ASIA DATA SET (1).ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "313bf651",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "411a35d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(\"C:/Users/priyasingh123/Downloads/asiacase.csv.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "83b4a7ea",
   "metadata": {},
   "outputs": [],
   "source": [
    "#1 understanding the data      "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5579c53d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Country</th>\n",
       "      <th>TotalCases</th>\n",
       "      <th>TotalDeaths</th>\n",
       "      <th>TotalRecovered</th>\n",
       "      <th>ActiveCases</th>\n",
       "      <th>TotalCasesPerMillion</th>\n",
       "      <th>TotalDeathsPerMillion</th>\n",
       "      <th>TotalTests</th>\n",
       "      <th>TotalTestsPerMillion</th>\n",
       "      <th>TotalPopulation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Yemen</td>\n",
       "      <td>9369</td>\n",
       "      <td>1778.0</td>\n",
       "      <td>5921</td>\n",
       "      <td>1670</td>\n",
       "      <td>306</td>\n",
       "      <td>58.0</td>\n",
       "      <td>265253.0</td>\n",
       "      <td>8651.0</td>\n",
       "      <td>30660443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Vietnam</td>\n",
       "      <td>839662</td>\n",
       "      <td>20555.0</td>\n",
       "      <td>782199</td>\n",
       "      <td>36908</td>\n",
       "      <td>8529</td>\n",
       "      <td>209.0</td>\n",
       "      <td>42517091.0</td>\n",
       "      <td>431850.0</td>\n",
       "      <td>98453377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Uzbekistan</td>\n",
       "      <td>178637</td>\n",
       "      <td>1271.0</td>\n",
       "      <td>174213</td>\n",
       "      <td>3153</td>\n",
       "      <td>5241</td>\n",
       "      <td>37.0</td>\n",
       "      <td>1377915.0</td>\n",
       "      <td>40425.0</td>\n",
       "      <td>34086135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>UAE</td>\n",
       "      <td>737890</td>\n",
       "      <td>2114.0</td>\n",
       "      <td>731295</td>\n",
       "      <td>4481</td>\n",
       "      <td>73477</td>\n",
       "      <td>211.0</td>\n",
       "      <td>87246490.0</td>\n",
       "      <td>8687776.0</td>\n",
       "      <td>10042442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Turkey</td>\n",
       "      <td>7444552</td>\n",
       "      <td>66180.0</td>\n",
       "      <td>6893476</td>\n",
       "      <td>484896</td>\n",
       "      <td>87077</td>\n",
       "      <td>774.0</td>\n",
       "      <td>89847975.0</td>\n",
       "      <td>1050928.0</td>\n",
       "      <td>85493959</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID     Country  TotalCases  TotalDeaths  TotalRecovered  ActiveCases  \\\n",
       "0   1       Yemen        9369       1778.0            5921         1670   \n",
       "1   2     Vietnam      839662      20555.0          782199        36908   \n",
       "2   3  Uzbekistan      178637       1271.0          174213         3153   \n",
       "3   4         UAE      737890       2114.0          731295         4481   \n",
       "4   5      Turkey     7444552      66180.0         6893476       484896   \n",
       "\n",
       "   TotalCasesPerMillion  TotalDeathsPerMillion  TotalTests  \\\n",
       "0                   306                   58.0    265253.0   \n",
       "1                  8529                  209.0  42517091.0   \n",
       "2                  5241                   37.0   1377915.0   \n",
       "3                 73477                  211.0  87246490.0   \n",
       "4                 87077                  774.0  89847975.0   \n",
       "\n",
       "   TotalTestsPerMillion  TotalPopulation  \n",
       "0                8651.0         30660443  \n",
       "1              431850.0         98453377  \n",
       "2               40425.0         34086135  \n",
       "3             8687776.0         10042442  \n",
       "4             1050928.0         85493959  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d06c8f38",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Country</th>\n",
       "      <th>TotalCases</th>\n",
       "      <th>TotalDeaths</th>\n",
       "      <th>TotalRecovered</th>\n",
       "      <th>ActiveCases</th>\n",
       "      <th>TotalCasesPerMillion</th>\n",
       "      <th>TotalDeathsPerMillion</th>\n",
       "      <th>TotalTests</th>\n",
       "      <th>TotalTestsPerMillion</th>\n",
       "      <th>TotalPopulation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>45</td>\n",
       "      <td>Bangladesh</td>\n",
       "      <td>1562359</td>\n",
       "      <td>27688.0</td>\n",
       "      <td>1523833</td>\n",
       "      <td>10838</td>\n",
       "      <td>9368</td>\n",
       "      <td>166.0</td>\n",
       "      <td>9952196.0</td>\n",
       "      <td>59673.0</td>\n",
       "      <td>166777589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>46</td>\n",
       "      <td>Bahrain</td>\n",
       "      <td>275654</td>\n",
       "      <td>1390.0</td>\n",
       "      <td>273672</td>\n",
       "      <td>592</td>\n",
       "      <td>155162</td>\n",
       "      <td>782.0</td>\n",
       "      <td>6597180.0</td>\n",
       "      <td>3713470.0</td>\n",
       "      <td>1776554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>47</td>\n",
       "      <td>Azerbaijan</td>\n",
       "      <td>492179</td>\n",
       "      <td>6664.0</td>\n",
       "      <td>473023</td>\n",
       "      <td>12492</td>\n",
       "      <td>47992</td>\n",
       "      <td>650.0</td>\n",
       "      <td>4952737.0</td>\n",
       "      <td>482935.0</td>\n",
       "      <td>10255503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>48</td>\n",
       "      <td>Armenia</td>\n",
       "      <td>272957</td>\n",
       "      <td>5575.0</td>\n",
