient contact monitor symptomat contact hospit isol amp asymptomat contact home isol surveil travel locat made precautionari step taken control spread',\n",
       " 'modi fie rule fight perform specifi ritual twice morn watch ramayana eve watch mahabharata worri pay per view free air hismast svoic dd',\n",
       " 'day post packet prepar maa sunita granni pack help pkt ps geeta coloni migrant pkt anand vihar isbt',\n",
       " 'pleas ensur strict lockdown need use polic forc larger public interest',\n",
       " 'small contribut toward belov ji fight agar mera koi sourc incom hota toh may bhi kuch dhan rashi rashtra ke sankatk aapk hato de pata',\n",
       " 'marriag hall made quarantin patient ampl safe distanc avail',\n",
       " 'red wattl lapw pair practic social distanc amp',\n",
       " 'final indian compani mylab pune success made test kit cost import kit rs bbc news coronaviru woman behind india first test kit',\n",
       " 'today give confid abundantli combat thank front warrior encourag peopl talk cure patient time action ask apolog inconveni due win leadership',\n",
       " 'recent time whichev movi watch multiplex coincident movi amp happi see given money right person',\n",
       " 'free food distribut redhil divis bjp team nampal constitu respond call nation presid',\n",
       " 'small contribut side urg citizen countri contribut fight',\n",
       " 'done part countri combat citizen india must come forward amp donat toward pm care',\n",
       " 'tough time pleas request time come educ rel friend nearbi stay home import us prevent break chain mass effect countri',\n",
       " 'face almost though ministri extern affair subscrib view start biolog weapon check press releas',\n",
       " 'leech go extent call damn thing fraud done pm govt boycott leech help whatev shall come strong ever fight one ye fight amp leech like',\n",
       " 'care',\n",
       " 'smell flower listen bird sing smile',\n",
       " 'worst infect larg part popul still continu guy punish behaviour act time emerg',\n",
       " 'even troubl time help differ',\n",
       " 'religion wait posit respons scienc need support govern uniti divers',\n",
       " 'small contribut fight',\n",
       " 'thank health worker essenti servic provid govern india govern leadership team across globe stand togeth fight covid possibl pleas donat pm care fund',\n",
       " 'true stori chip',\n",
       " 'rabi harvest like pick come day govern agri research bodi icar ask farmer follow social distanc safeti precaut handl farm machin labour field',\n",
       " 'action u taken good noth polic worst blot forc tell us u irrespons polic commission u control personnel',\n",
       " 'across world somewher role dubiou hide threat china ko maro l',\n",
       " 'advisori issu today state nd union territori gather daili labour state district respons consid dm sp homeministri',\n",
       " 'lik snake place u never thought n danger u see p ji job keep us love one safe smart stay home late viru smarter',\n",
       " 'icar lab test',\n",
       " 'proud indian compani mylab pune india develop test kit success duli approv concern author cost rs import kit thank brave ladi minal bhosal virologist see link',\n",
       " 'appeal prime minist narendra modi combat paramilitari forc personnel contribut one day salari total rs crore fund express gratitud home minist amit shah',\n",
       " 'pleas take care',\n",
       " 'posit',\n",
       " 'scientist still claim human readi pandem start take care mother natur serious',\n",
       " 'timelin india start fight well ahead mani develop countri',\n",
       " 'anyon face sever mental health stress due ongo outbreak call nimhan helplin',\n",
       " 'believ doctor keep test patient specif time recoveri phase make sure person bodi consecut test come neg person declar recov',\n",
       " 'peopl want listen opinion time show patriot toward nation countri need help right moment show mirror one thing learn',\n",
       " 'one think kill anim bird feed evil food lust burden planet tast minut endang entir mankind like leav spare',\n",
       " 'educ respect current scenario littl bit understand collect prevent better prepar pandem time',\n",
       " 'help needi',\n",
       " 'gift exploreml team hard time hit would like celebr proudest achiev becam facilit definit one greatest experi life thank',\n",
       " 'two posit one total case pune',\n",
       " 'nice',\n",
       " 'mayor smt vanita rane bar post suspend parti give permiss attend massiv wed crucial time boy also present may infect hundr peopl',\n",
       " 'possibl figur fals china got medicin plan viru attack china',\n",
       " 'pm modi toward indian tradit medic system ayurveda yoga unani siddha homeopathi ayush conduct evid base research cure corona outbreak',\n",
       " 'anand vihar bu termin nationwid lockdown due coronaviru pandem new delhi anand vihar bu stand',\n",
       " 'love mother stay home',\n",
       " 'donat kg rice zone thank donor nithya anoop portia karthik nitish sai priya satish gautam work help anyway possibl us',\n",
       " 'human train pet sit amp stay one place amp ironi stay place well built call home',\n",
       " 'take care mental health well outbreak get help concern nimhan see detail',\n",
       " 'islam scholar spread propaganda whatsapp name',\n",
       " 'sinc one among trust news fell hand corrupt pandem plan attack china',\n",
       " 'stay home',\n",
       " 'student given applic lodg f r concern ps hussainganj shree arvind kejriw cm delhi minist offic pl lodg f r',\n",
       " 'webinar impact covid year end closur log link march pm particip webinar',\n",
       " 'offer unverifi home remedi tackl viru float fake advisori ask peopl avoid certain food indian phone flood misinform',\n",
       " 'clean hand envri hour',\n",
       " 'bodi',\n",
       " 'respect',\n",
       " 'dozen diseas wax wane season',\n",
       " 'even grappl oper aspect crisi mani leader bring beginn mind experi discov sliver opportun prepar post world',\n",
       " 'tt get offens pl immun got vaccin world yet know',\n",
       " 'make life give behalf fan donat ji pm relief fund save ensur let fight togeth',\n",
       " 'like commun might make feel better capit save life credit',\n",
       " 'f shrimp seller identifi patient zero believ chines govern could check spread diseas act sooner',\n",
       " 'think corona viru',\n",
       " 'contribut small amount fight',\n",
       " 'alcohol everyth drunkard care rest mind thought purpos control lack liquor lockdown trigger suicid kerala',\n",
       " 'stay home stay safe',\n",
       " 'ensur migrant worker support neighborhood head mainten sankaranarayanan seen comfort migrant landlord',\n",
       " 'ppl alway say world go end tomorrow thing later u know world end tym u cn die anytym without reason fullfil ur dream enjoy ur lyf live fullest today u know u gonna die',\n",
       " 'pleas contribut inform group respect area post area mention list pl submit new post need help sail phase',\n",
       " 'shri ji poem khoon ke chape watch amp famou channel pl feel free share other',\n",
       " 'know dog get excit go walk',\n",
       " 'dear pm sir done bit nation indian need stand togeth support sure india emerg healthi amp safe phase jai hind',\n",
       " 'transmen face due lockdown help profession psychologist safe space transmen share issu talk pleas dm us get meet link',\n",
       " 'world could run condom due pandem',\n",
       " 'solv',\n",
       " 'realiti',\n",
       " 'appreci respons twitter far action ground question mani resid',\n",
       " 'kanika kapoor test coronaviru posit fourth time',\n",
       " 'fact airborn',\n",
       " 'structur basi recognit full length human ace',\n",
       " 'promot fake news want india fail fight',\n",
       " 'take precaut properli need panic togeth',\n",
       " 'doctor work patient thread differ present chest xray patient courtesi',\n",
       " 'way go indigo allow passeng book lock use pnr futur travel passeng wife beneficiari round trip coimbator mumbai due',\n",
       " 'best case outcom worst',\n",
       " 'sir grandpa feel well deoghar villag ghorpra know crisi situat stay home r helpless sir need permiss till thn stay deoghar car',\n",
       " 'decid want run time even usa plan use one two patient',\n",
       " 'day cook food poor needi bapunagar',\n",
       " 'sister appoint govern hospit rajgarh mp today train provid whole staff take care quarantin peopl even get safeti kit',\n",
       " 'fight',\n",
       " 'colon mar seem like bad option appli pilot program',\n",
