{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "4a87b5ef",
   "metadata": {},
   "source": [
    "---   \n",
    " <img align=\"left\" width=\"75\" height=\"75\"  src=\"https://upload.wikimedia.org/wikipedia/en/c/c8/University_of_the_Punjab_logo.png\"> \n",
    "\n",
    "<h1 align=\"center\">Department of Data Science</h1>\n",
    "<h1 align=\"center\">Course: Tools and Techniques for Data Science</h1>\n",
    "\n",
    "---\n",
    "<h3><div align=\"right\">Instructor: Muhammad Arif Butt, Ph.D.</div></h3>    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ab0dc25c",
   "metadata": {},
   "source": [
    "<h1 align=\"center\">Lecture 3.9 (Pandas-01)</h1>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cbc0f68d",
   "metadata": {},
   "source": [
    "<a href=\"https://colab.research.google.com/github/arifpucit/data-science/blob/master/Section-3-Python-for-Data-Scientists/Lec-3.09(Pandas-01-From-Python-Dictionary-to-Pandas-Dataframe).ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19f82705",
   "metadata": {},
   "source": [
    "## _From Python Dictionary to Pandas Dataframe.ipynb_"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f12d302e",
   "metadata": {},
   "source": [
    "## 1. Overview of Pandas Library and its Datastructures"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8180130e",
   "metadata": {},
   "source": [
    "<img align=\"center\" width=\"700\" height=\"700\"  src=\"images/pandas-apps.png\"  >"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "73f16850",
   "metadata": {},
   "source": [
    "> **A Pandas Dataframe is a 2-dimensional labeled data structure (like SQL table) with heterogeneously typed columns, having both a row and a column index.**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9727124d",
   "metadata": {},
   "source": [
    "## Learning agenda of this notebook\n",
    "\n",
    "1. Overview of Pandas Library and its Data Structures\n",
    "2. Install Pandas Library\n",
    "3. Read Datasets into Pandas Dataframe\n",
    "4. Python Dictionaries vs Pandas Dataframes\n",
    "5. Anatomy of a Dataframe\n",
    "6. Bonus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b4900f0e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "32024162",
   "metadata": {},
   "source": [
    "## 2. Install Pandas Library"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "e251bdc6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# To install this library in Jupyter notebook\n",
    "import sys\n",
    "!{sys.executable} -m pip install pandas --quiet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "dba905d0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('1.3.4',\n",
       " ['/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/pandas'])"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "pd.__version__ , pd.__path__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4472aee7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "315fe124",
   "metadata": {},
   "source": [
    "## 3. Read Data Sets into Pandas Dataframe"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e0700704",
   "metadata": {},
   "source": [
    "### a. Titanic Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c6cec056",
   "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>pclass</th>\n",
       "      <th>survived</th>\n",
       "      <th>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>sibsp</th>\n",
       "      <th>parch</th>\n",
       "      <th>ticket</th>\n",
       "      <th>fare</th>\n",
       "      <th>cabin</th>\n",
       "      <th>embarked</th>\n",
       "      <th>boat</th>\n",
       "      <th>body</th>\n",
       "      <th>home.dest</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Allen, Miss. Elisabeth Walton</td>\n",
       "      <td>female</td>\n",
       "      <td>29.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24160</td>\n",
       "      <td>211.3375</td>\n",
       "      <td>B5</td>\n",
       "      <td>S</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>St Louis, MO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Allison, Master. Hudson Trevor</td>\n",
       "      <td>male</td>\n",
       "      <td>0.9167</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>113781</td>\n",
       "      <td>151.5500</td>\n",
       "      <td>C22 C26</td>\n",
       "      <td>S</td>\n",
       "      <td>11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Montreal, PQ / Chesterville, ON</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Allison, Miss. Helen Loraine</td>\n",
       "      <td>female</td>\n",
       "      <td>2.0000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>113781</td>\n",
       "      <td>151.5500</td>\n",
       "      <td>C22 C26</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Montreal, PQ / Chesterville, ON</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Allison, Mr. Hudson Joshua Creighton</td>\n",
       "      <td>male</td>\n",
       "      <td>30.0000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>113781</td>\n",
       "      <td>151.5500</td>\n",
       "      <td>C22 C26</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "      <td>135.0</td>\n",
       "      <td>Montreal, PQ / Chesterville, ON</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Allison, Mrs. Hudson J C (Bessie Waldo Daniels)</td>\n",
       "      <td>female</td>\n",
       "      <td>25.0000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>113781</td>\n",
       "      <td>151.5500</td>\n",
       "      <td>C22 C26</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Montreal, PQ / Chesterville, ON</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1305</th>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Zabour, Miss. Thamine</td>\n",
       "      <td>female</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2665</td>\n",
       "      <td>14.4542</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1306</th>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Zakarian, Mr. Mapriededer</td>\n",
       "      <td>male</td>\n",
       "      <td>26.5000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2656</td>\n",
       "      <td>7.2250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "      <td>304.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1307</th>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Zakarian, Mr. Ortin</td>\n",
       "      <td>male</td>\n",
       "      <td>27.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2670</td>\n",
       "      <td>7.2250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1308</th>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Zimmerman, Mr. Leo</td>\n",
       "      <td>male</td>\n",
       "      <td>29.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>315082</td>\n",
       "      <td>7.8750</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1309</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1310 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      pclass  survived                                             name  \\\n",
       "0        1.0       1.0                    Allen, Miss. Elisabeth Walton   \n",
       "1        1.0       1.0                   Allison, Master. Hudson Trevor   \n",
       "2        1.0       0.0                     Allison, Miss. Helen Loraine   \n",
       "3        1.0       0.0             Allison, Mr. Hudson Joshua Creighton   \n",
       "4        1.0       0.0  Allison, Mrs. Hudson J C (Bessie Waldo Daniels)   \n",
       "...      ...       ...                                              ...   \n",
       "1305     3.0       0.0                            Zabour, Miss. Thamine   \n",
       "1306     3.0       0.0                        Zakarian, Mr. Mapriededer   \n",
       "1307     3.0       0.0                              Zakarian, Mr. Ortin   \n",
       "1308     3.0       0.0                               Zimmerman, Mr. Leo   \n",
       "1309     NaN       NaN                                              NaN   \n",
       "\n",
       "         sex      age  sibsp  parch  ticket      fare    cabin embarked boat  \\\n",
       "0     female  29.0000    0.0    0.0   24160  211.3375       B5        S    2   \n",
       "1       male   0.9167    1.0    2.0  113781  151.5500  C22 C26        S   11   \n",
       "2     female   2.0000    1.0    2.0  113781  151.5500  C22 C26        S  NaN   \n",
       "3       male  30.0000    1.0    2.0  113781  151.5500  C22 C26        S  NaN   \n",
       "4     female  25.0000    1.0    2.0  113781  151.5500  C22 C26        S  NaN   \n",
       "...      ...      ...    ...    ...     ...       ...      ...      ...  ...   \n",
       "1305  female      NaN    1.0    0.0    2665   14.4542      NaN        C  NaN   \n",
       "1306    male  26.5000    0.0    0.0    2656    7.2250      NaN        C  NaN   \n",
       "1307    male  27.0000    0.0    0.0    2670    7.2250      NaN        C  NaN   \n",
       "1308    male  29.0000    0.0    0.0  315082    7.8750      NaN        S  NaN   \n",
       "1309     NaN      NaN    NaN    NaN     NaN       NaN      NaN      NaN  NaN   \n",
       "\n",
       "       body                        home.dest  \n",
       "0       NaN                     St Louis, MO  \n",
       "1       NaN  Montreal, PQ / Chesterville, ON  \n",
       "2       NaN  Montreal, PQ / Chesterville, ON  \n",
       "3     135.0  Montreal, PQ / Chesterville, ON  \n",
       "4       NaN  Montreal, PQ / Chesterville, ON  \n",
       "...     ...                              ...  \n",
       "1305    NaN                              NaN  \n",
       "1306  304.0                              NaN  \n",
       "1307    NaN                              NaN  \n",
       "1308    NaN                              NaN  \n",
       "1309    NaN                              NaN  \n",
       "\n",
       "[1310 rows x 14 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_titanic = pd.read_csv('datasets/titanic3.csv')\n",
    "df_titanic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "76cd9afe",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "e6c7c6a6",
   "metadata": {},
   "source": [
    "### b. IMDB Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a4c88b75",
   "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>star_rating</th>\n",
       "      <th>title</th>\n",
       "      <th>content_rating</th>\n",
       "      <th>genre</th>\n",
       "      <th>duration</th>\n",
       "      <th>actors_list</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>9.3</td>\n",
       "      <td>The Shawshank Redemption</td>\n",
       "      <td>R</td>\n",
       "      <td>Crime</td>\n",
       "      <td>142</td>\n",
       "      <td>[u'Tim Robbins', u'Morgan Freeman', u'Bob Gunt...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9.2</td>\n",
       "      <td>The Godfather</td>\n",
       "      <td>R</td>\n",
       "      <td>Crime</td>\n",
       "      <td>175</td>\n",
       "      <td>[u'Marlon Brando', u'Al Pacino', u'James Caan']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9.1</td>\n",
       "      <td>The Godfather: Part II</td>\n",
       "      <td>R</td>\n",
       "      <td>Crime</td>\n",
       "      <td>200</td>\n",
       "      <td>[u'Al Pacino', u'Robert De Niro', u'Robert Duv...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>9.0</td>\n",
       "      <td>The Dark Knight</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Action</td>\n",
       "      <td>152</td>\n",
       "      <td>[u'Christian Bale', u'Heath Ledger', u'Aaron E...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8.9</td>\n",
       "      <td>Pulp Fiction</td>\n",
       "      <td>R</td>\n",
       "      <td>Crime</td>\n",
       "      <td>154</td>\n",
       "      <td>[u'John Travolta', u'Uma Thurman', u'Samuel L....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>974</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Tootsie</td>\n",
       "      <td>PG</td>\n",
       "      <td>Comedy</td>\n",
       "      <td>116</td>\n",
       "      <td>[u'Dustin Hoffman', u'Jessica Lange', u'Teri G...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>975</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Back to the Future Part III</td>\n",
       "      <td>PG</td>\n",
       "      <td>Adventure</td>\n",
       "      <td>118</td>\n",
       "      <td>[u'Michael J. Fox', u'Christopher Lloyd', u'Ma...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>976</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Master and Commander: The Far Side of the World</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Action</td>\n",
       "      <td>138</td>\n",
       "      <td>[u'Russell Crowe', u'Paul Bettany', u'Billy Bo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>977</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Poltergeist</td>\n",
       "      <td>PG</td>\n",
       "      <td>Horror</td>\n",
       "      <td>114</td>\n",
       "      <td>[u'JoBeth Williams', u\"Heather O'Rourke\", u'Cr...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>978</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Wall Street</td>\n",
       "      <td>R</td>\n",
       "      <td>Crime</td>\n",
       "      <td>126</td>\n",
       "      <td>[u'Charlie Sheen', u'Michael Douglas', u'Tamar...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>979 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     star_rating                                            title  \\\n",
       "0            9.3                         The Shawshank Redemption   \n",
       "1            9.2                                    The Godfather   \n",
       "2            9.1                           The Godfather: Part II   \n",
       "3            9.0                                  The Dark Knight   \n",
       "4            8.9                                     Pulp Fiction   \n",
       "..           ...                                              ...   \n",
       "974          7.4                                          Tootsie   \n",
       "975          7.4                      Back to the Future Part III   \n",
       "976          7.4  Master and Commander: The Far Side of the World   \n",
       "977          7.4                                      Poltergeist   \n",
       "978          7.4                                      Wall Street   \n",
       "\n",
       "    content_rating      genre  duration  \\\n",
       "0                R      Crime       142   \n",
       "1                R      Crime       175   \n",
       "2                R      Crime       200   \n",
       "3            PG-13     Action       152   \n",
       "4                R      Crime       154   \n",
       "..             ...        ...       ...   \n",
       "974             PG     Comedy       116   \n",
       "975             PG  Adventure       118   \n",
       "976          PG-13     Action       138   \n",
       "977             PG     Horror       114   \n",
       "978              R      Crime       126   \n",
       "\n",
       "                                           actors_list  \n",
       "0    [u'Tim Robbins', u'Morgan Freeman', u'Bob Gunt...  \n",
       "1      [u'Marlon Brando', u'Al Pacino', u'James Caan']  \n",
       "2    [u'Al Pacino', u'Robert De Niro', u'Robert Duv...  \n",
       "3    [u'Christian Bale', u'Heath Ledger', u'Aaron E...  \n",
       "4    [u'John Travolta', u'Uma Thurman', u'Samuel L....  \n",
       "..                                                 ...  \n",
       "974  [u'Dustin Hoffman', u'Jessica Lange', u'Teri G...  \n",
       "975  [u'Michael J. Fox', u'Christopher Lloyd', u'Ma...  \n",
       "976  [u'Russell Crowe', u'Paul Bettany', u'Billy Bo...  \n",
       "977  [u'JoBeth Williams', u\"Heather O'Rourke\", u'Cr...  \n",
       "978  [u'Charlie Sheen', u'Michael Douglas', u'Tamar...  \n",
       "\n",
       "[979 rows x 6 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_imdb = pd.read_csv('datasets/imdb.csv')\n",
    "df_imdb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1dc651ad",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "3ab7b6e2",
   "metadata": {},
   "source": [
    "### c. Covid Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e132d8a1",
   "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>iso_code</th>\n",
       "      <th>continent</th>\n",
       "      <th>location</th>\n",
       "      <th>date</th>\n",
       "      <th>total_cases</th>\n",
       "      <th>new_cases</th>\n",
       "      <th>new_cases_smoothed</th>\n",
       "      <th>total_deaths</th>\n",
       "      <th>new_deaths</th>\n",
       "      <th>new_deaths_smoothed</th>\n",
       "      <th>...</th>\n",
       "      <th>female_smokers</th>\n",
       "      <th>male_smokers</th>\n",
       "      <th>handwashing_facilities</th>\n",
       "      <th>hospital_beds_per_thousand</th>\n",
       "      <th>life_expectancy</th>\n",
       "      <th>human_development_index</th>\n",
       "      <th>excess_mortality_cumulative_absolute</th>\n",
       "      <th>excess_mortality_cumulative</th>\n",
       "      <th>excess_mortality</th>\n",
       "      <th>excess_mortality_cumulative_per_million</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-24</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-25</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-26</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-27</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-28</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151080</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-26</td>\n",
       "      <td>204351.0</td>\n",
       "      <td>605.0</td>\n",
       "      <td>1811.143</td>\n",
       "      <td>4891.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>15.571</td>\n",
       "      <td>...</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151081</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-27</td>\n",
       "      <td>205449.0</td>\n",
       "      <td>1098.0</td>\n",
       "      <td>1481.429</td>\n",
       "      <td>4908.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>14.714</td>\n",
       "      <td>...</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151082</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-28</td>\n",
       "      <td>207548.0</td>\n",
       "      <td>2099.0</td>\n",
       "      <td>1397.143</td>\n",
       "      <td>4940.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>17.286</td>\n",
       "      <td>...</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151083</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-29</td>\n",
       "      <td>207548.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1163.429</td>\n",
       "      <td>4940.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151084</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-30</td>\n",
       "      <td>211728.0</td>\n",
       "      <td>4180.0</td>\n",
       "      <td>1483.429</td>\n",
       "      <td>4997.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>20.286</td>\n",
       "      <td>...</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>151085 rows × 67 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       iso_code continent     location        date  total_cases  new_cases  \\\n",
       "0           AFG      Asia  Afghanistan  2020-02-24          5.0        5.0   \n",
       "1           AFG      Asia  Afghanistan  2020-02-25          5.0        0.0   \n",
       "2           AFG      Asia  Afghanistan  2020-02-26          5.0        0.0   \n",
       "3           AFG      Asia  Afghanistan  2020-02-27          5.0        0.0   \n",
       "4           AFG      Asia  Afghanistan  2020-02-28          5.0        0.0   \n",
       "...         ...       ...          ...         ...          ...        ...   \n",
       "151080      ZWE    Africa     Zimbabwe  2021-12-26     204351.0      605.0   \n",
       "151081      ZWE    Africa     Zimbabwe  2021-12-27     205449.0     1098.0   \n",
       "151082      ZWE    Africa     Zimbabwe  2021-12-28     207548.0     2099.0   \n",
       "151083      ZWE    Africa     Zimbabwe  2021-12-29     207548.0        0.0   \n",
       "151084      ZWE    Africa     Zimbabwe  2021-12-30     211728.0     4180.0   \n",
       "\n",
       "        new_cases_smoothed  total_deaths  new_deaths  new_deaths_smoothed  \\\n",
       "0                      NaN           NaN         NaN                  NaN   \n",
       "1                      NaN           NaN         NaN                  NaN   \n",
       "2                      NaN           NaN         NaN                  NaN   \n",
       "3                      NaN           NaN         NaN                  NaN   \n",
       "4                      NaN           NaN         NaN                  NaN   \n",
       "...                    ...           ...         ...                  ...   \n",
       "151080            1811.143        4891.0         6.0               15.571   \n",
       "151081            1481.429        4908.0        17.0               14.714   \n",
       "151082            1397.143        4940.0        32.0               17.286   \n",
       "151083            1163.429        4940.0         0.0               16.000   \n",
       "151084            1483.429        4997.0        57.0               20.286   \n",
       "\n",
       "        ...  female_smokers  male_smokers  handwashing_facilities  \\\n",
       "0       ...             NaN           NaN                  37.746   \n",
       "1       ...             NaN           NaN                  37.746   \n",
       "2       ...             NaN           NaN                  37.746   \n",
       "3       ...             NaN           NaN                  37.746   \n",
       "4       ...             NaN           NaN                  37.746   \n",
       "...     ...             ...           ...                     ...   \n",
       "151080  ...             1.6          30.7                  36.791   \n",
       "151081  ...             1.6          30.7                  36.791   \n",
       "151082  ...             1.6          30.7                  36.791   \n",
       "151083  ...             1.6          30.7                  36.791   \n",
       "151084  ...             1.6          30.7                  36.791   \n",
       "\n",
       "        hospital_beds_per_thousand  life_expectancy  human_development_index  \\\n",
       "0                              0.5            64.83                    0.511   \n",
       "1                              0.5            64.83                    0.511   \n",
       "2                              0.5            64.83                    0.511   \n",
       "3                              0.5            64.83                    0.511   \n",
       "4                              0.5            64.83                    0.511   \n",
       "...                            ...              ...                      ...   \n",
       "151080                         1.7            61.49                    0.571   \n",
       "151081                         1.7            61.49                    0.571   \n",
       "151082                         1.7            61.49                    0.571   \n",
       "151083                         1.7            61.49                    0.571   \n",
       "151084                         1.7            61.49                    0.571   \n",
       "\n",
       "        excess_mortality_cumulative_absolute  excess_mortality_cumulative  \\\n",
       "0                                        NaN                          NaN   \n",
       "1                                        NaN                          NaN   \n",
       "2                                        NaN                          NaN   \n",
       "3                                        NaN                          NaN   \n",
       "4                                        NaN                          NaN   \n",
       "...                                      ...                          ...   \n",
       "151080                                   NaN                          NaN   \n",
       "151081                                   NaN                          NaN   \n",
       "151082                                   NaN                          NaN   \n",
       "151083                                   NaN                          NaN   \n",
       "151084                                   NaN                          NaN   \n",
       "\n",
       "        excess_mortality  excess_mortality_cumulative_per_million  \n",
       "0                    NaN                                      NaN  \n",
       "1                    NaN                                      NaN  \n",
       "2                    NaN                                      NaN  \n",
       "3                    NaN                                      NaN  \n",
       "4                    NaN                                      NaN  \n",
       "...                  ...                                      ...  \n",
       "151080               NaN                                      NaN  \n",
       "151081               NaN                                      NaN  \n",
       "151082               NaN                                      NaN  \n",
       "151083               NaN                                      NaN  \n",
       "151084               NaN                                      NaN  \n",
       "\n",
       "[151085 rows x 67 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_covid =pd.read_csv('datasets/covid-data.csv')\n",
    "df_covid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6fca783d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "b94f16ae",
   "metadata": {},
   "source": [
    "## 4. Python Dictionaries vs Pandas Dataframes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "dcdae2d8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'name': 'Arif',\n",
       " 'age': 51,\n",
       " 'address': 'Karachi',\n",
       " 'cell': '0320-431',\n",
       " 'bg': 'A-'}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "person = {\n",
    "    \"name\" : \"Arif\",\n",
    "    \"age\" : 51,\n",
    "    \"address\" : \"Karachi\",\n",
    "    \"cell\" : \"0320-431\",\n",
    "    \"bg\": \"A-\"\n",
    "}\n",
    "person"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a330a4f4",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "13db82ee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'name': ['Rauf', 'Arif', 'Maaz', 'Hadeed', 'Mujahid', 'Mohid'],\n",
       " 'age': [52, 51, 26, 22, 18, 17],\n",
       " 'address': ['Lahore', 'Karachi', 'Lahore', 'Islamabad', 'Kakul', 'Karachi'],\n",
       " 'cell': ['321-123', '320-431', '321-478', '324-446', '321-967', '320-678'],\n",
       " 'bg': ['B+', 'A-', 'B+', 'O-', 'A-', 'B+']}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "people = {\n",
    "    \"name\" : [\"Rauf\", \"Arif\", \"Maaz\", \"Hadeed\", \"Mujahid\", \"Mohid\"],\n",
    "    \"age\" : [52, 51, 26, 22, 18, 17],\n",
    "    \"address\": [\"Lahore\", \"Karachi\", \"Lahore\", \"Islamabad\", \"Kakul\", \"Karachi\"],\n",
    "    \"cell\" : [\"321-123\", \"320-431\", \"321-478\", \"324-446\", \"321-967\", \"320-678\"],\n",
    "    \"bg\": [\"B+\", \"A-\", \"B+\", \"O-\", \"A-\", \"B+\"]\n",
    "}\n",
    "people"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3a9f9f8a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "39e35beb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name, age, address, cell, bg\r\n",
      "Rauf, 52, Lahore, 321-123, B+\r\n",
      "Arif,51, Karachi,320-431,A-\r\n",
      "Maaz,26, Lahore,321-478,B+\r\n",
      "Hadeed,22, Islamabad, 324-446,O-\r\n",
      "Mujahid,18, Kakul,321-967,A-\r\n",
      "Mohid,17,Karachi,320-678,B+"
     ]
    }
   ],
   "source": [
    "! cat datasets/people.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a34604c7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "762c5742",
   "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>name</th>\n",
       "      <th>age</th>\n",
       "      <th>address</th>\n",
       "      <th>cell</th>\n",
       "      <th>bg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Rauf</td>\n",
       "      <td>52</td>\n",
       "      <td>Lahore</td>\n",
       "      <td>321-123</td>\n",
       "      <td>B+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Arif</td>\n",
       "      <td>51</td>\n",
       "      <td>Karachi</td>\n",
       "      <td>320-431</td>\n",
       "      <td>A-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Maaz</td>\n",
       "      <td>26</td>\n",
       "      <td>Lahore</td>\n",
       "      <td>321-478</td>\n",
       "      <td>B+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Hadeed</td>\n",
       "      <td>22</td>\n",
       "      <td>Islamabad</td>\n",
       "      <td>324-446</td>\n",
       "      <td>O-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Mujahid</td>\n",
       "      <td>18</td>\n",
       "      <td>Kakul</td>\n",
       "      <td>321-967</td>\n",
       "      <td>A-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Mohid</td>\n",
       "      <td>17</td>\n",
       "      <td>Karachi</td>\n",
       "      <td>320-678</td>\n",
       "      <td>B+</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      name   age     address      cell   bg\n",
       "0     Rauf    52      Lahore   321-123   B+\n",
       "1     Arif    51     Karachi   320-431   A-\n",
       "2     Maaz    26      Lahore   321-478   B+\n",
       "3   Hadeed    22   Islamabad   324-446   O-\n",
       "4  Mujahid    18       Kakul   321-967   A-\n",
       "5    Mohid    17     Karachi   320-678   B+"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_people = pd.read_csv('datasets/people.csv')\n",
    "df_people"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7f45a8f0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "92e9126c",
   "metadata": {},
   "source": [
    "**Accessing Elements of Dictionaries and Dataframes**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "829ff1f7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[52, 51, 26, 22, 18, 17]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "people.get('age')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ad7f9cea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Rauf', 'Arif', 'Maaz', 'Hadeed', 'Mujahid', 'Mohid']"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mylist = people['name']\n",
    "mylist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cd2fe44d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "78e3d1f6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "list"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(mylist)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "25f1c8fc",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e48b0ce0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    52\n",
       "1    51\n",
       "2    26\n",
       "3    22\n",
       "4    18\n",
       "5    17\n",
       "Name:  age, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_people[' age']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d8f6f125",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       Rauf\n",
       "1       Arif\n",
       "2       Maaz\n",
       "3     Hadeed\n",
       "4    Mujahid\n",
       "5      Mohid\n",
       "Name: name, dtype: object"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "myseries = df_people['name']\n",
    "myseries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "36f5ef09",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(myseries)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c8c2111a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RangeIndex(start=0, stop=6, step=1)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_people.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "6825517a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['name', ' age', ' address', ' cell', ' bg'], dtype='object')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_people.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "84b01910",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "4451c617",
   "metadata": {},
   "source": [
    "## 5. Anatomy of a Dataframe\n",
    "<img align=\"center\" width=\"800\" height=\"500\"  src=\"images/pandas00.png\"  >"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "09def88e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "c2aa9214",
   "metadata": {},
   "source": [
    "## 6. Bonus (Changing display properties of a Dataframe Object)\n",
    "- Get the option names `pd.describe_option()`\n",
    "- Get current value of a display option `pd.get_option('nameofoption')`\n",
    "- Change value of a display option `pd.set_option('nameofoption', newvalue)`\n",