       "      <td>249158</td>\n",
       "      <td>18224</td>\n",
       "      <td>91895</td>\n",
       "      <td>1877.0</td>\n",
       "      <td>1811131.0</td>\n",
       "      <td>609747.0</td>\n",
       "      <td>2970299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>49</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>155540</td>\n",
       "      <td>7228.0</td>\n",
       "      <td>126459</td>\n",
       "      <td>21853</td>\n",
       "      <td>3884</td>\n",
       "      <td>181.0</td>\n",
       "      <td>764934.0</td>\n",
       "      <td>19103.0</td>\n",
       "      <td>40041972</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    ID      Country  TotalCases  TotalDeaths  TotalRecovered  ActiveCases  \\\n",
       "44  45   Bangladesh     1562359      27688.0         1523833        10838   \n",
       "45  46      Bahrain      275654       1390.0          273672          592   \n",
       "46  47   Azerbaijan      492179       6664.0          473023        12492   \n",
       "47  48      Armenia      272957       5575.0          249158        18224   \n",
       "48  49  Afghanistan      155540       7228.0          126459        21853   \n",
       "\n",
       "    TotalCasesPerMillion  TotalDeathsPerMillion  TotalTests  \\\n",
       "44                  9368                  166.0   9952196.0   \n",
       "45                155162                  782.0   6597180.0   \n",
       "46                 47992                  650.0   4952737.0   \n",
       "47                 91895                 1877.0   1811131.0   \n",
       "48                  3884                  181.0    764934.0   \n",
       "\n",
       "    TotalTestsPerMillion  TotalPopulation  \n",
       "44               59673.0        166777589  \n",
       "45             3713470.0          1776554  \n",
       "46              482935.0         10255503  \n",
       "47              609747.0          2970299  \n",
       "48               19103.0         40041972  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "88f931ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(49, 11)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "fa2f6d4e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>TotalCases</th>\n",
       "      <th>TotalDeaths</th>\n",
       "      <th>TotalRecovered</th>\n",
       "      <th>ActiveCases</th>\n",
       "      <th>TotalCasesPerMillion</th>\n",
       "      <th>TotalDeathsPerMillion</th>\n",
       "      <th>TotalTests</th>\n",
       "      <th>TotalTestsPerMillion</th>\n",
       "      <th>TotalPopulation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>49.00000</td>\n",
       "      <td>4.900000e+01</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>4.900000e+01</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>4.800000e+01</td>\n",
       "      <td>4.800000e+01</td>\n",
       "      <td>4.900000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>25.00000</td>\n",
       "      <td>1.574671e+06</td>\n",
       "      <td>23732.937500</td>\n",
       "      <td>1.510029e+06</td>\n",
       "      <td>41393.000000</td>\n",
       "      <td>43871.632653</td>\n",
       "      <td>455.375000</td>\n",
       "      <td>2.952919e+07</td>\n",
       "      <td>1.173289e+06</td>\n",
       "      <td>9.495127e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>14.28869</td>\n",
       "      <td>4.943437e+06</td>\n",
       "      <td>68852.400621</td>\n",
       "      <td>4.829174e+06</td>\n",
       "      <td>89902.688282</td>\n",
       "      <td>46256.329145</td>\n",
       "      <td>489.395399</td>\n",
       "      <td>8.651915e+07</td>\n",
       "      <td>1.864261e+06</td>\n",
       "      <td>2.818387e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.00000</td>\n",
       "      <td>7.700000e+01</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>6.400000e+01</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>67.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>4.951000e+03</td>\n",
       "      <td>5.741000e+03</td>\n",
       "      <td>4.428110e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>13.00000</td>\n",
       "      <td>1.150680e+05</td>\n",
       "      <td>1360.250000</td>\n",
       "      <td>9.107400e+04</td>\n",
       "      <td>1670.000000</td>\n",
       "      <td>6484.000000</td>\n",
       "      <td>128.500000</td>\n",
       "      <td>2.334699e+06</td>\n",
       "      <td>1.409660e+05</td>\n",
       "      <td>5.252032e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>25.00000</td>\n",
       "      <td>4.120790e+05</td>\n",
       "      <td>5105.500000</td>\n",
       "      <td>3.913590e+05</td>\n",
       "      <td>14787.000000</td>\n",
       "      <td>24313.000000</td>\n",
       "      <td>326.500000</td>\n",
       "      <td>7.978141e+06</td>\n",
       "      <td>4.247715e+05</td>\n",
       "      <td>1.701328e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>37.00000</td>\n",
       "      <td>9.056410e+05</td>\n",
       "      <td>17798.500000</td>\n",
       "      <td>8.474560e+05</td>\n",
       "      <td>29242.000000</td>\n",
       "      <td>78714.000000</td>\n",
       "      <td>626.750000</td>\n",
       "      <td>2.510008e+07</td>\n",
       "      <td>1.031733e+06</td>\n",
       "      <td>5.132540e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>49.00000</td>\n",
       "      <td>3.397161e+07</td>\n",
       "      <td>450814.000000</td>\n",
       "      <td>3.329348e+07</td>\n",
       "      <td>484896.000000</td>\n",
       "      <td>159718.000000</td>\n",
       "      <td>2329.000000</td>\n",
       "      <td>5.836315e+08</td>\n",
       "      <td>8.687776e+06</td>\n",
       "      <td>1.439324e+09</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             ID    TotalCases    TotalDeaths  TotalRecovered    ActiveCases  \\\n",
       "count  49.00000  4.900000e+01      48.000000    4.900000e+01      49.000000   \n",