       " 'landlord cannot ask rent lockdown period worker live rent accommod cannot ask vacat mha',\n",
       " 'oper detail insur scheme health worker fight',\n",
       " 'develop know much test import hope pandem significantli improv valu',\n",
       " 'good news famou fiction writer decid donat million copi gujarat file fill demand suppli gap tissu paper hat need citizen like',\n",
       " 'done littl bit contribut hungri homeless peopl due littl drop water littl grain sand make mighti ocean pleasant land',\n",
       " 'implement rule state ask other implement model ever sinc famili follow lectur govt variou issu incap anyth let accept',\n",
       " 'thank input pleas keep come need follow area pune number meal morn even deliv nearbi collect',\n",
       " 'instruct presid sb day relief distribut hakeempet kunta surround relief distribut famili karwan mla amp nanal ngr overseen relief effort',\n",
       " 'thmarch thmarch death ratio increas day said vaccin take least year come peopl understand',\n",
       " 'help deliveri essenti variou section sociti',\n",
       " 'ji one friend small villag rajasthan contribut small bit save toward fight doesnt use twitter post behalf friend abhi jangid',\n",
       " 'avoid public gather break spread corona viru great initi shg member',\n",
       " 'get approv pass plan take utmost care amp precaut deliv food needi amp cannot deliv volunt live vicin rare',\n",
       " 'pleas provid permiss judici use',\n",
       " 'whatev world gener magnitud inform deal bio war effect like civil amp militari joint exercis',\n",
       " 'man said year back reason pop timelin today wow nobodi listen next outbreak readi bill gate via',\n",
       " 'whattttttttt villag name corona corona affect two differ thing bruh',\n",
       " 'bollywood singer test posit th test',\n",
       " 'say one person chang whole world see person ate bat somewher whole world shut suffer lockdown',\n",
       " 'serious wonder china hide behind truth scari',\n",
       " 'small contribut toward belov ji fight agar mera koi sourc incom hota toh may bhi kuch dhan rashi rashtra ke sankatk aapk hato de pata',\n",
       " 'dear sir pleas accept littl contribut countri fight jobless last month small contribut hope someth big countri futur',\n",
       " 'month noth happen month decad happen march liter sort month',\n",
       " 'princess first royal die coronaviru lifestyl news',\n",
       " 'time need need contribut whatev way motil oswal group pledg crore toward save live fight crisi contribut pm care fund hon maharashtra chief minist fund',\n",
       " 'tweet reassur kind news badli need time bombard pessimist news world keep flow',\n",
       " 'delhi govt updat googl map locat covid hunger relief center',\n",
       " 'high time china amp product entir world everyday peopl suffer everi moment everyday',\n",
       " 'allow landlord other villag also keep n feed follow gener protocol innwak send intim dc monitor',\n",
       " 'indian aviat regul suspend breath analys test due crew give understand random check done good move time',\n",
       " 'initi peopl peopl fight',\n",
       " 'kind',\n",
       " 'first made migrant leav delhi intent spread blame ji spread get expos drama shame',\n",
       " 'call corona helplin west bengal respons help mind phone auto disconnect',\n",
       " 'today gratitud salut built healthcar accomod peopl neighbour itali amp franc conspiraci theori demean neighbour call human civilis call hope india take note',\n",
       " 'war let support needi around us fight provid food amp mask educ basic hygien like',\n",
       " 'day lockdown',\n",
       " 'scientist doctor govern offici world author pleas stay home stay safe practic social distanc milleni',\n",
       " 'would first like congratul wonder work regard madam sir big problem nalhati paschim bazar veget market highli congest',\n",
       " 'kill time without kill',\n",
       " 'prototyp isol coach made railway kamakhya assam new delhi work day night fight pandem contribut everi possibl way',\n",
       " 'alert say',\n",
       " 'donat nadaun',\n",
       " 'pleas stay aloof respons opposit thing would differ',\n",
       " 'india evacu citizen struck hot bed like china itali iran part world pmo statement',\n",
       " 'ye dear must follow instruct pm ji defeat ensur minimum loss preciou live citizen',\n",
       " 'covid posit case bengaluru today',\n",
       " 'littl contribut help defeat war even small contribut bring big chang',\n",
       " 'vice presid laud virologist team develop india first test kit',\n",
       " 'organis eye juli start game postpon due',\n",
       " 'learnt bird today atharva made stori',\n",
       " 'respond issu modif debentur due issuer perspect regist get day access repositori free post day avail bonanza subscrib one repositori',\n",
       " 'small contribut pm care fund nation fight',\n",
       " 'mani doctor news channel debat request channel let work debat delay till channel shuld concentr posit stori rather creat doubt havoc atmospher amid',\n",
       " 'coronaviru spread less countri temperatur humid high',\n",
       " 'f ckin storm pune hailston hous di left',\n",
       " 'pleas take action amp someth peopl r come like picnic request take strict action everyon roam outsid amp follow rule',\n",
       " 'better deal situat jail provid bail parol furlough trial set prison return respect home releas caus mani unintend consequ tri amp isol whole jail premis',\n",
       " 'volunt violent youth east polic coloni dimapur maninng entranc coloni provid hand sanit mask outsid enter coloni safeti precaut measur',\n",
       " 'new posit case tamil nadu erod contact thai nation undergo treatment irt perundurai patient identifi contact trace patient isol treatment dr c vijayabaskar tamil nadu health minist file pic',\n",
       " 'aviat author dgca suspend breathalys test pilot personnel amid pandem news agenc pti',\n",
       " 'happen everyday last day job peopl understand risk well other life critic need act immedi otherwis spread pleas someth',\n",
       " 'hard time import grate doctor polic cleaner worker dedic time help us real hero countri click link',\n",
       " 'much crow gandhinagar market pokharan social distanc went toss wait disast pl look',\n",
       " 'man liter noth els kolkata',\n",
       " 'inde challeng mention herein beyond test time thank take dr velumani amp activ highlight industri perspect',\n",
       " 'storm pune felt like thunder ju hit home der spark switch board n ceil fan',\n",
       " 'along mehdipatnam corpor majid hussain team aimim nampal distribut ration kit today sunday march afzal sagar mallep divis',\n",
       " 'join v forc volunt fight covid',\n",
       " 'happi birthday time pass year gloriou one',\n",
       " 'request support govern fight',\n",
       " 'central govt expand exempt list transport good without essenti amp non essenti good allow product soap disinfect hand wash shampoo toothpast surfac cleaner diaper sanitari pad batteri etc entir suppli chain milk newspap',\n",
       " 'anoth fabul thread lucid explan test detect even non medico understand one read',\n",
       " 'entir world buy medicin support',\n",
       " 'progress without manag mean invit disast',\n",
       " 'cook eat sleep repeat punjab region',\n",
       " 'win battl definit win battl coronaviru say pm',\n",
       " 'china need punish',\n",
       " 'learn updat case india',\n",
       " 'instruct presid sahab along amp aimim nampal team distribut ration kit today ac guard redhil divis',\n",
       " 'help donat cm fund account number bank syndic bank delhi secretariat branch if code synb',\n",
       " 'today along majid hussain team distribut kit kishan nagar asifnagar divis nampal constitu',\n",
       " 'mexico trajectori similar india common featur includ increment test densiti inform worker',\n",
       " 'uttarakhand year old man test posit today total number posit case state rise discharg test neg',\n",
       " 'fix test posit fourth time china worri',\n",
       " 'notic learn queue well adjust new norm longer happen',\n",
       " 'labour strand',\n",
       " 'could stop earlier',\n",
       " 'one say',\n",
       " 'think china think chang nation flag follow us',\n",
       " 'best way help helpless peopl direct bank account megastar financi support wage worker film industri amid outbreak truli peopl man salut bhaijaan',\n",
       " 'done beauti world',\n",
       " 'one case nashik proud moment farmer help peopl',\n",
       " 'imo chines peopl brace like face lot xenophobia peopl around world harsh realiti happen',\n",
       " ...]"