    "- Resetting options to default `pd.reset_option('all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "4317b181",
   "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>iso_code</th>\n",
       "      <th>continent</th>\n",
       "      <th>location</th>\n",
       "      <th>date</th>\n",
       "      <th>total_cases</th>\n",
       "      <th>new_cases</th>\n",
       "      <th>new_cases_smoothed</th>\n",
       "      <th>total_deaths</th>\n",
       "      <th>new_deaths</th>\n",
       "      <th>new_deaths_smoothed</th>\n",
       "      <th>...</th>\n",
       "      <th>female_smokers</th>\n",
       "      <th>male_smokers</th>\n",
       "      <th>handwashing_facilities</th>\n",
       "      <th>hospital_beds_per_thousand</th>\n",
       "      <th>life_expectancy</th>\n",
       "      <th>human_development_index</th>\n",
       "      <th>excess_mortality_cumulative_absolute</th>\n",
       "      <th>excess_mortality_cumulative</th>\n",
       "      <th>excess_mortality</th>\n",
       "      <th>excess_mortality_cumulative_per_million</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-24</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-25</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-26</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-27</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-28</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151080</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-26</td>\n",
       "      <td>204351.0</td>\n",
       "      <td>605.0</td>\n",
       "      <td>1811.143</td>\n",
       "      <td>4891.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>15.571</td>\n",
       "      <td>...</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151081</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-27</td>\n",
       "      <td>205449.0</td>\n",
       "      <td>1098.0</td>\n",
       "      <td>1481.429</td>\n",
       "      <td>4908.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>14.714</td>\n",
       "      <td>...</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151082</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-28</td>\n",
       "      <td>207548.0</td>\n",
       "      <td>2099.0</td>\n",
       "      <td>1397.143</td>\n",
       "      <td>4940.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>17.286</td>\n",
       "      <td>...</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151083</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-29</td>\n",
       "      <td>207548.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1163.429</td>\n",
       "      <td>4940.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151084</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-30</td>\n",
       "      <td>211728.0</td>\n",
       "      <td>4180.0</td>\n",
       "      <td>1483.429</td>\n",
       "      <td>4997.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>20.286</td>\n",
       "      <td>...</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>151085 rows × 67 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       iso_code continent     location        date  total_cases  new_cases  \\\n",
       "0           AFG      Asia  Afghanistan  2020-02-24          5.0        5.0   \n",
       "1           AFG      Asia  Afghanistan  2020-02-25          5.0        0.0   \n",
       "2           AFG      Asia  Afghanistan  2020-02-26          5.0        0.0   \n",
       "3           AFG      Asia  Afghanistan  2020-02-27          5.0        0.0   \n",
       "4           AFG      Asia  Afghanistan  2020-02-28          5.0        0.0   \n",
       "...         ...       ...          ...         ...          ...        ...   \n",
       "151080      ZWE    Africa     Zimbabwe  2021-12-26     204351.0      605.0   \n",
       "151081      ZWE    Africa     Zimbabwe  2021-12-27     205449.0     1098.0   \n",
       "151082      ZWE    Africa     Zimbabwe  2021-12-28     207548.0     2099.0   \n",
       "151083      ZWE    Africa     Zimbabwe  2021-12-29     207548.0        0.0   \n",
       "151084      ZWE    Africa     Zimbabwe  2021-12-30     211728.0     4180.0   \n",
       "\n",
       "        new_cases_smoothed  total_deaths  new_deaths  new_deaths_smoothed  \\\n",
       "0                      NaN           NaN         NaN                  NaN   \n",
       "1                      NaN           NaN         NaN                  NaN   \n",
       "2                      NaN           NaN         NaN                  NaN   \n",
       "3                      NaN           NaN         NaN                  NaN   \n",
       "4                      NaN           NaN         NaN                  NaN   \n",
       "...                    ...           ...         ...                  ...   \n",
       "151080            1811.143        4891.0         6.0               15.571   \n",
       "151081            1481.429        4908.0        17.0               14.714   \n",
       "151082            1397.143        4940.0        32.0               17.286   \n",
       "151083            1163.429        4940.0         0.0               16.000   \n",
       "151084            1483.429        4997.0        57.0               20.286   \n",
       "\n",
       "        ...  female_smokers  male_smokers  handwashing_facilities  \\\n",
       "0       ...             NaN           NaN                  37.746   \n",
       "1       ...             NaN           NaN                  37.746   \n",
       "2       ...             NaN           NaN                  37.746   \n",
       "3       ...             NaN           NaN                  37.746   \n",
       "4       ...             NaN           NaN                  37.746   \n",
       "...     ...             ...           ...                     ...   \n",
       "151080  ...             1.6          30.7                  36.791   \n",
       "151081  ...             1.6          30.7                  36.791   \n",
       "151082  ...             1.6          30.7                  36.791   \n",
       "151083  ...             1.6          30.7                  36.791   \n",
       "151084  ...             1.6          30.7                  36.791   \n",
       "\n",
       "        hospital_beds_per_thousand  life_expectancy  human_development_index  \\\n",
       "0                              0.5            64.83                    0.511   \n",
       "1                              0.5            64.83                    0.511   \n",
       "2                              0.5            64.83                    0.511   \n",
       "3                              0.5            64.83                    0.511   \n",
       "4                              0.5            64.83                    0.511   \n",
       "...                            ...              ...                      ...   \n",
       "151080                         1.7            61.49                    0.571   \n",
       "151081                         1.7            61.49                    0.571   \n",
       "151082                         1.7            61.49                    0.571   \n",
       "151083                         1.7            61.49                    0.571   \n",
       "151084                         1.7            61.49                    0.571   \n",
       "\n",
       "        excess_mortality_cumulative_absolute  excess_mortality_cumulative  \\\n",
       "0                                        NaN                          NaN   \n",
       "1                                        NaN                          NaN   \n",
       "2                                        NaN                          NaN   \n",
       "3                                        NaN                          NaN   \n",
       "4                                        NaN                          NaN   \n",
       "...                                      ...                          ...   \n",
       "151080                                   NaN                          NaN   \n",
       "151081                                   NaN                          NaN   \n",
       "151082                                   NaN                          NaN   \n",
       "151083                                   NaN                          NaN   \n",
       "151084                                   NaN                          NaN   \n",
       "\n",
       "        excess_mortality  excess_mortality_cumulative_per_million  \n",
       "0                    NaN                                      NaN  \n",
       "1                    NaN                                      NaN  \n",
       "2                    NaN                                      NaN  \n",
       "3                    NaN                                      NaN  \n",
       "4                    NaN                                      NaN  \n",
       "...                  ...                                      ...  \n",
       "151080               NaN                                      NaN  \n",
       "151081               NaN                                      NaN  \n",
       "151082               NaN                                      NaN  \n",
       "151083               NaN                                      NaN  \n",
       "151084               NaN                                      NaN  \n",
       "\n",
       "[151085 rows x 67 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_covid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cde41636",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "b9da09c2",
   "metadata": {},
   "source": [
    "### a. Changing the number of columns to be displayed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "d3bb0e9b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "compute.use_bottleneck : bool\n",
      "    Use the bottleneck library to accelerate if it is installed,\n",
      "    the default is True\n",
      "    Valid values: False,True\n",
      "    [default: True] [currently: True]\n",
      "compute.use_numba : bool\n",
      "    Use the numba engine option for select operations if it is installed,\n",
      "    the default is False\n",
      "    Valid values: False,True\n",
      "    [default: False] [currently: False]\n",
      "compute.use_numexpr : bool\n",
      "    Use the numexpr library to accelerate computation if it is installed,\n",
      "    the default is True\n",
      "    Valid values: False,True\n",
      "    [default: True] [currently: True]\n",
      "display.chop_threshold : float or None\n",
      "    if set to a float value, all float values smaller then the given threshold\n",
      "    will be displayed as exactly 0 by repr and friends.\n",
      "    [default: None] [currently: None]\n",
      "display.colheader_justify : 'left'/'right'\n",
      "    Controls the justification of column headers. used by DataFrameFormatter.\n",
      "    [default: right] [currently: right]\n",
      "display.column_space No description available.\n",
      "    [default: 12] [currently: 12]\n",
      "display.date_dayfirst : boolean\n",
      "    When True, prints and parses dates with the day first, eg 20/01/2005\n",
      "    [default: False] [currently: False]\n",
      "display.date_yearfirst : boolean\n",
      "    When True, prints and parses dates with the year first, eg 2005/01/20\n",
      "    [default: False] [currently: False]\n",
      "display.encoding : str/unicode\n",
      "    Defaults to the detected encoding of the console.\n",
      "    Specifies the encoding to be used for strings returned by to_string,\n",
      "    these are generally strings meant to be displayed on the console.\n",
      "    [default: UTF-8] [currently: UTF-8]\n",
      "display.expand_frame_repr : boolean\n",
      "    Whether to print out the full DataFrame repr for wide DataFrames across\n",
      "    multiple lines, `max_columns` is still respected, but the output will\n",
      "    wrap-around across multiple \"pages\" if its width exceeds `display.width`.\n",
      "    [default: True] [currently: True]\n",
      "display.float_format : callable\n",
      "    The callable should accept a floating point number and return\n",
      "    a string with the desired format of the number. This is used\n",
      "    in some places like SeriesFormatter.\n",
      "    See formats.format.EngFormatter for an example.\n",
      "    [default: None] [currently: None]\n",
      "display.html.border : int\n",
      "    A ``border=value`` attribute is inserted in the ``<table>`` tag\n",
      "    for the DataFrame HTML repr.\n",
      "    [default: 1] [currently: 1]\n",
      "display.html.table_schema : boolean\n",
      "    Whether to publish a Table Schema representation for frontends\n",
      "    that support it.\n",
      "    (default: False)\n",
      "    [default: False] [currently: False]\n",
      "display.html.use_mathjax : boolean\n",
      "    When True, Jupyter notebook will process table contents using MathJax,\n",
      "    rendering mathematical expressions enclosed by the dollar symbol.\n",
      "    (default: True)\n",
      "    [default: True] [currently: True]\n",
      "display.large_repr : 'truncate'/'info'\n",
      "    For DataFrames exceeding max_rows/max_cols, the repr (and HTML repr) can\n",
      "    show a truncated table (the default from 0.13), or switch to the view from\n",
      "    df.info() (the behaviour in earlier versions of pandas).\n",
      "    [default: truncate] [currently: truncate]\n",
      "display.latex.escape : bool\n",
      "    This specifies if the to_latex method of a Dataframe uses escapes special\n",
      "    characters.\n",
      "    Valid values: False,True\n",
      "    [default: True] [currently: True]\n",
      "display.latex.longtable :bool\n",
      "    This specifies if the to_latex method of a Dataframe uses the longtable\n",
      "    format.\n",
      "    Valid values: False,True\n",
      "    [default: False] [currently: False]\n",
      "display.latex.multicolumn : bool\n",
      "    This specifies if the to_latex method of a Dataframe uses multicolumns\n",
      "    to pretty-print MultiIndex columns.\n",
      "    Valid values: False,True\n",
      "    [default: True] [currently: True]\n",
      "display.latex.multicolumn_format : bool\n",
      "    This specifies if the to_latex method of a Dataframe uses multicolumns\n",
      "    to pretty-print MultiIndex columns.\n",
      "    Valid values: False,True\n",
      "    [default: l] [currently: l]\n",
      "display.latex.multirow : bool\n",
      "    This specifies if the to_latex method of a Dataframe uses multirows\n",
      "    to pretty-print MultiIndex rows.\n",
      "    Valid values: False,True\n",
      "    [default: False] [currently: False]\n",
      "display.latex.repr : boolean\n",
      "    Whether to produce a latex DataFrame representation for jupyter\n",
      "    environments that support it.\n",
      "    (default: False)\n",
      "    [default: False] [currently: False]\n",
      "display.max_categories : int\n",
      "    This sets the maximum number of categories pandas should output when\n",
      "    printing out a `Categorical` or a Series of dtype \"category\".\n",
      "    [default: 8] [currently: 8]\n",
      "display.max_columns : int\n",
      "    If max_cols is exceeded, switch to truncate view. Depending on\n",
      "    `large_repr`, objects are either centrally truncated or printed as\n",
      "    a summary view. 'None' value means unlimited.\n",
      "\n",
      "    In case python/IPython is running in a terminal and `large_repr`\n",
      "    equals 'truncate' this can be set to 0 and pandas will auto-detect\n",
      "    the width of the terminal and print a truncated object which fits\n",
      "    the screen width. The IPython notebook, IPython qtconsole, or IDLE\n",
      "    do not run in a terminal and hence it is not possible to do\n",
      "    correct auto-detection.\n",
      "    [default: 20] [currently: 20]\n",
      "display.max_colwidth : int or None\n",
      "    The maximum width in characters of a column in the repr of\n",
      "    a pandas data structure. When the column overflows, a \"...\"\n",
      "    placeholder is embedded in the output. A 'None' value means unlimited.\n",
      "    [default: 50] [currently: 50]\n",
      "display.max_info_columns : int\n",
      "    max_info_columns is used in DataFrame.info method to decide if\n",
      "    per column information will be printed.\n",
      "    [default: 100] [currently: 100]\n",
      "display.max_info_rows : int or None\n",
      "    df.info() will usually show null-counts for each column.\n",
      "    For large frames this can be quite slow. max_info_rows and max_info_cols\n",
      "    limit this null check only to frames with smaller dimensions than\n",
      "    specified.\n",
      "    [default: 1690785] [currently: 1690785]\n",
      "display.max_rows : int\n",
      "    If max_rows is exceeded, switch to truncate view. Depending on\n",
      "    `large_repr`, objects are either centrally truncated or printed as\n",
      "    a summary view. 'None' value means unlimited.\n",
      "\n",
      "    In case python/IPython is running in a terminal and `large_repr`\n",
      "    equals 'truncate' this can be set to 0 and pandas will auto-detect\n",
      "    the height of the terminal and print a truncated object which fits\n",
      "    the screen height. The IPython notebook, IPython qtconsole, or\n",
      "    IDLE do not run in a terminal and hence it is not possible to do\n",
      "    correct auto-detection.\n",
      "    [default: 60] [currently: 60]\n",
      "display.max_seq_items : int or None\n",
      "    When pretty-printing a long sequence, no more then `max_seq_items`\n",
      "    will be printed. If items are omitted, they will be denoted by the\n",
      "    addition of \"...\" to the resulting string.\n",
      "\n",
      "    If set to None, the number of items to be printed is unlimited.\n",
      "    [default: 100] [currently: 100]\n",
      "display.memory_usage : bool, string or None\n",
      "    This specifies if the memory usage of a DataFrame should be displayed when\n",
      "    df.info() is called. Valid values True,False,'deep'\n",
      "    [default: True] [currently: True]\n",
      "display.min_rows : int\n",
      "    The numbers of rows to show in a truncated view (when `max_rows` is\n",
      "    exceeded). Ignored when `max_rows` is set to None or 0. When set to\n",
      "    None, follows the value of `max_rows`.\n",
      "    [default: 10] [currently: 10]\n",
      "display.multi_sparse : boolean\n",
      "    \"sparsify\" MultiIndex display (don't display repeated\n",
      "    elements in outer levels within groups)\n",
      "    [default: True] [currently: True]\n",
      "display.notebook_repr_html : boolean\n",
      "    When True, IPython notebook will use html representation for\n",
      "    pandas objects (if it is available).\n",
      "    [default: True] [currently: True]\n",
      "display.pprint_nest_depth : int\n",
      "    Controls the number of nested levels to process when pretty-printing\n",
      "    [default: 3] [currently: 3]\n",
      "display.precision : int\n",
      "    Floating point output precision in terms of number of places after the\n",
      "    decimal, for regular formatting as well as scientific notation. Similar\n",
      "    to ``precision`` in :meth:`numpy.set_printoptions`.\n",
      "    [default: 6] [currently: 6]\n",
      "display.show_dimensions : boolean or 'truncate'\n",
      "    Whether to print out dimensions at the end of DataFrame repr.\n",
      "    If 'truncate' is specified, only print out the dimensions if the\n",
      "    frame is truncated (e.g. not display all rows and/or columns)\n",
      "    [default: truncate] [currently: truncate]\n",
      "display.unicode.ambiguous_as_wide : boolean\n",
      "    Whether to use the Unicode East Asian Width to calculate the display text\n",
      "    width.\n",
      "    Enabling this may affect to the performance (default: False)\n",
      "    [default: False] [currently: False]\n",
      "display.unicode.east_asian_width : boolean\n",
      "    Whether to use the Unicode East Asian Width to calculate the display text\n",
      "    width.\n",
      "    Enabling this may affect to the performance (default: False)\n",
      "    [default: False] [currently: False]\n",
      "display.width : int\n",
      "    Width of the display in characters. In case python/IPython is running in\n",
      "    a terminal this can be set to None and pandas will correctly auto-detect\n",
      "    the width.\n",
      "    Note that the IPython notebook, IPython qtconsole, or IDLE do not run in a\n",
      "    terminal and hence it is not possible to correctly detect the width.\n",
      "    [default: 80] [currently: 80]\n",
      "io.excel.ods.reader : string\n",
      "    The default Excel reader engine for 'ods' files. Available options:\n",
      "    auto, odf.\n",
      "    [default: auto] [currently: auto]\n",
      "io.excel.ods.writer : string\n",
      "    The default Excel writer engine for 'ods' files. Available options:\n",
      "    auto, odf.\n",
      "    [default: auto] [currently: auto]\n",
      "io.excel.xls.reader : string\n",
      "    The default Excel reader engine for 'xls' files. Available options:\n",
      "    auto, xlrd.\n",
      "    [default: auto] [currently: auto]\n",
      "io.excel.xls.writer : string\n",
      "    The default Excel writer engine for 'xls' files. Available options:\n",
      "    auto, xlwt.\n",
      "    [default: auto] [currently: auto]\n",
      "    (Deprecated, use `` instead.)\n",
      "io.excel.xlsb.reader : string\n",
      "    The default Excel reader engine for 'xlsb' files. Available options:\n",
      "    auto, pyxlsb.\n",
      "    [default: auto] [currently: auto]\n",
      "io.excel.xlsm.reader : string\n",
      "    The default Excel reader engine for 'xlsm' files. Available options:\n",
      "    auto, xlrd, openpyxl.\n",
      "    [default: auto] [currently: auto]\n",
      "io.excel.xlsm.writer : string\n",
      "    The default Excel writer engine for 'xlsm' files. Available options:\n",
      "    auto, openpyxl.\n",
      "    [default: auto] [currently: auto]\n",
      "io.excel.xlsx.reader : string\n",
      "    The default Excel reader engine for 'xlsx' files. Available options:\n",
      "    auto, xlrd, openpyxl.\n",
      "    [default: auto] [currently: auto]\n",
      "io.excel.xlsx.writer : string\n",
      "    The default Excel writer engine for 'xlsx' files. Available options:\n",
      "    auto, openpyxl, xlsxwriter.\n",
      "    [default: auto] [currently: auto]\n",
      "io.hdf.default_format : format\n",
      "    default format writing format, if None, then\n",
      "    put will default to 'fixed' and append will default to 'table'\n",
      "    [default: None] [currently: None]\n",
      "io.hdf.dropna_table : boolean\n",
      "    drop ALL nan rows when appending to a table\n",
      "    [default: False] [currently: False]\n",
      "io.parquet.engine : string\n",
      "    The default parquet reader/writer engine. Available options:\n",
      "    'auto', 'pyarrow', 'fastparquet', the default is 'auto'\n",
      "    [default: auto] [currently: auto]\n",
      "io.sql.engine : string\n",
      "    The default sql reader/writer engine. Available options:\n",
      "    'auto', 'sqlalchemy', the default is 'auto'\n",
      "    [default: auto] [currently: auto]\n",
      "mode.chained_assignment : string\n",
      "    Raise an exception, warn, or no action if trying to use chained assignment,\n",
      "    The default is warn\n",
      "    [default: warn] [currently: warn]\n",
      "mode.data_manager : string\n",
      "    Internal data manager type; can be \"block\" or \"array\". Defaults to \"block\",\n",
      "    unless overridden by the 'PANDAS_DATA_MANAGER' environment variable (needs\n",
      "    to be set before pandas is imported).\n",
      "    [default: block] [currently: block]\n",
      "mode.sim_interactive : boolean\n",
      "    Whether to simulate interactive mode for purposes of testing\n",
      "    [default: False] [currently: False]\n",
      "mode.string_storage : string\n",
      "    The default storage for StringDtype.\n",
      "    [default: python] [currently: python]\n",
      "mode.use_inf_as_na : boolean\n",
      "    True means treat None, NaN, INF, -INF as NA (old way),\n",
      "    False means None and NaN are null, but INF, -INF are not NA\n",
      "    (new way).\n",
      "    [default: False] [currently: False]\n",
      "mode.use_inf_as_null : boolean\n",
      "    use_inf_as_null had been deprecated and will be removed in a future\n",
      "    version. Use `use_inf_as_na` instead.\n",
      "    [default: False] [currently: False]\n",
      "    (Deprecated, use `mode.use_inf_as_na` instead.)\n",
      "plotting.backend : str\n",
      "    The plotting backend to use. The default value is \"matplotlib\", the\n",
      "    backend provided with pandas. Other backends can be specified by\n",
      "    providing the name of the module that implements the backend.\n",
      "    [default: matplotlib] [currently: matplotlib]\n",
      "plotting.matplotlib.register_converters : bool or 'auto'.\n",
      "    Whether to register converters with matplotlib's units registry for\n",
      "    dates, times, datetimes, and Periods. Toggling to False will remove\n",
      "    the converters, restoring any converters that pandas overwrote.\n",
      "    [default: auto] [currently: auto]\n",
      "styler.render.max_elements : int\n",
      "    The maximum number of data-cell (<td>) elements that will be rendered before\n",
      "    trimming will occur over columns, rows or both if needed.\n",
      "    [default: 262144] [currently: 262144]\n",
      "styler.sparse.columns : bool\n",
      "    Whether to sparsify the display of hierarchical columns. Setting to False will\n",
      "    display each explicit level element in a hierarchical key for each column.\n",
      "    [default: True] [currently: True]\n",
      "styler.sparse.index : bool\n",
      "    Whether to sparsify the display of a hierarchical index. Setting to False will\n",
      "    display each explicit level element in a hierarchical key for each row.\n",
      "    [default: True] [currently: True]\n"
     ]
    }
   ],
   "source": [
    "pd.describe_option()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "791eb99e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.get_option('max_columns')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "d7aeeab4",
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.set_option('max_columns', 67)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "d56c6b7c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "67"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.get_option('max_columns')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "2892eae7",
   "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>iso_code</th>\n",
       "      <th>continent</th>\n",
       "      <th>location</th>\n",
       "      <th>date</th>\n",
       "      <th>total_cases</th>\n",
       "      <th>new_cases</th>\n",
       "      <th>new_cases_smoothed</th>\n",
       "      <th>total_deaths</th>\n",
       "      <th>new_deaths</th>\n",
       "      <th>new_deaths_smoothed</th>\n",
       "      <th>total_cases_per_million</th>\n",
       "      <th>new_cases_per_million</th>\n",
       "      <th>new_cases_smoothed_per_million</th>\n",
       "      <th>total_deaths_per_million</th>\n",
       "      <th>new_deaths_per_million</th>\n",
       "      <th>new_deaths_smoothed_per_million</th>\n",
       "      <th>reproduction_rate</th>\n",
       "      <th>icu_patients</th>\n",
       "      <th>icu_patients_per_million</th>\n",
       "      <th>hosp_patients</th>\n",
       "      <th>hosp_patients_per_million</th>\n",
       "      <th>weekly_icu_admissions</th>\n",
       "      <th>weekly_icu_admissions_per_million</th>\n",
       "      <th>weekly_hosp_admissions</th>\n",
       "      <th>weekly_hosp_admissions_per_million</th>\n",
       "      <th>new_tests</th>\n",
       "      <th>total_tests</th>\n",
       "      <th>total_tests_per_thousand</th>\n",
       "      <th>new_tests_per_thousand</th>\n",
       "      <th>new_tests_smoothed</th>\n",
       "      <th>new_tests_smoothed_per_thousand</th>\n",
       "      <th>positive_rate</th>\n",
       "      <th>tests_per_case</th>\n",
       "      <th>tests_units</th>\n",
       "      <th>total_vaccinations</th>\n",
       "      <th>people_vaccinated</th>\n",
       "      <th>people_fully_vaccinated</th>\n",
       "      <th>total_boosters</th>\n",
       "      <th>new_vaccinations</th>\n",
       "      <th>new_vaccinations_smoothed</th>\n",
       "      <th>total_vaccinations_per_hundred</th>\n",
       "      <th>people_vaccinated_per_hundred</th>\n",
       "      <th>people_fully_vaccinated_per_hundred</th>\n",
       "      <th>total_boosters_per_hundred</th>\n",
       "      <th>new_vaccinations_smoothed_per_million</th>\n",
       "      <th>new_people_vaccinated_smoothed</th>\n",
       "      <th>new_people_vaccinated_smoothed_per_hundred</th>\n",
       "      <th>stringency_index</th>\n",
       "      <th>population</th>\n",
       "      <th>population_density</th>\n",
       "      <th>median_age</th>\n",
       "      <th>aged_65_older</th>\n",
       "      <th>aged_70_older</th>\n",
       "      <th>gdp_per_capita</th>\n",
       "      <th>extreme_poverty</th>\n",
       "      <th>cardiovasc_death_rate</th>\n",
       "      <th>diabetes_prevalence</th>\n",
       "      <th>female_smokers</th>\n",
       "      <th>male_smokers</th>\n",
       "      <th>handwashing_facilities</th>\n",
       "      <th>hospital_beds_per_thousand</th>\n",
       "      <th>life_expectancy</th>\n",
       "      <th>human_development_index</th>\n",
       "      <th>excess_mortality_cumulative_absolute</th>\n",
       "      <th>excess_mortality_cumulative</th>\n",
       "      <th>excess_mortality</th>\n",
       "      <th>excess_mortality_cumulative_per_million</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-24</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.126</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.33</td>\n",
       "      <td>39835428.0</td>\n",
       "      <td>54.422</td>\n",
       "      <td>18.6</td>\n",
       "      <td>2.581</td>\n",
       "      <td>1.337</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-25</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.33</td>\n",
       "      <td>39835428.0</td>\n",
       "      <td>54.422</td>\n",
       "      <td>18.6</td>\n",
       "      <td>2.581</td>\n",
       "      <td>1.337</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-26</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.33</td>\n",
       "      <td>39835428.0</td>\n",
       "      <td>54.422</td>\n",
       "      <td>18.6</td>\n",
       "      <td>2.581</td>\n",
       "      <td>1.337</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-27</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.33</td>\n",
       "      <td>39835428.0</td>\n",
       "      <td>54.422</td>\n",
       "      <td>18.6</td>\n",
       "      <td>2.581</td>\n",
       "      <td>1.337</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-28</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.33</td>\n",
       "      <td>39835428.0</td>\n",
       "      <td>54.422</td>\n",
       "      <td>18.6</td>\n",
       "      <td>2.581</td>\n",
       "      <td>1.337</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151080</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-26</td>\n",
       "      <td>204351.0</td>\n",
       "      <td>605.0</td>\n",
       "      <td>1811.143</td>\n",
       "      <td>4891.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>15.571</td>\n",
       "      <td>13540.199</td>\n",
       "      <td>40.087</td>\n",
       "      <td>120.005</td>\n",
       "      <td>324.075</td>\n",
       "      <td>0.398</td>\n",
       "      <td>1.032</td>\n",
       "      <td>0.87</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1843.0</td>\n",
       "      <td>1675163.0</td>\n",
       "      <td>110.995</td>\n",
       "      <td>0.122</td>\n",
       "      <td>4957.0</td>\n",
       "      <td>0.328</td>\n",
       "      <td>0.3654</td>\n",
       "      <td>2.7</td>\n",
       "      <td>tests performed</td>\n",
       "      <td>7214640.0</td>\n",
       "      <td>4103288.0</td>\n",
       "      <td>3111352.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5591.0</td>\n",
       "      <td>12994.0</td>\n",
       "      <td>47.80</td>\n",
