Covid Dashboard.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "c0459efa",
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "7adffc63",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn import preprocessing,cross_decomposition,model_selection,metrics\n",
    "import matplotlib.pyplot as plt\n",
    "# import seaborn as sns\n",
    "# import xgboost as xgb\n",
    "%matplotlib inline\n",
    "import dateutil\n",
    "from sklearn import linear_model\n",
    "import datetime\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import plotly.graph_objects as go\n",
    "from ipywidgets import widgets\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import plotly.graph_objects as go\n",
    "from ipywidgets import widgets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "ff0c91d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "confirmedGlobal=pd.read_csv('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv',encoding='utf-8',na_values=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "386b5478",
   "metadata": {
    "scrolled": false
   },
   "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>Province/State</th>\n",
       "      <th>Country/Region</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Long</th>\n",
       "      <th>1/22/20</th>\n",
       "      <th>1/23/20</th>\n",
       "      <th>1/24/20</th>\n",
       "      <th>1/25/20</th>\n",
       "      <th>1/26/20</th>\n",
       "      <th>1/27/20</th>\n",
       "      <th>...</th>\n",
       "      <th>6/11/22</th>\n",
       "      <th>6/12/22</th>\n",
       "      <th>6/13/22</th>\n",
       "      <th>6/14/22</th>\n",
       "      <th>6/15/22</th>\n",
       "      <th>6/16/22</th>\n",
       "      <th>6/17/22</th>\n",
       "      <th>6/18/22</th>\n",
       "      <th>6/19/22</th>\n",
       "      <th>6/20/22</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>33.93911</td>\n",
       "      <td>67.709953</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>181178</td>\n",
       "      <td>181236</td>\n",
       "      <td>181465</td>\n",
       "      <td>181534</td>\n",
       "      <td>181574</td>\n",
       "      <td>181666</td>\n",
       "      <td>181725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Albania</td>\n",
       "      <td>41.15330</td>\n",
       "      <td>20.168300</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>276690</td>\n",
       "      <td>276731</td>\n",
       "      <td>276731</td>\n",
       "      <td>276821</td>\n",
       "      <td>276821</td>\n",
       "      <td>276821</td>\n",
       "      <td>277141</td>\n",
       "      <td>277141</td>\n",
       "      <td>277409</td>\n",
       "      <td>277444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Algeria</td>\n",
       "      <td>28.03390</td>\n",
       "      <td>1.659600</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>265925</td>\n",
       "      <td>265927</td>\n",
       "      <td>265937</td>\n",
       "      <td>265943</td>\n",
       "      <td>265952</td>\n",
       "      <td>265964</td>\n",
       "      <td>265968</td>\n",
       "      <td>265971</td>\n",
       "      <td>265975</td>\n",
       "      <td>265985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Andorra</td>\n",
       "      <td>42.50630</td>\n",
       "      <td>1.521800</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>43449</td>\n",
       "      <td>43449</td>\n",
       "      <td>43449</td>\n",
       "      <td>43449</td>\n",
       "      <td>43449</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Angola</td>\n",
       "      <td>-11.20270</td>\n",
       "      <td>17.873900</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>99761</td>\n",
       "      <td>99761</td>\n",
       "      <td>99761</td>\n",
       "      <td>99761</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 885 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Province/State Country/Region       Lat       Long  1/22/20  1/23/20  \\\n",
       "0            NaN    Afghanistan  33.93911  67.709953        0        0   \n",
       "1            NaN        Albania  41.15330  20.168300        0        0   \n",
       "2            NaN        Algeria  28.03390   1.659600        0        0   \n",
       "3            NaN        Andorra  42.50630   1.521800        0        0   \n",
       "4            NaN         Angola -11.20270  17.873900        0        0   \n",
       "\n",
       "   1/24/20  1/25/20  1/26/20  1/27/20  ...  6/11/22  6/12/22  6/13/22  \\\n",