      ]
     },
     "execution_count": 7,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corpus = []\n",
    "words = []\n",
    "ps = PorterStemmer()\n",
    "for i in range(0, 41618):\n",
    "  review2 = dataset['Text'][i]\n",
    "  review2 = re.sub('\"', ' ', review2)\n",
    "  review2 = re.sub('https://[a-zA-Z0-9./]+', ' ',review2)\n",
    "  review2 = re.sub('#[a-zA-Z0-9._]+', ' ', review2)\n",
    "  review2 = re.sub('@[a-zA-Z0-9._]+', ' ', review2)\n",
    "  review2 = re.sub('\\n', ' ', review2)\n",
    "  review2 = re.sub('[^a-zA-Z]', ' ', review2)\n",
    "  review2 = review2.lower()\n",
    "  review2 = review2.split()\n",
    "  review2 = [word for word in review2 if not word in stopwords.words('english')]\n",
    "  for j in review2:\n",
    "    words.append(j)\n",
    "  review2 = [ps.stem(word) for word in review2]\n",
    "  review2 = ' '.join(review2)\n",
    "  corpus.append(review2)\n",
    "corpus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "-eAhKbRZl-at",
    "outputId": "7664124f-7491-41d1-cc3e-bdcb2a13b5b2"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['indian',\n",
       " 'way',\n",
       " 'possible',\n",
       " 'case',\n",
       " 'human',\n",
       " 'animal',\n",
       " 'transmission',\n",
       " 'way',\n",
       " 'around',\n",
       " 'worried',\n",
       " 'pets',\n",
       " 'look',\n",
       " 'india',\n",
       " 'look',\n",
       " 'stray',\n",
       " 'animal',\n",
       " 'population',\n",
       " 'look',\n",
       " 'idiots',\n",
       " 'still',\n",
       " 'continue',\n",
       " 'go',\n",
       " 'god',\n",
       " 'help',\n",
       " 'us',\n",
       " 'eclipses',\n",
       " 'confirmed',\n",
       " 'cases',\n",
       " 'deaths',\n",
       " 'usa',\n",
       " 'bitter',\n",
       " 'truth',\n",
       " 'india',\n",
       " 'churches',\n",
       " 'shd',\n",
       " 'realize',\n",
       " 'mass',\n",
       " 'forms',\n",
       " 'worship',\n",
       " 'r',\n",
       " 'important',\n",
       " 'making',\n",
       " 'arrangements',\n",
       " 'counter',\n",
       " 'spread',\n",
       " 'infection',\n",
       " 'n',\n",
       " 'treating',\n",
       " 'infected',\n",
       " 'church',\n",
       " 'premises',\n",
       " 'incl',\n",
       " 'palatial',\n",
       " 'bp',\n",
       " 'houses',\n",
       " 'allowed',\n",
       " 'used',\n",
       " 'isolation',\n",
       " 'wards',\n",
       " 'amp',\n",
       " 'reaches',\n",
       " 'due',\n",
       " 'death',\n",
       " 'count',\n",
       " 'march',\n",
       " 'th',\n",
       " 'italy',\n",
       " 'deaths',\n",
       " 'total',\n",
       " 'spain',\n",
       " 'france',\n",
       " 'causing',\n",
       " 'havoc',\n",
       " 'save',\n",
       " 'family',\n",
       " 'staying',\n",
       " 'home',\n",
       " 'unfortunate',\n",
       " 'see',\n",
       " 'unplanned',\n",
       " 'ill',\n",
       " 'intended',\n",
       " 'mayhem',\n",
       " 'add',\n",
       " 'gasoline',\n",
       " 'fire',\n",
       " 'two',\n",
       " 'weeks',\n",
       " 'ago',\n",
       " 'today',\n",
       " 'made',\n",
       " 'small',\n",
       " 'contribution',\n",
       " 'towards',\n",
       " 'country',\n",
       " 'please',\n",
       " 'contribute',\n",
       " 'even',\n",
       " 'small',\n",
       " 'amount',\n",
       " 'matters',\n",
       " 'ji',\n",
       " 'lot',\n",
       " 'country',\n",
       " 'let',\n",
       " 'participate',\n",
       " 'save',\n",
       " 'country',\n",
       " 'epidemic',\n",
       " 'strange',\n",
       " 'feeling',\n",
       " 'dat',\n",
       " 'lockdown',\n",
       " 'going',\n",
       " 'b',\n",
       " 'extended',\n",
       " 'madurai',\n",
       " 'kavalan',\n",
       " 'app',\n",
       " 'uses',\n",
       " 'gps',\n",
       " 'tracking',\n",
       " 'coronavirus',\n",
       " 'pandemic',\n",
       " 'police',\n",
       " 'deploy',\n",
       " 'monitor',\n",
       " 'movement',\n",
       " 'vehicles',\n",
       " 'people',\n",
       " 'appreciate',\n",
       " 'true',\n",
       " 'humanity',\n",
       " 'serve',\n",
       " 'citizen',\n",
       " 'soil',\n",
       " 'time',\n",
       " 'delhi',\n",
       " 'government',\n",
       " 'thousand',\n",
       " 'infected',\n",
       " 'thousand',\n",
       " 'plus',\n",
       " 'dead',\n",
       " 'death',\n",
       " 'rate',\n",
       " 'italy',\n",
       " 'numbers',\n",
       " 'dangerous',\n",
       " 'horrible',\n",
       " 'killers',\n",
       " 'team',\n",
       " 'activists',\n",
       " 'combination',\n",
       " 'journalists',\n",
       " 'urban',\n",
       " 'naxals',\n",
       " 'support',\n",
       " 'china',\n",
       " 'friendly',\n",
       " 'china',\n",
       " 'countries',\n",
       " 'population',\n",
       " 'non',\n",
       " 'muslims',\n",
       " 'suffering',\n",
       " 'trying',\n",
       " 'failed',\n",
       " 'coronavirus',\n",
       " 'tweets',\n",
       " 'indian',\n",
       " 'authorities',\n",
       " 'cases',\n",
       " 'march',\n",
       " 'u',\n",
       " 'reached',\n",
       " 'italy',\n",
       " 'reached',\n",
       " 'spain',\n",
       " 'reached',\n",
       " 'worldwide',\n",
       " 'cases',\n",
       " 'delhi',\n",
       " 'cm',\n",
       " 'apriciate',\n",
       " 'central',\n",
       " 'government',\n",
       " 'advise',\n",
       " 'drink',\n",
       " 'cow',\n",
       " 'urine',\n",
       " 'shame',\n",
       " 'govt',\n",
       " 'fool',\n",
       " 'mindless',\n",
       " 'peoples',\n",
       " 'hiding',\n",
       " 'every',\n",
       " 'article',\n",
       " 'every',\n",
       " 'opinion',\n",
       " 'attacking',\n",
       " 'lockdown',\n",
       " 'measure',\n",
       " 'ill',\n",
       " 'planned',\n",
       " 'take',\n",
       " 'country',\n",
       " 'like',\n",
       " 'logistical',\n",
       " 'nightmare',\n",
       " 'second',\n",
       " 'instead',\n",
       " 'hurling',\n",
       " 'accusations',\n",
       " 'give',\n",
       " 'solutions',\n",
       " 'know',\n",
       " 'work',\n",
       " 'need',\n",
       " 'understand',\n",
       " 'india',\n",
       " 'joint',\n",
       " 'family',\n",
       " 'system',\n",
       " 'live',\n",
       " 'houses',\n",
       " 'defined',\n",
       " 'boundaries',\n",
       " 'teach',\n",
       " 'social',\n",
       " 'distancing',\n",
       " 'ready',\n",
       " 'even',\n",
       " 'think',\n",
       " 'distance',\n",
       " 'issue',\n",
       " 'resistance',\n",
       " 'starts',\n",
       " 'said',\n",
       " 'migrant',\n",
       " 'workers',\n",
       " 'shoukd',\n",
       " 'put',\n",
       " 'shelters',\n",
       " 'food',\n",
       " 'basic',\n",
       " 'amneties',\n",
       " 'monitoring',\n",
       " 'would',\n",
       " 'worked',\n",
       " 'better',\n",
       " 'panic',\n",
       " 'fear',\n",
       " 'confusion',\n",
       " 'going',\n",
       " 'create',\n",
       " 'far',\n",
       " 'problems',\n",
       " 'onset',\n",
       " 'communism',\n",
       " 'socialism',\n",
       " 'era',\n",
       " 'today',\n",
       " 'whole',\n",
       " 'world',\n",
       " 'fight',\n",
       " 'dangerous',\n",
       " 'disease',\n",
       " 'everyone',\n",
       " 'worry',\n",
       " 'follow',\n",
       " 'guidelines',\n",
       " 'government',\n",
       " 'health',\n",
       " 'care',\n",
       " 'tips',\n",
       " 'fight',\n",
       " 'yesterday',\n",
       " 'global',\n",
       " 'case',\n",
       " 'today',\n",
       " 'increase',\n",
       " 'never',\n",
       " 'history',\n",
       " 'human',\n",
       " 'civilisation',\n",
       " 'humanity',\n",
       " 'faced',\n",
       " 'formidable',\n",
       " 'challenge',\n",
       " 'role',\n",
       " 'corp',\n",
       " 'sector',\n",
       " 'mission',\n",
       " 'critical',\n",
       " 'fight',\n",
       " 'corp',\n",
       " 'citizens',\n",
       " 'amp',\n",
       " 'lead',\n",
       " 'way',\n",
       " 'amp',\n",
       " 'commit',\n",
       " 'rs',\n",
       " 'cr',\n",
       " 'many',\n",
       " 'companies',\n",
       " 'compete',\n",
       " 'companies',\n",
       " 'create',\n",
       " 'good',\n",
       " 'morning',\n",
       " 'sleepy',\n",
       " 'quarantine',\n",
       " 'ask',\n",
       " 'free',\n",
       " 'say',\n",
       " 'true',\n",
       " 'fights',\n",
       " 'corona',\n",
       " 'need',\n",
       " 'go',\n",
       " 'side',\n",
       " 'fight',\n",
       " 'fight',\n",
       " 'inside',\n",
       " 'home',\n",
       " 'anyone',\n",