       "      <td>27.19</td>\n",
       "      <td>20.62</td>\n",
       "      <td>NaN</td>\n",
       "      <td>861.0</td>\n",
       "      <td>7018.0</td>\n",
       "      <td>0.047</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15092171.0</td>\n",
       "      <td>42.729</td>\n",
       "      <td>19.6</td>\n",
       "      <td>2.822</td>\n",
       "      <td>1.882</td>\n",
       "      <td>1899.775</td>\n",
       "      <td>21.4</td>\n",
       "      <td>307.846</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151081</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-27</td>\n",
       "      <td>205449.0</td>\n",
       "      <td>1098.0</td>\n",
       "      <td>1481.429</td>\n",
       "      <td>4908.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>14.714</td>\n",
       "      <td>13612.952</td>\n",
       "      <td>72.753</td>\n",
       "      <td>98.159</td>\n",
       "      <td>325.202</td>\n",
       "      <td>1.126</td>\n",
       "      <td>0.975</td>\n",
       "      <td>0.87</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7218438.0</td>\n",
       "      <td>4105296.0</td>\n",
       "      <td>3113142.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3798.0</td>\n",
       "      <td>11918.0</td>\n",
       "      <td>47.83</td>\n",
       "      <td>27.20</td>\n",
       "      <td>20.63</td>\n",
       "      <td>NaN</td>\n",
       "      <td>790.0</td>\n",
       "      <td>6425.0</td>\n",
       "      <td>0.043</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15092171.0</td>\n",
       "      <td>42.729</td>\n",
       "      <td>19.6</td>\n",
       "      <td>2.822</td>\n",
       "      <td>1.882</td>\n",
       "      <td>1899.775</td>\n",
       "      <td>21.4</td>\n",
       "      <td>307.846</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151082</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-28</td>\n",
       "      <td>207548.0</td>\n",
       "      <td>2099.0</td>\n",
       "      <td>1397.143</td>\n",
       "      <td>4940.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>17.286</td>\n",
       "      <td>13752.031</td>\n",
       "      <td>139.079</td>\n",
       "      <td>92.574</td>\n",
       "      <td>327.322</td>\n",
       "      <td>2.120</td>\n",
       "      <td>1.145</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7222341.0</td>\n",
       "      <td>4107151.0</td>\n",
       "      <td>3115190.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3903.0</td>\n",
       "      <td>10056.0</td>\n",
       "      <td>47.85</td>\n",
       "      <td>27.21</td>\n",
       "      <td>20.64</td>\n",
       "      <td>NaN</td>\n",
       "      <td>666.0</td>\n",
       "      <td>5407.0</td>\n",
       "      <td>0.036</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15092171.0</td>\n",
       "      <td>42.729</td>\n",
       "      <td>19.6</td>\n",
       "      <td>2.822</td>\n",
       "      <td>1.882</td>\n",
       "      <td>1899.775</td>\n",
       "      <td>21.4</td>\n",
       "      <td>307.846</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151083</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-29</td>\n",
       "      <td>207548.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1163.429</td>\n",
       "      <td>4940.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.000</td>\n",
       "      <td>13752.031</td>\n",
       "      <td>0.000</td>\n",
       "      <td>77.088</td>\n",
       "      <td>327.322</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.060</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7234293.0</td>\n",
       "      <td>4112517.0</td>\n",
       "      <td>3121776.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11952.0</td>\n",
       "      <td>9526.0</td>\n",
       "      <td>47.93</td>\n",
       "      <td>27.25</td>\n",
       "      <td>20.68</td>\n",
       "      <td>NaN</td>\n",
       "      <td>631.0</td>\n",
       "      <td>4796.0</td>\n",
       "      <td>0.032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15092171.0</td>\n",
       "      <td>42.729</td>\n",
       "      <td>19.6</td>\n",
       "      <td>2.822</td>\n",
       "      <td>1.882</td>\n",
       "      <td>1899.775</td>\n",
       "      <td>21.4</td>\n",
       "      <td>307.846</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151084</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-30</td>\n",
       "      <td>211728.0</td>\n",
       "      <td>4180.0</td>\n",
       "      <td>1483.429</td>\n",
       "      <td>4997.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>20.286</td>\n",
       "      <td>14028.996</td>\n",
       "      <td>276.965</td>\n",
       "      <td>98.291</td>\n",
       "      <td>331.099</td>\n",
       "      <td>3.777</td>\n",
       "      <td>1.344</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15092171.0</td>\n",
       "      <td>42.729</td>\n",
       "      <td>19.6</td>\n",
       "      <td>2.822</td>\n",
       "      <td>1.882</td>\n",
       "      <td>1899.775</td>\n",
       "      <td>21.4</td>\n",
       "      <td>307.846</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>151085 rows × 67 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       iso_code continent     location        date  total_cases  new_cases  \\\n",
       "0           AFG      Asia  Afghanistan  2020-02-24          5.0        5.0   \n",
       "1           AFG      Asia  Afghanistan  2020-02-25          5.0        0.0   \n",
       "2           AFG      Asia  Afghanistan  2020-02-26          5.0        0.0   \n",
       "3           AFG      Asia  Afghanistan  2020-02-27          5.0        0.0   \n",
       "4           AFG      Asia  Afghanistan  2020-02-28          5.0        0.0   \n",
       "...         ...       ...          ...         ...          ...        ...   \n",
       "151080      ZWE    Africa     Zimbabwe  2021-12-26     204351.0      605.0   \n",
       "151081      ZWE    Africa     Zimbabwe  2021-12-27     205449.0     1098.0   \n",
       "151082      ZWE    Africa     Zimbabwe  2021-12-28     207548.0     2099.0   \n",
       "151083      ZWE    Africa     Zimbabwe  2021-12-29     207548.0        0.0   \n",
       "151084      ZWE    Africa     Zimbabwe  2021-12-30     211728.0     4180.0   \n",
       "\n",
       "        new_cases_smoothed  total_deaths  new_deaths  new_deaths_smoothed  \\\n",
       "0                      NaN           NaN         NaN                  NaN   \n",
       "1                      NaN           NaN         NaN                  NaN   \n",
       "2                      NaN           NaN         NaN                  NaN   \n",
       "3                      NaN           NaN         NaN                  NaN   \n",
       "4                      NaN           NaN         NaN                  NaN   \n",
       "...                    ...           ...         ...                  ...   \n",
       "151080            1811.143        4891.0         6.0               15.571   \n",
       "151081            1481.429        4908.0        17.0               14.714   \n",
       "151082            1397.143        4940.0        32.0               17.286   \n",
       "151083            1163.429        4940.0         0.0               16.000   \n",
       "151084            1483.429        4997.0        57.0               20.286   \n",
       "\n",
       "        total_cases_per_million  new_cases_per_million  \\\n",
       "0                         0.126                  0.126   \n",
       "1                         0.126                  0.000   \n",
       "2                         0.126                  0.000   \n",
       "3                         0.126                  0.000   \n",
       "4                         0.126                  0.000   \n",
       "...                         ...                    ...   \n",
       "151080                13540.199                 40.087   \n",
       "151081                13612.952                 72.753   \n",
       "151082                13752.031                139.079   \n",
       "151083                13752.031                  0.000   \n",
       "151084                14028.996                276.965   \n",
       "\n",
       "        new_cases_smoothed_per_million  total_deaths_per_million  \\\n",
       "0                                  NaN                       NaN   \n",
       "1                                  NaN                       NaN   \n",
       "2                                  NaN                       NaN   \n",
       "3                                  NaN                       NaN   \n",
       "4                                  NaN                       NaN   \n",
       "...                                ...                       ...   \n",
       "151080                         120.005                   324.075   \n",
       "151081                          98.159                   325.202   \n",
       "151082                          92.574                   327.322   \n",
       "151083                          77.088                   327.322   \n",
       "151084                          98.291                   331.099   \n",
       "\n",
       "        new_deaths_per_million  new_deaths_smoothed_per_million  \\\n",
       "0                          NaN                              NaN   \n",
       "1                          NaN                              NaN   \n",
       "2                          NaN                              NaN   \n",
       "3                          NaN                              NaN   \n",
       "4                          NaN                              NaN   \n",
       "...                        ...                              ...   \n",
       "151080                   0.398                            1.032   \n",
       "151081                   1.126                            0.975   \n",
       "151082                   2.120                            1.145   \n",
       "151083                   0.000                            1.060   \n",
       "151084                   3.777                            1.344   \n",
       "\n",
       "        reproduction_rate  icu_patients  icu_patients_per_million  \\\n",
       "0                     NaN           NaN                       NaN   \n",
       "1                     NaN           NaN                       NaN   \n",
       "2                     NaN           NaN                       NaN   \n",
       "3                     NaN           NaN                       NaN   \n",
       "4                     NaN           NaN                       NaN   \n",
       "...                   ...           ...                       ...   \n",
       "151080               0.87           NaN                       NaN   \n",
       "151081               0.87           NaN                       NaN   \n",
       "151082                NaN           NaN                       NaN   \n",
       "151083                NaN           NaN                       NaN   \n",
       "151084                NaN           NaN                       NaN   \n",
       "\n",
       "        hosp_patients  hosp_patients_per_million  weekly_icu_admissions  \\\n",
       "0                 NaN                        NaN                    NaN   \n",
       "1                 NaN                        NaN                    NaN   \n",
       "2                 NaN                        NaN                    NaN   \n",
       "3                 NaN                        NaN                    NaN   \n",
       "4                 NaN                        NaN                    NaN   \n",
       "...               ...                        ...                    ...   \n",
       "151080            NaN                        NaN                    NaN   \n",
       "151081            NaN                        NaN                    NaN   \n",
       "151082            NaN                        NaN                    NaN   \n",
       "151083            NaN                        NaN                    NaN   \n",
       "151084            NaN                        NaN                    NaN   \n",
       "\n",
       "        weekly_icu_admissions_per_million  weekly_hosp_admissions  \\\n",
       "0                                     NaN                     NaN   \n",
       "1                                     NaN                     NaN   \n",
       "2                                     NaN                     NaN   \n",
       "3                                     NaN                     NaN   \n",
       "4                                     NaN                     NaN   \n",
       "...                                   ...                     ...   \n",
       "151080                                NaN                     NaN   \n",
       "151081                                NaN                     NaN   \n",
       "151082                                NaN                     NaN   \n",
       "151083                                NaN                     NaN   \n",
       "151084                                NaN                     NaN   \n",
       "\n",
       "        weekly_hosp_admissions_per_million  new_tests  total_tests  \\\n",
       "0                                      NaN        NaN          NaN   \n",
       "1                                      NaN        NaN          NaN   \n",
       "2                                      NaN        NaN          NaN   \n",
       "3                                      NaN        NaN          NaN   \n",
       "4                                      NaN        NaN          NaN   \n",
       "...                                    ...        ...          ...   \n",
       "151080                                 NaN     1843.0    1675163.0   \n",
       "151081                                 NaN        NaN          NaN   \n",
       "151082                                 NaN        NaN          NaN   \n",
       "151083                                 NaN        NaN          NaN   \n",
       "151084                                 NaN        NaN          NaN   \n",
       "\n",
       "        total_tests_per_thousand  new_tests_per_thousand  new_tests_smoothed  \\\n",
       "0                            NaN                     NaN                 NaN   \n",
       "1                            NaN                     NaN                 NaN   \n",
       "2                            NaN                     NaN                 NaN   \n",
       "3                            NaN                     NaN                 NaN   \n",
       "4                            NaN                     NaN                 NaN   \n",
       "...                          ...                     ...                 ...   \n",
       "151080                   110.995                   0.122              4957.0   \n",
       "151081                       NaN                     NaN                 NaN   \n",
       "151082                       NaN                     NaN                 NaN   \n",
       "151083                       NaN                     NaN                 NaN   \n",
       "151084                       NaN                     NaN                 NaN   \n",
       "\n",
       "        new_tests_smoothed_per_thousand  positive_rate  tests_per_case  \\\n",
       "0                                   NaN            NaN             NaN   \n",
       "1                                   NaN            NaN             NaN   \n",
       "2                                   NaN            NaN             NaN   \n",
       "3                                   NaN            NaN             NaN   \n",
       "4                                   NaN            NaN             NaN   \n",
       "...                                 ...            ...             ...   \n",
       "151080                            0.328         0.3654             2.7   \n",
       "151081                              NaN            NaN             NaN   \n",
       "151082                              NaN            NaN             NaN   \n",
       "151083                              NaN            NaN             NaN   \n",
       "151084                              NaN            NaN             NaN   \n",
       "\n",
       "            tests_units  total_vaccinations  people_vaccinated  \\\n",
       "0                   NaN                 NaN                NaN   \n",
       "1                   NaN                 NaN                NaN   \n",
       "2                   NaN                 NaN                NaN   \n",
       "3                   NaN                 NaN                NaN   \n",
       "4                   NaN                 NaN                NaN   \n",
       "...                 ...                 ...                ...   \n",
       "151080  tests performed           7214640.0          4103288.0   \n",
       "151081              NaN           7218438.0          4105296.0   \n",
       "151082              NaN           7222341.0          4107151.0   \n",
       "151083              NaN           7234293.0          4112517.0   \n",
       "151084              NaN                 NaN                NaN   \n",
       "\n",
       "        people_fully_vaccinated  total_boosters  new_vaccinations  \\\n",
       "0                           NaN             NaN               NaN   \n",
       "1                           NaN             NaN               NaN   \n",
       "2                           NaN             NaN               NaN   \n",
       "3                           NaN             NaN               NaN   \n",
       "4                           NaN             NaN               NaN   \n",
       "...                         ...             ...               ...   \n",
       "151080                3111352.0             NaN            5591.0   \n",
       "151081                3113142.0             NaN            3798.0   \n",
       "151082                3115190.0             NaN            3903.0   \n",
       "151083                3121776.0             NaN           11952.0   \n",
       "151084                      NaN             NaN               NaN   \n",
       "\n",
       "        new_vaccinations_smoothed  total_vaccinations_per_hundred  \\\n",
       "0                             NaN                             NaN   \n",
       "1                             NaN                             NaN   \n",
       "2                             NaN                             NaN   \n",
       "3                             NaN                             NaN   \n",
       "4                             NaN                             NaN   \n",
       "...                           ...                             ...   \n",
       "151080                    12994.0                           47.80   \n",
       "151081                    11918.0                           47.83   \n",
       "151082                    10056.0                           47.85   \n",
       "151083                     9526.0                           47.93   \n",
       "151084                        NaN                             NaN   \n",
       "\n",
       "        people_vaccinated_per_hundred  people_fully_vaccinated_per_hundred  \\\n",
       "0                                 NaN                                  NaN   \n",
       "1                                 NaN                                  NaN   \n",
       "2                                 NaN                                  NaN   \n",
       "3                                 NaN                                  NaN   \n",
       "4                                 NaN                                  NaN   \n",
       "...                               ...                                  ...   \n",
       "151080                          27.19                                20.62   \n",
       "151081                          27.20                                20.63   \n",
       "151082                          27.21                                20.64   \n",
       "151083                          27.25                                20.68   \n",
       "151084                            NaN                                  NaN   \n",
       "\n",
       "        total_boosters_per_hundred  new_vaccinations_smoothed_per_million  \\\n",
       "0                              NaN                                    NaN   \n",
       "1                              NaN                                    NaN   \n",
       "2                              NaN                                    NaN   \n",
       "3                              NaN                                    NaN   \n",
       "4                              NaN                                    NaN   \n",
       "...                            ...                                    ...   \n",
       "151080                         NaN                                  861.0   \n",
       "151081                         NaN                                  790.0   \n",
       "151082                         NaN                                  666.0   \n",
       "151083                         NaN                                  631.0   \n",
       "151084                         NaN                                    NaN   \n",
       "\n",
       "        new_people_vaccinated_smoothed  \\\n",
       "0                                  NaN   \n",
       "1                                  NaN   \n",
       "2                                  NaN   \n",
       "3                                  NaN   \n",
       "4                                  NaN   \n",
       "...                                ...   \n",
       "151080                          7018.0   \n",
       "151081                          6425.0   \n",
       "151082                          5407.0   \n",
       "151083                          4796.0   \n",
       "151084                             NaN   \n",
       "\n",
       "        new_people_vaccinated_smoothed_per_hundred  stringency_index  \\\n",
       "0                                              NaN              8.33   \n",
       "1                                              NaN              8.33   \n",
       "2                                              NaN              8.33   \n",
       "3                                              NaN              8.33   \n",
       "4                                              NaN              8.33   \n",
       "...                                            ...               ...   \n",
       "151080                                       0.047               NaN   \n",
       "151081                                       0.043               NaN   \n",
       "151082                                       0.036               NaN   \n",
       "151083                                       0.032               NaN   \n",
       "151084                                         NaN               NaN   \n",
       "\n",
       "        population  population_density  median_age  aged_65_older  \\\n",
       "0       39835428.0              54.422        18.6          2.581   \n",
       "1       39835428.0              54.422        18.6          2.581   \n",
       "2       39835428.0              54.422        18.6          2.581   \n",
       "3       39835428.0              54.422        18.6          2.581   \n",
       "4       39835428.0              54.422        18.6          2.581   \n",
       "...            ...                 ...         ...            ...   \n",
       "151080  15092171.0              42.729        19.6          2.822   \n",
       "151081  15092171.0              42.729        19.6          2.822   \n",
       "151082  15092171.0              42.729        19.6          2.822   \n",
       "151083  15092171.0              42.729        19.6          2.822   \n",
       "151084  15092171.0              42.729        19.6          2.822   \n",
       "\n",
       "        aged_70_older  gdp_per_capita  extreme_poverty  cardiovasc_death_rate  \\\n",
       "0               1.337        1803.987              NaN                597.029   \n",
       "1               1.337        1803.987              NaN                597.029   \n",
       "2               1.337        1803.987              NaN                597.029   \n",
       "3               1.337        1803.987              NaN                597.029   \n",
       "4               1.337        1803.987              NaN                597.029   \n",
       "...               ...             ...              ...                    ...   \n",
       "151080          1.882        1899.775             21.4                307.846   \n",
       "151081          1.882        1899.775             21.4                307.846   \n",
       "151082          1.882        1899.775             21.4                307.846   \n",
       "151083          1.882        1899.775             21.4                307.846   \n",
       "151084          1.882        1899.775             21.4                307.846   \n",
       "\n",
       "        diabetes_prevalence  female_smokers  male_smokers  \\\n",
       "0                      9.59             NaN           NaN   \n",
       "1                      9.59             NaN           NaN   \n",
       "2                      9.59             NaN           NaN   \n",
       "3                      9.59             NaN           NaN   \n",
       "4                      9.59             NaN           NaN   \n",
       "...                     ...             ...           ...   \n",
       "151080                 1.82             1.6          30.7   \n",
       "151081                 1.82             1.6          30.7   \n",
       "151082                 1.82             1.6          30.7   \n",
       "151083                 1.82             1.6          30.7   \n",
       "151084                 1.82             1.6          30.7   \n",
       "\n",
       "        handwashing_facilities  hospital_beds_per_thousand  life_expectancy  \\\n",
       "0                       37.746                         0.5            64.83   \n",
       "1                       37.746                         0.5            64.83   \n",
       "2                       37.746                         0.5            64.83   \n",
       "3                       37.746                         0.5            64.83   \n",
       "4                       37.746                         0.5            64.83   \n",
       "...                        ...                         ...              ...   \n",
       "151080                  36.791                         1.7            61.49   \n",
       "151081                  36.791                         1.7            61.49   \n",
       "151082                  36.791                         1.7            61.49   \n",
       "151083                  36.791                         1.7            61.49   \n",
       "151084                  36.791                         1.7            61.49   \n",
       "\n",
       "        human_development_index  excess_mortality_cumulative_absolute  \\\n",
       "0                         0.511                                   NaN   \n",
       "1                         0.511                                   NaN   \n",
       "2                         0.511                                   NaN   \n",
       "3                         0.511                                   NaN   \n",
       "4                         0.511                                   NaN   \n",
       "...                         ...                                   ...   \n",
       "151080                    0.571                                   NaN   \n",
       "151081                    0.571                                   NaN   \n",
       "151082                    0.571                                   NaN   \n",
       "151083                    0.571                                   NaN   \n",
       "151084                    0.571                                   NaN   \n",
       "\n",
       "        excess_mortality_cumulative  excess_mortality  \\\n",
       "0                               NaN               NaN   \n",
       "1                               NaN               NaN   \n",
       "2                               NaN               NaN   \n",
       "3                               NaN               NaN   \n",
       "4                               NaN               NaN   \n",
       "...                             ...               ...   \n",
       "151080                          NaN               NaN   \n",
       "151081                          NaN               NaN   \n",
       "151082                          NaN               NaN   \n",
       "151083                          NaN               NaN   \n",
       "151084                          NaN               NaN   \n",
       "\n",
       "        excess_mortality_cumulative_per_million  \n",
       "0                                           NaN  \n",
       "1                                           NaN  \n",
       "2                                           NaN  \n",
       "3                                           NaN  \n",
       "4                                           NaN  \n",
       "...                                         ...  \n",
       "151080                                      NaN  \n",
       "151081                                      NaN  \n",
       "151082                                      NaN  \n",
       "151083                                      NaN  \n",
       "151084                                      NaN  \n",
       "\n",
       "[151085 rows x 67 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_covid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "effef964",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "b71457cc",
   "metadata": {},
   "source": [
    "### b. Changing the number of rows to be displayed"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3d17dde",
   "metadata": {},
   "source": [
    "**Display 6 rows instead of default of 10**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "34b20396",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.get_option('min_rows')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d3b1f4aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.set_option('min_rows', 8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "a01b3c68",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.get_option('min_rows')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "43bdb2e0",
   "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>iso_code</th>\n",
       "      <th>continent</th>\n",
       "      <th>location</th>\n",
       "      <th>date</th>\n",
       "      <th>total_cases</th>\n",
       "      <th>new_cases</th>\n",
       "      <th>new_cases_smoothed</th>\n",
       "      <th>total_deaths</th>\n",
       "      <th>new_deaths</th>\n",
       "      <th>new_deaths_smoothed</th>\n",
       "      <th>total_cases_per_million</th>\n",
       "      <th>new_cases_per_million</th>\n",
       "      <th>new_cases_smoothed_per_million</th>\n",
       "      <th>total_deaths_per_million</th>\n",
       "      <th>new_deaths_per_million</th>\n",
       "      <th>new_deaths_smoothed_per_million</th>\n",
       "      <th>reproduction_rate</th>\n",
       "      <th>icu_patients</th>\n",
       "      <th>icu_patients_per_million</th>\n",
       "      <th>hosp_patients</th>\n",
       "      <th>hosp_patients_per_million</th>\n",
       "      <th>weekly_icu_admissions</th>\n",
       "      <th>weekly_icu_admissions_per_million</th>\n",
       "      <th>weekly_hosp_admissions</th>\n",
       "      <th>weekly_hosp_admissions_per_million</th>\n",
       "      <th>new_tests</th>\n",
       "      <th>total_tests</th>\n",
       "      <th>total_tests_per_thousand</th>\n",
       "      <th>new_tests_per_thousand</th>\n",
       "      <th>new_tests_smoothed</th>\n",
       "      <th>new_tests_smoothed_per_thousand</th>\n",
       "      <th>positive_rate</th>\n",
       "      <th>tests_per_case</th>\n",
       "      <th>tests_units</th>\n",
       "      <th>total_vaccinations</th>\n",
       "      <th>people_vaccinated</th>\n",
       "      <th>people_fully_vaccinated</th>\n",
       "      <th>total_boosters</th>\n",
       "      <th>new_vaccinations</th>\n",
       "      <th>new_vaccinations_smoothed</th>\n",
       "      <th>total_vaccinations_per_hundred</th>\n",
       "      <th>people_vaccinated_per_hundred</th>\n",
       "      <th>people_fully_vaccinated_per_hundred</th>\n",
       "      <th>total_boosters_per_hundred</th>\n",
       "      <th>new_vaccinations_smoothed_per_million</th>\n",
       "      <th>new_people_vaccinated_smoothed</th>\n",
       "      <th>new_people_vaccinated_smoothed_per_hundred</th>\n",