       "0        0        0        0        0  ...   180864   180864   181120   \n",
       "1        0        0        0        0  ...   276690   276731   276731   \n",
       "2        0        0        0        0  ...   265925   265927   265937   \n",
       "3        0        0        0        0  ...    43224    43224    43224   \n",
       "4        0        0        0        0  ...    99761    99761    99761   \n",
       "\n",
       "   6/14/22  6/15/22  6/16/22  6/17/22  6/18/22  6/19/22  6/20/22  \n",
       "0   181178   181236   181465   181534   181574   181666   181725  \n",
       "1   276821   276821   276821   277141   277141   277409   277444  \n",
       "2   265943   265952   265964   265968   265971   265975   265985  \n",
       "3    43224    43449    43449    43449    43449    43449    43449  \n",
       "4    99761    99761    99761    99761    99761    99761    99761  \n",
       "\n",
       "[5 rows x 885 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "confirmedGlobal.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "be78a371",
   "metadata": {},
   "outputs": [],
   "source": [
    "bar_graph = confirmedGlobal[['Country/Region',confirmedGlobal.columns[-1]]].groupby('Country/Region').sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "43d6ef28",
   "metadata": {},
   "outputs": [],
   "source": [
    "bar_graph = bar_graph.reset_index()\n",
    "bar_graph.columns = ['Country/Region', 'values']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "c963d996",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['US',\n",
       " 'India',\n",
       " 'Brazil',\n",
       " 'France',\n",
       " 'Germany',\n",
       " 'United Kingdom',\n",
       " 'Korea, South',\n",
       " 'Russia',\n",
       " 'Italy',\n",
       " 'Turkey',\n",
       " 'Spain',\n",
       " 'Vietnam',\n",
       " 'Argentina',\n",
       " 'Japan',\n",
       " 'Netherlands',\n",
       " 'Australia',\n",
       " 'Iran',\n",
       " 'Colombia',\n",
       " 'Indonesia',\n",
       " 'Poland',\n",
       " 'Mexico',\n",
       " 'Portugal',\n",
       " 'Ukraine',\n",
       " 'Malaysia',\n",
       " 'Thailand',\n",
       " 'Austria',\n",
       " 'Israel',\n",
       " 'Belgium',\n",
       " 'South Africa',\n",
       " 'Canada',\n",
       " 'Czechia',\n",
       " 'Chile',\n",
       " 'Switzerland',\n",
       " 'Philippines',\n",
       " 'Peru',\n",
       " 'Greece',\n",
       " 'Taiwan*',\n",
       " 'Denmark',\n",
       " 'Romania',\n",
       " 'Slovakia',\n",
       " 'Sweden',\n",
       " 'Iraq',\n",
       " 'China',\n",
       " 'Serbia',\n",
       " 'Bangladesh',\n",
       " 'Hungary',\n",
       " 'Jordan',\n",
       " 'Georgia',\n",
       " 'Ireland',\n",
       " 'Pakistan',\n",
       " 'Norway',\n",
       " 'Kazakhstan',\n",
       " 'Singapore',\n",
       " 'New Zealand',\n",
       " 'Morocco',\n",
       " 'Bulgaria',\n",
       " 'Croatia',\n",
       " 'Finland',\n",
       " 'Cuba',\n",
       " 'Lebanon',\n",
       " 'Lithuania',\n",
       " 'Tunisia',\n",
       " 'Slovenia',\n",
       " 'Belarus',\n",
       " 'Nepal',\n",
       " 'Uruguay',\n",
       " 'United Arab Emirates',\n",
       " 'Mongolia',\n",
       " 'Bolivia',\n",
       " 'Costa Rica',\n",
       " 'Panama',\n",
       " 'Ecuador',\n",
       " 'Guatemala',\n",
       " 'Latvia',\n",
       " 'Azerbaijan',\n",
       " 'Saudi Arabia',\n",
       " 'Sri Lanka',\n",
       " 'West Bank and Gaza',\n",
       " 'Paraguay',\n",
       " 'Kuwait',\n",
       " 'Burma',\n",
       " 'Bahrain',\n",
       " 'Dominican Republic',\n",
       " 'Estonia',\n",
       " 'Venezuela',\n",
       " 'Moldova',\n",
       " 'Egypt',\n",
       " 'Libya',\n",
       " 'Cyprus',\n",
       " 'Ethiopia',\n",
       " 'Honduras',\n",
       " 'Armenia',\n",
       " 'Oman',\n",
       " 'Bosnia and Herzegovina',\n",
       " 'Qatar',\n",
       " 'Kenya',\n",
       " 'Zambia',\n",
       " 'Botswana',\n",
       " 'North Macedonia',\n",
       " 'Albania',\n",
       " 'Algeria',\n",
       " 'Nigeria',\n",
       " 'Luxembourg',\n",
       " 'Zimbabwe',\n",
       " 'Uzbekistan',\n",
       " 'Montenegro',\n",
       " 'Kosovo',\n",
       " 'Mauritius',\n",
       " 'Mozambique',\n",
       " 'Laos',\n",
       " 'Kyrgyzstan',\n",
       " 'Iceland',\n",
       " 'Afghanistan',\n",
       " 'Maldives',\n",
       " 'Namibia',\n",
       " 'Uganda',\n",
       " 'Trinidad and Tobago',\n",
       " 'Ghana',\n",
       " 'El Salvador',\n",