       "mean   25.00000  1.574671e+06   23732.937500    1.510029e+06   41393.000000   \n",
       "std    14.28869  4.943437e+06   68852.400621    4.829174e+06   89902.688282   \n",
       "min     1.00000  7.700000e+01       3.000000    6.400000e+01       0.000000   \n",
       "25%    13.00000  1.150680e+05    1360.250000    9.107400e+04    1670.000000   \n",
       "50%    25.00000  4.120790e+05    5105.500000    3.913590e+05   14787.000000   \n",
       "75%    37.00000  9.056410e+05   17798.500000    8.474560e+05   29242.000000   \n",
       "max    49.00000  3.397161e+07  450814.000000    3.329348e+07  484896.000000   \n",
       "\n",
       "       TotalCasesPerMillion  TotalDeathsPerMillion    TotalTests  \\\n",
       "count             49.000000              48.000000  4.800000e+01   \n",
       "mean           43871.632653             455.375000  2.952919e+07   \n",
       "std            46256.329145             489.395399  8.651915e+07   \n",
       "min               67.000000               3.000000  4.951000e+03   \n",
       "25%             6484.000000             128.500000  2.334699e+06   \n",
       "50%            24313.000000             326.500000  7.978141e+06   \n",
       "75%            78714.000000             626.750000  2.510008e+07   \n",
       "max           159718.000000            2329.000000  5.836315e+08   \n",
       "\n",
       "       TotalTestsPerMillion  TotalPopulation  \n",
       "count          4.800000e+01     4.900000e+01  \n",
       "mean           1.173289e+06     9.495127e+07  \n",
       "std            1.864261e+06     2.818387e+08  \n",
       "min            5.741000e+03     4.428110e+05  \n",
       "25%            1.409660e+05     5.252032e+06  \n",
       "50%            4.247715e+05     1.701328e+07  \n",
       "75%            1.031733e+06     5.132540e+07  \n",
       "max            8.687776e+06     1.439324e+09  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "55f675bd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 49 entries, 0 to 48\n",
      "Data columns (total 11 columns):\n",
      " #   Column                 Non-Null Count  Dtype  \n",
      "---  ------                 --------------  -----  \n",
      " 0   ID                     49 non-null     int64  \n",
      " 1   Country                49 non-null     object \n",
      " 2   TotalCases             49 non-null     int64  \n",
      " 3   TotalDeaths            48 non-null     float64\n",
      " 4   TotalRecovered         49 non-null     int64  \n",
      " 5   ActiveCases            49 non-null     int64  \n",
      " 6   TotalCasesPerMillion   49 non-null     int64  \n",
      " 7   TotalDeathsPerMillion  48 non-null     float64\n",
      " 8   TotalTests             48 non-null     float64\n",
      " 9   TotalTestsPerMillion   48 non-null     float64\n",
      " 10  TotalPopulation        49 non-null     int64  \n",
      "dtypes: float64(4), int64(6), object(1)\n",
      "memory usage: 4.3+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "866d6e6d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['ID', 'Country', 'TotalCases', 'TotalDeaths', 'TotalRecovered',\n",
       "       'ActiveCases', 'TotalCasesPerMillion', 'TotalDeathsPerMillion',\n",
       "       'TotalTests', 'TotalTestsPerMillion', 'TotalPopulation'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "365a0243",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ID                       49\n",
       "Country                  49\n",
       "TotalCases               49\n",
       "TotalDeaths              48\n",
       "TotalRecovered           49\n",
       "ActiveCases              49\n",
       "TotalCasesPerMillion     49\n",
       "TotalDeathsPerMillion    47\n",
       "TotalTests               48\n",
       "TotalTestsPerMillion     48\n",
       "TotalPopulation          49\n",
       "dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "aeddb06c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Yemen', 'Vietnam', 'Uzbekistan', 'UAE', 'Turkey', 'Timor-Leste',\n",
       "       'Thailand', 'Tajikistan', 'Taiwan', 'Syria', 'Sri Lanka',\n",
       "       'Singapore', 'Saudi Arabia', 'S. Korea', 'Qatar', 'Philippines',\n",
       "       'Palestine', 'Pakistan', 'Oman', 'Nepal', 'Myanmar', 'Mongolia',\n",
       "       'Maldives', 'Malaysia', 'Macao', 'Lebanon', 'Laos', 'Kyrgyzstan',\n",
       "       'Kuwait', 'Kazakhstan', 'Jordan', 'Japan', 'Israel', 'Iraq',\n",
       "       'Iran', 'Indonesia', 'India', 'Hong Kong', 'Georgia', 'Cyprus',\n",
       "       'China', 'Cambodia', 'Brunei', 'Bhutan', 'Bangladesh', 'Bahrain',\n",
       "       'Azerbaijan', 'Armenia', 'Afghanistan'], dtype=object)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Country'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "8f25aea4",
   "metadata": {},
   "outputs": [],
   "source": [
    "#2 cleaning the data set       "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "e81ddcae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ID                       0\n",
       "Country                  0\n",
       "TotalCases               0\n",
       "TotalDeaths              1\n",
       "TotalRecovered           0\n",
       "ActiveCases              0\n",
       "TotalCasesPerMillion     0\n",
       "TotalDeathsPerMillion    1\n",
       "TotalTests               1\n",
       "TotalTestsPerMillion     1\n",
       "TotalPopulation          0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "683c2930",
   "metadata": {},
   "outputs": [],
   "source": [
    "asiacase = data.drop(['TotalDeaths', 'TotalDeathsPerMillion', 'TotalTests', 'TotalTestsPerMillion', 'ID'], axis=1) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "9c959796",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>TotalCases</th>\n",
       "      <th>TotalRecovered</th>\n",
       "      <th>ActiveCases</th>\n",
       "      <th>TotalCasesPerMillion</th>\n",