       "      <th>stringency_index</th>\n",
       "      <th>population</th>\n",
       "      <th>population_density</th>\n",
       "      <th>median_age</th>\n",
       "      <th>aged_65_older</th>\n",
       "      <th>aged_70_older</th>\n",
       "      <th>gdp_per_capita</th>\n",
       "      <th>extreme_poverty</th>\n",
       "      <th>cardiovasc_death_rate</th>\n",
       "      <th>diabetes_prevalence</th>\n",
       "      <th>female_smokers</th>\n",
       "      <th>male_smokers</th>\n",
       "      <th>handwashing_facilities</th>\n",
       "      <th>hospital_beds_per_thousand</th>\n",
       "      <th>life_expectancy</th>\n",
       "      <th>human_development_index</th>\n",
       "      <th>excess_mortality_cumulative_absolute</th>\n",
       "      <th>excess_mortality_cumulative</th>\n",
       "      <th>excess_mortality</th>\n",
       "      <th>excess_mortality_cumulative_per_million</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-24</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.126</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.33</td>\n",
       "      <td>39835428.0</td>\n",
       "      <td>54.422</td>\n",
       "      <td>18.6</td>\n",
       "      <td>2.581</td>\n",
       "      <td>1.337</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-25</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.33</td>\n",
       "      <td>39835428.0</td>\n",
       "      <td>54.422</td>\n",
       "      <td>18.6</td>\n",
       "      <td>2.581</td>\n",
       "      <td>1.337</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-26</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.33</td>\n",
       "      <td>39835428.0</td>\n",
       "      <td>54.422</td>\n",
       "      <td>18.6</td>\n",
       "      <td>2.581</td>\n",
       "      <td>1.337</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-27</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.33</td>\n",
       "      <td>39835428.0</td>\n",
       "      <td>54.422</td>\n",
       "      <td>18.6</td>\n",
       "      <td>2.581</td>\n",
       "      <td>1.337</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151081</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-27</td>\n",
       "      <td>205449.0</td>\n",
       "      <td>1098.0</td>\n",
       "      <td>1481.429</td>\n",
       "      <td>4908.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>14.714</td>\n",
       "      <td>13612.952</td>\n",
       "      <td>72.753</td>\n",
       "      <td>98.159</td>\n",
       "      <td>325.202</td>\n",
       "      <td>1.126</td>\n",
       "      <td>0.975</td>\n",
       "      <td>0.87</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7218438.0</td>\n",
       "      <td>4105296.0</td>\n",
       "      <td>3113142.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3798.0</td>\n",
       "      <td>11918.0</td>\n",
       "      <td>47.83</td>\n",
       "      <td>27.20</td>\n",
       "      <td>20.63</td>\n",
       "      <td>NaN</td>\n",
       "      <td>790.0</td>\n",
       "      <td>6425.0</td>\n",
       "      <td>0.043</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15092171.0</td>\n",
       "      <td>42.729</td>\n",
       "      <td>19.6</td>\n",
       "      <td>2.822</td>\n",
       "      <td>1.882</td>\n",
       "      <td>1899.775</td>\n",
       "      <td>21.4</td>\n",
       "      <td>307.846</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151082</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-28</td>\n",
       "      <td>207548.0</td>\n",
       "      <td>2099.0</td>\n",
       "      <td>1397.143</td>\n",
       "      <td>4940.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>17.286</td>\n",
       "      <td>13752.031</td>\n",
       "      <td>139.079</td>\n",
       "      <td>92.574</td>\n",
       "      <td>327.322</td>\n",
       "      <td>2.120</td>\n",
       "      <td>1.145</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7222341.0</td>\n",
       "      <td>4107151.0</td>\n",
       "      <td>3115190.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3903.0</td>\n",
       "      <td>10056.0</td>\n",
       "      <td>47.85</td>\n",
       "      <td>27.21</td>\n",
       "      <td>20.64</td>\n",
       "      <td>NaN</td>\n",
       "      <td>666.0</td>\n",
       "      <td>5407.0</td>\n",
       "      <td>0.036</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15092171.0</td>\n",
       "      <td>42.729</td>\n",
       "      <td>19.6</td>\n",
       "      <td>2.822</td>\n",
       "      <td>1.882</td>\n",
       "      <td>1899.775</td>\n",
       "      <td>21.4</td>\n",
       "      <td>307.846</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151083</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-29</td>\n",
       "      <td>207548.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1163.429</td>\n",
       "      <td>4940.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.000</td>\n",
       "      <td>13752.031</td>\n",
       "      <td>0.000</td>\n",
       "      <td>77.088</td>\n",
       "      <td>327.322</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.060</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7234293.0</td>\n",
       "      <td>4112517.0</td>\n",
       "      <td>3121776.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11952.0</td>\n",
       "      <td>9526.0</td>\n",
       "      <td>47.93</td>\n",
       "      <td>27.25</td>\n",
       "      <td>20.68</td>\n",
       "      <td>NaN</td>\n",
       "      <td>631.0</td>\n",
       "      <td>4796.0</td>\n",
       "      <td>0.032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15092171.0</td>\n",
       "      <td>42.729</td>\n",
       "      <td>19.6</td>\n",
       "      <td>2.822</td>\n",
       "      <td>1.882</td>\n",
       "      <td>1899.775</td>\n",
       "      <td>21.4</td>\n",
       "      <td>307.846</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151084</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-30</td>\n",
       "      <td>211728.0</td>\n",
       "      <td>4180.0</td>\n",
       "      <td>1483.429</td>\n",
       "      <td>4997.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>20.286</td>\n",
       "      <td>14028.996</td>\n",
       "      <td>276.965</td>\n",
       "      <td>98.291</td>\n",
       "      <td>331.099</td>\n",
       "      <td>3.777</td>\n",
       "      <td>1.344</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15092171.0</td>\n",
       "      <td>42.729</td>\n",
       "      <td>19.6</td>\n",
       "      <td>2.822</td>\n",
       "      <td>1.882</td>\n",
       "      <td>1899.775</td>\n",
       "      <td>21.4</td>\n",
       "      <td>307.846</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>151085 rows × 67 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       iso_code continent     location        date  total_cases  new_cases  \\\n",
       "0           AFG      Asia  Afghanistan  2020-02-24          5.0        5.0   \n",
       "1           AFG      Asia  Afghanistan  2020-02-25          5.0        0.0   \n",
       "2           AFG      Asia  Afghanistan  2020-02-26          5.0        0.0   \n",
       "3           AFG      Asia  Afghanistan  2020-02-27          5.0        0.0   \n",
       "...         ...       ...          ...         ...          ...        ...   \n",
       "151081      ZWE    Africa     Zimbabwe  2021-12-27     205449.0     1098.0   \n",
       "151082      ZWE    Africa     Zimbabwe  2021-12-28     207548.0     2099.0   \n",
       "151083      ZWE    Africa     Zimbabwe  2021-12-29     207548.0        0.0   \n",
       "151084      ZWE    Africa     Zimbabwe  2021-12-30     211728.0     4180.0   \n",
       "\n",
       "        new_cases_smoothed  total_deaths  new_deaths  new_deaths_smoothed  \\\n",
       "0                      NaN           NaN         NaN                  NaN   \n",
       "1                      NaN           NaN         NaN                  NaN   \n",
       "2                      NaN           NaN         NaN                  NaN   \n",
       "3                      NaN           NaN         NaN                  NaN   \n",
       "...                    ...           ...         ...                  ...   \n",
       "151081            1481.429        4908.0        17.0               14.714   \n",
       "151082            1397.143        4940.0        32.0               17.286   \n",
       "151083            1163.429        4940.0         0.0               16.000   \n",
       "151084            1483.429        4997.0        57.0               20.286   \n",
       "\n",
       "        total_cases_per_million  new_cases_per_million  \\\n",
       "0                         0.126                  0.126   \n",
       "1                         0.126                  0.000   \n",
       "2                         0.126                  0.000   \n",
       "3                         0.126                  0.000   \n",
       "...                         ...                    ...   \n",
       "151081                13612.952                 72.753   \n",
       "151082                13752.031                139.079   \n",
       "151083                13752.031                  0.000   \n",
       "151084                14028.996                276.965   \n",
       "\n",
       "        new_cases_smoothed_per_million  total_deaths_per_million  \\\n",
       "0                                  NaN                       NaN   \n",
       "1                                  NaN                       NaN   \n",
       "2                                  NaN                       NaN   \n",
       "3                                  NaN                       NaN   \n",
       "...                                ...                       ...   \n",
       "151081                          98.159                   325.202   \n",
       "151082                          92.574                   327.322   \n",
       "151083                          77.088                   327.322   \n",
       "151084                          98.291                   331.099   \n",
       "\n",
       "        new_deaths_per_million  new_deaths_smoothed_per_million  \\\n",
       "0                          NaN                              NaN   \n",
       "1                          NaN                              NaN   \n",
       "2                          NaN                              NaN   \n",
       "3                          NaN                              NaN   \n",
       "...                        ...                              ...   \n",
       "151081                   1.126                            0.975   \n",
       "151082                   2.120                            1.145   \n",
       "151083                   0.000                            1.060   \n",
       "151084                   3.777                            1.344   \n",
       "\n",
       "        reproduction_rate  icu_patients  icu_patients_per_million  \\\n",
       "0                     NaN           NaN                       NaN   \n",
       "1                     NaN           NaN                       NaN   \n",
       "2                     NaN           NaN                       NaN   \n",
       "3                     NaN           NaN                       NaN   \n",
       "...                   ...           ...                       ...   \n",
       "151081               0.87           NaN                       NaN   \n",
       "151082                NaN           NaN                       NaN   \n",
       "151083                NaN           NaN                       NaN   \n",
       "151084                NaN           NaN                       NaN   \n",
       "\n",
       "        hosp_patients  hosp_patients_per_million  weekly_icu_admissions  \\\n",
       "0                 NaN                        NaN                    NaN   \n",
       "1                 NaN                        NaN                    NaN   \n",
       "2                 NaN                        NaN                    NaN   \n",
       "3                 NaN                        NaN                    NaN   \n",
       "...               ...                        ...                    ...   \n",
       "151081            NaN                        NaN                    NaN   \n",
       "151082            NaN                        NaN                    NaN   \n",
       "151083            NaN                        NaN                    NaN   \n",
       "151084            NaN                        NaN                    NaN   \n",
       "\n",
       "        weekly_icu_admissions_per_million  weekly_hosp_admissions  \\\n",
       "0                                     NaN                     NaN   \n",
       "1                                     NaN                     NaN   \n",
       "2                                     NaN                     NaN   \n",
       "3                                     NaN                     NaN   \n",
       "...                                   ...                     ...   \n",
       "151081                                NaN                     NaN   \n",
       "151082                                NaN                     NaN   \n",
       "151083                                NaN                     NaN   \n",
       "151084                                NaN                     NaN   \n",
       "\n",
       "        weekly_hosp_admissions_per_million  new_tests  total_tests  \\\n",
       "0                                      NaN        NaN          NaN   \n",
       "1                                      NaN        NaN          NaN   \n",
       "2                                      NaN        NaN          NaN   \n",
       "3                                      NaN        NaN          NaN   \n",
       "...                                    ...        ...          ...   \n",
       "151081                                 NaN        NaN          NaN   \n",
       "151082                                 NaN        NaN          NaN   \n",
       "151083                                 NaN        NaN          NaN   \n",
       "151084                                 NaN        NaN          NaN   \n",
       "\n",
       "        total_tests_per_thousand  new_tests_per_thousand  new_tests_smoothed  \\\n",
       "0                            NaN                     NaN                 NaN   \n",
       "1                            NaN                     NaN                 NaN   \n",
       "2                            NaN                     NaN                 NaN   \n",
       "3                            NaN                     NaN                 NaN   \n",
       "...                          ...                     ...                 ...   \n",
       "151081                       NaN                     NaN                 NaN   \n",
       "151082                       NaN                     NaN                 NaN   \n",
       "151083                       NaN                     NaN                 NaN   \n",
       "151084                       NaN                     NaN                 NaN   \n",
       "\n",
       "        new_tests_smoothed_per_thousand  positive_rate  tests_per_case  \\\n",
       "0                                   NaN            NaN             NaN   \n",
       "1                                   NaN            NaN             NaN   \n",
       "2                                   NaN            NaN             NaN   \n",
       "3                                   NaN            NaN             NaN   \n",
       "...                                 ...            ...             ...   \n",
       "151081                              NaN            NaN             NaN   \n",
       "151082                              NaN            NaN             NaN   \n",
       "151083                              NaN            NaN             NaN   \n",
       "151084                              NaN            NaN             NaN   \n",
       "\n",
       "       tests_units  total_vaccinations  people_vaccinated  \\\n",
       "0              NaN                 NaN                NaN   \n",
       "1              NaN                 NaN                NaN   \n",
       "2              NaN                 NaN                NaN   \n",
       "3              NaN                 NaN                NaN   \n",
       "...            ...                 ...                ...   \n",
       "151081         NaN           7218438.0          4105296.0   \n",
       "151082         NaN           7222341.0          4107151.0   \n",
       "151083         NaN           7234293.0          4112517.0   \n",
       "151084         NaN                 NaN                NaN   \n",
       "\n",
       "        people_fully_vaccinated  total_boosters  new_vaccinations  \\\n",
       "0                           NaN             NaN               NaN   \n",
       "1                           NaN             NaN               NaN   \n",
       "2                           NaN             NaN               NaN   \n",
       "3                           NaN             NaN               NaN   \n",
       "...                         ...             ...               ...   \n",
       "151081                3113142.0             NaN            3798.0   \n",
       "151082                3115190.0             NaN            3903.0   \n",
       "151083                3121776.0             NaN           11952.0   \n",
       "151084                      NaN             NaN               NaN   \n",
       "\n",
       "        new_vaccinations_smoothed  total_vaccinations_per_hundred  \\\n",
       "0                             NaN                             NaN   \n",
       "1                             NaN                             NaN   \n",
       "2                             NaN                             NaN   \n",
       "3                             NaN                             NaN   \n",
       "...                           ...                             ...   \n",
       "151081                    11918.0                           47.83   \n",
       "151082                    10056.0                           47.85   \n",
       "151083                     9526.0                           47.93   \n",
       "151084                        NaN                             NaN   \n",
       "\n",
       "        people_vaccinated_per_hundred  people_fully_vaccinated_per_hundred  \\\n",
       "0                                 NaN                                  NaN   \n",
       "1                                 NaN                                  NaN   \n",
       "2                                 NaN                                  NaN   \n",
       "3                                 NaN                                  NaN   \n",
       "...                               ...                                  ...   \n",
       "151081                          27.20                                20.63   \n",
       "151082                          27.21                                20.64   \n",
       "151083                          27.25                                20.68   \n",
       "151084                            NaN                                  NaN   \n",
       "\n",
       "        total_boosters_per_hundred  new_vaccinations_smoothed_per_million  \\\n",
       "0                              NaN                                    NaN   \n",
       "1                              NaN                                    NaN   \n",
       "2                              NaN                                    NaN   \n",
       "3                              NaN                                    NaN   \n",
       "...                            ...                                    ...   \n",
       "151081                         NaN                                  790.0   \n",
       "151082                         NaN                                  666.0   \n",
       "151083                         NaN                                  631.0   \n",
       "151084                         NaN                                    NaN   \n",
       "\n",
       "        new_people_vaccinated_smoothed  \\\n",
       "0                                  NaN   \n",
       "1                                  NaN   \n",
       "2                                  NaN   \n",
       "3                                  NaN   \n",
       "...                                ...   \n",
       "151081                          6425.0   \n",
       "151082                          5407.0   \n",
       "151083                          4796.0   \n",
       "151084                             NaN   \n",
       "\n",
       "        new_people_vaccinated_smoothed_per_hundred  stringency_index  \\\n",
       "0                                              NaN              8.33   \n",
       "1                                              NaN              8.33   \n",
       "2                                              NaN              8.33   \n",
       "3                                              NaN              8.33   \n",
       "...                                            ...               ...   \n",
       "151081                                       0.043               NaN   \n",
       "151082                                       0.036               NaN   \n",
       "151083                                       0.032               NaN   \n",
       "151084                                         NaN               NaN   \n",
       "\n",
       "        population  population_density  median_age  aged_65_older  \\\n",
       "0       39835428.0              54.422        18.6          2.581   \n",
       "1       39835428.0              54.422        18.6          2.581   \n",
       "2       39835428.0              54.422        18.6          2.581   \n",
       "3       39835428.0              54.422        18.6          2.581   \n",
       "...            ...                 ...         ...            ...   \n",
       "151081  15092171.0              42.729        19.6          2.822   \n",
       "151082  15092171.0              42.729        19.6          2.822   \n",
       "151083  15092171.0              42.729        19.6          2.822   \n",
       "151084  15092171.0              42.729        19.6          2.822   \n",
       "\n",
       "        aged_70_older  gdp_per_capita  extreme_poverty  cardiovasc_death_rate  \\\n",
       "0               1.337        1803.987              NaN                597.029   \n",
       "1               1.337        1803.987              NaN                597.029   \n",
       "2               1.337        1803.987              NaN                597.029   \n",
       "3               1.337        1803.987              NaN                597.029   \n",
       "...               ...             ...              ...                    ...   \n",
       "151081          1.882        1899.775             21.4                307.846   \n",
       "151082          1.882        1899.775             21.4                307.846   \n",
       "151083          1.882        1899.775             21.4                307.846   \n",
       "151084          1.882        1899.775             21.4                307.846   \n",
       "\n",
       "        diabetes_prevalence  female_smokers  male_smokers  \\\n",
       "0                      9.59             NaN           NaN   \n",
       "1                      9.59             NaN           NaN   \n",
       "2                      9.59             NaN           NaN   \n",
       "3                      9.59             NaN           NaN   \n",
       "...                     ...             ...           ...   \n",
       "151081                 1.82             1.6          30.7   \n",
       "151082                 1.82             1.6          30.7   \n",
       "151083                 1.82             1.6          30.7   \n",
       "151084                 1.82             1.6          30.7   \n",
       "\n",
       "        handwashing_facilities  hospital_beds_per_thousand  life_expectancy  \\\n",
       "0                       37.746                         0.5            64.83   \n",
       "1                       37.746                         0.5            64.83   \n",
       "2                       37.746                         0.5            64.83   \n",
       "3                       37.746                         0.5            64.83   \n",
       "...                        ...                         ...              ...   \n",
       "151081                  36.791                         1.7            61.49   \n",
       "151082                  36.791                         1.7            61.49   \n",
       "151083                  36.791                         1.7            61.49   \n",
       "151084                  36.791                         1.7            61.49   \n",
       "\n",
       "        human_development_index  excess_mortality_cumulative_absolute  \\\n",
       "0                         0.511                                   NaN   \n",
       "1                         0.511                                   NaN   \n",
       "2                         0.511                                   NaN   \n",
       "3                         0.511                                   NaN   \n",
       "...                         ...                                   ...   \n",
       "151081                    0.571                                   NaN   \n",
       "151082                    0.571                                   NaN   \n",
       "151083                    0.571                                   NaN   \n",
       "151084                    0.571                                   NaN   \n",
       "\n",
       "        excess_mortality_cumulative  excess_mortality  \\\n",
       "0                               NaN               NaN   \n",
       "1                               NaN               NaN   \n",
       "2                               NaN               NaN   \n",
       "3                               NaN               NaN   \n",
       "...                             ...               ...   \n",
       "151081                          NaN               NaN   \n",
       "151082                          NaN               NaN   \n",
       "151083                          NaN               NaN   \n",
       "151084                          NaN               NaN   \n",
       "\n",
       "        excess_mortality_cumulative_per_million  \n",
       "0                                           NaN  \n",
       "1                                           NaN  \n",
       "2                                           NaN  \n",
       "3                                           NaN  \n",
       "...                                         ...  \n",
       "151081                                      NaN  \n",
       "151082                                      NaN  \n",
       "151083                                      NaN  \n",
       "151084                                      NaN  \n",
       "\n",
       "[151085 rows x 67 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_covid"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6e0969f",
   "metadata": {},
   "source": [
    "**Display 30 rows instead of default of 10**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "6ffa3be6",
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.set_option('min_rows', 30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "e6562f6f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "30"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.get_option('min_rows')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "b5520649",
   "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>iso_code</th>\n",
       "      <th>continent</th>\n",
       "      <th>location</th>\n",
       "      <th>date</th>\n",
       "      <th>total_cases</th>\n",
       "      <th>new_cases</th>\n",
       "      <th>new_cases_smoothed</th>\n",
       "      <th>total_deaths</th>\n",
       "      <th>new_deaths</th>\n",
       "      <th>new_deaths_smoothed</th>\n",
       "      <th>total_cases_per_million</th>\n",
       "      <th>new_cases_per_million</th>\n",
       "      <th>new_cases_smoothed_per_million</th>\n",
       "      <th>total_deaths_per_million</th>\n",
       "      <th>new_deaths_per_million</th>\n",
       "      <th>new_deaths_smoothed_per_million</th>\n",
       "      <th>reproduction_rate</th>\n",
       "      <th>icu_patients</th>\n",
       "      <th>icu_patients_per_million</th>\n",
       "      <th>hosp_patients</th>\n",
       "      <th>hosp_patients_per_million</th>\n",
       "      <th>weekly_icu_admissions</th>\n",
       "      <th>weekly_icu_admissions_per_million</th>\n",
       "      <th>weekly_hosp_admissions</th>\n",
       "      <th>weekly_hosp_admissions_per_million</th>\n",
       "      <th>new_tests</th>\n",
       "      <th>total_tests</th>\n",
       "      <th>total_tests_per_thousand</th>\n",
       "      <th>new_tests_per_thousand</th>\n",
       "      <th>new_tests_smoothed</th>\n",
       "      <th>new_tests_smoothed_per_thousand</th>\n",
       "      <th>positive_rate</th>\n",
       "      <th>tests_per_case</th>\n",
       "      <th>tests_units</th>\n",
       "      <th>total_vaccinations</th>\n",
       "      <th>people_vaccinated</th>\n",
       "      <th>people_fully_vaccinated</th>\n",
       "      <th>total_boosters</th>\n",
       "      <th>new_vaccinations</th>\n",
       "      <th>new_vaccinations_smoothed</th>\n",
       "      <th>total_vaccinations_per_hundred</th>\n",
       "      <th>people_vaccinated_per_hundred</th>\n",
       "      <th>people_fully_vaccinated_per_hundred</th>\n",
       "      <th>total_boosters_per_hundred</th>\n",
       "      <th>new_vaccinations_smoothed_per_million</th>\n",
       "      <th>new_people_vaccinated_smoothed</th>\n",
       "      <th>new_people_vaccinated_smoothed_per_hundred</th>\n",
       "      <th>stringency_index</th>\n",
       "      <th>population</th>\n",
       "      <th>population_density</th>\n",
       "      <th>median_age</th>\n",
       "      <th>aged_65_older</th>\n",
       "      <th>aged_70_older</th>\n",
       "      <th>gdp_per_capita</th>\n",
       "      <th>extreme_poverty</th>\n",
       "      <th>cardiovasc_death_rate</th>\n",
       "      <th>diabetes_prevalence</th>\n",
       "      <th>female_smokers</th>\n",
       "      <th>male_smokers</th>\n",
       "      <th>handwashing_facilities</th>\n",
       "      <th>hospital_beds_per_thousand</th>\n",
       "      <th>life_expectancy</th>\n",
       "      <th>human_development_index</th>\n",
       "      <th>excess_mortality_cumulative_absolute</th>\n",
       "      <th>excess_mortality_cumulative</th>\n",
       "      <th>excess_mortality</th>\n",
       "      <th>excess_mortality_cumulative_per_million</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-24</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.126</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.33</td>\n",
       "      <td>39835428.0</td>\n",
       "      <td>54.422</td>\n",
       "      <td>18.6</td>\n",
       "      <td>2.581</td>\n",
       "      <td>1.337</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-25</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.33</td>\n",
       "      <td>39835428.0</td>\n",
       "      <td>54.422</td>\n",
       "      <td>18.6</td>\n",
       "      <td>2.581</td>\n",
       "      <td>1.337</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-26</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.33</td>\n",
       "      <td>39835428.0</td>\n",
       "      <td>54.422</td>\n",
       "      <td>18.6</td>\n",
       "      <td>2.581</td>\n",
       "      <td>1.337</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-27</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.33</td>\n",
       "      <td>39835428.0</td>\n",
       "      <td>54.422</td>\n",
       "      <td>18.6</td>\n",
       "      <td>2.581</td>\n",
       "      <td>1.337</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-28</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.33</td>\n",
       "      <td>39835428.0</td>\n",
       "      <td>54.422</td>\n",
       "      <td>18.6</td>\n",
       "      <td>2.581</td>\n",
       "      <td>1.337</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-02-29</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.714</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.018</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.33</td>\n",
       "      <td>39835428.0</td>\n",
       "      <td>54.422</td>\n",
       "      <td>18.6</td>\n",