       " 'interested',\n",
       " 'donating',\n",
       " 'volunteering',\n",
       " 'giving',\n",
       " 'support',\n",
       " 'daily',\n",
       " 'wage',\n",
       " 'earners',\n",
       " 'across',\n",
       " 'telangana',\n",
       " 'reach',\n",
       " 'amp',\n",
       " 'covid',\n",
       " 'relief',\n",
       " 'dear',\n",
       " 'sir',\n",
       " 'happy',\n",
       " 'pm',\n",
       " 'like',\n",
       " 'u',\n",
       " 'tollywood',\n",
       " 'lot',\n",
       " 'celebrities',\n",
       " 'like',\n",
       " 'sir',\n",
       " 'donated',\n",
       " 'money',\n",
       " 'fight',\n",
       " 'plz',\n",
       " 'u',\n",
       " 'recognize',\n",
       " 'n',\n",
       " 'appreciate',\n",
       " 'duty',\n",
       " 'one',\n",
       " 'tweet',\n",
       " 'sir',\n",
       " 'thank',\n",
       " 'u',\n",
       " 'asia',\n",
       " 'famous',\n",
       " 'cricket',\n",
       " 'board',\n",
       " 'donation',\n",
       " 'combat',\n",
       " 'rs',\n",
       " 'million',\n",
       " 'nearly',\n",
       " 'lakhs',\n",
       " 'taka',\n",
       " 'crore',\n",
       " 'million',\n",
       " 'usd',\n",
       " 'see',\n",
       " 'favourite',\n",
       " 'team',\n",
       " 'stands',\n",
       " 'bcci',\n",
       " 'try',\n",
       " 'put',\n",
       " 'india',\n",
       " 'case',\n",
       " 'people',\n",
       " 'goes',\n",
       " 'start',\n",
       " 'special',\n",
       " 'screen',\n",
       " 'passengers',\n",
       " 'board',\n",
       " 'except',\n",
       " 'symptoms',\n",
       " 'unless',\n",
       " 'host',\n",
       " 'state',\n",
       " 'provide',\n",
       " 'food',\n",
       " 'amp',\n",
       " 'shelter',\n",
       " 'amp',\n",
       " 'security',\n",
       " 'pl',\n",
       " 'grave',\n",
       " 'negligence',\n",
       " 'whoever',\n",
       " 'fight',\n",
       " 'without',\n",
       " 'paying',\n",
       " 'salaries',\n",
       " 'need',\n",
       " 'apart',\n",
       " 'pat',\n",
       " 'back',\n",
       " 'know',\n",
       " 'reach',\n",
       " 'amp',\n",
       " 'provide',\n",
       " 'medicines',\n",
       " 'patients',\n",
       " 'getting',\n",
       " 'free',\n",
       " 'medicines',\n",
       " 'supply',\n",
       " 'government',\n",
       " 'hospitals',\n",
       " 'suggestions',\n",
       " 'please',\n",
       " 'done',\n",
       " 'govt',\n",
       " 'public',\n",
       " 'money',\n",
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       " 'completely',\n",
       " 'empty',\n",
       " 'vatican',\n",
       " 'city',\n",
       " 'tommorow',\n",
       " 'sunrise',\n",
       " 'see',\n",
       " 'corona',\n",
       " 'mortality',\n",
       " 'pray',\n",
       " 'world',\n",
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       " 'hampered',\n",
       " 'covid',\n",
       " 'infection',\n",
       " 'thereby',\n",
       " 'reducing',\n",
       " 'immunity',\n",
       " 'person',\n",
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       " 'coming',\n",
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       " 'hard',\n",
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       " 'towards',\n",
       " 'jai',\n",
       " 'hind',\n",
       " 'would',\n",
       " 'urge',\n",
       " 'people',\n",
       " 'network',\n",
       " 'pls',\n",
       " 'contribute',\n",
       " 'nation',\n",
       " 'jaan',\n",
       " 'hai',\n",
       " 'jahan',\n",
       " 'hai',\n",
       " 'god',\n",
       " 'bless',\n",
       " 'frontline',\n",
       " 'workers',\n",
       " 'selflessly',\n",
       " 'serving',\n",
       " 'communities',\n",
       " 'crisis',\n",
       " 'thank',\n",
       " 'health',\n",
       " 'care',\n",
       " 'workers',\n",
       " 'first',\n",
       " 'responders',\n",
       " 'nurses',\n",
       " 'grocery',\n",
       " 'store',\n",
       " 'employees',\n",
       " 'truck',\n",
       " 'drivers',\n",
       " 'amp',\n",
       " 'stepping',\n",
       " 'keep',\n",
       " 'us',\n",
       " 'safe',\n",
       " 'unprecedented',\n",
       " 'times',\n",
       " 'know',\n",
       " 'key',\n",
       " 'success',\n",
       " 'situation',\n",
       " 'like',\n",
       " 'key',\n",
       " 'failure',\n",
       " 'towards',\n",
       " 'trying',\n",
       " 'please',\n",
       " 'everybody',\n",
       " 'maintaining',\n",
       " 'government',\n",
       " 'doctors',\n",
       " 'best',\n",
       " 'judges',\n",
       " 'handle',\n",
       " 'everyone',\n",
       " 'stay',\n",
       " 'home',\n",
       " 'stay',\n",
       " 'afe',\n",
       " 'one',\n",
       " 'best',\n",
       " 'doctors',\n",
       " 'world',\n",
       " 'dr',\n",
       " 'nageswar',\n",
       " 'reddy',\n",
       " 'garu',\n",
       " 'aig',\n",
       " 'hyd',\n",
       " 'detailed',\n",
       " 'analysis',\n",
       " 'telugu',\n",
       " 'corona',\n",
       " 'virus',\n",
       " 'cure',\n",
       " 'vacine',\n",
       " 'prevention',\n",
       " 'must',\n",
       " 'watch',\n",
       " 'come',\n",
       " 'join',\n",
       " 'us',\n",
       " 'worship',\n",
       " 'living',\n",
       " 'god',\n",
       " 'telangana',\n",
       " 'let',\n",
       " 'us',\n",
       " 'drill',\n",
       " 'space',\n",
       " 'live',\n",
       " 'connected',\n",
       " 'world',\n",
       " 'let',\n",
       " 'us',\n",
       " 'fight',\n",
       " 'together',\n",
       " 'small',\n",
       " 'contribution',\n",
       " 'towards',\n",
       " 'nation',\n",
       " 'defeat',\n",
       " 'think',\n",
       " 'go',\n",
       " 'days',\n",
       " 'control',\n",
       " 'one',\n",
       " 'time',\n",
       " 'lock',\n",
       " 'help',\n",
       " 'world',\n",
       " 'control',\n",
       " 'rather',\n",
       " 'going',\n",
       " 'part',\n",
       " 'wise',\n",
       " 'countries',\n",
       " 'today',\n",
       " 'mann',\n",
       " 'ki',\n",
       " 'baat',\n",
       " 'episode',\n",
       " 'focus',\n",
       " 'situation',\n",
       " 'prevailing',\n",
       " 'due',\n",
       " 'covid',\n",
       " 'awe',\n",
       " 'mumbai',\n",
       " 'dealing',\n",
       " 'migrants',\n",
       " 'delhi',\n",
       " 'disaster',\n",
       " 'managing',\n",
       " 'crowds',\n",
       " 'news',\n",
       " 'mumbai',\n",
       " 'far',\n",
       " 'dear',\n",
       " 'wish',\n",
       " 'donate',\n",
       " 'cm',\n",
       " 'relief',\n",
       " 'fund',\n",
       " 'google',\n",
       " 'pay',\n",
       " 'amp',\n",
       " 'online',\n",
       " 'modes',\n",
       " 'fighting',\n",
       " 'please',\n",
       " 'publish',\n",
       " 'rajasthan',\n",
       " 'cm',\n",
       " 'upi',\n",
       " 'id',\n",
       " 'maharashtra',\n",
       " 'cm',\n",
       " 'published',\n",
       " 'cmrfmahacovid',\n",
       " 'guide',\n",
       " 'social',\n",
       " 'distancing',\n",
       " 'motown',\n",
       " 'india',\n",
       " 'afsar',\n",
       " 'baig',\n",
       " 'captured',\n",
       " 'horrifying',\n",
       " 'scene',\n",
       " 'near',\n",
       " 'delhi',\n",
       " 'border',\n",
       " 'march',\n",
       " 'delhi',\n",
       " 'summary',\n",
       " 'fatality',\n",
       " 'symptomatic',\n",
       " 'amp',\n",
       " 'asymptomatic',\n",
       " 'patients',\n",
       " 'via',\n",
       " 'age',\n",
       " 'age',\n",
       " 'age',\n",
       " 'age',\n",
       " 'age',\n",
       " 'age',\n",
       " 'age',\n",
       " 'age',\n",
       " 'age',\n",
       " 'dear',\n",
       " 'ji',\n",
       " 'one',\n",
       " 'step',\n",
       " 'evacuate',\n",
       " 'people',\n",
       " 'delhi',\n",
       " 'ncr',\n",
       " 'homes',\n",
       " 'creates',\n",
       " 'situation',\n",
       " 'make',\n",
       " 'better',\n",
       " 'easier',\n",
       " 'arrangements',\n",
       " 'workplace',\n",
       " 'keep',\n",
       " 'away',\n",
       " 'vilagers',\n",
       " 'dengurus',\n",
       " 'railways',\n",
       " 'converting',\n",
       " 'coaches',\n",
       " 'isolation',\n",
       " 'treatment',\n",
       " 'rooms',\n",
       " 'pm',\n",
       " 'address',\n",
       " 'nation',\n",
       " 'today',\n",
       " 'today',\n",
       " 'episode',\n",
       " 'focused',\n",
       " 'situation',\n",
       " 'prevailing',\n",
       " 'due',\n",
       " 'stay',\n",
       " 'tuned',\n",
       " 'live',\n",
       " 'person',\n",
       " 'come',\n",
       " 'back',\n",
       " 'maharashtra',\n",
       " 'amravati',\n",
       " 'four',\n",
       " 'members',\n",