       " 'Brunei',\n",
       " 'Jamaica',\n",
       " 'Cambodia',\n",
       " 'Rwanda',\n",
       " 'Cameroon',\n",
       " 'Angola',\n",
       " 'Malta',\n",
       " 'Congo (Kinshasa)',\n",
       " 'Senegal',\n",
       " 'Malawi',\n",
       " 'Barbados',\n",
       " \"Cote d'Ivoire\",\n",
       " 'Suriname',\n",
       " 'Eswatini',\n",
       " 'Guyana',\n",
       " 'Fiji',\n",
       " 'Madagascar',\n",
       " 'Sudan',\n",
       " 'Belize',\n",
       " 'Bhutan',\n",
       " 'Mauritania',\n",
       " 'Cabo Verde',\n",
       " 'Syria',\n",
       " 'Gabon',\n",
       " 'Papua New Guinea',\n",
       " 'Seychelles',\n",
       " 'Andorra',\n",
       " 'Burundi',\n",
       " 'Togo',\n",
       " 'Guinea',\n",
       " 'Bahamas',\n",
       " 'Tanzania',\n",
       " 'Lesotho',\n",
       " 'Mali',\n",
       " 'Haiti',\n",
       " 'Benin',\n",
       " 'Saint Lucia',\n",
       " 'Somalia',\n",
       " 'Congo (Brazzaville)',\n",
       " 'Timor-Leste',\n",
       " 'Solomon Islands',\n",
       " 'Burkina Faso',\n",
       " 'Grenada',\n",
       " 'Tajikistan',\n",
       " 'Liechtenstein',\n",
       " 'South Sudan',\n",
       " 'San Marino',\n",
       " 'Equatorial Guinea',\n",
       " 'Djibouti',\n",
       " 'Dominica',\n",
       " 'Central African Republic',\n",
       " 'Nicaragua',\n",
       " 'Samoa',\n",
       " 'Monaco',\n",
       " 'Tonga',\n",
       " 'Gambia',\n",
       " 'Yemen',\n",
       " 'Vanuatu',\n",
       " 'Eritrea',\n",
       " 'Niger',\n",
       " 'Saint Vincent and the Grenadines',\n",
       " 'Antigua and Barbuda',\n",
       " 'Guinea-Bissau',\n",
       " 'Comoros',\n",
       " 'Sierra Leone',\n",
       " 'Liberia',\n",
       " 'Chad',\n",
       " 'Sao Tome and Principe',\n",
       " 'Saint Kitts and Nevis',\n",
       " 'Palau',\n",
       " 'Kiribati',\n",
       " 'Summer Olympics 2020',\n",
       " 'Diamond Princess',\n",
       " 'Winter Olympics 2022',\n",
       " 'Micronesia',\n",
       " 'Holy See',\n",
       " 'Marshall Islands',\n",
       " 'Antarctica',\n",
       " 'MS Zaandam',\n",
       " 'Korea, North']"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bar_graph = bar_graph.sort_values(by='values', ascending = False)\n",
    "bar_graph['Country/Region'].values.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "5ece1ed7",
   "metadata": {},
   "outputs": [
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       " 7424,\n",
       " 6023,\n",
       " 5913,\n",
       " 5181,\n",
       " 3215,\n",
       " 865,\n",
       " 712,\n",
       " 535,\n",
       " 38,\n",
       " 29,\n",
       " 18,\n",
       " 11,\n",
       " 9,\n",
       " 1]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
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    "bar_graph['values'].values.tolist()"
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  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "04ff9939",
   "metadata": {},
   "outputs": [],
   "source": [
    "country_names = bar_graph['Country/Region'].values.tolist()\n",
    "cases = bar_graph['values'].values.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "2395ec08",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<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/Region</th>\n",
       "      <th>values</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>US</td>\n",
       "      <td>86297081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>India</td>\n",
       "      <td>43319396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>31754465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>France</td>\n",
       "      <td>30381221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>Germany</td>\n",
       "      <td>27334993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>Holy See</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>Marshall Islands</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Antarctica</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>MS Zaandam</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>Korea, North</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>199 rows × 2 columns</p>\n",
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      "text/plain": [
       "       Country/Region    values\n",
       "184                US  86297081\n",
       "80              India  43319396\n",
       "24             Brazil  31754465\n",
       "63             France  30381221\n",
       "67            Germany  27334993\n",