       "      <td>2.581</td>\n",
       "      <td>1.337</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-03-01</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.714</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.018</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.78</td>\n",
       "      <td>39835428.0</td>\n",
       "      <td>54.422</td>\n",
       "      <td>18.6</td>\n",
       "      <td>2.581</td>\n",
       "      <td>1.337</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-03-02</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.78</td>\n",
       "      <td>39835428.0</td>\n",
       "      <td>54.422</td>\n",
       "      <td>18.6</td>\n",
       "      <td>2.581</td>\n",
       "      <td>1.337</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-03-03</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.78</td>\n",
       "      <td>39835428.0</td>\n",
       "      <td>54.422</td>\n",
       "      <td>18.6</td>\n",
       "      <td>2.581</td>\n",
       "      <td>1.337</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-03-04</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.78</td>\n",
       "      <td>39835428.0</td>\n",
       "      <td>54.422</td>\n",
       "      <td>18.6</td>\n",
       "      <td>2.581</td>\n",
       "      <td>1.337</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-03-05</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.78</td>\n",
       "      <td>39835428.0</td>\n",
       "      <td>54.422</td>\n",
       "      <td>18.6</td>\n",
       "      <td>2.581</td>\n",
       "      <td>1.337</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-03-06</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.78</td>\n",
       "      <td>39835428.0</td>\n",
       "      <td>54.422</td>\n",
       "      <td>18.6</td>\n",
       "      <td>2.581</td>\n",
       "      <td>1.337</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-03-07</td>\n",
       "      <td>8.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.429</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.201</td>\n",
       "      <td>0.075</td>\n",
       "      <td>0.011</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.78</td>\n",
       "      <td>39835428.0</td>\n",
       "      <td>54.422</td>\n",
       "      <td>18.6</td>\n",
       "      <td>2.581</td>\n",
       "      <td>1.337</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-03-08</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.429</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.201</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.011</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.78</td>\n",
       "      <td>39835428.0</td>\n",
       "      <td>54.422</td>\n",
       "      <td>18.6</td>\n",
       "      <td>2.581</td>\n",
       "      <td>1.337</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2020-03-09</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.429</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.201</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.011</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.78</td>\n",
       "      <td>39835428.0</td>\n",
       "      <td>54.422</td>\n",
       "      <td>18.6</td>\n",
       "      <td>2.581</td>\n",
       "      <td>1.337</td>\n",
       "      <td>1803.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.746</td>\n",
       "      <td>0.5</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151070</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-16</td>\n",
       "      <td>182057.0</td>\n",
       "      <td>4367.0</td>\n",
       "      <td>3748.571</td>\n",
       "      <td>4759.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>5.143</td>\n",
       "      <td>12063.009</td>\n",
       "      <td>289.355</td>\n",
       "      <td>248.379</td>\n",
       "      <td>315.329</td>\n",
       "      <td>0.928</td>\n",
       "      <td>0.341</td>\n",
       "      <td>1.42</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12390.0</td>\n",
       "      <td>1622279.0</td>\n",
       "      <td>107.491</td>\n",
       "      <td>0.821</td>\n",
       "      <td>12471.0</td>\n",
       "      <td>0.826</td>\n",
       "      <td>0.3006</td>\n",
       "      <td>3.3</td>\n",
       "      <td>tests performed</td>\n",
       "      <td>7058474.0</td>\n",
       "      <td>4023289.0</td>\n",
       "      <td>3035185.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45074.0</td>\n",
       "      <td>26738.0</td>\n",
       "      <td>46.77</td>\n",
       "      <td>26.66</td>\n",
       "      <td>20.11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1772.0</td>\n",
       "      <td>14047.0</td>\n",
       "      <td>0.093</td>\n",
       "      <td>63.89</td>\n",
       "      <td>15092171.0</td>\n",
       "      <td>42.729</td>\n",
       "      <td>19.6</td>\n",
       "      <td>2.822</td>\n",
       "      <td>1.882</td>\n",
       "      <td>1899.775</td>\n",
       "      <td>21.4</td>\n",
       "      <td>307.846</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151071</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-17</td>\n",
       "      <td>189567.0</td>\n",
       "      <td>7510.0</td>\n",
       "      <td>4821.429</td>\n",
       "      <td>4779.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>8.000</td>\n",
       "      <td>12560.618</td>\n",
       "      <td>497.609</td>\n",
       "      <td>319.466</td>\n",
       "      <td>316.654</td>\n",
       "      <td>1.325</td>\n",
       "      <td>0.530</td>\n",
       "      <td>1.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9483.0</td>\n",
       "      <td>1631762.0</td>\n",
       "      <td>108.120</td>\n",
       "      <td>0.628</td>\n",
       "      <td>11700.0</td>\n",
       "      <td>0.775</td>\n",
       "      <td>0.4121</td>\n",
       "      <td>2.4</td>\n",
       "      <td>tests performed</td>\n",
       "      <td>7092391.0</td>\n",
       "      <td>4038743.0</td>\n",
       "      <td>3053648.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33917.0</td>\n",
       "      <td>27618.0</td>\n",
       "      <td>46.99</td>\n",
       "      <td>26.76</td>\n",
       "      <td>20.23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1830.0</td>\n",
       "      <td>14384.0</td>\n",
       "      <td>0.095</td>\n",
       "      <td>63.89</td>\n",
       "      <td>15092171.0</td>\n",
       "      <td>42.729</td>\n",
       "      <td>19.6</td>\n",
       "      <td>2.822</td>\n",
       "      <td>1.882</td>\n",
       "      <td>1899.775</td>\n",
       "      <td>21.4</td>\n",
       "      <td>307.846</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151072</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-18</td>\n",
       "      <td>189567.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3509.286</td>\n",
       "      <td>4779.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.286</td>\n",
       "      <td>12560.618</td>\n",
       "      <td>0.000</td>\n",
       "      <td>232.524</td>\n",
       "      <td>316.654</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.416</td>\n",
       "      <td>1.23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5430.0</td>\n",
       "      <td>1637192.0</td>\n",
       "      <td>108.480</td>\n",
       "      <td>0.360</td>\n",
       "      <td>11251.0</td>\n",
       "      <td>0.745</td>\n",
       "      <td>0.3119</td>\n",
       "      <td>3.2</td>\n",
       "      <td>tests performed</td>\n",
       "      <td>7111946.0</td>\n",
       "      <td>4048019.0</td>\n",
       "      <td>3063927.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19555.0</td>\n",
       "      <td>28607.0</td>\n",
       "      <td>47.12</td>\n",
       "      <td>26.82</td>\n",
       "      <td>20.30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1895.0</td>\n",
       "      <td>14744.0</td>\n",
       "      <td>0.098</td>\n",
       "      <td>63.89</td>\n",
       "      <td>15092171.0</td>\n",
       "      <td>42.729</td>\n",
       "      <td>19.6</td>\n",
       "      <td>2.822</td>\n",
       "      <td>1.882</td>\n",
       "      <td>1899.775</td>\n",
       "      <td>21.4</td>\n",
       "      <td>307.846</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151073</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-19</td>\n",
       "      <td>191673.0</td>\n",
       "      <td>2106.0</td>\n",
       "      <td>3504.714</td>\n",
       "      <td>4782.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.286</td>\n",
       "      <td>12700.161</td>\n",
       "      <td>139.543</td>\n",
       "      <td>232.221</td>\n",
       "      <td>316.853</td>\n",
       "      <td>0.199</td>\n",
       "      <td>0.416</td>\n",
       "      <td>1.15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3273.0</td>\n",
       "      <td>1640465.0</td>\n",
       "      <td>108.696</td>\n",
       "      <td>0.217</td>\n",
       "      <td>10478.0</td>\n",
       "      <td>0.694</td>\n",
       "      <td>0.3345</td>\n",
       "      <td>3.0</td>\n",
       "      <td>tests performed</td>\n",
       "      <td>7123684.0</td>\n",
       "      <td>4054165.0</td>\n",
       "      <td>3069519.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11738.0</td>\n",
       "      <td>27121.0</td>\n",
       "      <td>47.20</td>\n",
       "      <td>26.86</td>\n",
       "      <td>20.34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1797.0</td>\n",
       "      <td>13899.0</td>\n",
       "      <td>0.092</td>\n",
       "      <td>63.89</td>\n",
       "      <td>15092171.0</td>\n",
       "      <td>42.729</td>\n",
       "      <td>19.6</td>\n",
       "      <td>2.822</td>\n",
       "      <td>1.882</td>\n",
       "      <td>1899.775</td>\n",
       "      <td>21.4</td>\n",
       "      <td>307.846</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151074</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-20</td>\n",
       "      <td>195079.0</td>\n",
       "      <td>3406.0</td>\n",
       "      <td>3991.286</td>\n",
       "      <td>4805.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>9.571</td>\n",
       "      <td>12925.841</td>\n",
       "      <td>225.680</td>\n",
       "      <td>264.461</td>\n",
       "      <td>318.377</td>\n",
       "      <td>1.524</td>\n",
       "      <td>0.634</td>\n",
       "      <td>1.08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4830.0</td>\n",
       "      <td>1645295.0</td>\n",
       "      <td>109.016</td>\n",
       "      <td>0.320</td>\n",
       "      <td>9270.0</td>\n",
       "      <td>0.614</td>\n",
       "      <td>0.4306</td>\n",
       "      <td>2.3</td>\n",
       "      <td>tests performed</td>\n",
       "      <td>7135013.0</td>\n",
       "      <td>4060322.0</td>\n",
       "      <td>3074691.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11329.0</td>\n",
       "      <td>25553.0</td>\n",
       "      <td>47.28</td>\n",
       "      <td>26.90</td>\n",
       "      <td>20.37</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1693.0</td>\n",
       "      <td>13220.0</td>\n",
       "      <td>0.088</td>\n",
       "      <td>63.89</td>\n",
       "      <td>15092171.0</td>\n",
       "      <td>42.729</td>\n",
       "      <td>19.6</td>\n",
       "      <td>2.822</td>\n",
       "      <td>1.882</td>\n",
       "      <td>1899.775</td>\n",
       "      <td>21.4</td>\n",
       "      <td>307.846</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151075</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-21</td>\n",
       "      <td>197768.0</td>\n",
       "      <td>2689.0</td>\n",
       "      <td>3679.429</td>\n",
       "      <td>4819.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>11.286</td>\n",
       "      <td>13104.013</td>\n",
       "      <td>178.172</td>\n",
       "      <td>243.797</td>\n",
       "      <td>319.305</td>\n",
       "      <td>0.928</td>\n",
       "      <td>0.748</td>\n",
       "      <td>0.99</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12086.0</td>\n",
       "      <td>1657381.0</td>\n",
       "      <td>109.817</td>\n",
       "      <td>0.801</td>\n",
       "      <td>8597.0</td>\n",
       "      <td>0.570</td>\n",
       "      <td>0.4280</td>\n",
       "      <td>2.3</td>\n",
       "      <td>tests performed</td>\n",
       "      <td>7151946.0</td>\n",
       "      <td>4069302.0</td>\n",
       "      <td>3082644.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16933.0</td>\n",
       "      <td>24507.0</td>\n",
       "      <td>47.39</td>\n",
       "      <td>26.96</td>\n",
       "      <td>20.43</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1624.0</td>\n",
       "      <td>12505.0</td>\n",
       "      <td>0.083</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15092171.0</td>\n",
       "      <td>42.729</td>\n",
       "      <td>19.6</td>\n",
       "      <td>2.822</td>\n",
       "      <td>1.882</td>\n",
       "      <td>1899.775</td>\n",
       "      <td>21.4</td>\n",
       "      <td>307.846</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151076</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-22</td>\n",
       "      <td>199404.0</td>\n",
       "      <td>1636.0</td>\n",
       "      <td>3102.000</td>\n",
       "      <td>4828.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>11.857</td>\n",
       "      <td>13212.413</td>\n",
       "      <td>108.401</td>\n",
       "      <td>205.537</td>\n",
       "      <td>319.901</td>\n",
       "      <td>0.596</td>\n",
       "      <td>0.786</td>\n",
       "      <td>0.93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4663.0</td>\n",
       "      <td>1662044.0</td>\n",
       "      <td>110.126</td>\n",
       "      <td>0.309</td>\n",
       "      <td>7451.0</td>\n",
       "      <td>0.494</td>\n",
       "      <td>0.4163</td>\n",
       "      <td>2.4</td>\n",
       "      <td>tests performed</td>\n",
       "      <td>7167610.0</td>\n",
       "      <td>4078945.0</td>\n",
       "      <td>3088665.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15664.0</td>\n",
       "      <td>22030.0</td>\n",
       "      <td>47.49</td>\n",
       "      <td>27.03</td>\n",
       "      <td>20.47</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1460.0</td>\n",
       "      <td>11275.0</td>\n",
       "      <td>0.075</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15092171.0</td>\n",
       "      <td>42.729</td>\n",
       "      <td>19.6</td>\n",
       "      <td>2.822</td>\n",
       "      <td>1.882</td>\n",
       "      <td>1899.775</td>\n",
       "      <td>21.4</td>\n",
       "      <td>307.846</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151077</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-23</td>\n",
       "      <td>201344.0</td>\n",
       "      <td>1940.0</td>\n",
       "      <td>2755.286</td>\n",
       "      <td>4855.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>13.714</td>\n",
       "      <td>13340.957</td>\n",
       "      <td>128.543</td>\n",
       "      <td>182.564</td>\n",
       "      <td>321.690</td>\n",
       "      <td>1.789</td>\n",
       "      <td>0.909</td>\n",
       "      <td>0.90</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3919.0</td>\n",
       "      <td>1665963.0</td>\n",
       "      <td>110.386</td>\n",
       "      <td>0.260</td>\n",
       "      <td>6241.0</td>\n",
       "      <td>0.414</td>\n",
       "      <td>0.4415</td>\n",
       "      <td>2.3</td>\n",
       "      <td>tests performed</td>\n",
       "      <td>7188128.0</td>\n",
       "      <td>4089315.0</td>\n",
       "      <td>3098813.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20518.0</td>\n",
       "      <td>18522.0</td>\n",
       "      <td>47.63</td>\n",
       "      <td>27.10</td>\n",
       "      <td>20.53</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1227.0</td>\n",
       "      <td>9432.0</td>\n",
       "      <td>0.062</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15092171.0</td>\n",
       "      <td>42.729</td>\n",
       "      <td>19.6</td>\n",
       "      <td>2.822</td>\n",
       "      <td>1.882</td>\n",
       "      <td>1899.775</td>\n",
       "      <td>21.4</td>\n",
       "      <td>307.846</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151078</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-24</td>\n",
       "      <td>202736.0</td>\n",
       "      <td>1392.0</td>\n",
       "      <td>1881.286</td>\n",
       "      <td>4871.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>13.143</td>\n",
       "      <td>13433.190</td>\n",
       "      <td>92.233</td>\n",
       "      <td>124.653</td>\n",
       "      <td>322.750</td>\n",
       "      <td>1.060</td>\n",
       "      <td>0.871</td>\n",
       "      <td>0.88</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4454.0</td>\n",
       "      <td>1670417.0</td>\n",
       "      <td>110.681</td>\n",
       "      <td>0.295</td>\n",
       "      <td>5522.0</td>\n",
       "      <td>0.366</td>\n",
       "      <td>0.3407</td>\n",
       "      <td>2.9</td>\n",
       "      <td>tests performed</td>\n",
       "      <td>7200776.0</td>\n",
       "      <td>4095685.0</td>\n",
       "      <td>3105091.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12648.0</td>\n",
       "      <td>15484.0</td>\n",
       "      <td>47.71</td>\n",
       "      <td>27.14</td>\n",
       "      <td>20.57</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1026.0</td>\n",
       "      <td>8135.0</td>\n",
       "      <td>0.054</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15092171.0</td>\n",
       "      <td>42.729</td>\n",
       "      <td>19.6</td>\n",
       "      <td>2.822</td>\n",
       "      <td>1.882</td>\n",
       "      <td>1899.775</td>\n",
       "      <td>21.4</td>\n",
       "      <td>307.846</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151079</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-25</td>\n",
       "      <td>203746.0</td>\n",
       "      <td>1010.0</td>\n",
       "      <td>2025.571</td>\n",
       "      <td>4885.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>15.143</td>\n",
       "      <td>13500.112</td>\n",
       "      <td>66.922</td>\n",
       "      <td>134.213</td>\n",
       "      <td>323.678</td>\n",
       "      <td>0.928</td>\n",
       "      <td>1.003</td>\n",
       "      <td>0.87</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2903.0</td>\n",
       "      <td>1673320.0</td>\n",
       "      <td>110.873</td>\n",
       "      <td>0.192</td>\n",
       "      <td>5161.0</td>\n",
       "      <td>0.342</td>\n",
       "      <td>0.3925</td>\n",
       "      <td>2.5</td>\n",
       "      <td>tests performed</td>\n",
       "      <td>7209049.0</td>\n",
       "      <td>4100069.0</td>\n",
       "      <td>3108980.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8273.0</td>\n",
       "      <td>13872.0</td>\n",
       "      <td>47.77</td>\n",
       "      <td>27.17</td>\n",
       "      <td>20.60</td>\n",
       "      <td>NaN</td>\n",
       "      <td>919.0</td>\n",
       "      <td>7436.0</td>\n",
       "      <td>0.049</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15092171.0</td>\n",
       "      <td>42.729</td>\n",
       "      <td>19.6</td>\n",
       "      <td>2.822</td>\n",
       "      <td>1.882</td>\n",
       "      <td>1899.775</td>\n",
       "      <td>21.4</td>\n",
       "      <td>307.846</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151080</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-26</td>\n",
       "      <td>204351.0</td>\n",
       "      <td>605.0</td>\n",
       "      <td>1811.143</td>\n",
       "      <td>4891.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>15.571</td>\n",
       "      <td>13540.199</td>\n",
       "      <td>40.087</td>\n",
       "      <td>120.005</td>\n",
       "      <td>324.075</td>\n",
       "      <td>0.398</td>\n",
       "      <td>1.032</td>\n",
       "      <td>0.87</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1843.0</td>\n",
       "      <td>1675163.0</td>\n",
       "      <td>110.995</td>\n",
       "      <td>0.122</td>\n",
       "      <td>4957.0</td>\n",
       "      <td>0.328</td>\n",
       "      <td>0.3654</td>\n",
       "      <td>2.7</td>\n",
       "      <td>tests performed</td>\n",
       "      <td>7214640.0</td>\n",
       "      <td>4103288.0</td>\n",
       "      <td>3111352.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5591.0</td>\n",
       "      <td>12994.0</td>\n",
       "      <td>47.80</td>\n",
       "      <td>27.19</td>\n",
       "      <td>20.62</td>\n",
       "      <td>NaN</td>\n",
       "      <td>861.0</td>\n",
       "      <td>7018.0</td>\n",
       "      <td>0.047</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15092171.0</td>\n",
       "      <td>42.729</td>\n",
       "      <td>19.6</td>\n",
       "      <td>2.822</td>\n",
       "      <td>1.882</td>\n",
       "      <td>1899.775</td>\n",
       "      <td>21.4</td>\n",
       "      <td>307.846</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151081</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-27</td>\n",
       "      <td>205449.0</td>\n",
       "      <td>1098.0</td>\n",
       "      <td>1481.429</td>\n",
       "      <td>4908.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>14.714</td>\n",
       "      <td>13612.952</td>\n",
       "      <td>72.753</td>\n",
       "      <td>98.159</td>\n",
       "      <td>325.202</td>\n",
       "      <td>1.126</td>\n",
       "      <td>0.975</td>\n",
       "      <td>0.87</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7218438.0</td>\n",
       "      <td>4105296.0</td>\n",
       "      <td>3113142.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3798.0</td>\n",
       "      <td>11918.0</td>\n",
       "      <td>47.83</td>\n",
       "      <td>27.20</td>\n",
       "      <td>20.63</td>\n",
       "      <td>NaN</td>\n",
       "      <td>790.0</td>\n",
       "      <td>6425.0</td>\n",
       "      <td>0.043</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15092171.0</td>\n",
       "      <td>42.729</td>\n",
       "      <td>19.6</td>\n",
       "      <td>2.822</td>\n",
       "      <td>1.882</td>\n",
       "      <td>1899.775</td>\n",
       "      <td>21.4</td>\n",
       "      <td>307.846</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151082</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-28</td>\n",
       "      <td>207548.0</td>\n",
       "      <td>2099.0</td>\n",
       "      <td>1397.143</td>\n",
       "      <td>4940.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>17.286</td>\n",
       "      <td>13752.031</td>\n",
       "      <td>139.079</td>\n",
       "      <td>92.574</td>\n",
       "      <td>327.322</td>\n",
       "      <td>2.120</td>\n",
       "      <td>1.145</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7222341.0</td>\n",
       "      <td>4107151.0</td>\n",
       "      <td>3115190.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3903.0</td>\n",
       "      <td>10056.0</td>\n",
       "      <td>47.85</td>\n",
       "      <td>27.21</td>\n",
       "      <td>20.64</td>\n",
       "      <td>NaN</td>\n",
       "      <td>666.0</td>\n",
       "      <td>5407.0</td>\n",
       "      <td>0.036</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15092171.0</td>\n",
       "      <td>42.729</td>\n",
       "      <td>19.6</td>\n",
       "      <td>2.822</td>\n",
       "      <td>1.882</td>\n",
       "      <td>1899.775</td>\n",
       "      <td>21.4</td>\n",
       "      <td>307.846</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151083</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-29</td>\n",
       "      <td>207548.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1163.429</td>\n",
       "      <td>4940.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.000</td>\n",
       "      <td>13752.031</td>\n",
       "      <td>0.000</td>\n",
       "      <td>77.088</td>\n",
       "      <td>327.322</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.060</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7234293.0</td>\n",
       "      <td>4112517.0</td>\n",
       "      <td>3121776.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11952.0</td>\n",
       "      <td>9526.0</td>\n",
       "      <td>47.93</td>\n",
       "      <td>27.25</td>\n",
       "      <td>20.68</td>\n",
       "      <td>NaN</td>\n",
       "      <td>631.0</td>\n",
       "      <td>4796.0</td>\n",
       "      <td>0.032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15092171.0</td>\n",
       "      <td>42.729</td>\n",
       "      <td>19.6</td>\n",
       "      <td>2.822</td>\n",
       "      <td>1.882</td>\n",
       "      <td>1899.775</td>\n",
       "      <td>21.4</td>\n",
       "      <td>307.846</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151084</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021-12-30</td>\n",
       "      <td>211728.0</td>\n",
       "      <td>4180.0</td>\n",
       "      <td>1483.429</td>\n",
       "      <td>4997.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>20.286</td>\n",
       "      <td>14028.996</td>\n",
       "      <td>276.965</td>\n",
       "      <td>98.291</td>\n",
       "      <td>331.099</td>\n",
       "      <td>3.777</td>\n",
       "      <td>1.344</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15092171.0</td>\n",
       "      <td>42.729</td>\n",
       "      <td>19.6</td>\n",
       "      <td>2.822</td>\n",
       "      <td>1.882</td>\n",
       "      <td>1899.775</td>\n",
       "      <td>21.4</td>\n",
       "      <td>307.846</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.6</td>\n",
       "      <td>30.7</td>\n",
       "      <td>36.791</td>\n",
       "      <td>1.7</td>\n",
       "      <td>61.49</td>\n",
       "      <td>0.571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>151085 rows × 67 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       iso_code continent     location        date  total_cases  new_cases  \\\n",
       "0           AFG      Asia  Afghanistan  2020-02-24          5.0        5.0   \n",
       "1           AFG      Asia  Afghanistan  2020-02-25          5.0        0.0   \n",
       "2           AFG      Asia  Afghanistan  2020-02-26          5.0        0.0   \n",
       "3           AFG      Asia  Afghanistan  2020-02-27          5.0        0.0   \n",
       "4           AFG      Asia  Afghanistan  2020-02-28          5.0        0.0   \n",
       "5           AFG      Asia  Afghanistan  2020-02-29          5.0        0.0   \n",
       "6           AFG      Asia  Afghanistan  2020-03-01          5.0        0.0   \n",
       "7           AFG      Asia  Afghanistan  2020-03-02          5.0        0.0   \n",
       "8           AFG      Asia  Afghanistan  2020-03-03          5.0        0.0   \n",
       "9           AFG      Asia  Afghanistan  2020-03-04          5.0        0.0   \n",
       "10          AFG      Asia  Afghanistan  2020-03-05          5.0        0.0   \n",
       "11          AFG      Asia  Afghanistan  2020-03-06          5.0        0.0   \n",
       "12          AFG      Asia  Afghanistan  2020-03-07          8.0        3.0   \n",
       "13          AFG      Asia  Afghanistan  2020-03-08          8.0        0.0   \n",
       "14          AFG      Asia  Afghanistan  2020-03-09          8.0        0.0   \n",
       "...         ...       ...          ...         ...          ...        ...   \n",
       "151070      ZWE    Africa     Zimbabwe  2021-12-16     182057.0     4367.0   \n",
       "151071      ZWE    Africa     Zimbabwe  2021-12-17     189567.0     7510.0   \n",
       "151072      ZWE    Africa     Zimbabwe  2021-12-18     189567.0        0.0   \n",
       "151073      ZWE    Africa     Zimbabwe  2021-12-19     191673.0     2106.0   \n",
       "151074      ZWE    Africa     Zimbabwe  2021-12-20     195079.0     3406.0   \n",
       "151075      ZWE    Africa     Zimbabwe  2021-12-21     197768.0     2689.0   \n",
       "151076      ZWE    Africa     Zimbabwe  2021-12-22     199404.0     1636.0   \n",
       "151077      ZWE    Africa     Zimbabwe  2021-12-23     201344.0     1940.0   \n",
       "151078      ZWE    Africa     Zimbabwe  2021-12-24     202736.0     1392.0   \n",
       "151079      ZWE    Africa     Zimbabwe  2021-12-25     203746.0     1010.0   \n",
       "151080      ZWE    Africa     Zimbabwe  2021-12-26     204351.0      605.0   \n",
       "151081      ZWE    Africa     Zimbabwe  2021-12-27     205449.0     1098.0   \n",
       "151082      ZWE    Africa     Zimbabwe  2021-12-28     207548.0     2099.0   \n",
       "151083      ZWE    Africa     Zimbabwe  2021-12-29     207548.0        0.0   \n",
       "151084      ZWE    Africa     Zimbabwe  2021-12-30     211728.0     4180.0   \n",
       "\n",
       "        new_cases_smoothed  total_deaths  new_deaths  new_deaths_smoothed  \\\n",
       "0                      NaN           NaN         NaN                  NaN   \n",
       "1                      NaN           NaN         NaN                  NaN   \n",
       "2                      NaN           NaN         NaN                  NaN   \n",
       "3                      NaN           NaN         NaN                  NaN   \n",
       "4                      NaN           NaN         NaN                  NaN   \n",
       "5                    0.714           NaN         NaN                  NaN   \n",
       "6                    0.714           NaN         NaN                  NaN   \n",
       "7                    0.000           NaN         NaN                  NaN   \n",
       "8                    0.000           NaN         NaN                  NaN   \n",
       "9                    0.000           NaN         NaN                  NaN   \n",
       "10                   0.000           NaN         NaN                  NaN   \n",
       "11                   0.000           NaN         NaN                  NaN   \n",
       "12                   0.429           NaN         NaN                  NaN   \n",
       "13                   0.429           NaN         NaN                  NaN   \n",
       "14                   0.429           NaN         NaN                  NaN   \n",
       "...                    ...           ...         ...                  ...   \n",
       "151070            3748.571        4759.0        14.0                5.143   \n",
       "151071            4821.429        4779.0        20.0                8.000   \n",
       "151072            3509.286        4779.0         0.0                6.286   \n",
       "151073            3504.714        4782.0         3.0                6.286   \n",
       "151074            3991.286        4805.0        23.0                9.571   \n",
       "151075            3679.429        4819.0        14.0               11.286   \n",
       "151076            3102.000        4828.0         9.0               11.857   \n",
       "151077            2755.286        4855.0        27.0               13.714   \n",
       "151078            1881.286        4871.0        16.0               13.143   \n",
       "151079            2025.571        4885.0        14.0               15.143   \n",
       "151080            1811.143        4891.0         6.0               15.571   \n",
       "151081            1481.429        4908.0        17.0               14.714   \n",
       "151082            1397.143        4940.0        32.0               17.286   \n",
       "151083            1163.429        4940.0         0.0               16.000   \n",
       "151084            1483.429        4997.0        57.0               20.286   \n",
       "\n",
       "        total_cases_per_million  new_cases_per_million  \\\n",
       "0                         0.126                  0.126   \n",
       "1                         0.126                  0.000   \n",
       "2                         0.126                  0.000   \n",
       "3                         0.126                  0.000   \n",
       "4                         0.126                  0.000   \n",
       "5                         0.126                  0.000   \n",
       "6                         0.126                  0.000   \n",
       "7                         0.126                  0.000   \n",
       "8                         0.126                  0.000   \n",
       "9                         0.126                  0.000   \n",
       "10                        0.126                  0.000   \n",
       "11                        0.126                  0.000   \n",
       "12                        0.201                  0.075   \n",
       "13                        0.201                  0.000   \n",