       " 'family',\n",
       " 'tested',\n",
       " 'positive',\n",
       " 'meerut',\n",
       " 'india',\n",
       " 'total',\n",
       " 'cases',\n",
       " 'active',\n",
       " 'cases',\n",
       " 'recovered',\n",
       " 'death',\n",
       " 'groundswell',\n",
       " 'domestic',\n",
       " 'discontent',\n",
       " 'xi',\n",
       " 'ccp',\n",
       " 'crisis',\n",
       " 'crowning',\n",
       " 'tip',\n",
       " 'anger',\n",
       " 'iceberg',\n",
       " 'prime',\n",
       " 'minister',\n",
       " 'narendra',\n",
       " 'modi',\n",
       " 'address',\n",
       " 'nation',\n",
       " 'radio',\n",
       " 'programme',\n",
       " 'today',\n",
       " 'episode',\n",
       " 'focused',\n",
       " 'situation',\n",
       " 'prevailing',\n",
       " 'due',\n",
       " 'doctor',\n",
       " 'helped',\n",
       " 'defeat',\n",
       " 'smallpox',\n",
       " 'helps',\n",
       " 'explain',\n",
       " 'coming',\n",
       " 'thanks',\n",
       " 'sharing',\n",
       " 'nri',\n",
       " 'appreciate',\n",
       " 'exemplary',\n",
       " 'actions',\n",
       " 'pm',\n",
       " 'ji',\n",
       " 'especially',\n",
       " 'amp',\n",
       " 'appeals',\n",
       " 'citizens',\n",
       " 'india',\n",
       " 'strictly',\n",
       " 'obey',\n",
       " 'stay',\n",
       " 'safe',\n",
       " 'please',\n",
       " 'go',\n",
       " 'round',\n",
       " 'fake',\n",
       " 'religious',\n",
       " 'leaders',\n",
       " 'sorrow',\n",
       " 'redress',\n",
       " 'taking',\n",
       " 'shelter',\n",
       " 'certified',\n",
       " 'lord',\n",
       " 'kabir',\n",
       " 'saheb',\n",
       " 'rid',\n",
       " 'sorrows',\n",
       " 'must',\n",
       " 'watch',\n",
       " 'sadhana',\n",
       " 'tv',\n",
       " 'evening',\n",
       " 'small',\n",
       " 'donation',\n",
       " 'country',\n",
       " 'please',\n",
       " 'capability',\n",
       " 'jai',\n",
       " 'hind',\n",
       " 'bharat',\n",
       " 'mata',\n",
       " 'ki',\n",
       " 'jay',\n",
       " 'positive',\n",
       " 'cases',\n",
       " 'indore',\n",
       " 'last',\n",
       " 'night',\n",
       " 'detected',\n",
       " 'indore',\n",
       " 'new',\n",
       " 'epicentre',\n",
       " 'even',\n",
       " 'darkest',\n",
       " 'clouds',\n",
       " 'silver',\n",
       " ...]"
      ]
     },
     "execution_count": 23,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "EpPeoViaCAYy",
    "outputId": "dcf5aa64-a487-441b-8993-8ebf8a3c9a50"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "FreqDist({1: 14951,\n",
       "          2: 4310,\n",
       "          3: 2221,\n",
       "          4: 1400,\n",
       "          5: 918,\n",
       "          6: 737,\n",
       "          7: 609,\n",
       "          8: 461,\n",
       "          9: 412,\n",
       "          10: 368,\n",
       "          11: 328,\n",
       "          12: 264,\n",
       "          13: 206,\n",
       "          14: 235,\n",
       "          15: 199,\n",
       "          16: 137,\n",
       "          17: 161,\n",
       "          18: 128,\n",
       "          19: 113,\n",
       "          20: 92,\n",
       "          21: 99,\n",
       "          22: 82,\n",
       "          23: 91,\n",
       "          24: 85,\n",
       "          25: 88,\n",
       "          26: 78,\n",
       "          27: 77,\n",
       "          28: 53,\n",
       "          29: 67,\n",
       "          30: 66,\n",
       "          31: 63,\n",
       "          32: 60,\n",
       "          33: 54,\n",
       "          34: 53,\n",
       "          35: 43,\n",
       "          36: 57,\n",
       "          37: 37,\n",
       "          38: 44,\n",
       "          39: 34,\n",
       "          40: 36,\n",
       "          41: 35,\n",
       "          42: 35,\n",
       "          43: 29,\n",
       "          44: 27,\n",
       "          45: 43,\n",
       "          46: 30,\n",
       "          47: 26,\n",
       "          48: 37,\n",
       "          49: 36,\n",
       "          50: 33,\n",
       "          51: 30,\n",
       "          52: 34,\n",
       "          53: 23,\n",
       "          54: 19,\n",
       "          55: 23,\n",
       "          56: 25,\n",
       "          57: 19,\n",
       "          58: 22,\n",
       "          59: 20,\n",
       "          60: 16,\n",
       "          61: 23,\n",
       "          62: 21,\n",
       "          63: 21,\n",
       "          64: 19,\n",
       "          65: 14,\n",
       "          66: 11,\n",
       "          67: 19,\n",
       "          68: 12,\n",
       "          69: 14,\n",
       "          70: 11,\n",
       "          71: 13,\n",
       "          72: 15,\n",
       "          73: 15,\n",
       "          74: 8,\n",
       "          75: 14,\n",
       "          76: 9,\n",
       "          77: 16,\n",
       "          78: 23,\n",
       "          79: 22,\n",
       "          80: 8,\n",
       "          81: 14,\n",
       "          82: 6,\n",
       "          83: 15,\n",
       "          84: 13,\n",
       "          85: 8,\n",
       "          86: 10,\n",
       "          87: 8,\n",
       "          88: 18,\n",
       "          89: 15,\n",
       "          90: 8,\n",
       "          91: 7,\n",
       "          92: 8,\n",
       "          93: 5,\n",
       "          94: 8,\n",
       "          95: 4,\n",
       "          96: 12,\n",
       "          97: 7,\n",
       "          98: 2,\n",
       "          99: 12,\n",
       "          100: 5,\n",
       "          101: 9,\n",
       "          102: 12,\n",
       "          103: 7,\n",
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       "          105: 8,\n",
       "          106: 5,\n",
       "          107: 6,\n",
       "          108: 10,\n",
       "          109: 8,\n",
       "          110: 10,\n",
       "          111: 6,\n",
       "          112: 2,\n",
       "          113: 13,\n",
       "          114: 6,\n",
       "          115: 8,\n",
       "          116: 8,\n",
       "          117: 3,\n",
       "          118: 6,\n",
       "          119: 6,\n",
       "          120: 6,\n",
       "          121: 6,\n",
       "          122: 5,\n",
       "          123: 5,\n",
       "          124: 6,\n",
       "          125: 3,\n",
       "          126: 6,\n",
       "          127: 11,\n",
       "          128: 6,\n",
       "          129: 7,\n",
       "          130: 3,\n",
       "          131: 6,\n",
       "          132: 8,\n",
       "          133: 3,\n",
       "          134: 5,\n",
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       "          136: 3,\n",
       "          137: 5,\n",
       "          138: 3,\n",
       "          139: 3,\n",
       "          140: 2,\n",
       "          141: 3,\n",
       "          142: 3,\n",
       "          143: 5,\n",
       "          144: 3,\n",
       "          145: 5,\n",
       "          146: 5,\n",
       "          147: 7,\n",
       "          148: 13,\n",
       "          149: 5,\n",
       "          150: 9,\n",
       "          151: 2,\n",
       "          152: 4,\n",
       "          153: 3,\n",
       "          154: 4,\n",
       "          155: 6,\n",
       "          156: 3,\n",
       "          157: 6,\n",
       "          158: 4,\n",
       "          159: 7,\n",
       "          160: 2,\n",
       "          161: 4,\n",
       "          162: 2,\n",
       "          163: 2,\n",
       "          164: 5,\n",
       "          165: 7,\n",
       "          166: 5,\n",
       "          167: 3,\n",
       "          168: 2,\n",
       "          169: 3,\n",
       "          170: 3,\n",
       "          171: 3,\n",
       "          172: 4,\n",
       "          173: 3,\n",
       "          174: 3,\n",
       "          175: 4,\n",
       "          176: 4,\n",
       "          177: 5,\n",
       "          178: 4,\n",
       "          179: 2,\n",
       "          180: 1,\n",
       "          181: 2,\n",
       "          182: 1,\n",
       "          183: 3,\n",
       "          184: 4,\n",
       "          185: 2,\n",
       "          186: 3,\n",
       "          187: 2,\n",
       "          188: 3,\n",
       "          189: 2,\n",
       "          190: 5,\n",
       "          191: 1,\n",
       "          192: 5,\n",
       "          193: 5,\n",
       "          194: 3,\n",
       "          195: 2,\n",
       "          196: 2,\n",
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       "          198: 2,\n",
       "          199: 3,\n",
       "          200: 1,\n",