       "..                ...       ...\n",
       "76           Holy See        29\n",
       "114  Marshall Islands        18\n",
       "5          Antarctica        11\n",
       "107        MS Zaandam         9\n",
       "93       Korea, North         1\n",
       "\n",
       "[199 rows x 2 columns]"
      ]
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     "metadata": {},
     "output_type": "execute_result"
    }
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    "bar_graph"
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  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "914bcd83",
   "metadata": {},
   "outputs": [
    {
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     "text": [
      "           date  cases\n",
      "1746 2020-01-30      0\n",
      "1744 2020-01-31      0\n",
      "1742 2020-02-01      0\n",
      "1740 2020-02-02      1\n",
      "1738 2020-02-03      1\n",
      "...         ...    ...\n",
      "10   2022-06-16  12847\n",
      "8    2022-06-17  13216\n",
      "6    2022-06-18  12899\n",
      "4    2022-06-19  12781\n",
      "2    2022-06-20   9923\n",
      "\n",
      "[873 rows x 2 columns]\n"
     ]
    },
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           "showland": true,
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           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
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          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
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           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
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           "zaxis": {
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            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
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            "ticks": ""
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           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
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           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
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          },
          "title": {
           "x": 0.05
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          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
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           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
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           "zerolinewidth": 2
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     "metadata": {},
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   ],
   "source": [
    "row = confirmedGlobal[confirmedGlobal['Country/Region'] == 'India']\n",
    "data = []\n",
    "data_csv =  pd.DataFrame(columns=['date', 'cases'])\n",
    "date = \"20\"\n",
    "for i, col in enumerate(row):\n",
    "    cases = list(row[col])[0]\n",
    "    t = {}\n",
    "    if i > 3 and cases != 0:\n",
    "        new_cases = 0\n",
    "        if len(data_csv) > 1 :\n",
    "            new_cases = cases - (data[-1])['cases']\n",
    "\n",
    "        datetime_obj = datetime.datetime.strptime(str(col),\"%m/%d/%y\")\n",
    "        # print(datetime_obj)\n",
    "        t['cases'] = cases\n",
    "        t['date'] = datetime_obj\n",
    "        data_csv.loc[0] = [datetime_obj, new_cases]\n",
    "        data_csv.index = data_csv.index + 1\n",
    "        # print(col, cases)\n",
    "    data.append(t)\n",
    "    # print(data)\n",
    "\n",
    "    # data_csv.loc[-1] = [2, 3]  # adding a row\n",
    "    data_csv.index = data_csv.index + 1  # shifting index\n",
    "print(data_csv)\n",
    "fig = go.Figure([go.Scatter(x=data_csv['date'], y=data_csv['cases'])])\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "aa26fc82",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "539713364"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Total Cases Wordlwide\n",
    "confirmedGlobal[confirmedGlobal.columns[-1]].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "85340eb8",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_json(\"https://cdn.jsdelivr.net/gh/highcharts/highcharts@v7.0.0/samples/data/world-population-density.json\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "6015eda5",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  code3   name   value code\n",
       "0   ABW  Aruba  582.34   AW"
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     "execution_count": 37,