       "14                        0.201                  0.000   \n",
       "...                         ...                    ...   \n",
       "151070                12063.009                289.355   \n",
       "151071                12560.618                497.609   \n",
       "151072                12560.618                  0.000   \n",
       "151073                12700.161                139.543   \n",
       "151074                12925.841                225.680   \n",
       "151075                13104.013                178.172   \n",
       "151076                13212.413                108.401   \n",
       "151077                13340.957                128.543   \n",
       "151078                13433.190                 92.233   \n",
       "151079                13500.112                 66.922   \n",
       "151080                13540.199                 40.087   \n",
       "151081                13612.952                 72.753   \n",
       "151082                13752.031                139.079   \n",
       "151083                13752.031                  0.000   \n",
       "151084                14028.996                276.965   \n",
       "\n",
       "        new_cases_smoothed_per_million  total_deaths_per_million  \\\n",
       "0                                  NaN                       NaN   \n",
       "1                                  NaN                       NaN   \n",
       "2                                  NaN                       NaN   \n",
       "3                                  NaN                       NaN   \n",
       "4                                  NaN                       NaN   \n",
       "5                                0.018                       NaN   \n",
       "6                                0.018                       NaN   \n",
       "7                                0.000                       NaN   \n",
       "8                                0.000                       NaN   \n",
       "9                                0.000                       NaN   \n",
       "10                               0.000                       NaN   \n",
       "11                               0.000                       NaN   \n",
       "12                               0.011                       NaN   \n",
       "13                               0.011                       NaN   \n",
       "14                               0.011                       NaN   \n",
       "...                                ...                       ...   \n",
       "151070                         248.379                   315.329   \n",
       "151071                         319.466                   316.654   \n",
       "151072                         232.524                   316.654   \n",
       "151073                         232.221                   316.853   \n",
       "151074                         264.461                   318.377   \n",
       "151075                         243.797                   319.305   \n",
       "151076                         205.537                   319.901   \n",
       "151077                         182.564                   321.690   \n",
       "151078                         124.653                   322.750   \n",
       "151079                         134.213                   323.678   \n",
       "151080                         120.005                   324.075   \n",
       "151081                          98.159                   325.202   \n",
       "151082                          92.574                   327.322   \n",
       "151083                          77.088                   327.322   \n",
       "151084                          98.291                   331.099   \n",
       "\n",
       "        new_deaths_per_million  new_deaths_smoothed_per_million  \\\n",
       "0                          NaN                              NaN   \n",
       "1                          NaN                              NaN   \n",
       "2                          NaN                              NaN   \n",
       "3                          NaN                              NaN   \n",
       "4                          NaN                              NaN   \n",
       "5                          NaN                              NaN   \n",
       "6                          NaN                              NaN   \n",
       "7                          NaN                              NaN   \n",
       "8                          NaN                              NaN   \n",
       "9                          NaN                              NaN   \n",
       "10                         NaN                              NaN   \n",
       "11                         NaN                              NaN   \n",
       "12                         NaN                              NaN   \n",
       "13                         NaN                              NaN   \n",
       "14                         NaN                              NaN   \n",
       "...                        ...                              ...   \n",
       "151070                   0.928                            0.341   \n",
       "151071                   1.325                            0.530   \n",
       "151072                   0.000                            0.416   \n",
       "151073                   0.199                            0.416   \n",
       "151074                   1.524                            0.634   \n",
       "151075                   0.928                            0.748   \n",
       "151076                   0.596                            0.786   \n",
       "151077                   1.789                            0.909   \n",
       "151078                   1.060                            0.871   \n",
       "151079                   0.928                            1.003   \n",
       "151080                   0.398                            1.032   \n",
       "151081                   1.126                            0.975   \n",
       "151082                   2.120                            1.145   \n",
       "151083                   0.000                            1.060   \n",
       "151084                   3.777                            1.344   \n",
       "\n",
       "        reproduction_rate  icu_patients  icu_patients_per_million  \\\n",
       "0                     NaN           NaN                       NaN   \n",
       "1                     NaN           NaN                       NaN   \n",
       "2                     NaN           NaN                       NaN   \n",
       "3                     NaN           NaN                       NaN   \n",
       "4                     NaN           NaN                       NaN   \n",
       "5                     NaN           NaN                       NaN   \n",
       "6                     NaN           NaN                       NaN   \n",
       "7                     NaN           NaN                       NaN   \n",
       "8                     NaN           NaN                       NaN   \n",
       "9                     NaN           NaN                       NaN   \n",
       "10                    NaN           NaN                       NaN   \n",
       "11                    NaN           NaN                       NaN   \n",
       "12                    NaN           NaN                       NaN   \n",
       "13                    NaN           NaN                       NaN   \n",
       "14                    NaN           NaN                       NaN   \n",
       "...                   ...           ...                       ...   \n",
       "151070               1.42           NaN                       NaN   \n",
       "151071               1.35           NaN                       NaN   \n",
       "151072               1.23           NaN                       NaN   \n",
       "151073               1.15           NaN                       NaN   \n",
       "151074               1.08           NaN                       NaN   \n",
       "151075               0.99           NaN                       NaN   \n",
       "151076               0.93           NaN                       NaN   \n",
       "151077               0.90           NaN                       NaN   \n",
       "151078               0.88           NaN                       NaN   \n",
       "151079               0.87           NaN                       NaN   \n",
       "151080               0.87           NaN                       NaN   \n",
       "151081               0.87           NaN                       NaN   \n",
       "151082                NaN           NaN                       NaN   \n",
       "151083                NaN           NaN                       NaN   \n",
       "151084                NaN           NaN                       NaN   \n",
       "\n",
       "        hosp_patients  hosp_patients_per_million  weekly_icu_admissions  \\\n",
       "0                 NaN                        NaN                    NaN   \n",
       "1                 NaN                        NaN                    NaN   \n",
       "2                 NaN                        NaN                    NaN   \n",
       "3                 NaN                        NaN                    NaN   \n",
       "4                 NaN                        NaN                    NaN   \n",
       "5                 NaN                        NaN                    NaN   \n",
       "6                 NaN                        NaN                    NaN   \n",
       "7                 NaN                        NaN                    NaN   \n",
       "8                 NaN                        NaN                    NaN   \n",
       "9                 NaN                        NaN                    NaN   \n",
       "10                NaN                        NaN                    NaN   \n",
       "11                NaN                        NaN                    NaN   \n",
       "12                NaN                        NaN                    NaN   \n",
       "13                NaN                        NaN                    NaN   \n",
       "14                NaN                        NaN                    NaN   \n",
       "...               ...                        ...                    ...   \n",
       "151070            NaN                        NaN                    NaN   \n",
       "151071            NaN                        NaN                    NaN   \n",
       "151072            NaN                        NaN                    NaN   \n",
       "151073            NaN                        NaN                    NaN   \n",
       "151074            NaN                        NaN                    NaN   \n",
       "151075            NaN                        NaN                    NaN   \n",
       "151076            NaN                        NaN                    NaN   \n",
       "151077            NaN                        NaN                    NaN   \n",
       "151078            NaN                        NaN                    NaN   \n",
       "151079            NaN                        NaN                    NaN   \n",
       "151080            NaN                        NaN                    NaN   \n",
       "151081            NaN                        NaN                    NaN   \n",
       "151082            NaN                        NaN                    NaN   \n",
       "151083            NaN                        NaN                    NaN   \n",
       "151084            NaN                        NaN                    NaN   \n",
       "\n",
       "        weekly_icu_admissions_per_million  weekly_hosp_admissions  \\\n",
       "0                                     NaN                     NaN   \n",
       "1                                     NaN                     NaN   \n",
       "2                                     NaN                     NaN   \n",
       "3                                     NaN                     NaN   \n",
       "4                                     NaN                     NaN   \n",
       "5                                     NaN                     NaN   \n",
       "6                                     NaN                     NaN   \n",
       "7                                     NaN                     NaN   \n",
       "8                                     NaN                     NaN   \n",
       "9                                     NaN                     NaN   \n",
       "10                                    NaN                     NaN   \n",
       "11                                    NaN                     NaN   \n",
       "12                                    NaN                     NaN   \n",
       "13                                    NaN                     NaN   \n",
       "14                                    NaN                     NaN   \n",
       "...                                   ...                     ...   \n",
       "151070                                NaN                     NaN   \n",
       "151071                                NaN                     NaN   \n",
       "151072                                NaN                     NaN   \n",
       "151073                                NaN                     NaN   \n",
       "151074                                NaN                     NaN   \n",
       "151075                                NaN                     NaN   \n",
       "151076                                NaN                     NaN   \n",
       "151077                                NaN                     NaN   \n",
       "151078                                NaN                     NaN   \n",
       "151079                                NaN                     NaN   \n",
       "151080                                NaN                     NaN   \n",
       "151081                                NaN                     NaN   \n",
       "151082                                NaN                     NaN   \n",
       "151083                                NaN                     NaN   \n",
       "151084                                NaN                     NaN   \n",
       "\n",
       "        weekly_hosp_admissions_per_million  new_tests  total_tests  \\\n",
       "0                                      NaN        NaN          NaN   \n",
       "1                                      NaN        NaN          NaN   \n",
       "2                                      NaN        NaN          NaN   \n",
       "3                                      NaN        NaN          NaN   \n",
       "4                                      NaN        NaN          NaN   \n",
       "5                                      NaN        NaN          NaN   \n",
       "6                                      NaN        NaN          NaN   \n",
       "7                                      NaN        NaN          NaN   \n",
       "8                                      NaN        NaN          NaN   \n",
       "9                                      NaN        NaN          NaN   \n",
       "10                                     NaN        NaN          NaN   \n",
       "11                                     NaN        NaN          NaN   \n",
       "12                                     NaN        NaN          NaN   \n",
       "13                                     NaN        NaN          NaN   \n",
       "14                                     NaN        NaN          NaN   \n",
       "...                                    ...        ...          ...   \n",
       "151070                                 NaN    12390.0    1622279.0   \n",
       "151071                                 NaN     9483.0    1631762.0   \n",
       "151072                                 NaN     5430.0    1637192.0   \n",
       "151073                                 NaN     3273.0    1640465.0   \n",
       "151074                                 NaN     4830.0    1645295.0   \n",
       "151075                                 NaN    12086.0    1657381.0   \n",
       "151076                                 NaN     4663.0    1662044.0   \n",
       "151077                                 NaN     3919.0    1665963.0   \n",
       "151078                                 NaN     4454.0    1670417.0   \n",
       "151079                                 NaN     2903.0    1673320.0   \n",
       "151080                                 NaN     1843.0    1675163.0   \n",
       "151081                                 NaN        NaN          NaN   \n",
       "151082                                 NaN        NaN          NaN   \n",
       "151083                                 NaN        NaN          NaN   \n",
       "151084                                 NaN        NaN          NaN   \n",
       "\n",
       "        total_tests_per_thousand  new_tests_per_thousand  new_tests_smoothed  \\\n",
       "0                            NaN                     NaN                 NaN   \n",
       "1                            NaN                     NaN                 NaN   \n",
       "2                            NaN                     NaN                 NaN   \n",
       "3                            NaN                     NaN                 NaN   \n",
       "4                            NaN                     NaN                 NaN   \n",
       "5                            NaN                     NaN                 NaN   \n",
       "6                            NaN                     NaN                 NaN   \n",
       "7                            NaN                     NaN                 NaN   \n",
       "8                            NaN                     NaN                 NaN   \n",
       "9                            NaN                     NaN                 NaN   \n",
       "10                           NaN                     NaN                 NaN   \n",
       "11                           NaN                     NaN                 NaN   \n",
       "12                           NaN                     NaN                 NaN   \n",
       "13                           NaN                     NaN                 NaN   \n",
       "14                           NaN                     NaN                 NaN   \n",
       "...                          ...                     ...                 ...   \n",
       "151070                   107.491                   0.821             12471.0   \n",
       "151071                   108.120                   0.628             11700.0   \n",
       "151072                   108.480                   0.360             11251.0   \n",
       "151073                   108.696                   0.217             10478.0   \n",
       "151074                   109.016                   0.320              9270.0   \n",
       "151075                   109.817                   0.801              8597.0   \n",
       "151076                   110.126                   0.309              7451.0   \n",
       "151077                   110.386                   0.260              6241.0   \n",
       "151078                   110.681                   0.295              5522.0   \n",
       "151079                   110.873                   0.192              5161.0   \n",
       "151080                   110.995                   0.122              4957.0   \n",
       "151081                       NaN                     NaN                 NaN   \n",
       "151082                       NaN                     NaN                 NaN   \n",
       "151083                       NaN                     NaN                 NaN   \n",
       "151084                       NaN                     NaN                 NaN   \n",
       "\n",
       "        new_tests_smoothed_per_thousand  positive_rate  tests_per_case  \\\n",
       "0                                   NaN            NaN             NaN   \n",
       "1                                   NaN            NaN             NaN   \n",
       "2                                   NaN            NaN             NaN   \n",
       "3                                   NaN            NaN             NaN   \n",
       "4                                   NaN            NaN             NaN   \n",
       "5                                   NaN            NaN             NaN   \n",
       "6                                   NaN            NaN             NaN   \n",
       "7                                   NaN            NaN             NaN   \n",
       "8                                   NaN            NaN             NaN   \n",
       "9                                   NaN            NaN             NaN   \n",
       "10                                  NaN            NaN             NaN   \n",
       "11                                  NaN            NaN             NaN   \n",
       "12                                  NaN            NaN             NaN   \n",
       "13                                  NaN            NaN             NaN   \n",
       "14                                  NaN            NaN             NaN   \n",
       "...                                 ...            ...             ...   \n",
       "151070                            0.826         0.3006             3.3   \n",
       "151071                            0.775         0.4121             2.4   \n",
       "151072                            0.745         0.3119             3.2   \n",
       "151073                            0.694         0.3345             3.0   \n",
       "151074                            0.614         0.4306             2.3   \n",
       "151075                            0.570         0.4280             2.3   \n",
       "151076                            0.494         0.4163             2.4   \n",
       "151077                            0.414         0.4415             2.3   \n",
       "151078                            0.366         0.3407             2.9   \n",
       "151079                            0.342         0.3925             2.5   \n",
       "151080                            0.328         0.3654             2.7   \n",
       "151081                              NaN            NaN             NaN   \n",
       "151082                              NaN            NaN             NaN   \n",
       "151083                              NaN            NaN             NaN   \n",
       "151084                              NaN            NaN             NaN   \n",
       "\n",
       "            tests_units  total_vaccinations  people_vaccinated  \\\n",
       "0                   NaN                 NaN                NaN   \n",
       "1                   NaN                 NaN                NaN   \n",
       "2                   NaN                 NaN                NaN   \n",
       "3                   NaN                 NaN                NaN   \n",
       "4                   NaN                 NaN                NaN   \n",
       "5                   NaN                 NaN                NaN   \n",
       "6                   NaN                 NaN                NaN   \n",
       "7                   NaN                 NaN                NaN   \n",
       "8                   NaN                 NaN                NaN   \n",
       "9                   NaN                 NaN                NaN   \n",
       "10                  NaN                 NaN                NaN   \n",
       "11                  NaN                 NaN                NaN   \n",
       "12                  NaN                 NaN                NaN   \n",
       "13                  NaN                 NaN                NaN   \n",
       "14                  NaN                 NaN                NaN   \n",
       "...                 ...                 ...                ...   \n",
       "151070  tests performed           7058474.0          4023289.0   \n",
       "151071  tests performed           7092391.0          4038743.0   \n",
       "151072  tests performed           7111946.0          4048019.0   \n",
       "151073  tests performed           7123684.0          4054165.0   \n",
       "151074  tests performed           7135013.0          4060322.0   \n",
       "151075  tests performed           7151946.0          4069302.0   \n",
       "151076  tests performed           7167610.0          4078945.0   \n",
       "151077  tests performed           7188128.0          4089315.0   \n",
       "151078  tests performed           7200776.0          4095685.0   \n",
       "151079  tests performed           7209049.0          4100069.0   \n",
       "151080  tests performed           7214640.0          4103288.0   \n",
       "151081              NaN           7218438.0          4105296.0   \n",
       "151082              NaN           7222341.0          4107151.0   \n",
       "151083              NaN           7234293.0          4112517.0   \n",
       "151084              NaN                 NaN                NaN   \n",
       "\n",
       "        people_fully_vaccinated  total_boosters  new_vaccinations  \\\n",
       "0                           NaN             NaN               NaN   \n",
       "1                           NaN             NaN               NaN   \n",
       "2                           NaN             NaN               NaN   \n",
       "3                           NaN             NaN               NaN   \n",
       "4                           NaN             NaN               NaN   \n",
       "5                           NaN             NaN               NaN   \n",
       "6                           NaN             NaN               NaN   \n",
       "7                           NaN             NaN               NaN   \n",
       "8                           NaN             NaN               NaN   \n",
       "9                           NaN             NaN               NaN   \n",
       "10                          NaN             NaN               NaN   \n",
       "11                          NaN             NaN               NaN   \n",
       "12                          NaN             NaN               NaN   \n",
       "13                          NaN             NaN               NaN   \n",
       "14                          NaN             NaN               NaN   \n",
       "...                         ...             ...               ...   \n",
       "151070                3035185.0             NaN           45074.0   \n",
       "151071                3053648.0             NaN           33917.0   \n",
       "151072                3063927.0             NaN           19555.0   \n",
       "151073                3069519.0             NaN           11738.0   \n",
       "151074                3074691.0             NaN           11329.0   \n",
       "151075                3082644.0             NaN           16933.0   \n",
       "151076                3088665.0             NaN           15664.0   \n",
       "151077                3098813.0             NaN           20518.0   \n",
       "151078                3105091.0             NaN           12648.0   \n",
       "151079                3108980.0             NaN            8273.0   \n",
       "151080                3111352.0             NaN            5591.0   \n",
       "151081                3113142.0             NaN            3798.0   \n",
       "151082                3115190.0             NaN            3903.0   \n",
       "151083                3121776.0             NaN           11952.0   \n",
       "151084                      NaN             NaN               NaN   \n",
       "\n",
       "        new_vaccinations_smoothed  total_vaccinations_per_hundred  \\\n",
       "0                             NaN                             NaN   \n",
       "1                             NaN                             NaN   \n",
       "2                             NaN                             NaN   \n",
       "3                             NaN                             NaN   \n",
       "4                             NaN                             NaN   \n",
       "5                             NaN                             NaN   \n",
       "6                             NaN                             NaN   \n",
       "7                             NaN                             NaN   \n",
       "8                             NaN                             NaN   \n",
       "9                             NaN                             NaN   \n",
       "10                            NaN                             NaN   \n",
       "11                            NaN                             NaN   \n",
       "12                            NaN                             NaN   \n",
       "13                            NaN                             NaN   \n",
       "14                            NaN                             NaN   \n",
       "...                           ...                             ...   \n",
       "151070                    26738.0                           46.77   \n",
       "151071                    27618.0                           46.99   \n",
       "151072                    28607.0                           47.12   \n",
       "151073                    27121.0                           47.20   \n",
       "151074                    25553.0                           47.28   \n",
       "151075                    24507.0                           47.39   \n",
       "151076                    22030.0                           47.49   \n",
       "151077                    18522.0                           47.63   \n",
       "151078                    15484.0                           47.71   \n",
       "151079                    13872.0                           47.77   \n",
       "151080                    12994.0                           47.80   \n",
       "151081                    11918.0                           47.83   \n",
       "151082                    10056.0                           47.85   \n",
       "151083                     9526.0                           47.93   \n",
       "151084                        NaN                             NaN   \n",
       "\n",
       "        people_vaccinated_per_hundred  people_fully_vaccinated_per_hundred  \\\n",
       "0                                 NaN                                  NaN   \n",
       "1                                 NaN                                  NaN   \n",
       "2                                 NaN                                  NaN   \n",
       "3                                 NaN                                  NaN   \n",
       "4                                 NaN                                  NaN   \n",
       "5                                 NaN                                  NaN   \n",
       "6                                 NaN                                  NaN   \n",
       "7                                 NaN                                  NaN   \n",
       "8                                 NaN                                  NaN   \n",
       "9                                 NaN                                  NaN   \n",
       "10                                NaN                                  NaN   \n",
       "11                                NaN                                  NaN   \n",
       "12                                NaN                                  NaN   \n",
       "13                                NaN                                  NaN   \n",
       "14                                NaN                                  NaN   \n",
       "...                               ...                                  ...   \n",
       "151070                          26.66                                20.11   \n",
       "151071                          26.76                                20.23   \n",
       "151072                          26.82                                20.30   \n",
       "151073                          26.86                                20.34   \n",
       "151074                          26.90                                20.37   \n",
       "151075                          26.96                                20.43   \n",
       "151076                          27.03                                20.47   \n",
       "151077                          27.10                                20.53   \n",
       "151078                          27.14                                20.57   \n",
       "151079                          27.17                                20.60   \n",
       "151080                          27.19                                20.62   \n",
       "151081                          27.20                                20.63   \n",
       "151082                          27.21                                20.64   \n",
       "151083                          27.25                                20.68   \n",