       "      <th>TotalPopulation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Yemen</td>\n",
       "      <td>9369</td>\n",
       "      <td>5921</td>\n",
       "      <td>1670</td>\n",
       "      <td>306</td>\n",
       "      <td>30660443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Vietnam</td>\n",
       "      <td>839662</td>\n",
       "      <td>782199</td>\n",
       "      <td>36908</td>\n",
       "      <td>8529</td>\n",
       "      <td>98453377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Uzbekistan</td>\n",
       "      <td>178637</td>\n",
       "      <td>174213</td>\n",
       "      <td>3153</td>\n",
       "      <td>5241</td>\n",
       "      <td>34086135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>UAE</td>\n",
       "      <td>737890</td>\n",
       "      <td>731295</td>\n",
       "      <td>4481</td>\n",
       "      <td>73477</td>\n",
       "      <td>10042442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Turkey</td>\n",
       "      <td>7444552</td>\n",
       "      <td>6893476</td>\n",
       "      <td>484896</td>\n",
       "      <td>87077</td>\n",
       "      <td>85493959</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Country  TotalCases  TotalRecovered  ActiveCases  TotalCasesPerMillion  \\\n",
       "0       Yemen        9369            5921         1670                   306   \n",
       "1     Vietnam      839662          782199        36908                  8529   \n",
       "2  Uzbekistan      178637          174213         3153                  5241   \n",
       "3         UAE      737890          731295         4481                 73477   \n",
       "4      Turkey     7444552         6893476       484896                 87077   \n",
       "\n",
       "   TotalPopulation  \n",
       "0         30660443  \n",
       "1         98453377  \n",
       "2         34086135  \n",
       "3         10042442  \n",
       "4         85493959  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "asiacase.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "aa3fbb60",
   "metadata": {},
   "outputs": [],
   "source": [
    "#3 relationship analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "a5b8225a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>ActiveCases</th>\n",
       "      <th>TotalCases</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Turkey</td>\n",
       "      <td>484896</td>\n",
       "      <td>7444552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Iran</td>\n",
       "      <td>362299</td>\n",
       "      <td>5702890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>India</td>\n",
       "      <td>227315</td>\n",
       "      <td>33971607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Malaysia</td>\n",
       "      <td>116596</td>\n",
       "      <td>2339594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Thailand</td>\n",
       "      <td>110265</td>\n",
       "      <td>1720919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Philippines</td>\n",
       "      <td>98894</td>\n",
       "      <td>2674814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Iraq</td>\n",
       "      <td>55832</td>\n",
       "      <td>2023761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Kazakhstan</td>\n",
       "      <td>46626</td>\n",
       "      <td>905641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Pakistan</td>\n",
       "      <td>42263</td>\n",
       "      <td>1258959</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Vietnam</td>\n",
       "      <td>36908</td>\n",
       "      <td>839662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Sri Lanka</td>\n",
       "      <td>32955</td>\n",
       "      <td>526383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>S. Korea</td>\n",
       "      <td>32211</td>\n",
       "      <td>332816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Myanmar</td>\n",
       "      <td>29242</td>\n",
       "      <td>478651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>Cyprus</td>\n",
       "      <td>28328</td>\n",
       "      <td>119642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Singapore</td>\n",
       "      <td>26307</td>\n",
       "      <td>126966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Israel</td>\n",
       "      <td>25322</td>\n",
       "      <td>1306333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Mongolia</td>\n",
       "      <td>25214</td>\n",
       "      <td>326738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Indonesia</td>\n",
       "      <td>24430</td>\n",
       "      <td>4227932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Georgia</td>\n",
       "      <td>23942</td>\n",
       "      <td>635583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Laos</td>\n",
       "      <td>21956</td>\n",
       "      <td>28540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>21853</td>\n",
       "      <td>155540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Lebanon</td>\n",
       "      <td>19080</td>\n",
       "      <td>630180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>Armenia</td>\n",
       "      <td>18224</td>\n",
       "      <td>272957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Palestine</td>\n",
       "      <td>17815</td>\n",
       "      <td>413410</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Nepal</td>\n",
       "      <td>14787</td>\n",
       "      <td>802861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Jordan</td>\n",
       "      <td>13688</td>\n",
       "      <td>833471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Azerbaijan</td>\n",
       "      <td>12492</td>\n",
       "      <td>492179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Japan</td>\n",
       "      <td>11830</td>\n",
       "      <td>1710973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Bangladesh</td>\n",