       "          201: 3,\n",
       "          202: 3,\n",
       "          204: 3,\n",
       "          205: 2,\n",
       "          206: 3,\n",
       "          207: 3,\n",
       "          208: 1,\n",
       "          209: 2,\n",
       "          210: 2,\n",
       "          212: 3,\n",
       "          213: 4,\n",
       "          214: 3,\n",
       "          215: 2,\n",
       "          216: 3,\n",
       "          217: 2,\n",
       "          218: 3,\n",
       "          219: 1,\n",
       "          221: 2,\n",
       "          222: 3,\n",
       "          223: 2,\n",
       "          224: 1,\n",
       "          225: 4,\n",
       "          226: 2,\n",
       "          227: 2,\n",
       "          229: 2,\n",
       "          231: 1,\n",
       "          232: 2,\n",
       "          233: 3,\n",
       "          234: 1,\n",
       "          235: 3,\n",
       "          236: 1,\n",
       "          237: 3,\n",
       "          238: 1,\n",
       "          239: 1,\n",
       "          240: 1,\n",
       "          241: 2,\n",
       "          242: 3,\n",
       "          243: 1,\n",
       "          244: 2,\n",
       "          245: 2,\n",
       "          246: 1,\n",
       "          248: 1,\n",
       "          249: 2,\n",
       "          250: 3,\n",
       "          251: 1,\n",
       "          252: 1,\n",
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       "          254: 4,\n",
       "          255: 4,\n",
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       "          954: 1,\n",
       "          992: 1,\n",
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       "          1086: 1,\n",
       "          1112: 1,\n",
       "          1114: 1,\n",
       "          1119: 2,\n",
       "          1124: 1,\n",
       "          1126: 1,\n",
       "          1129: 1,\n",
       "          1130: 1,\n",
       "          1168: 1,\n",
       "          1176: 1,\n",
       "          1201: 1,\n",
       "          1224: 1,\n",
       "          1232: 1,\n",
       "          1255: 1,\n",
       "          1296: 1,\n",
       "          1307: 1,\n",
       "          1342: 1,\n",
       "          1466: 1,\n",
       "          1518: 1,\n",
       "          1566: 1,\n",
       "          1583: 1,\n",
       "          1607: 1,\n",
       "          1618: 1,\n",
       "          1629: 1,\n",
       "          1685: 1,\n",
       "          1791: 1,\n",
       "          1893: 1,\n",
       "          1971: 1,\n",
       "          2006: 1,\n",
       "          2016: 1,\n",
       "          2049: 1,\n",
       "          2085: 1,\n",
       "          2108: 1,\n",
       "          2213: 1,\n",
       "          2378: 1,\n",
       "          2638: 1,\n",
       "          2694: 1,\n",
       "          2722: 1,\n",
       "          2807: 1,\n",
       "          3456: 1,\n",
       "          3802: 1,\n",
       "          4543: 1,\n",
       "          6104: 1})"
      ]
     },
     "execution_count": 24,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = pd.DataFrame(words)\n",
    "df2 = df2[0].value_counts()\n",
    "\n",
    "from nltk.probability import FreqDist\n",
    "freqdist2 = FreqDist()\n",
    "\n",
    "for word_ in df2:\n",
    "  freqdist2[word_] += 1\n",
    "\n",
    "freqdist2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 515
    },
    "id": "wmxDQ406Czu6",
    "outputId": "a44f205e-d81e-4a1c-dd7a-ccae025f4706"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df2 = df2[:20, ]\n",
    "plt.figure(figsize = (12, 8))\n",
    "sns.barplot(df2.values, df2.index, alpha = 0.8)\n",
    "plt.title(\"Top Words Used\", fontdict = {'fontsize' : 15})\n",
    "plt.ylabel(\"Words\")\n",
    "plt.xlabel(\"Count\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "C8ieQJ5mdqcb"
   },
   "source": [
    "## **Using Tfidf Vectorizer**\n",
    "## **Splitting the Dataset into Training and Test Set**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 402
    },
    "id": "R6Chdqa4JbDD",
    "outputId": "e56cde3f-81e8-4195-fdf2-1fc635b42e7a"
   },
   "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>positive</th>\n",
       "      <th>Content</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>indian way</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>possibl case human anim transmiss way around w...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>eclips confirm case death usa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>bitter truth india</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>church shd realiz mass form worship r import m...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41613</th>\n",
       "      <td>1</td>\n",
       "      <td>util camera instal across hope util huge inves...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41614</th>\n",
       "      <td>1</td>\n",
       "      <td>welcom ceremoni year old woman beat coronaviru...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41615</th>\n",
       "      <td>1</td>\n",
       "      <td>first may god protect us stay unit spread love...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41616</th>\n",
       "      <td>0</td>\n",
       "      <td>easi transport gov need arrang test assur carr...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41617</th>\n",
       "      <td>1</td>\n",
       "      <td>look ask realli money taken name relief</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>41618 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       positive                                            Content\n",
       "0             1                                         indian way\n",
       "1             0  possibl case human anim transmiss way around w...\n",
       "2             1                      eclips confirm case death usa\n",
       "3             0                                 bitter truth india\n",
       "4             1  church shd realiz mass form worship r import m...\n",
       "...         ...                                                ...\n",
       "41613         1  util camera instal across hope util huge inves...\n",
       "41614         1  welcom ceremoni year old woman beat coronaviru...\n",
       "41615         1  first may god protect us stay unit spread love...\n",
       "41616         0  easi transport gov need arrang test assur carr...\n",
       "41617         1            look ask realli money taken name relief\n",
       "\n",
       "[41618 rows x 2 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset_final = pd.DataFrame(corpus, columns = ['Content'])  # To convert a List into a DataFrame\n",
    "dataset_final = pd.concat([dataset['positive'], dataset_final], axis = 1)\n",
    "dataset_final"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "Ks3J1cr-JvUp"
   },
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "X_train, X_test, Y_train, Y_test = train_test_split(dataset_final.Content, dataset_final.positive, test_size=0.25)\n",
    "\n",
    "X_1 = X_train.reset_index(drop = True)\n",
    "X_2 = X_test.reset_index(drop = True)\n",
    "\n",
    "Y_1 = Y_train.reset_index(drop = True)\n",
    "Y_2 = Y_test.reset_index(drop = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "bc-Mnw00KWIq"
   },
   "outputs": [],
   "source": [
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "\n",
    "vectorizer = TfidfVectorizer(min_df=3, max_df=0.9)\n",
    "# max_df is used for removing terms that appear too frequently\n",
    "# max_df = 0.90 means \"ignore terms that appear in more than 90% of the documents\".\n",
    "# min_df is used for removing terms that appear too infrequently\n",
    "# min_df = 0.01 means \"ignore terms that appear in less than 1% of the documents\".\n",
    "\n",
    "X_train = vectorizer.fit_transform(X_1)\n",
    "X_test = vectorizer.transform(X_2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "3l1qTaOswzj3"
   },
   "source": [
    "## **Classification Models**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "8O5G4sFl9cyt"
   },
   "source": [
    "#### **Logistic Regression**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "OYHGchgIs6a_",
    "outputId": "244c6b56-886f-4530-8fe6-ad6af7b89b9b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of Logistic Regression is: 89.40893801057183%\n",
      "Confusion Matrix of Logistic Regression is: \n",
      "[[ 585 1020]\n",
      " [  82 8718]]\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.88      0.36      0.51      1605\n",
      "           1       0.90      0.99      0.94      8800\n",
      "\n",