       "151084                            NaN                                  NaN   \n",
       "\n",
       "        total_boosters_per_hundred  new_vaccinations_smoothed_per_million  \\\n",
       "0                              NaN                                    NaN   \n",
       "1                              NaN                                    NaN   \n",
       "2                              NaN                                    NaN   \n",
       "3                              NaN                                    NaN   \n",
       "4                              NaN                                    NaN   \n",
       "5                              NaN                                    NaN   \n",
       "6                              NaN                                    NaN   \n",
       "7                              NaN                                    NaN   \n",
       "8                              NaN                                    NaN   \n",
       "9                              NaN                                    NaN   \n",
       "10                             NaN                                    NaN   \n",
       "11                             NaN                                    NaN   \n",
       "12                             NaN                                    NaN   \n",
       "13                             NaN                                    NaN   \n",
       "14                             NaN                                    NaN   \n",
       "...                            ...                                    ...   \n",
       "151070                         NaN                                 1772.0   \n",
       "151071                         NaN                                 1830.0   \n",
       "151072                         NaN                                 1895.0   \n",
       "151073                         NaN                                 1797.0   \n",
       "151074                         NaN                                 1693.0   \n",
       "151075                         NaN                                 1624.0   \n",
       "151076                         NaN                                 1460.0   \n",
       "151077                         NaN                                 1227.0   \n",
       "151078                         NaN                                 1026.0   \n",
       "151079                         NaN                                  919.0   \n",
       "151080                         NaN                                  861.0   \n",
       "151081                         NaN                                  790.0   \n",
       "151082                         NaN                                  666.0   \n",
       "151083                         NaN                                  631.0   \n",
       "151084                         NaN                                    NaN   \n",
       "\n",
       "        new_people_vaccinated_smoothed  \\\n",
       "0                                  NaN   \n",
       "1                                  NaN   \n",
       "2                                  NaN   \n",
       "3                                  NaN   \n",
       "4                                  NaN   \n",
       "5                                  NaN   \n",
       "6                                  NaN   \n",
       "7                                  NaN   \n",
       "8                                  NaN   \n",
       "9                                  NaN   \n",
       "10                                 NaN   \n",
       "11                                 NaN   \n",
       "12                                 NaN   \n",
       "13                                 NaN   \n",
       "14                                 NaN   \n",
       "...                                ...   \n",
       "151070                         14047.0   \n",
       "151071                         14384.0   \n",
       "151072                         14744.0   \n",
       "151073                         13899.0   \n",
       "151074                         13220.0   \n",
       "151075                         12505.0   \n",
       "151076                         11275.0   \n",
       "151077                          9432.0   \n",
       "151078                          8135.0   \n",
       "151079                          7436.0   \n",
       "151080                          7018.0   \n",
       "151081                          6425.0   \n",
       "151082                          5407.0   \n",
       "151083                          4796.0   \n",
       "151084                             NaN   \n",
       "\n",
       "        new_people_vaccinated_smoothed_per_hundred  stringency_index  \\\n",
       "0                                              NaN              8.33   \n",
       "1                                              NaN              8.33   \n",
       "2                                              NaN              8.33   \n",
       "3                                              NaN              8.33   \n",
       "4                                              NaN              8.33   \n",
       "5                                              NaN              8.33   \n",
       "6                                              NaN             27.78   \n",
       "7                                              NaN             27.78   \n",
       "8                                              NaN             27.78   \n",
       "9                                              NaN             27.78   \n",
       "10                                             NaN             27.78   \n",
       "11                                             NaN             27.78   \n",
       "12                                             NaN             27.78   \n",
       "13                                             NaN             27.78   \n",
       "14                                             NaN             27.78   \n",
       "...                                            ...               ...   \n",
       "151070                                       0.093             63.89   \n",
       "151071                                       0.095             63.89   \n",
       "151072                                       0.098             63.89   \n",
       "151073                                       0.092             63.89   \n",
       "151074                                       0.088             63.89   \n",
       "151075                                       0.083               NaN   \n",
       "151076                                       0.075               NaN   \n",
       "151077                                       0.062               NaN   \n",
       "151078                                       0.054               NaN   \n",
       "151079                                       0.049               NaN   \n",
       "151080                                       0.047               NaN   \n",
       "151081                                       0.043               NaN   \n",
       "151082                                       0.036               NaN   \n",
       "151083                                       0.032               NaN   \n",
       "151084                                         NaN               NaN   \n",
       "\n",
       "        population  population_density  median_age  aged_65_older  \\\n",
       "0       39835428.0              54.422        18.6          2.581   \n",
       "1       39835428.0              54.422        18.6          2.581   \n",
       "2       39835428.0              54.422        18.6          2.581   \n",
       "3       39835428.0              54.422        18.6          2.581   \n",
       "4       39835428.0              54.422        18.6          2.581   \n",
       "5       39835428.0              54.422        18.6          2.581   \n",
       "6       39835428.0              54.422        18.6          2.581   \n",
       "7       39835428.0              54.422        18.6          2.581   \n",
       "8       39835428.0              54.422        18.6          2.581   \n",
       "9       39835428.0              54.422        18.6          2.581   \n",
       "10      39835428.0              54.422        18.6          2.581   \n",
       "11      39835428.0              54.422        18.6          2.581   \n",
       "12      39835428.0              54.422        18.6          2.581   \n",
       "13      39835428.0              54.422        18.6          2.581   \n",
       "14      39835428.0              54.422        18.6          2.581   \n",
       "...            ...                 ...         ...            ...   \n",
       "151070  15092171.0              42.729        19.6          2.822   \n",
       "151071  15092171.0              42.729        19.6          2.822   \n",
       "151072  15092171.0              42.729        19.6          2.822   \n",
       "151073  15092171.0              42.729        19.6          2.822   \n",
       "151074  15092171.0              42.729        19.6          2.822   \n",
       "151075  15092171.0              42.729        19.6          2.822   \n",
       "151076  15092171.0              42.729        19.6          2.822   \n",
       "151077  15092171.0              42.729        19.6          2.822   \n",
       "151078  15092171.0              42.729        19.6          2.822   \n",
       "151079  15092171.0              42.729        19.6          2.822   \n",
       "151080  15092171.0              42.729        19.6          2.822   \n",
       "151081  15092171.0              42.729        19.6          2.822   \n",
       "151082  15092171.0              42.729        19.6          2.822   \n",
       "151083  15092171.0              42.729        19.6          2.822   \n",
       "151084  15092171.0              42.729        19.6          2.822   \n",
       "\n",
       "        aged_70_older  gdp_per_capita  extreme_poverty  cardiovasc_death_rate  \\\n",
       "0               1.337        1803.987              NaN                597.029   \n",
       "1               1.337        1803.987              NaN                597.029   \n",
       "2               1.337        1803.987              NaN                597.029   \n",
       "3               1.337        1803.987              NaN                597.029   \n",
       "4               1.337        1803.987              NaN                597.029   \n",
       "5               1.337        1803.987              NaN                597.029   \n",
       "6               1.337        1803.987              NaN                597.029   \n",
       "7               1.337        1803.987              NaN                597.029   \n",
       "8               1.337        1803.987              NaN                597.029   \n",
       "9               1.337        1803.987              NaN                597.029   \n",
       "10              1.337        1803.987              NaN                597.029   \n",
       "11              1.337        1803.987              NaN                597.029   \n",
       "12              1.337        1803.987              NaN                597.029   \n",
       "13              1.337        1803.987              NaN                597.029   \n",
       "14              1.337        1803.987              NaN                597.029   \n",
       "...               ...             ...              ...                    ...   \n",
       "151070          1.882        1899.775             21.4                307.846   \n",
       "151071          1.882        1899.775             21.4                307.846   \n",
       "151072          1.882        1899.775             21.4                307.846   \n",
       "151073          1.882        1899.775             21.4                307.846   \n",
       "151074          1.882        1899.775             21.4                307.846   \n",
       "151075          1.882        1899.775             21.4                307.846   \n",
       "151076          1.882        1899.775             21.4                307.846   \n",
       "151077          1.882        1899.775             21.4                307.846   \n",
       "151078          1.882        1899.775             21.4                307.846   \n",
       "151079          1.882        1899.775             21.4                307.846   \n",
       "151080          1.882        1899.775             21.4                307.846   \n",
       "151081          1.882        1899.775             21.4                307.846   \n",
       "151082          1.882        1899.775             21.4                307.846   \n",
       "151083          1.882        1899.775             21.4                307.846   \n",
       "151084          1.882        1899.775             21.4                307.846   \n",
       "\n",
       "        diabetes_prevalence  female_smokers  male_smokers  \\\n",
       "0                      9.59             NaN           NaN   \n",
       "1                      9.59             NaN           NaN   \n",
       "2                      9.59             NaN           NaN   \n",
       "3                      9.59             NaN           NaN   \n",
       "4                      9.59             NaN           NaN   \n",
       "5                      9.59             NaN           NaN   \n",
       "6                      9.59             NaN           NaN   \n",
       "7                      9.59             NaN           NaN   \n",
       "8                      9.59             NaN           NaN   \n",
       "9                      9.59             NaN           NaN   \n",
       "10                     9.59             NaN           NaN   \n",
       "11                     9.59             NaN           NaN   \n",
       "12                     9.59             NaN           NaN   \n",
       "13                     9.59             NaN           NaN   \n",
       "14                     9.59             NaN           NaN   \n",
       "...                     ...             ...           ...   \n",
       "151070                 1.82             1.6          30.7   \n",
       "151071                 1.82             1.6          30.7   \n",
       "151072                 1.82             1.6          30.7   \n",
       "151073                 1.82             1.6          30.7   \n",
       "151074                 1.82             1.6          30.7   \n",
       "151075                 1.82             1.6          30.7   \n",
       "151076                 1.82             1.6          30.7   \n",
       "151077                 1.82             1.6          30.7   \n",
       "151078                 1.82             1.6          30.7   \n",
       "151079                 1.82             1.6          30.7   \n",
       "151080                 1.82             1.6          30.7   \n",
       "151081                 1.82             1.6          30.7   \n",
       "151082                 1.82             1.6          30.7   \n",
       "151083                 1.82             1.6          30.7   \n",
       "151084                 1.82             1.6          30.7   \n",
       "\n",
       "        handwashing_facilities  hospital_beds_per_thousand  life_expectancy  \\\n",
       "0                       37.746                         0.5            64.83   \n",
       "1                       37.746                         0.5            64.83   \n",
       "2                       37.746                         0.5            64.83   \n",
       "3                       37.746                         0.5            64.83   \n",
       "4                       37.746                         0.5            64.83   \n",
       "5                       37.746                         0.5            64.83   \n",
       "6                       37.746                         0.5            64.83   \n",
       "7                       37.746                         0.5            64.83   \n",
       "8                       37.746                         0.5            64.83   \n",
       "9                       37.746                         0.5            64.83   \n",
       "10                      37.746                         0.5            64.83   \n",
       "11                      37.746                         0.5            64.83   \n",
       "12                      37.746                         0.5            64.83   \n",
       "13                      37.746                         0.5            64.83   \n",
       "14                      37.746                         0.5            64.83   \n",
       "...                        ...                         ...              ...   \n",
       "151070                  36.791                         1.7            61.49   \n",
       "151071                  36.791                         1.7            61.49   \n",
       "151072                  36.791                         1.7            61.49   \n",
       "151073                  36.791                         1.7            61.49   \n",
       "151074                  36.791                         1.7            61.49   \n",
       "151075                  36.791                         1.7            61.49   \n",
       "151076                  36.791                         1.7            61.49   \n",
       "151077                  36.791                         1.7            61.49   \n",
       "151078                  36.791                         1.7            61.49   \n",
       "151079                  36.791                         1.7            61.49   \n",
       "151080                  36.791                         1.7            61.49   \n",
       "151081                  36.791                         1.7            61.49   \n",
       "151082                  36.791                         1.7            61.49   \n",
       "151083                  36.791                         1.7            61.49   \n",
       "151084                  36.791                         1.7            61.49   \n",
       "\n",
       "        human_development_index  excess_mortality_cumulative_absolute  \\\n",
       "0                         0.511                                   NaN   \n",
       "1                         0.511                                   NaN   \n",
       "2                         0.511                                   NaN   \n",
       "3                         0.511                                   NaN   \n",
       "4                         0.511                                   NaN   \n",
       "5                         0.511                                   NaN   \n",
       "6                         0.511                                   NaN   \n",
       "7                         0.511                                   NaN   \n",
       "8                         0.511                                   NaN   \n",
       "9                         0.511                                   NaN   \n",
       "10                        0.511                                   NaN   \n",
       "11                        0.511                                   NaN   \n",
       "12                        0.511                                   NaN   \n",
       "13                        0.511                                   NaN   \n",
       "14                        0.511                                   NaN   \n",
       "...                         ...                                   ...   \n",
       "151070                    0.571                                   NaN   \n",
       "151071                    0.571                                   NaN   \n",
       "151072                    0.571                                   NaN   \n",
       "151073                    0.571                                   NaN   \n",
       "151074                    0.571                                   NaN   \n",
       "151075                    0.571                                   NaN   \n",
       "151076                    0.571                                   NaN   \n",
       "151077                    0.571                                   NaN   \n",
       "151078                    0.571                                   NaN   \n",
       "151079                    0.571                                   NaN   \n",
       "151080                    0.571                                   NaN   \n",
       "151081                    0.571                                   NaN   \n",
       "151082                    0.571                                   NaN   \n",
       "151083                    0.571                                   NaN   \n",
       "151084                    0.571                                   NaN   \n",
       "\n",
       "        excess_mortality_cumulative  excess_mortality  \\\n",
       "0                               NaN               NaN   \n",
       "1                               NaN               NaN   \n",
       "2                               NaN               NaN   \n",
       "3                               NaN               NaN   \n",
       "4                               NaN               NaN   \n",
       "5                               NaN               NaN   \n",
       "6                               NaN               NaN   \n",
       "7                               NaN               NaN   \n",
       "8                               NaN               NaN   \n",
       "9                               NaN               NaN   \n",
       "10                              NaN               NaN   \n",
       "11                              NaN               NaN   \n",
       "12                              NaN               NaN   \n",
       "13                              NaN               NaN   \n",
       "14                              NaN               NaN   \n",
       "...                             ...               ...   \n",
       "151070                          NaN               NaN   \n",
       "151071                          NaN               NaN   \n",
       "151072                          NaN               NaN   \n",
       "151073                          NaN               NaN   \n",
       "151074                          NaN               NaN   \n",
       "151075                          NaN               NaN   \n",
       "151076                          NaN               NaN   \n",
       "151077                          NaN               NaN   \n",
       "151078                          NaN               NaN   \n",
       "151079                          NaN               NaN   \n",
       "151080                          NaN               NaN   \n",
       "151081                          NaN               NaN   \n",
       "151082                          NaN               NaN   \n",
       "151083                          NaN               NaN   \n",
       "151084                          NaN               NaN   \n",
       "\n",
       "        excess_mortality_cumulative_per_million  \n",
       "0                                           NaN  \n",
       "1                                           NaN  \n",
       "2                                           NaN  \n",
       "3                                           NaN  \n",
       "4                                           NaN  \n",
       "5                                           NaN  \n",
       "6                                           NaN  \n",
       "7                                           NaN  \n",
       "8                                           NaN  \n",
       "9                                           NaN  \n",
       "10                                          NaN  \n",
       "11                                          NaN  \n",
       "12                                          NaN  \n",
       "13                                          NaN  \n",
       "14                                          NaN  \n",
       "...                                         ...  \n",
       "151070                                      NaN  \n",
       "151071                                      NaN  \n",
       "151072                                      NaN  \n",
       "151073                                      NaN  \n",
       "151074                                      NaN  \n",
       "151075                                      NaN  \n",
       "151076                                      NaN  \n",
       "151077                                      NaN  \n",
       "151078                                      NaN  \n",
       "151079                                      NaN  \n",
       "151080                                      NaN  \n",
       "151081                                      NaN  \n",
       "151082                                      NaN  \n",
       "151083                                      NaN  \n",
       "151084                                      NaN  \n",
       "\n",
       "[151085 rows x 67 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_covid"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "13b870df",
   "metadata": {},
   "source": [
    ">Students should check out the relationship of option `max_rows` with `min_rows` at your own"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c392d812",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2ae151fc",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "db8c24cb",
   "metadata": {},
   "source": [
    "### c. Changing Number of Characters to be Displayed in each Column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "801acd32",
   "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>star_rating</th>\n",
       "      <th>title</th>\n",
       "      <th>content_rating</th>\n",
       "      <th>genre</th>\n",
       "      <th>duration</th>\n",
       "      <th>actors_list</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>9.3</td>\n",
       "      <td>The Shawshank Redemption</td>\n",
       "      <td>R</td>\n",
       "      <td>Crime</td>\n",
       "      <td>142</td>\n",
       "      <td>[u'Tim Robbins', u'Morgan Freeman', u'Bob Gunt...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9.2</td>\n",
       "      <td>The Godfather</td>\n",
       "      <td>R</td>\n",
       "      <td>Crime</td>\n",
       "      <td>175</td>\n",
       "      <td>[u'Marlon Brando', u'Al Pacino', u'James Caan']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9.1</td>\n",
       "      <td>The Godfather: Part II</td>\n",
       "      <td>R</td>\n",
       "      <td>Crime</td>\n",
       "      <td>200</td>\n",
       "      <td>[u'Al Pacino', u'Robert De Niro', u'Robert Duv...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>9.0</td>\n",
       "      <td>The Dark Knight</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Action</td>\n",
       "      <td>152</td>\n",
       "      <td>[u'Christian Bale', u'Heath Ledger', u'Aaron E...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8.9</td>\n",
       "      <td>Pulp Fiction</td>\n",
       "      <td>R</td>\n",
       "      <td>Crime</td>\n",
       "      <td>154</td>\n",
       "      <td>[u'John Travolta', u'Uma Thurman', u'Samuel L....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>8.9</td>\n",
       "      <td>12 Angry Men</td>\n",
       "      <td>NOT RATED</td>\n",
       "      <td>Drama</td>\n",
       "      <td>96</td>\n",
       "      <td>[u'Henry Fonda', u'Lee J. Cobb', u'Martin Bals...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>8.9</td>\n",
       "      <td>The Good, the Bad and the Ugly</td>\n",
       "      <td>NOT RATED</td>\n",
       "      <td>Western</td>\n",
       "      <td>161</td>\n",
       "      <td>[u'Clint Eastwood', u'Eli Wallach', u'Lee Van ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8.9</td>\n",
       "      <td>The Lord of the Rings: The Return of the King</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Adventure</td>\n",
       "      <td>201</td>\n",
       "      <td>[u'Elijah Wood', u'Viggo Mortensen', u'Ian McK...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8.9</td>\n",
       "      <td>Schindler's List</td>\n",
       "      <td>R</td>\n",
       "      <td>Biography</td>\n",
       "      <td>195</td>\n",
       "      <td>[u'Liam Neeson', u'Ralph Fiennes', u'Ben Kings...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>8.9</td>\n",
       "      <td>Fight Club</td>\n",
       "      <td>R</td>\n",
       "      <td>Drama</td>\n",
       "      <td>139</td>\n",
       "      <td>[u'Brad Pitt', u'Edward Norton', u'Helena Bonh...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>8.8</td>\n",
       "      <td>The Lord of the Rings: The Fellowship of the Ring</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Adventure</td>\n",
       "      <td>178</td>\n",
       "      <td>[u'Elijah Wood', u'Ian McKellen', u'Orlando Bl...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>8.8</td>\n",
       "      <td>Inception</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Action</td>\n",
       "      <td>148</td>\n",
       "      <td>[u'Leonardo DiCaprio', u'Joseph Gordon-Levitt'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>8.8</td>\n",
       "      <td>Star Wars: Episode V - The Empire Strikes Back</td>\n",
       "      <td>PG</td>\n",
       "      <td>Action</td>\n",
       "      <td>124</td>\n",
       "      <td>[u'Mark Hamill', u'Harrison Ford', u'Carrie Fi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>8.8</td>\n",
       "      <td>Forrest Gump</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Drama</td>\n",
       "      <td>142</td>\n",
       "      <td>[u'Tom Hanks', u'Robin Wright', u'Gary Sinise']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>8.8</td>\n",
       "      <td>The Lord of the Rings: The Two Towers</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Adventure</td>\n",
       "      <td>179</td>\n",
       "      <td>[u'Elijah Wood', u'Ian McKellen', u'Viggo Mort...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>964</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Lincoln</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Biography</td>\n",
       "      <td>150</td>\n",
       "      <td>[u'Daniel Day-Lewis', u'Sally Field', u'David ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>965</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Limitless</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Mystery</td>\n",
       "      <td>105</td>\n",
       "      <td>[u'Bradley Cooper', u'Anna Friel', u'Abbie Cor...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>966</th>\n",
       "      <td>7.4</td>\n",
       "      <td>The Simpsons Movie</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Animation</td>\n",
       "      <td>87</td>\n",
       "      <td>[u'Dan Castellaneta', u'Julie Kavner', u'Nancy...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>967</th>\n",
       "      <td>7.4</td>\n",
       "      <td>The Rock</td>\n",
       "      <td>R</td>\n",
       "      <td>Action</td>\n",
       "      <td>136</td>\n",
       "      <td>[u'Sean Connery', u'Nicolas Cage', u'Ed Harris']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>968</th>\n",
       "      <td>7.4</td>\n",
       "      <td>The English Patient</td>\n",
       "      <td>R</td>\n",
       "      <td>Drama</td>\n",
       "      <td>162</td>\n",
       "      <td>[u'Ralph Fiennes', u'Juliette Binoche', u'Will...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>969</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Law Abiding Citizen</td>\n",
       "      <td>R</td>\n",
       "      <td>Crime</td>\n",
       "      <td>109</td>\n",
       "      <td>[u'Gerard Butler', u'Jamie Foxx', u'Leslie Bibb']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>970</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Wonder Boys</td>\n",
       "      <td>R</td>\n",
       "      <td>Drama</td>\n",
       "      <td>107</td>\n",
       "      <td>[u'Michael Douglas', u'Tobey Maguire', u'Franc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>971</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Death at a Funeral</td>\n",
       "      <td>R</td>\n",
       "      <td>Comedy</td>\n",
       "      <td>90</td>\n",
       "      <td>[u'Matthew Macfadyen', u'Peter Dinklage', u'Ew...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>972</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Blue Valentine</td>\n",
       "      <td>NC-17</td>\n",
       "      <td>Drama</td>\n",
       "      <td>112</td>\n",
       "      <td>[u'Ryan Gosling', u'Michelle Williams', u'John...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>973</th>\n",
       "      <td>7.4</td>\n",
       "      <td>The Cider House Rules</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Drama</td>\n",
       "      <td>126</td>\n",