       "      <td>10838</td>\n",
       "      <td>1562359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Syria</td>\n",
       "      <td>10109</td>\n",
       "      <td>36953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>UAE</td>\n",
       "      <td>4481</td>\n",
       "      <td>737890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Cambodia</td>\n",
       "      <td>4138</td>\n",
       "      <td>115068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Uzbekistan</td>\n",
       "      <td>3153</td>\n",
       "      <td>178637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Kyrgyzstan</td>\n",
       "      <td>2632</td>\n",
       "      <td>179338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Brunei</td>\n",
       "      <td>2226</td>\n",
       "      <td>8980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Saudi Arabia</td>\n",
       "      <td>2220</td>\n",
       "      <td>547591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Yemen</td>\n",
       "      <td>1670</td>\n",
       "      <td>9369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Maldives</td>\n",
       "      <td>1250</td>\n",
       "      <td>85548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Qatar</td>\n",
       "      <td>977</td>\n",
       "      <td>237424</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>China</td>\n",
       "      <td>713</td>\n",
       "      <td>96423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Kuwait</td>\n",
       "      <td>623</td>\n",
       "      <td>412079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Bahrain</td>\n",
       "      <td>592</td>\n",
       "      <td>275654</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Oman</td>\n",
       "      <td>567</td>\n",
       "      <td>303978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Timor-Leste</td>\n",
       "      <td>222</td>\n",
       "      <td>19673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Taiwan</td>\n",
       "      <td>153</td>\n",
       "      <td>16305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Hong Kong</td>\n",
       "      <td>103</td>\n",
       "      <td>12269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Macao</td>\n",
       "      <td>13</td>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Bhutan</td>\n",
       "      <td>7</td>\n",
       "      <td>2613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Tajikistan</td>\n",
       "      <td>0</td>\n",
       "      <td>17084</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Country  ActiveCases  TotalCases\n",
       "4         Turkey       484896     7444552\n",
       "34          Iran       362299     5702890\n",
       "36         India       227315    33971607\n",
       "23      Malaysia       116596     2339594\n",
       "6       Thailand       110265     1720919\n",
       "15   Philippines        98894     2674814\n",
       "33          Iraq        55832     2023761\n",
       "29    Kazakhstan        46626      905641\n",
       "17      Pakistan        42263     1258959\n",
       "1        Vietnam        36908      839662\n",
       "10     Sri Lanka        32955      526383\n",
       "13      S. Korea        32211      332816\n",
       "20       Myanmar        29242      478651\n",
       "39        Cyprus        28328      119642\n",
       "11     Singapore        26307      126966\n",
       "32        Israel        25322     1306333\n",
       "21      Mongolia        25214      326738\n",
       "35     Indonesia        24430     4227932\n",
       "38       Georgia        23942      635583\n",
       "26          Laos        21956       28540\n",
       "48   Afghanistan        21853      155540\n",
       "25       Lebanon        19080      630180\n",
       "47       Armenia        18224      272957\n",
       "16     Palestine        17815      413410\n",
       "19         Nepal        14787      802861\n",
       "30        Jordan        13688      833471\n",
       "46    Azerbaijan        12492      492179\n",
       "31         Japan        11830     1710973\n",
       "44    Bangladesh        10838     1562359\n",
       "9          Syria        10109       36953\n",
       "3            UAE         4481      737890\n",
       "41      Cambodia         4138      115068\n",
       "2     Uzbekistan         3153      178637\n",
       "27    Kyrgyzstan         2632      179338\n",
       "42        Brunei         2226        8980\n",
       "12  Saudi Arabia         2220      547591\n",
       "0          Yemen         1670        9369\n",
       "22      Maldives         1250       85548\n",
       "14         Qatar          977      237424\n",
       "40         China          713       96423\n",
       "28        Kuwait          623      412079\n",
       "45       Bahrain          592      275654\n",
       "18          Oman          567      303978\n",
       "5    Timor-Leste          222       19673\n",
       "8         Taiwan          153       16305\n",
       "37     Hong Kong          103       12269\n",
       "24         Macao           13          77\n",
       "43        Bhutan            7        2613\n",
       "7     Tajikistan            0       17084"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# finding the country with most active cases in Asia\n",
    "high_total=data[['Country', 'ActiveCases','TotalCases']].sort_values(by=\"ActiveCases\", ascending=False)\n",
    "high_total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "f249a411",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>TotalPopulation</th>\n",
       "      <th>TotalCases</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>India</td>\n",
       "      <td>1397272327</td>\n",
       "      <td>33971607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Turkey</td>\n",
       "      <td>85493959</td>\n",
       "      <td>7444552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Iran</td>\n",