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    "data.head(1)"
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  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "a7e5960e",
   "metadata": {},
   "outputs": [
    {
     "data": {
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   ],
   "source": [
    "data[data['name'] == 'Russia']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "b1301509",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country/Region</th>\n",
       "      <th>values</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
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       "Empty DataFrame\n",
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     "execution_count": 39,
     "metadata": {},
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   ],
   "source": [
    "bar_graph[bar_graph['Country/Region'] == 'Greenland']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "3d5b7c72",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "        vertical-align: top;\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
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       "      <th>values</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>US</td>\n",
       "      <td>86297081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>India</td>\n",
       "      <td>43319396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>31754465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>France</td>\n",
       "      <td>30381221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>Germany</td>\n",
       "      <td>27334993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>Holy See</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>Marshall Islands</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Antarctica</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>MS Zaandam</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>Korea, North</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>199 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Country/Region    values\n",
       "184                US  86297081\n",
       "80              India  43319396\n",
       "24             Brazil  31754465\n",
       "63             France  30381221\n",
       "67            Germany  27334993\n",
       "..                ...       ...\n",
       "76           Holy See        29\n",
       "114  Marshall Islands        18\n",
       "5          Antarctica        11\n",
       "107        MS Zaandam         9\n",
       "93       Korea, North         1\n",
       "\n",
       "[199 rows x 2 columns]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = bar_graph[bar_graph['Country/Region'] == 'Russia'] \n",
    "x['Country/Region'] = \"ROC\"\n",
    "# bar_graph[bar_graph['Country/Region'] == 'Russia'] \n",
    "# confirmedGlobal.head(1)\n",
    "t = confirmedGlobal\n",
    "\n",
    "# t.loc[0, 'Country/Region'] = 'hi'\n",
    "# t['Country/Region']['hi'] = t['Country/Region']['hi'].replace('hello')\n",
    "# t.head(1)\n",
    "bar_graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "cc48b6c3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "164\n"
     ]
    }
   ],
   "source": [
    "heat_map = []\n",
    "c = 0\n",
    "# for val in data:\n",
    "#     if data \n",
    "\n",
    "rdf = data[data['name'] == \"Russian Federation\"]\n",
    "for country in country_names:\n",
    "    try :\n",
    "        df = data[data['name'] == country]\n",
    "        temp = {}\n",
    "        temp['code3'] = list(df['code3'].values)[0]\n",
    "        temp['code'] = list(df['code'].values)[0]\n",
    "        temp['name'] = country\n",
    "        temp['value'] = bar_graph[bar_graph['Country/Region'] == country]['values'].sum()\n",
    "        # Or\n",
    "        # tdf = bar_graph[bar_graph['Country/Region'] == country]\n",
    "        # temp['value'] = list(tdf['values'].values)[0]\n",
    "        heat_map.append(temp)\n",
    "        c += 1\n",
    "        # print(country)\n",
    "    except:\n",
    "        pass\n",
    "# for country in country_names:\n",
    "#     if data[data['name'] == country] is not None:\n",
    "#         c += 1\n",
    "print(c)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "2a635cf7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'code3': 'IND', 'code': 'IN', 'name': 'India', 'value': 43319396},\n",
       " {'code3': 'BRA', 'code': 'BR', 'name': 'Brazil', 'value': 31754465},\n",