      "    accuracy                           0.89     10405\n",
      "   macro avg       0.89      0.68      0.73     10405\n",
      "weighted avg       0.89      0.89      0.87     10405\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "classifier_log = LogisticRegression()\n",
    "classifier_log.fit(X_train, Y_train)\n",
    "\n",
    "Y_pred_log = classifier_log.predict(X_test)\n",
    "\n",
    "print(\"Accuracy of Logistic Regression is: {}%\".format(accuracy_score(Y_test, Y_pred_log) * 100))\n",
    "print(\"Confusion Matrix of Logistic Regression is: \\n{}\".format(confusion_matrix(Y_test, Y_pred_log)))\n",
    "print(\"{}\".format(classification_report(Y_test, Y_pred_log)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "zpOrlgI29iTh"
   },
   "source": [
    "#### **Multinomial Naive Bayes**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "3InYAVK2w_fZ",
    "outputId": "a6250479-b42c-4c27-dc47-308cbff3cf9a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of MultinomialNB is: 85.61268620855358%\n",
      "Confusion Matrix of MultinomialNB is: \n",
      "[[ 116 1489]\n",
      " [   8 8792]]\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.94      0.07      0.13      1605\n",
      "           1       0.86      1.00      0.92      8800\n",
      "\n",
      "    accuracy                           0.86     10405\n",
      "   macro avg       0.90      0.54      0.53     10405\n",
      "weighted avg       0.87      0.86      0.80     10405\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.naive_bayes import MultinomialNB\n",
    "classifier_mnb = MultinomialNB()\n",
    "classifier_mnb.fit(X_train, Y_train)\n",
    "\n",
    "Y_pred_mnb = classifier_mnb.predict(X_test)\n",
    "\n",
    "print(\"Accuracy of MultinomialNB is: {}%\".format(accuracy_score(Y_test, Y_pred_mnb) * 100))\n",
    "print(\"Confusion Matrix of MultinomialNB is: \\n{}\".format(confusion_matrix(Y_test, Y_pred_mnb)))\n",
    "print(\"{}\".format(classification_report(Y_test, Y_pred_mnb)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ns8pGAKU9nHg"
   },
   "source": [
    "#### **Support Vector Classifier (SVM)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "as0EIuzN9mda",
    "outputId": "ce83049c-31cd-4287-b9c9-30589e1d7c14"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of Support Vector Classifier is: 90.02402691013936%\n",
      "Confusion Matrix of Support Vector Classifier is: \n",
      "[[ 664  941]\n",
      " [  97 8703]]\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.87      0.41      0.56      1605\n",
      "           1       0.90      0.99      0.94      8800\n",
      "\n",
      "    accuracy                           0.90     10405\n",
      "   macro avg       0.89      0.70      0.75     10405\n",
      "weighted avg       0.90      0.90      0.88     10405\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.svm import SVC\n",
    "classifier_svc = SVC(kernel = 'rbf')\n",
    "classifier_svc.fit(X_train, Y_train)\n",
    "\n",
    "Y_pred_svc = classifier_svc.predict(X_test)\n",
    "\n",
    "print(\"Accuracy of Support Vector Classifier is: {}%\".format(accuracy_score(Y_test, Y_pred_svc) * 100))\n",
    "print(\"Confusion Matrix of Support Vector Classifier is: \\n{}\".format(confusion_matrix(Y_test, Y_pred_svc)))\n",
    "print(\"{}\".format(classification_report(Y_test, Y_pred_svc)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "rTj13zES9tp-"
   },
   "source": [
    "#### **Decision Tree**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "AzdIGeiF9uMG",
    "outputId": "981c41dd-ab58-46bd-9849-3c0de64df9f4"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of Decision tree Classifier is: 87.93849111004324%\n",
      "Confusion Matrix of Decision tree Classifier is: \n",
      "[[ 968  637]\n",
      " [ 618 8182]]\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.61      0.60      0.61      1605\n",
      "           1       0.93      0.93      0.93      8800\n",
      "\n",
      "    accuracy                           0.88     10405\n",
      "   macro avg       0.77      0.77      0.77     10405\n",
      "weighted avg       0.88      0.88      0.88     10405\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.tree import DecisionTreeClassifier\n",
    "classifier_dt = DecisionTreeClassifier(criterion = 'entropy')\n",
    "classifier_dt.fit(X_train, Y_train)\n",
    "\n",
    "Y_pred_dt = classifier_dt.predict(X_test)\n",
    "\n",
    "print(\"Accuracy of Decision tree Classifier is: {}%\".format(accuracy_score(Y_test, Y_pred_dt) * 100))\n",
    "print(\"Confusion Matrix of Decision tree Classifier is: \\n{}\".format(confusion_matrix(Y_test, Y_pred_dt)))\n",
    "print(\"{}\".format(classification_report(Y_test, Y_pred_dt)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "waQiWznb9yxD"
   },
   "source": [
    "#### **Random Forest**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "Gzp6zlgJ92ve",
    "outputId": "dad9c2f7-82f3-4d1e-bc59-9afb80869d32"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of Random Forest Classifier is: 90.93704949543489%\n",
      "Confusion Matrix of Random Forest Classifier is: \n",
      "[[ 889  716]\n",
      " [ 227 8573]]\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.80      0.55      0.65      1605\n",
      "           1       0.92      0.97      0.95      8800\n",
      "\n",
      "    accuracy                           0.91     10405\n",
      "   macro avg       0.86      0.76      0.80     10405\n",
      "weighted avg       0.90      0.91      0.90     10405\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "classifier_rf = RandomForestClassifier(n_estimators = 300, criterion = 'entropy')\n",
    "classifier_rf.fit(X_train, Y_train)\n",
    "\n",
    "Y_pred_rf = classifier_rf.predict(X_test)\n",
    "\n",
    "print(\"Accuracy of Random Forest Classifier is: {}%\".format(accuracy_score(Y_test, Y_pred_rf) * 100))\n",
    "print(\"Confusion Matrix of Random Forest Classifier is: \\n{}\".format(confusion_matrix(Y_test, Y_pred_rf)))\n",
    "print(\"{}\".format(classification_report(Y_test, Y_pred_rf)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "13JR_F-i93w8"
   },
   "source": [
    "#### **XG Boost Classifier**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "sGiFUsH097yl",
    "outputId": "dcd591e8-35af-448d-dd25-75ef29b2c70c"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of XGBoost Classifier is: 86.32388274867851%\n",
      "Confusion Matrix of XGBoost Classifier is: \n",
      "[[ 238 1367]\n",
      " [  56 8744]]\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.81      0.15      0.25      1605\n",
      "           1       0.86      0.99      0.92      8800\n",
      "\n",
      "    accuracy                           0.86     10405\n",
      "   macro avg       0.84      0.57      0.59     10405\n",
      "weighted avg       0.86      0.86      0.82     10405\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from xgboost import XGBClassifier\n",
    "classifier_xg = XGBClassifier()\n",
    "classifier_xg.fit(X_train, Y_train)\n",
    "\n",
    "Y_pred_xg = classifier_xg.predict(X_test)\n",
    "\n",
    "print(\"Accuracy of XGBoost Classifier is: {}%\".format(accuracy_score(Y_test, Y_pred_xg) * 100))\n",
    "print(\"Confusion Matrix of XGBoost Classifier is: \\n{}\".format(confusion_matrix(Y_test, Y_pred_xg)))\n",
    "print(\"{}\".format(classification_report(Y_test, Y_pred_xg)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "9_RpezWW98g8"
   },
   "source": [
    "#### **Sochastic Gradient Descent Classifier (SGD)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "snk8IybL-CRh",
    "outputId": "a1f21c53-7e06-41b2-c8d1-db30150a9e51"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of Sochastic Gradient Descent Classifier is: 89.14944738106679%\n",
      "Confusion Matrix of Sochastic Gradient Descent Classifier is: \n",
      "[[ 558 1047]\n",
      " [  82 8718]]\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.87      0.35      0.50      1605\n",
      "           1       0.89      0.99      0.94      8800\n",
      "\n",
      "    accuracy                           0.89     10405\n",
      "   macro avg       0.88      0.67      0.72     10405\n",
      "weighted avg       0.89      0.89      0.87     10405\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.linear_model import SGDClassifier\n",
    "classifier_sgd = SGDClassifier()\n",
    "classifier_sgd.fit(X_train, Y_train)\n",
    "\n",
    "Y_pred_sgd = classifier_sgd.predict(X_test)\n",
    "\n",
    "print(\"Accuracy of Sochastic Gradient Descent Classifier is: {}%\".format(accuracy_score(Y_test, Y_pred_sgd) * 100))\n",