       "      <td>85360646</td>\n",
       "      <td>5702890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Indonesia</td>\n",
       "      <td>277204401</td>\n",
       "      <td>4227932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Philippines</td>\n",
       "      <td>111436429</td>\n",
       "      <td>2674814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Malaysia</td>\n",
       "      <td>32893558</td>\n",
       "      <td>2339594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Iraq</td>\n",
       "      <td>41369013</td>\n",
       "      <td>2023761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Thailand</td>\n",
       "      <td>70023091</td>\n",
       "      <td>1720919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Japan</td>\n",
       "      <td>125982980</td>\n",
       "      <td>1710973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Bangladesh</td>\n",
       "      <td>166777589</td>\n",
       "      <td>1562359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Israel</td>\n",
       "      <td>9326000</td>\n",
       "      <td>1306333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Pakistan</td>\n",
       "      <td>226343318</td>\n",
       "      <td>1258959</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Kazakhstan</td>\n",
       "      <td>19062471</td>\n",
       "      <td>905641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Vietnam</td>\n",
       "      <td>98453377</td>\n",
       "      <td>839662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Jordan</td>\n",
       "      <td>10332048</td>\n",
       "      <td>833471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Nepal</td>\n",
       "      <td>29802972</td>\n",
       "      <td>802861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>UAE</td>\n",
       "      <td>10042442</td>\n",
       "      <td>737890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Georgia</td>\n",
       "      <td>3979408</td>\n",
       "      <td>635583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Lebanon</td>\n",
       "      <td>6786483</td>\n",
       "      <td>630180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Saudi Arabia</td>\n",
       "      <td>35503333</td>\n",
       "      <td>547591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Sri Lanka</td>\n",
       "      <td>21527599</td>\n",
       "      <td>526383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Azerbaijan</td>\n",
       "      <td>10255503</td>\n",
       "      <td>492179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Myanmar</td>\n",
       "      <td>54874222</td>\n",
       "      <td>478651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Palestine</td>\n",
       "      <td>5252032</td>\n",
       "      <td>413410</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Kuwait</td>\n",
       "      <td>4350895</td>\n",
       "      <td>412079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>S. Korea</td>\n",
       "      <td>51325401</td>\n",
       "      <td>332816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Mongolia</td>\n",
       "      <td>3345419</td>\n",
       "      <td>326738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Oman</td>\n",
       "      <td>5271518</td>\n",
       "      <td>303978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Bahrain</td>\n",
       "      <td>1776554</td>\n",
       "      <td>275654</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>Armenia</td>\n",
       "      <td>2970299</td>\n",
       "      <td>272957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Qatar</td>\n",
       "      <td>2807805</td>\n",
       "      <td>237424</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Kyrgyzstan</td>\n",
       "      <td>6661055</td>\n",
       "      <td>179338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Uzbekistan</td>\n",
       "      <td>34086135</td>\n",
       "      <td>178637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>40041972</td>\n",
       "      <td>155540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Singapore</td>\n",
       "      <td>5908916</td>\n",
       "      <td>126966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>Cyprus</td>\n",
       "      <td>1218549</td>\n",
       "      <td>119642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Cambodia</td>\n",
       "      <td>17013282</td>\n",
       "      <td>115068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>China</td>\n",
       "      <td>1439323776</td>\n",
       "      <td>96423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Maldives</td>\n",
       "      <td>552647</td>\n",
       "      <td>85548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Syria</td>\n",
       "      <td>18040518</td>\n",
       "      <td>36953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Laos</td>\n",
       "      <td>7409837</td>\n",
       "      <td>28540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Timor-Leste</td>\n",
       "      <td>1350361</td>\n",
       "      <td>19673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Tajikistan</td>\n",
       "      <td>9809760</td>\n",
       "      <td>17084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Taiwan</td>\n",
       "      <td>23871692</td>\n",
       "      <td>16305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Hong Kong</td>\n",
       "      <td>7574410</td>\n",
       "      <td>12269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Yemen</td>\n",
       "      <td>30660443</td>\n",
       "      <td>9369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Brunei</td>\n",
       "      <td>442811</td>\n",
       "      <td>8980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Bhutan</td>\n",
       "      <td>782420</td>\n",
       "      <td>2613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Macao</td>\n",