       " {'code3': 'FRA', 'code': 'FR', 'name': 'France', 'value': 30381221},\n",
       " {'code3': 'DEU', 'code': 'DE', 'name': 'Germany', 'value': 27334993},\n",
       " {'code3': 'GBR', 'code': 'GB', 'name': 'United Kingdom', 'value': 22701557},\n",
       " {'code3': 'ITA', 'code': 'IT', 'name': 'Italy', 'value': 17896065},\n",
       " {'code3': 'TUR', 'code': 'TR', 'name': 'Turkey', 'value': 15085742},\n",
       " {'code3': 'ESP', 'code': 'ES', 'name': 'Spain', 'value': 12563399},\n",
       " {'code3': 'VNM', 'code': 'VN', 'name': 'Vietnam', 'value': 10738161},\n",
       " {'code3': 'ARG', 'code': 'AR', 'name': 'Argentina', 'value': 9341492},\n",
       " {'code3': 'JPN', 'code': 'JP', 'name': 'Japan', 'value': 9145373},\n",
       " {'code3': 'NLD', 'code': 'NL', 'name': 'Netherlands', 'value': 8237473},\n",
       " {'code3': 'AUS', 'code': 'AU', 'name': 'Australia', 'value': 7854915},\n",
       " {'code3': 'COL', 'code': 'CO', 'name': 'Colombia', 'value': 6131657},\n",
       " {'code3': 'IDN', 'code': 'ID', 'name': 'Indonesia', 'value': 6069255},\n",
       " {'code3': 'POL', 'code': 'PL', 'name': 'Poland', 'value': 6011286},\n",
       " {'code3': 'MEX', 'code': 'MX', 'name': 'Mexico', 'value': 5877837},\n",
       " {'code3': 'PRT', 'code': 'PT', 'name': 'Portugal', 'value': 5062552},\n",
       " {'code3': 'UKR', 'code': 'UA', 'name': 'Ukraine', 'value': 5040518},\n",
       " {'code3': 'MYS', 'code': 'MY', 'name': 'Malaysia', 'value': 4542705},\n",
       " {'code3': 'THA', 'code': 'TH', 'name': 'Thailand', 'value': 4502542},\n",
       " {'code3': 'AUT', 'code': 'AT', 'name': 'Austria', 'value': 4367190},\n",
       " {'code3': 'ISR', 'code': 'IL', 'name': 'Israel', 'value': 4244453},\n",
       " {'code3': 'BEL', 'code': 'BE', 'name': 'Belgium', 'value': 4197345},\n",
       " {'code3': 'ZAF', 'code': 'ZA', 'name': 'South Africa', 'value': 3986892},\n",
       " {'code3': 'CAN', 'code': 'CA', 'name': 'Canada', 'value': 3927161},\n",
       " {'code3': 'CHL', 'code': 'CL', 'name': 'Chile', 'value': 3901215},\n",
       " {'code3': 'CHE', 'code': 'CH', 'name': 'Switzerland', 'value': 3701895},\n",
       " {'code3': 'PHL', 'code': 'PH', 'name': 'Philippines', 'value': 3696793},\n",
       " {'code3': 'PER', 'code': 'PE', 'name': 'Peru', 'value': 3600993},\n",
       " {'code3': 'GRC', 'code': 'GR', 'name': 'Greece', 'value': 3549944},\n",
       " {'code3': 'DNK', 'code': 'DK', 'name': 'Denmark', 'value': 3200460},\n",
       " {'code3': 'ROU', 'code': 'RO', 'name': 'Romania', 'value': 2915487},\n",
       " {'code3': 'SWE', 'code': 'SE', 'name': 'Sweden', 'value': 2512853},\n",
       " {'code3': 'IRQ', 'code': 'IQ', 'name': 'Iraq', 'value': 2332692},\n",
       " {'code3': 'CHN', 'code': 'CN', 'name': 'China', 'value': 2115561},\n",
       " {'code3': 'SRB', 'code': 'RS', 'name': 'Serbia', 'value': 2022902},\n",
       " {'code3': 'BGD', 'code': 'BD', 'name': 'Bangladesh', 'value': 1957200},\n",
       " {'code3': 'HUN', 'code': 'HU', 'name': 'Hungary', 'value': 1923122},\n",
       " {'code3': 'JOR', 'code': 'JO', 'name': 'Jordan', 'value': 1698316},\n",
       " {'code3': 'GEO', 'code': 'GE', 'name': 'Georgia', 'value': 1658755},\n",
       " {'code3': 'IRL', 'code': 'IE', 'name': 'Ireland', 'value': 1578284},\n",
       " {'code3': 'PAK', 'code': 'PK', 'name': 'Pakistan', 'value': 1532266},\n",
       " {'code3': 'NOR', 'code': 'NO', 'name': 'Norway', 'value': 1440517},\n",
       " {'code3': 'KAZ', 'code': 'KZ', 'name': 'Kazakhstan', 'value': 1395200},\n",
       " {'code3': 'SGP', 'code': 'SG', 'name': 'Singapore', 'value': 1370981},\n",
       " {'code3': 'NZL', 'code': 'NZ', 'name': 'New Zealand', 'value': 1289202},\n",
       " {'code3': 'MAR', 'code': 'MA', 'name': 'Morocco', 'value': 1186597},\n",
       " {'code3': 'BGR', 'code': 'BG', 'name': 'Bulgaria', 'value': 1168508},\n",
       " {'code3': 'HRV', 'code': 'HR', 'name': 'Croatia', 'value': 1141948},\n",
       " {'code3': 'FIN', 'code': 'FI', 'name': 'Finland', 'value': 1125342},\n",
       " {'code3': 'CUB', 'code': 'CU', 'name': 'Cuba', 'value': 1105778},\n",
       " {'code3': 'LBN', 'code': 'LB', 'name': 'Lebanon', 'value': 1103711},\n",
       " {'code3': 'LTU', 'code': 'LT', 'name': 'Lithuania', 'value': 1065186},\n",
       " {'code3': 'TUN', 'code': 'TN', 'name': 'Tunisia', 'value': 1044426},\n",
       " {'code3': 'SVN', 'code': 'SI', 'name': 'Slovenia', 'value': 1031216},\n",
       " {'code3': 'BLR', 'code': 'BY', 'name': 'Belarus', 'value': 982867},\n",