    "print(\"Confusion Matrix of Sochastic Gradient Descent Classifier is: \\n{}\".format(confusion_matrix(Y_test, Y_pred_sgd)))\n",
    "print(\"{}\".format(classification_report(Y_test, Y_pred_sgd)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "VhIGSHY1-T8l"
   },
   "source": [
    "## **Exploratory Data Analysis - II (Including the Sentiment Column)**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "OGqdtBsaXm8a"
   },
   "source": [
    "#### **HeatMap to check the Correlation (if any)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 500
    },
    "id": "qul1vnPtEmQG",
    "outputId": "968ef536-0bf0-44ad-e75d-292e60f35009"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (12, 8))\n",
    "dataset_cor_1 = dataset[['Favourites_Count', 'Retweet_count', 'Text_length', 'positive']].corr()\n",
    "axes1 = sns.heatmap(dataset_cor_1, linecolor = 'white', linewidths = 1, cmap = 'coolwarm', annot = True)\n",
    "axes1.set_title(\"Heatmap of Variables\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "xwZ1lKggXzEG"
   },
   "source": [
    "#### **Pair Plot to find relation between the features**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 903
    },
    "id": "GPeq8VwqEmEW",
    "outputId": "a9ff0607-16db-4768-e021-b724658d25d2"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x900 with 30 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(dataset)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_ZbrzgLOX9b8"
   },
   "source": [
    "#### **Date vs. Sentiment**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 626
    },
    "id": "gLC3ueQ--cR0",
    "outputId": "828ba261-6873-4c88-80c7-43225e87d604"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3240x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (45, 10))\n",
    "sns.countplot(x = dataset['Date_of_tweet'], hue = dataset['positive'], data = dataset)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "MamCV_1kYCA0"
   },
   "source": [
    "#### **Top 5 Most Favourited Tweets**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "N-Q7LyRkVsOy",
    "outputId": "e83bf081-6a55-452e-c64b-d1cf626dfd41"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "**Top 5 most Favourited tweets:**\n",
      "\n",
      "0 . #COVID19 stands still for no one. We're here, we're together, we're strong, and we're ready to fight back.\n",
      "#IndiaFightsCorona #AarogyaSetu #AarogyaSetuApp https://t.co/oDfQ0FeX79 \n",
      "\n",
      "1 . You are more prone to catching #COVID-19 infection if you are Smoking or Vaping ‼️\n",
      "\n",
      "Smoking 🚬 &amp; all forms of smoking products increase your chances of getting infected with #CoronaVirus ❗️\n",
      "Smoking transfers the virus from your hand to your mouth.\n",
      "\n",
      "Quit now 🚭\n",
      "Never too late 😊 https://t.co/3e9DGro0vu \n",
      "\n",
      "2 . Two more people die of #coronavirus in Maharashtra's Pune; toll in district climbs to 10: Officials \n",
      "\n",
      "3 . MP: A 65-year-old man who tested positive for #COVID19 passed away in Indore today.\n",
      "#PTI \n",
      "\n",
      "4 . Good morning my dear friends. \n",
      "\n",
      "My distinguished friend &amp; champion of #environment &amp;#cleanair @kavitaashok1969 has made an amazing video for our responsibility in this #coronavirus lockdown period.\n",
      "\n",
      "Request everyone to watch it and share their thoughts. \n",
      "\n",
      "https://t.co/T6dt6iInAq \n",
      "\n"
     ]
    }
   ],
   "source": [
    "fav = dataset[['Favourites_Count','Text']].sort_values('Favourites_Count',ascending = False)[:5].reset_index()\n",
    "print(\"**Top 5 most Favourited tweets:**\\n\")\n",
    "for j in range(0, 5):\n",
    "  print(j,'.', fav['Text'][j],'\\n')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "lP99Ij3MYGwG"
   },
   "source": [
    "#### **Top 5 Most Retweeted Tweet**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "_GWWpaltXF5o",
    "outputId": "cd5c8b3f-6bd9-40c6-c744-28cb2c0f341d"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "**Top 5 most Retweeted tweets:**\n",
      "\n",
      "0 . At Safdarjung Hospital: 500 faculty, 1700 resident docs, 2000 nursing staff are in shortage of protective gear\n",
      "\n",
      "The staff is in dire need of\n",
      "1 PPE Kits (Hazmat Suits)- 50,000\n",
      "2 N95 Masks- 50,000\n",
      "3 Triple Layer Masks- 3,00,000\n",
      "4 Hand Sanitizer (500ml bottles) -10,000\n",
      "\n",
      "#Covid_19 \n",
      "\n",
      "1 . This lady is working in a ICU deptt. in hospital where covid patients are treated.She came home after 20 days of non-stop service.Her family &amp; society people welcomed her\n",
      "@narendramodi\n",
      "@drharshvardhan \n",
      "@akshaykumar \n",
      "@ZeeMusicCompany \n",
      "@ParineetiChopra \n",
      "@DrKumarVishwas \n",
      "#Covid_19 https://t.co/bOncwKVMAi \n",
      "\n",
      "2 . BIG #BREAKING : Out of 9 cases of #Covid19 in Telangana, 6 ARE DEAD due to #Coronavirus All 6 had participated in this congregation in Nizamuddin! @IndiaToday \n",
      "\n",
      "3 . MY REQUEST to all.When U switch off your lights this evening at 9pm &amp; light a candle,diya or torch to show U are united against #COVID19, PLS ensure U don’t use sanitiser on your hand before lighting the fire.Sanitisers are highly inflammable. #9pm9Minute #StaySafe #StayHome \n",
      "\n",
      "4 . Ancient spiritual value system is upheld by saints,philosophers and monks of the country. Brutality towards them is an attack on the Indian culture and civilization. #PalgharMobLynching #Palghar_Incident #एकांतऔषधिहै #StayHomeStaySafe #StayAtHome @ani_digital #एकांतऔषधिहै #pryer \n",
      "\n"
     ]
    }
   ],
   "source": [
    "fav = dataset[['Retweet_count','Text']].sort_values('Retweet_count',ascending = False)[:5].reset_index()\n",
    "print(\"**Top 5 most Retweeted tweets:**\\n\")\n",
    "for j in range(5):\n",
    "  print(j,'.', fav['Text'][j],'\\n')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "hQPS5yu3EiKf"
   },
   "source": [
    "## **Conclusion**"
   ]
  },
  {
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    "#### **What is COVID-19?**\n",
    "\n",
    "COVID-19 is a disease that is caused by the SARS-CoV-2 virus. In 2020 there was a global COVID-19 pandemic.\n",
    "Most people who fall sick with COVID-19 will experience mild to moderate symptoms and recover without special treatment. \n",
    "\n",
    "The virus that causes COVID-19 is mainly transmitted through droplets generated when an infected person coughs, sneezes, or exhales. These droplets are too heavy to hang in the air, and quickly fall on floors or surfaces.\n",
    "You can be infected by breathing in the virus if you are within close proximity of someone who has COVID-19, or by touching a contaminated surface and then your eyes, nose or mouth.\n",
    "\n",
    "#### **Steps invloved:**\n",
    "\n",
    "***Step 1:*** We merged all the 33 datasets with the help of the 'os' library.\n",
    "\n",
    "***Step 2:*** We did some Data Wrangling, and obtained some vital informations about  the COVID-19 Dataset\n",
    "\n",
    "***Step 3:*** We did some Exploratory Data Analysis to gain some additional insights about the Dataset\n",
    "\n",
    "***Step 4:*** We used 'TextBlob' to create the 'Sentiment' column, which primarily stored the sentiment of people based on their tweets.\n",
    "\n",
    "(1 - Postive, 0 - Negative)\n",
    "\n",
    "***Step 5:*** Data Cleaning, i.e got rid of all the extras(https, #, @, Numeric values ,etc.) and kept only the necessary words, we used Regex to do so. \n",
    "We also used Porter Stemmer to stem the words.\n",
    "\n",
    "***Step 6:*** We used Tfidf Vectorizer to vectorize all the words.\n",
    "\n",
    "***Step 7:*** Finally, we applied the vectorized training and test sets to various classification models. \n",
    "\n",
    "#### **Results:**\n",
    "\n",
    "We trained our Model on various Machine Learning Algorithms, the results of which are attached below.\n",
    "\n",
    "1) Accuracy of **Logistic Regression** is: **89.408%**\n",
    "\n",
    "2) Accuracy of **MultinomialNB** is: **85.612%**\n",
    "\n",
    "3) Accuracy of **SVC** is: **90.024%**\n",
    "\n",
    "4) Accuracy of **Decision Tree** is: **87.938%**\n",
    "\n",
    "5) Accuracy of **Random Forest** is: **90.937%**\n",
    "\n",
    "6) Accuracy of **XG Boost** is: **86.323%**\n",
    "\n",
    "7) Accuracy of **SGD Classifier** is: **89.149%**\n"
   ]
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