       "      <td>660595</td>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Country  TotalPopulation  TotalCases\n",
       "36         India       1397272327    33971607\n",
       "4         Turkey         85493959     7444552\n",
       "34          Iran         85360646     5702890\n",
       "35     Indonesia        277204401     4227932\n",
       "15   Philippines        111436429     2674814\n",
       "23      Malaysia         32893558     2339594\n",
       "33          Iraq         41369013     2023761\n",
       "6       Thailand         70023091     1720919\n",
       "31         Japan        125982980     1710973\n",
       "44    Bangladesh        166777589     1562359\n",
       "32        Israel          9326000     1306333\n",
       "17      Pakistan        226343318     1258959\n",
       "29    Kazakhstan         19062471      905641\n",
       "1        Vietnam         98453377      839662\n",
       "30        Jordan         10332048      833471\n",
       "19         Nepal         29802972      802861\n",
       "3            UAE         10042442      737890\n",
       "38       Georgia          3979408      635583\n",
       "25       Lebanon          6786483      630180\n",
       "12  Saudi Arabia         35503333      547591\n",
       "10     Sri Lanka         21527599      526383\n",
       "46    Azerbaijan         10255503      492179\n",
       "20       Myanmar         54874222      478651\n",
       "16     Palestine          5252032      413410\n",
       "28        Kuwait          4350895      412079\n",
       "13      S. Korea         51325401      332816\n",
       "21      Mongolia          3345419      326738\n",
       "18          Oman          5271518      303978\n",
       "45       Bahrain          1776554      275654\n",
       "47       Armenia          2970299      272957\n",
       "14         Qatar          2807805      237424\n",
       "27    Kyrgyzstan          6661055      179338\n",
       "2     Uzbekistan         34086135      178637\n",
       "48   Afghanistan         40041972      155540\n",
       "11     Singapore          5908916      126966\n",
       "39        Cyprus          1218549      119642\n",
       "41      Cambodia         17013282      115068\n",
       "40         China       1439323776       96423\n",
       "22      Maldives           552647       85548\n",
       "9          Syria         18040518       36953\n",
       "26          Laos          7409837       28540\n",
       "5    Timor-Leste          1350361       19673\n",
       "7     Tajikistan          9809760       17084\n",
       "8         Taiwan         23871692       16305\n",
       "37     Hong Kong          7574410       12269\n",
       "0          Yemen         30660443        9369\n",
       "42        Brunei           442811        8980\n",
       "43        Bhutan           782420        2613\n",
       "24         Macao           660595          77"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# finding the country with most total cases in Asia\n",
    "high_total=data[['Country', 'TotalPopulation','TotalCases']].sort_values(by=\"TotalCases\", ascending=False)\n",
    "high_total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "25d3254c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>TotalPopulation</th>\n",
       "      <th>TotalCases</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>India</td>\n",
       "      <td>1397272327</td>\n",
       "      <td>33971607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Turkey</td>\n",
       "      <td>85493959</td>\n",
       "      <td>7444552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Iran</td>\n",
       "      <td>85360646</td>\n",
       "      <td>5702890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Indonesia</td>\n",
       "      <td>277204401</td>\n",
       "      <td>4227932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Philippines</td>\n",
       "      <td>111436429</td>\n",
       "      <td>2674814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Malaysia</td>\n",
       "      <td>32893558</td>\n",
       "      <td>2339594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Iraq</td>\n",
       "      <td>41369013</td>\n",
       "      <td>2023761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Thailand</td>\n",
       "      <td>70023091</td>\n",
       "      <td>1720919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Japan</td>\n",
       "      <td>125982980</td>\n",
       "      <td>1710973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Bangladesh</td>\n",
       "      <td>166777589</td>\n",
       "      <td>1562359</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Country TotalPopulation TotalCases\n",
       "0        India      1397272327   33971607\n",
       "1       Turkey        85493959    7444552\n",
       "2         Iran        85360646    5702890\n",
       "3    Indonesia       277204401    4227932\n",
       "4  Philippines       111436429    2674814\n",
       "5     Malaysia        32893558    2339594\n",
       "6         Iraq        41369013    2023761\n",
       "7     Thailand        70023091    1720919\n",
       "8        Japan       125982980    1710973\n",
       "9   Bangladesh       166777589    1562359"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "high_total = high_total.iloc[:10,:]\n",
    "country = pd.DataFrame(high_total.values, columns= high_total.columns)\n",
    "country"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "fbb53b25",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,5))\n",
    "plt.bar(country[\"Country\"], country[\"TotalCases\"])\n",
    "plt.xlabel(\"Countries\")\n",
    "plt.xticks(rotation='45')\n",
    "plt.ylabel(\"Total Cases\")\n",
    "plt.title(\"Top 10 Asia Country with  most cases\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "daaa551b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>TotalPopulation</th>\n",
       "      <th>TotalCases</th>\n",