       " {'code3': 'NPL', 'code': 'NP', 'name': 'Nepal', 'value': 979382},\n",
       " {'code3': 'URY', 'code': 'UY', 'name': 'Uruguay', 'value': 951948},\n",
       " {'code3': 'ARE',\n",
       "  'code': 'AE',\n",
       "  'name': 'United Arab Emirates',\n",
       "  'value': 928919},\n",
       " {'code3': 'MNG', 'code': 'MN', 'name': 'Mongolia', 'value': 926282},\n",
       " {'code3': 'BOL', 'code': 'BO', 'name': 'Bolivia', 'value': 916092},\n",
       " {'code3': 'CRI', 'code': 'CR', 'name': 'Costa Rica', 'value': 904934},\n",
       " {'code3': 'PAN', 'code': 'PA', 'name': 'Panama', 'value': 904355},\n",
       " {'code3': 'ECU', 'code': 'EC', 'name': 'Ecuador', 'value': 896483},\n",
       " {'code3': 'GTM', 'code': 'GT', 'name': 'Guatemala', 'value': 880715},\n",
       " {'code3': 'LVA', 'code': 'LV', 'name': 'Latvia', 'value': 832168},\n",
       " {'code3': 'AZE', 'code': 'AZ', 'name': 'Azerbaijan', 'value': 793015},\n",
       " {'code3': 'SAU', 'code': 'SA', 'name': 'Saudi Arabia', 'value': 786069},\n",
       " {'code3': 'LKA', 'code': 'LK', 'name': 'Sri Lanka', 'value': 664010},\n",
       " {'code3': 'PSE', 'code': 'PS', 'name': 'West Bank and Gaza', 'value': 658503},\n",
       " {'code3': 'PRY', 'code': 'PY', 'name': 'Paraguay', 'value': 653428},\n",
       " {'code3': 'KWT', 'code': 'KW', 'name': 'Kuwait', 'value': 639290},\n",
       " {'code3': 'BHR', 'code': 'BH', 'name': 'Bahrain', 'value': 607475},\n",
       " {'code3': 'DOM', 'code': 'DO', 'name': 'Dominican Republic', 'value': 598079},\n",
       " {'code3': 'EST', 'code': 'EE', 'name': 'Estonia', 'value': 578494},\n",
       " {'code3': 'MDA', 'code': 'MD', 'name': 'Moldova', 'value': 519452},\n",
       " {'code3': 'LBY', 'code': 'LY', 'name': 'Libya', 'value': 502110},\n",
       " {'code3': 'CYP', 'code': 'CY', 'name': 'Cyprus', 'value': 497454},\n",
       " {'code3': 'ETH', 'code': 'ET', 'name': 'Ethiopia', 'value': 484536},\n",
       " {'code3': 'HND', 'code': 'HN', 'name': 'Honduras', 'value': 426095},\n",
       " {'code3': 'ARM', 'code': 'AM', 'name': 'Armenia', 'value': 423104},\n",
       " {'code3': 'OMN', 'code': 'OM', 'name': 'Oman', 'value': 390244},\n",
       " {'code3': 'BIH',\n",
       "  'code': 'BA',\n",
       "  'name': 'Bosnia and Herzegovina',\n",
       "  'value': 378295},\n",
       " {'code3': 'QAT', 'code': 'QA', 'name': 'Qatar', 'value': 376149},\n",
       " {'code3': 'KEN', 'code': 'KE', 'name': 'Kenya', 'value': 329605},\n",
       " {'code3': 'ZMB', 'code': 'ZM', 'name': 'Zambia', 'value': 324344},\n",
       " {'code3': 'BWA', 'code': 'BW', 'name': 'Botswana', 'value': 314242},\n",
       " {'code3': 'ALB', 'code': 'AL', 'name': 'Albania', 'value': 277444},\n",
       " {'code3': 'DZA', 'code': 'DZ', 'name': 'Algeria', 'value': 265985},\n",
       " {'code3': 'NGA', 'code': 'NG', 'name': 'Nigeria', 'value': 256573},\n",
       " {'code3': 'LUX', 'code': 'LU', 'name': 'Luxembourg', 'value': 255469},\n",
       " {'code3': 'ZWE', 'code': 'ZW', 'name': 'Zimbabwe', 'value': 254831},\n",
       " {'code3': 'UZB', 'code': 'UZ', 'name': 'Uzbekistan', 'value': 239726},\n",
       " {'code3': 'MNE', 'code': 'ME', 'name': 'Montenegro', 'value': 238549},\n",
       " {'code3': 'MUS', 'code': 'MU', 'name': 'Mauritius', 'value': 227442},\n",
       " {'code3': 'MOZ', 'code': 'MZ', 'name': 'Mozambique', 'value': 227161},\n",
       " {'code3': 'ISL', 'code': 'IS', 'name': 'Iceland', 'value': 191079},\n",
       " {'code3': 'AFG', 'code': 'AF', 'name': 'Afghanistan', 'value': 181725},\n",
       " {'code3': 'MDV', 'code': 'MV', 'name': 'Maldives', 'value': 180384},\n",
       " {'code3': 'NAM', 'code': 'NA', 'name': 'Namibia', 'value': 168904},\n",
       " {'code3': 'UGA', 'code': 'UG', 'name': 'Uganda', 'value': 166954},\n",
       " {'code3': 'TTO',\n",
       "  'code': 'TT',\n",
       "  'name': 'Trinidad and Tobago',\n",
       "  'value': 165908},\n",
       " {'code3': 'GHA', 'code': 'GH', 'name': 'Ghana', 'value': 164164},\n",
       " {'code3': 'SLV', 'code': 'SV', 'name': 'El Salvador', 'value': 164134},\n",
       " {'code3': 'JAM', 'code': 'JM', 'name': 'Jamaica', 'value': 141720},\n",
       " {'code3': 'KHM', 'code': 'KH', 'name': 'Cambodia', 'value': 136262},\n",
       " {'code3': 'RWA', 'code': 'RW', 'name': 'Rwanda', 'value': 130608},\n",
       " {'code3': 'CMR', 'code': 'CM', 'name': 'Cameroon', 'value': 119947},\n",
       " {'code3': 'AGO', 'code': 'AO', 'name': 'Angola', 'value': 99761},\n",
       " {'code3': 'MLT', 'code': 'MT', 'name': 'Malta', 'value': 98105},\n",
       " {'code3': 'SEN', 'code': 'SN', 'name': 'Senegal', 'value': 86230},\n",
       " {'code3': 'MWI', 'code': 'MW', 'name': 'Malawi', 'value': 86225},\n",
       " {'code3': 'BRB', 'code': 'BB', 'name': 'Barbados', 'value': 82950},\n",
       " {'code3': 'CIV', 'code': 'CI', 'name': \"Cote d'Ivoire\", 'value': 82743},\n",
       " {'code3': 'SUR', 'code': 'SR', 'name': 'Suriname', 'value': 80766},\n",
       " {'code3': 'GUY', 'code': 'GY', 'name': 'Guyana', 'value': 66506},\n",
       " {'code3': 'FJI', 'code': 'FJ', 'name': 'Fiji', 'value': 65361},\n",
       " {'code3': 'MDG', 'code': 'MG', 'name': 'Madagascar', 'value': 65009},\n",
       " {'code3': 'SDN', 'code': 'SD', 'name': 'Sudan', 'value': 62521},\n",
       " {'code3': 'BLZ', 'code': 'BZ', 'name': 'Belize', 'value': 62188},\n",
       " {'code3': 'BTN', 'code': 'BT', 'name': 'Bhutan', 'value': 59674},\n",
       " {'code3': 'MRT', 'code': 'MR', 'name': 'Mauritania', 'value': 59310},\n",
       " {'code3': 'CPV', 'code': 'CV', 'name': 'Cabo Verde', 'value': 58271},\n",
       " {'code3': 'GAB', 'code': 'GA', 'name': 'Gabon', 'value': 47742},\n",
       " {'code3': 'PNG', 'code': 'PG', 'name': 'Papua New Guinea', 'value': 44691},\n",
       " {'code3': 'SYC', 'code': 'SC', 'name': 'Seychelles', 'value': 44521},\n",
       " {'code3': 'AND', 'code': 'AD', 'name': 'Andorra', 'value': 43449},\n",
       " {'code3': 'BDI', 'code': 'BI', 'name': 'Burundi', 'value': 42472},\n",
       " {'code3': 'TGO', 'code': 'TG', 'name': 'Togo', 'value': 37263},\n",
       " {'code3': 'GIN', 'code': 'GN', 'name': 'Guinea', 'value': 36817},\n",
       " {'code3': 'TZA', 'code': 'TZ', 'name': 'Tanzania', 'value': 35354},\n",
       " {'code3': 'LSO', 'code': 'LS', 'name': 'Lesotho', 'value': 33938},\n",
       " {'code3': 'MLI', 'code': 'ML', 'name': 'Mali', 'value': 31140},\n",
       " {'code3': 'HTI', 'code': 'HT', 'name': 'Haiti', 'value': 31115},\n",
       " {'code3': 'BEN', 'code': 'BJ', 'name': 'Benin', 'value': 27122},\n",
       " {'code3': 'SOM', 'code': 'SO', 'name': 'Somalia', 'value': 26748},\n",
       " {'code3': 'TLS', 'code': 'TL', 'name': 'Timor-Leste', 'value': 22944},\n",
       " {'code3': 'SLB', 'code': 'SB', 'name': 'Solomon Islands', 'value': 21544},\n",
       " {'code3': 'BFA', 'code': 'BF', 'name': 'Burkina Faso', 'value': 21044},\n",
       " {'code3': 'GRD', 'code': 'GD', 'name': 'Grenada', 'value': 18115},\n",
       " {'code3': 'TJK', 'code': 'TJ', 'name': 'Tajikistan', 'value': 17786},\n",
       " {'code3': 'LIE', 'code': 'LI', 'name': 'Liechtenstein', 'value': 17706},\n",
       " {'code3': 'SMR', 'code': 'SM', 'name': 'San Marino', 'value': 17502},\n",
       " {'code3': 'GNQ', 'code': 'GQ', 'name': 'Equatorial Guinea', 'value': 15951},\n",
       " {'code3': 'DJI', 'code': 'DJ', 'name': 'Djibouti', 'value': 15690},\n",
       " {'code3': 'DMA', 'code': 'DM', 'name': 'Dominica', 'value': 14781},\n",
       " {'code3': 'CAF',\n",
       "  'code': 'CF',\n",
       "  'name': 'Central African Republic',\n",
       "  'value': 14649},\n",
       " {'code3': 'NIC', 'code': 'NI', 'name': 'Nicaragua', 'value': 14619},\n",
       " {'code3': 'WSM', 'code': 'WS', 'name': 'Samoa', 'value': 14497},\n",
       " {'code3': 'MCO', 'code': 'MC', 'name': 'Monaco', 'value': 12616},\n",
       " {'code3': 'TON', 'code': 'TO', 'name': 'Tonga', 'value': 12079},\n",
       " {'code3': 'VUT', 'code': 'VU', 'name': 'Vanuatu', 'value': 10924},\n",
       " {'code3': 'NER', 'code': 'NE', 'name': 'Niger', 'value': 9031},\n",
       " {'code3': 'ATG', 'code': 'AG', 'name': 'Antigua and Barbuda', 'value': 8581},\n",
       " {'code3': 'GNB', 'code': 'GW', 'name': 'Guinea-Bissau', 'value': 8307},\n",
       " {'code3': 'COM', 'code': 'KM', 'name': 'Comoros', 'value': 8131},\n",
       " {'code3': 'SLE', 'code': 'SL', 'name': 'Sierra Leone', 'value': 7688},\n",
       " {'code3': 'LBR', 'code': 'LR', 'name': 'Liberia', 'value': 7493},\n",
       " {'code3': 'TCD', 'code': 'TD', 'name': 'Chad', 'value': 7424},\n",
       " {'code3': 'STP',\n",
       "  'code': 'ST',\n",
       "  'name': 'Sao Tome and Principe',\n",
       "  'value': 6023},\n",
       " {'code3': 'PLW', 'code': 'PW', 'name': 'Palau', 'value': 5181},\n",
       " {'code3': 'KIR', 'code': 'KI', 'name': 'Kiribati', 'value': 3215},\n",
       " {'code3': 'MHL', 'code': 'MH', 'name': 'Marshall Islands', 'value': 18}]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heat_map"
   ]
  }
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