       "      <th>TotalDeaths</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>India</td>\n",
       "      <td>1397272327</td>\n",
       "      <td>33971607</td>\n",
       "      <td>450814.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Indonesia</td>\n",
       "      <td>277204401</td>\n",
       "      <td>4227932</td>\n",
       "      <td>142651.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Iran</td>\n",
       "      <td>85360646</td>\n",
       "      <td>5702890</td>\n",
       "      <td>122592.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Turkey</td>\n",
       "      <td>85493959</td>\n",
       "      <td>7444552</td>\n",
       "      <td>66180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Philippines</td>\n",
       "      <td>111436429</td>\n",
       "      <td>2674814</td>\n",
       "      <td>39660.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Pakistan</td>\n",
       "      <td>226343318</td>\n",
       "      <td>1258959</td>\n",
       "      <td>28134.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Bangladesh</td>\n",
       "      <td>166777589</td>\n",
       "      <td>1562359</td>\n",
       "      <td>27688.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Malaysia</td>\n",
       "      <td>32893558</td>\n",
       "      <td>2339594</td>\n",
       "      <td>27329.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Iraq</td>\n",
       "      <td>41369013</td>\n",
       "      <td>2023761</td>\n",
       "      <td>22563.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Vietnam</td>\n",
       "      <td>98453377</td>\n",
       "      <td>839662</td>\n",
       "      <td>20555.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Country TotalPopulation TotalCases TotalDeaths\n",
       "0        India      1397272327   33971607    450814.0\n",
       "1    Indonesia       277204401    4227932    142651.0\n",
       "2         Iran        85360646    5702890    122592.0\n",
       "3       Turkey        85493959    7444552     66180.0\n",
       "4  Philippines       111436429    2674814     39660.0\n",
       "5     Pakistan       226343318    1258959     28134.0\n",
       "6   Bangladesh       166777589    1562359     27688.0\n",
       "7     Malaysia        32893558    2339594     27329.0\n",
       "8         Iraq        41369013    2023761     22563.0\n",
       "9      Vietnam        98453377     839662     20555.0"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "death=data[['Country', 'TotalPopulation','TotalCases', \"TotalDeaths\"]].sort_values(by=\"TotalDeaths\", ascending=False).iloc[:10,:]\n",
    "death_bar=pd.DataFrame(death.values, columns= death.columns)\n",
    "death_bar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "55e9c8e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,5))\n",
    "plt.plot(death_bar[\"Country\"],death_bar[\"TotalDeaths\"])\n",
    "plt.xlabel(\"Countries\")\n",
    "plt.xticks(rotation='45')\n",
    "plt.ylabel(\"Total Deaths\")\n",
    "plt.title(\"Top 10 Asia Country with  most deaths\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "fddd18bf",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Data of India"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "3a0d275e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Country</th>\n",
       "      <th>TotalCases</th>\n",
       "      <th>TotalDeaths</th>\n",
       "      <th>TotalRecovered</th>\n",
       "      <th>ActiveCases</th>\n",
       "      <th>TotalCasesPerMillion</th>\n",
       "      <th>TotalDeathsPerMillion</th>\n",
       "      <th>TotalTests</th>\n",
       "      <th>TotalTestsPerMillion</th>\n",
       "      <th>TotalPopulation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>37</td>\n",
       "      <td>India</td>\n",
       "      <td>33971607</td>\n",
       "      <td>450814.0</td>\n",
       "      <td>33293478</td>\n",
       "      <td>227315</td>\n",
       "      <td>24313</td>\n",
       "      <td>323.0</td>\n",
       "      <td>583631490.0</td>\n",
       "      <td>417693.0</td>\n",
       "      <td>1397272327</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    ID Country  TotalCases  TotalDeaths  TotalRecovered  ActiveCases  \\\n",
       "36  37   India    33971607     450814.0        33293478       227315   \n",
       "\n",
       "    TotalCasesPerMillion  TotalDeathsPerMillion   TotalTests  \\\n",
       "36                 24313                  323.0  583631490.0   \n",
       "\n",
       "    TotalTestsPerMillion  TotalPopulation  \n",
       "36              417693.0       1397272327  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "india= data[data['Country']== 'India']\n",
    "india"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "71d05715",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "label=( 'TotalTests','TotalCases', 'TotalDeaths', 'TotalRecovered')\n",
    "y=np.array([ float(india['TotalTests']),float(india['TotalCases']),float(india['TotalDeaths']),float(india['TotalRecovered'])])\n",
    "\n",
    "n_explode = [ 0.1, 0.1, 0.15,0.2]\n",
    "my_colors=['silver','blue','black','orange']\n",
    "\n",
    "plt.pie(y, labels = label, startangle = 90,colors=my_colors, explode=n_explode)\n",
    "plt.legend(loc= 2)\n",
    "plt.tight_layout(pad=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "2efadbd8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "label=('TotalCases', 'TotalDeaths', 'TotalRecovered')\n",
    "y=np.array([ float(india['TotalCases']),float(india['TotalDeaths']),float(india['TotalRecovered'])])\n",
    "\n",
    "n_explode = [ 0.04, 0,0.01]\n",
    "my_colors=['red','green','yellow']\n",
    "\n",
    "plt.pie(y, labels = label, startangle = 90,colors=my_colors, explode=n_explode)\n",
    "plt.legend(loc= 2)\n",
    "plt.tight_layout(pad=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "728f5a01",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}