       "      <td>[u'Tobey Maguire', u'Charlize Theron', u'Micha...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>974</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Tootsie</td>\n",
       "      <td>PG</td>\n",
       "      <td>Comedy</td>\n",
       "      <td>116</td>\n",
       "      <td>[u'Dustin Hoffman', u'Jessica Lange', u'Teri G...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>975</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Back to the Future Part III</td>\n",
       "      <td>PG</td>\n",
       "      <td>Adventure</td>\n",
       "      <td>118</td>\n",
       "      <td>[u'Michael J. Fox', u'Christopher Lloyd', u'Ma...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>976</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Master and Commander: The Far Side of the World</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Action</td>\n",
       "      <td>138</td>\n",
       "      <td>[u'Russell Crowe', u'Paul Bettany', u'Billy Bo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>977</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Poltergeist</td>\n",
       "      <td>PG</td>\n",
       "      <td>Horror</td>\n",
       "      <td>114</td>\n",
       "      <td>[u'JoBeth Williams', u\"Heather O'Rourke\", u'Cr...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>978</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Wall Street</td>\n",
       "      <td>R</td>\n",
       "      <td>Crime</td>\n",
       "      <td>126</td>\n",
       "      <td>[u'Charlie Sheen', u'Michael Douglas', u'Tamar...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>979 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     star_rating                                              title  \\\n",
       "0            9.3                           The Shawshank Redemption   \n",
       "1            9.2                                      The Godfather   \n",
       "2            9.1                             The Godfather: Part II   \n",
       "3            9.0                                    The Dark Knight   \n",
       "4            8.9                                       Pulp Fiction   \n",
       "5            8.9                                       12 Angry Men   \n",
       "6            8.9                     The Good, the Bad and the Ugly   \n",
       "7            8.9      The Lord of the Rings: The Return of the King   \n",
       "8            8.9                                   Schindler's List   \n",
       "9            8.9                                         Fight Club   \n",
       "10           8.8  The Lord of the Rings: The Fellowship of the Ring   \n",
       "11           8.8                                          Inception   \n",
       "12           8.8     Star Wars: Episode V - The Empire Strikes Back   \n",
       "13           8.8                                       Forrest Gump   \n",
       "14           8.8              The Lord of the Rings: The Two Towers   \n",
       "..           ...                                                ...   \n",
       "964          7.4                                            Lincoln   \n",
       "965          7.4                                          Limitless   \n",
       "966          7.4                                 The Simpsons Movie   \n",
       "967          7.4                                           The Rock   \n",
       "968          7.4                                The English Patient   \n",
       "969          7.4                                Law Abiding Citizen   \n",
       "970          7.4                                        Wonder Boys   \n",
       "971          7.4                                 Death at a Funeral   \n",
       "972          7.4                                     Blue Valentine   \n",
       "973          7.4                              The Cider House Rules   \n",
       "974          7.4                                            Tootsie   \n",
       "975          7.4                        Back to the Future Part III   \n",
       "976          7.4    Master and Commander: The Far Side of the World   \n",
       "977          7.4                                        Poltergeist   \n",
       "978          7.4                                        Wall Street   \n",
       "\n",
       "    content_rating      genre  duration  \\\n",
       "0                R      Crime       142   \n",
       "1                R      Crime       175   \n",
       "2                R      Crime       200   \n",
       "3            PG-13     Action       152   \n",
       "4                R      Crime       154   \n",
       "5        NOT RATED      Drama        96   \n",
       "6        NOT RATED    Western       161   \n",
       "7            PG-13  Adventure       201   \n",
       "8                R  Biography       195   \n",
       "9                R      Drama       139   \n",
       "10           PG-13  Adventure       178   \n",
       "11           PG-13     Action       148   \n",
       "12              PG     Action       124   \n",
       "13           PG-13      Drama       142   \n",
       "14           PG-13  Adventure       179   \n",
       "..             ...        ...       ...   \n",
       "964          PG-13  Biography       150   \n",
       "965          PG-13    Mystery       105   \n",
       "966          PG-13  Animation        87   \n",
       "967              R     Action       136   \n",
       "968              R      Drama       162   \n",
       "969              R      Crime       109   \n",
       "970              R      Drama       107   \n",
       "971              R     Comedy        90   \n",
       "972          NC-17      Drama       112   \n",
       "973          PG-13      Drama       126   \n",
       "974             PG     Comedy       116   \n",
       "975             PG  Adventure       118   \n",
       "976          PG-13     Action       138   \n",
       "977             PG     Horror       114   \n",
       "978              R      Crime       126   \n",
       "\n",
       "                                           actors_list  \n",
       "0    [u'Tim Robbins', u'Morgan Freeman', u'Bob Gunt...  \n",
       "1      [u'Marlon Brando', u'Al Pacino', u'James Caan']  \n",
       "2    [u'Al Pacino', u'Robert De Niro', u'Robert Duv...  \n",
       "3    [u'Christian Bale', u'Heath Ledger', u'Aaron E...  \n",
       "4    [u'John Travolta', u'Uma Thurman', u'Samuel L....  \n",
       "5    [u'Henry Fonda', u'Lee J. Cobb', u'Martin Bals...  \n",
       "6    [u'Clint Eastwood', u'Eli Wallach', u'Lee Van ...  \n",
       "7    [u'Elijah Wood', u'Viggo Mortensen', u'Ian McK...  \n",
       "8    [u'Liam Neeson', u'Ralph Fiennes', u'Ben Kings...  \n",
       "9    [u'Brad Pitt', u'Edward Norton', u'Helena Bonh...  \n",
       "10   [u'Elijah Wood', u'Ian McKellen', u'Orlando Bl...  \n",
       "11   [u'Leonardo DiCaprio', u'Joseph Gordon-Levitt'...  \n",
       "12   [u'Mark Hamill', u'Harrison Ford', u'Carrie Fi...  \n",
       "13     [u'Tom Hanks', u'Robin Wright', u'Gary Sinise']  \n",
       "14   [u'Elijah Wood', u'Ian McKellen', u'Viggo Mort...  \n",
       "..                                                 ...  \n",
       "964  [u'Daniel Day-Lewis', u'Sally Field', u'David ...  \n",
       "965  [u'Bradley Cooper', u'Anna Friel', u'Abbie Cor...  \n",
       "966  [u'Dan Castellaneta', u'Julie Kavner', u'Nancy...  \n",
       "967   [u'Sean Connery', u'Nicolas Cage', u'Ed Harris']  \n",
       "968  [u'Ralph Fiennes', u'Juliette Binoche', u'Will...  \n",
       "969  [u'Gerard Butler', u'Jamie Foxx', u'Leslie Bibb']  \n",
       "970  [u'Michael Douglas', u'Tobey Maguire', u'Franc...  \n",
       "971  [u'Matthew Macfadyen', u'Peter Dinklage', u'Ew...  \n",
       "972  [u'Ryan Gosling', u'Michelle Williams', u'John...  \n",
       "973  [u'Tobey Maguire', u'Charlize Theron', u'Micha...  \n",
       "974  [u'Dustin Hoffman', u'Jessica Lange', u'Teri G...  \n",
       "975  [u'Michael J. Fox', u'Christopher Lloyd', u'Ma...  \n",
       "976  [u'Russell Crowe', u'Paul Bettany', u'Billy Bo...  \n",
       "977  [u'JoBeth Williams', u\"Heather O'Rourke\", u'Cr...  \n",
       "978  [u'Charlie Sheen', u'Michael Douglas', u'Tamar...  \n",
       "\n",
       "[979 rows x 6 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_imdb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "91193f0d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.get_option('display.max_colwidth')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "6fbb9266",
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.set_option('display.max_colwidth', 200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "4fc52812",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "200"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.get_option('display.max_colwidth')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "9c39b278",
   "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>star_rating</th>\n",
       "      <th>title</th>\n",
       "      <th>content_rating</th>\n",
       "      <th>genre</th>\n",
       "      <th>duration</th>\n",
       "      <th>actors_list</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>9.3</td>\n",
       "      <td>The Shawshank Redemption</td>\n",
       "      <td>R</td>\n",
       "      <td>Crime</td>\n",
       "      <td>142</td>\n",
       "      <td>[u'Tim Robbins', u'Morgan Freeman', u'Bob Gunton']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9.2</td>\n",
       "      <td>The Godfather</td>\n",
       "      <td>R</td>\n",
       "      <td>Crime</td>\n",
       "      <td>175</td>\n",
       "      <td>[u'Marlon Brando', u'Al Pacino', u'James Caan']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9.1</td>\n",
       "      <td>The Godfather: Part II</td>\n",
       "      <td>R</td>\n",
       "      <td>Crime</td>\n",
       "      <td>200</td>\n",
       "      <td>[u'Al Pacino', u'Robert De Niro', u'Robert Duvall']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>9.0</td>\n",
       "      <td>The Dark Knight</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Action</td>\n",
       "      <td>152</td>\n",
       "      <td>[u'Christian Bale', u'Heath Ledger', u'Aaron Eckhart']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8.9</td>\n",
       "      <td>Pulp Fiction</td>\n",
       "      <td>R</td>\n",
       "      <td>Crime</td>\n",
       "      <td>154</td>\n",
       "      <td>[u'John Travolta', u'Uma Thurman', u'Samuel L. Jackson']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>8.9</td>\n",
       "      <td>12 Angry Men</td>\n",
       "      <td>NOT RATED</td>\n",
       "      <td>Drama</td>\n",
       "      <td>96</td>\n",
       "      <td>[u'Henry Fonda', u'Lee J. Cobb', u'Martin Balsam']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>8.9</td>\n",
       "      <td>The Good, the Bad and the Ugly</td>\n",
       "      <td>NOT RATED</td>\n",
       "      <td>Western</td>\n",
       "      <td>161</td>\n",
       "      <td>[u'Clint Eastwood', u'Eli Wallach', u'Lee Van Cleef']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8.9</td>\n",
       "      <td>The Lord of the Rings: The Return of the King</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Adventure</td>\n",
       "      <td>201</td>\n",
       "      <td>[u'Elijah Wood', u'Viggo Mortensen', u'Ian McKellen']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8.9</td>\n",
       "      <td>Schindler's List</td>\n",
       "      <td>R</td>\n",
       "      <td>Biography</td>\n",
       "      <td>195</td>\n",
       "      <td>[u'Liam Neeson', u'Ralph Fiennes', u'Ben Kingsley']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>8.9</td>\n",
       "      <td>Fight Club</td>\n",
       "      <td>R</td>\n",
       "      <td>Drama</td>\n",
       "      <td>139</td>\n",
       "      <td>[u'Brad Pitt', u'Edward Norton', u'Helena Bonham Carter']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>8.8</td>\n",
       "      <td>The Lord of the Rings: The Fellowship of the Ring</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Adventure</td>\n",
       "      <td>178</td>\n",
       "      <td>[u'Elijah Wood', u'Ian McKellen', u'Orlando Bloom']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>8.8</td>\n",
       "      <td>Inception</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Action</td>\n",
       "      <td>148</td>\n",
       "      <td>[u'Leonardo DiCaprio', u'Joseph Gordon-Levitt', u'Ellen Page']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>8.8</td>\n",
       "      <td>Star Wars: Episode V - The Empire Strikes Back</td>\n",
       "      <td>PG</td>\n",
       "      <td>Action</td>\n",
       "      <td>124</td>\n",
       "      <td>[u'Mark Hamill', u'Harrison Ford', u'Carrie Fisher']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>8.8</td>\n",
       "      <td>Forrest Gump</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Drama</td>\n",
       "      <td>142</td>\n",
       "      <td>[u'Tom Hanks', u'Robin Wright', u'Gary Sinise']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>8.8</td>\n",
       "      <td>The Lord of the Rings: The Two Towers</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Adventure</td>\n",
       "      <td>179</td>\n",
       "      <td>[u'Elijah Wood', u'Ian McKellen', u'Viggo Mortensen']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>964</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Lincoln</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Biography</td>\n",
       "      <td>150</td>\n",
       "      <td>[u'Daniel Day-Lewis', u'Sally Field', u'David Strathairn']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>965</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Limitless</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Mystery</td>\n",
       "      <td>105</td>\n",
       "      <td>[u'Bradley Cooper', u'Anna Friel', u'Abbie Cornish']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>966</th>\n",
       "      <td>7.4</td>\n",
       "      <td>The Simpsons Movie</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Animation</td>\n",
       "      <td>87</td>\n",
       "      <td>[u'Dan Castellaneta', u'Julie Kavner', u'Nancy Cartwright']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>967</th>\n",
       "      <td>7.4</td>\n",
       "      <td>The Rock</td>\n",
       "      <td>R</td>\n",
       "      <td>Action</td>\n",
       "      <td>136</td>\n",
       "      <td>[u'Sean Connery', u'Nicolas Cage', u'Ed Harris']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>968</th>\n",
       "      <td>7.4</td>\n",
       "      <td>The English Patient</td>\n",
       "      <td>R</td>\n",
       "      <td>Drama</td>\n",
       "      <td>162</td>\n",
       "      <td>[u'Ralph Fiennes', u'Juliette Binoche', u'Willem Dafoe']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>969</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Law Abiding Citizen</td>\n",
       "      <td>R</td>\n",
       "      <td>Crime</td>\n",
       "      <td>109</td>\n",
       "      <td>[u'Gerard Butler', u'Jamie Foxx', u'Leslie Bibb']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>970</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Wonder Boys</td>\n",
       "      <td>R</td>\n",
       "      <td>Drama</td>\n",
       "      <td>107</td>\n",
       "      <td>[u'Michael Douglas', u'Tobey Maguire', u'Frances McDormand']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>971</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Death at a Funeral</td>\n",
       "      <td>R</td>\n",
       "      <td>Comedy</td>\n",
       "      <td>90</td>\n",
       "      <td>[u'Matthew Macfadyen', u'Peter Dinklage', u'Ewen Bremner']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>972</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Blue Valentine</td>\n",
       "      <td>NC-17</td>\n",
       "      <td>Drama</td>\n",
       "      <td>112</td>\n",
       "      <td>[u'Ryan Gosling', u'Michelle Williams', u'John Doman']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>973</th>\n",
       "      <td>7.4</td>\n",
       "      <td>The Cider House Rules</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Drama</td>\n",
       "      <td>126</td>\n",
       "      <td>[u'Tobey Maguire', u'Charlize Theron', u'Michael Caine']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>974</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Tootsie</td>\n",
       "      <td>PG</td>\n",
       "      <td>Comedy</td>\n",
       "      <td>116</td>\n",
       "      <td>[u'Dustin Hoffman', u'Jessica Lange', u'Teri Garr']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>975</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Back to the Future Part III</td>\n",
       "      <td>PG</td>\n",
       "      <td>Adventure</td>\n",
       "      <td>118</td>\n",
       "      <td>[u'Michael J. Fox', u'Christopher Lloyd', u'Mary Steenburgen']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>976</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Master and Commander: The Far Side of the World</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Action</td>\n",
       "      <td>138</td>\n",
       "      <td>[u'Russell Crowe', u'Paul Bettany', u'Billy Boyd']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>977</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Poltergeist</td>\n",
       "      <td>PG</td>\n",
       "      <td>Horror</td>\n",
       "      <td>114</td>\n",
       "      <td>[u'JoBeth Williams', u\"Heather O'Rourke\", u'Craig T. Nelson']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>978</th>\n",
       "      <td>7.4</td>\n",
       "      <td>Wall Street</td>\n",
       "      <td>R</td>\n",
       "      <td>Crime</td>\n",
       "      <td>126</td>\n",
       "      <td>[u'Charlie Sheen', u'Michael Douglas', u'Tamara Tunie']</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>979 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     star_rating                                              title  \\\n",
       "0            9.3                           The Shawshank Redemption   \n",
       "1            9.2                                      The Godfather   \n",
       "2            9.1                             The Godfather: Part II   \n",
       "3            9.0                                    The Dark Knight   \n",
       "4            8.9                                       Pulp Fiction   \n",
       "5            8.9                                       12 Angry Men   \n",
       "6            8.9                     The Good, the Bad and the Ugly   \n",
       "7            8.9      The Lord of the Rings: The Return of the King   \n",
       "8            8.9                                   Schindler's List   \n",
       "9            8.9                                         Fight Club   \n",
       "10           8.8  The Lord of the Rings: The Fellowship of the Ring   \n",
       "11           8.8                                          Inception   \n",
       "12           8.8     Star Wars: Episode V - The Empire Strikes Back   \n",
       "13           8.8                                       Forrest Gump   \n",
       "14           8.8              The Lord of the Rings: The Two Towers   \n",
       "..           ...                                                ...   \n",
       "964          7.4                                            Lincoln   \n",
       "965          7.4                                          Limitless   \n",
       "966          7.4                                 The Simpsons Movie   \n",
       "967          7.4                                           The Rock   \n",
       "968          7.4                                The English Patient   \n",
       "969          7.4                                Law Abiding Citizen   \n",
       "970          7.4                                        Wonder Boys   \n",
       "971          7.4                                 Death at a Funeral   \n",
       "972          7.4                                     Blue Valentine   \n",
       "973          7.4                              The Cider House Rules   \n",
       "974          7.4                                            Tootsie   \n",
       "975          7.4                        Back to the Future Part III   \n",
       "976          7.4    Master and Commander: The Far Side of the World   \n",
       "977          7.4                                        Poltergeist   \n",
       "978          7.4                                        Wall Street   \n",
       "\n",
       "    content_rating      genre  duration  \\\n",
       "0                R      Crime       142   \n",
       "1                R      Crime       175   \n",
       "2                R      Crime       200   \n",
       "3            PG-13     Action       152   \n",
       "4                R      Crime       154   \n",
       "5        NOT RATED      Drama        96   \n",
       "6        NOT RATED    Western       161   \n",
       "7            PG-13  Adventure       201   \n",
       "8                R  Biography       195   \n",
       "9                R      Drama       139   \n",
       "10           PG-13  Adventure       178   \n",
       "11           PG-13     Action       148   \n",
       "12              PG     Action       124   \n",
       "13           PG-13      Drama       142   \n",
       "14           PG-13  Adventure       179   \n",
       "..             ...        ...       ...   \n",
       "964          PG-13  Biography       150   \n",
       "965          PG-13    Mystery       105   \n",
       "966          PG-13  Animation        87   \n",
       "967              R     Action       136   \n",
       "968              R      Drama       162   \n",
       "969              R      Crime       109   \n",
       "970              R      Drama       107   \n",
       "971              R     Comedy        90   \n",
       "972          NC-17      Drama       112   \n",
       "973          PG-13      Drama       126   \n",
       "974             PG     Comedy       116   \n",
       "975             PG  Adventure       118   \n",
       "976          PG-13     Action       138   \n",
       "977             PG     Horror       114   \n",
       "978              R      Crime       126   \n",
       "\n",
       "                                                        actors_list  \n",
       "0                [u'Tim Robbins', u'Morgan Freeman', u'Bob Gunton']  \n",
       "1                   [u'Marlon Brando', u'Al Pacino', u'James Caan']  \n",
       "2               [u'Al Pacino', u'Robert De Niro', u'Robert Duvall']  \n",
       "3            [u'Christian Bale', u'Heath Ledger', u'Aaron Eckhart']  \n",
       "4          [u'John Travolta', u'Uma Thurman', u'Samuel L. Jackson']  \n",
       "5                [u'Henry Fonda', u'Lee J. Cobb', u'Martin Balsam']  \n",
       "6             [u'Clint Eastwood', u'Eli Wallach', u'Lee Van Cleef']  \n",
       "7             [u'Elijah Wood', u'Viggo Mortensen', u'Ian McKellen']  \n",
       "8               [u'Liam Neeson', u'Ralph Fiennes', u'Ben Kingsley']  \n",
       "9         [u'Brad Pitt', u'Edward Norton', u'Helena Bonham Carter']  \n",
       "10              [u'Elijah Wood', u'Ian McKellen', u'Orlando Bloom']  \n",
       "11   [u'Leonardo DiCaprio', u'Joseph Gordon-Levitt', u'Ellen Page']  \n",
       "12             [u'Mark Hamill', u'Harrison Ford', u'Carrie Fisher']  \n",
       "13                  [u'Tom Hanks', u'Robin Wright', u'Gary Sinise']  \n",
       "14            [u'Elijah Wood', u'Ian McKellen', u'Viggo Mortensen']  \n",
       "..                                                              ...  \n",
       "964      [u'Daniel Day-Lewis', u'Sally Field', u'David Strathairn']  \n",
       "965            [u'Bradley Cooper', u'Anna Friel', u'Abbie Cornish']  \n",
       "966     [u'Dan Castellaneta', u'Julie Kavner', u'Nancy Cartwright']  \n",
       "967                [u'Sean Connery', u'Nicolas Cage', u'Ed Harris']  \n",
       "968        [u'Ralph Fiennes', u'Juliette Binoche', u'Willem Dafoe']  \n",
       "969               [u'Gerard Butler', u'Jamie Foxx', u'Leslie Bibb']  \n",
       "970    [u'Michael Douglas', u'Tobey Maguire', u'Frances McDormand']  \n",
       "971      [u'Matthew Macfadyen', u'Peter Dinklage', u'Ewen Bremner']  \n",
       "972          [u'Ryan Gosling', u'Michelle Williams', u'John Doman']  \n",
       "973        [u'Tobey Maguire', u'Charlize Theron', u'Michael Caine']  \n",
       "974             [u'Dustin Hoffman', u'Jessica Lange', u'Teri Garr']  \n",
       "975  [u'Michael J. Fox', u'Christopher Lloyd', u'Mary Steenburgen']  \n",
       "976              [u'Russell Crowe', u'Paul Bettany', u'Billy Boyd']  \n",
       "977   [u'JoBeth Williams', u\"Heather O'Rourke\", u'Craig T. Nelson']  \n",
       "978         [u'Charlie Sheen', u'Michael Douglas', u'Tamara Tunie']  \n",
       "\n",
       "[979 rows x 6 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_imdb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "89f42cd2",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "ffbcf507",
   "metadata": {},
   "source": [
    "### c. Setting the options back to default"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "3dfc219a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "As the xlwt package is no longer maintained, the xlwt engine will be removed in a future version of pandas. This is the only engine in pandas that supports writing in the xls format. Install openpyxl and write to an xlsx file instead.\n",
      "\n",
      ": boolean\n",
      "    use_inf_as_null had been deprecated and will be removed in a future\n",
      "    version. Use `use_inf_as_na` instead.\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/pandas/_config/config.py:630: FutureWarning: As the xlwt package is no longer maintained, the xlwt engine will be removed in a future version of pandas. This is the only engine in pandas that supports writing in the xls format. Install openpyxl and write to an xlsx file instead.\n",
      "  warnings.warn(d.msg, FutureWarning)\n",
      "/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/pandas/_config/config.py:630: FutureWarning: \n",
      ": boolean\n",
      "    use_inf_as_null had been deprecated and will be removed in a future\n",
      "    version. Use `use_inf_as_na` instead.\n",
      "\n",
      "  warnings.warn(d.msg, FutureWarning)\n"
     ]
    }
   ],
   "source": [
    "pd.reset_option('all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "97d3d773",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "4fc9cde6",
   "metadata": {},
   "source": [
    "### d. Changing Style by applying CSS to Pandas Dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "9cd2a4e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_58214_ th {\n",
       "  background: #7CAE00;\n",
       "  color: white;\n",
       "  font-family: verdana;\n",
       "}\n",
       "#T_58214_ td {\n",
       "  font-family: verdana;\n",
       "}\n",
       "#T_58214_ tr:nth-of-type(odd) {\n",
       "  background: #DCDCDC;\n",
       "}\n",
       "#T_58214_ tr:nth-of-type(even) {\n",
       "  background: white;\n",
       "}\n",
       "#T_58214_ tr:hover {\n",
       "  background: pink;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_58214_\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"col_heading level0 col0\" >pclass</th>\n",
       "      <th class=\"col_heading level0 col1\" >survived</th>\n",
       "      <th class=\"col_heading level0 col2\" >name</th>\n",
       "      <th class=\"col_heading level0 col3\" >sex</th>\n",
       "      <th class=\"col_heading level0 col4\" >age</th>\n",
       "      <th class=\"col_heading level0 col5\" >sibsp</th>\n",
       "      <th class=\"col_heading level0 col6\" >parch</th>\n",
       "      <th class=\"col_heading level0 col7\" >ticket</th>\n",
       "      <th class=\"col_heading level0 col8\" >fare</th>\n",
       "      <th class=\"col_heading level0 col9\" >cabin</th>\n",
       "      <th class=\"col_heading level0 col10\" >embarked</th>\n",
       "      <th class=\"col_heading level0 col11\" >boat</th>\n",
       "      <th class=\"col_heading level0 col12\" >body</th>\n",
       "      <th class=\"col_heading level0 col13\" >home.dest</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td id=\"T_58214_row0_col0\" class=\"data row0 col0\" >1.000000</td>\n",
       "      <td id=\"T_58214_row0_col1\" class=\"data row0 col1\" >1.000000</td>\n",
       "      <td id=\"T_58214_row0_col2\" class=\"data row0 col2\" >Allen, Miss. Elisabeth Walton</td>\n",
       "      <td id=\"T_58214_row0_col3\" class=\"data row0 col3\" >female</td>\n",
       "      <td id=\"T_58214_row0_col4\" class=\"data row0 col4\" >29.000000</td>\n",
       "      <td id=\"T_58214_row0_col5\" class=\"data row0 col5\" >0.000000</td>\n",
       "      <td id=\"T_58214_row0_col6\" class=\"data row0 col6\" >0.000000</td>\n",
       "      <td id=\"T_58214_row0_col7\" class=\"data row0 col7\" >24160</td>\n",
       "      <td id=\"T_58214_row0_col8\" class=\"data row0 col8\" >211.337500</td>\n",
       "      <td id=\"T_58214_row0_col9\" class=\"data row0 col9\" >B5</td>\n",
       "      <td id=\"T_58214_row0_col10\" class=\"data row0 col10\" >S</td>\n",
       "      <td id=\"T_58214_row0_col11\" class=\"data row0 col11\" >2</td>\n",
       "      <td id=\"T_58214_row0_col12\" class=\"data row0 col12\" >nan</td>\n",
       "      <td id=\"T_58214_row0_col13\" class=\"data row0 col13\" >St Louis, MO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td id=\"T_58214_row1_col0\" class=\"data row1 col0\" >1.000000</td>\n",
       "      <td id=\"T_58214_row1_col1\" class=\"data row1 col1\" >1.000000</td>\n",
       "      <td id=\"T_58214_row1_col2\" class=\"data row1 col2\" >Allison, Master. Hudson Trevor</td>\n",
       "      <td id=\"T_58214_row1_col3\" class=\"data row1 col3\" >male</td>\n",
       "      <td id=\"T_58214_row1_col4\" class=\"data row1 col4\" >0.916700</td>\n",
       "      <td id=\"T_58214_row1_col5\" class=\"data row1 col5\" >1.000000</td>\n",
       "      <td id=\"T_58214_row1_col6\" class=\"data row1 col6\" >2.000000</td>\n",
       "      <td id=\"T_58214_row1_col7\" class=\"data row1 col7\" >113781</td>\n",
       "      <td id=\"T_58214_row1_col8\" class=\"data row1 col8\" >151.550000</td>\n",
       "      <td id=\"T_58214_row1_col9\" class=\"data row1 col9\" >C22 C26</td>\n",
       "      <td id=\"T_58214_row1_col10\" class=\"data row1 col10\" >S</td>\n",
       "      <td id=\"T_58214_row1_col11\" class=\"data row1 col11\" >11</td>\n",
       "      <td id=\"T_58214_row1_col12\" class=\"data row1 col12\" >nan</td>\n",
       "      <td id=\"T_58214_row1_col13\" class=\"data row1 col13\" >Montreal, PQ / Chesterville, ON</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td id=\"T_58214_row2_col0\" class=\"data row2 col0\" >1.000000</td>\n",
       "      <td id=\"T_58214_row2_col1\" class=\"data row2 col1\" >0.000000</td>\n",
       "      <td id=\"T_58214_row2_col2\" class=\"data row2 col2\" >Allison, Miss. Helen Loraine</td>\n",
       "      <td id=\"T_58214_row2_col3\" class=\"data row2 col3\" >female</td>\n",
       "      <td id=\"T_58214_row2_col4\" class=\"data row2 col4\" >2.000000</td>\n",
       "      <td id=\"T_58214_row2_col5\" class=\"data row2 col5\" >1.000000</td>\n",
       "      <td id=\"T_58214_row2_col6\" class=\"data row2 col6\" >2.000000</td>\n",
       "      <td id=\"T_58214_row2_col7\" class=\"data row2 col7\" >113781</td>\n",
       "      <td id=\"T_58214_row2_col8\" class=\"data row2 col8\" >151.550000</td>\n",
       "      <td id=\"T_58214_row2_col9\" class=\"data row2 col9\" >C22 C26</td>\n",
       "      <td id=\"T_58214_row2_col10\" class=\"data row2 col10\" >S</td>\n",
       "      <td id=\"T_58214_row2_col11\" class=\"data row2 col11\" >nan</td>\n",
       "      <td id=\"T_58214_row2_col12\" class=\"data row2 col12\" >nan</td>\n",
       "      <td id=\"T_58214_row2_col13\" class=\"data row2 col13\" >Montreal, PQ / Chesterville, ON</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td id=\"T_58214_row3_col0\" class=\"data row3 col0\" >1.000000</td>\n",
       "      <td id=\"T_58214_row3_col1\" class=\"data row3 col1\" >0.000000</td>\n",
       "      <td id=\"T_58214_row3_col2\" class=\"data row3 col2\" >Allison, Mr. Hudson Joshua Creighton</td>\n",
       "      <td id=\"T_58214_row3_col3\" class=\"data row3 col3\" >male</td>\n",
       "      <td id=\"T_58214_row3_col4\" class=\"data row3 col4\" >30.000000</td>\n",
       "      <td id=\"T_58214_row3_col5\" class=\"data row3 col5\" >1.000000</td>\n",
       "      <td id=\"T_58214_row3_col6\" class=\"data row3 col6\" >2.000000</td>\n",
       "      <td id=\"T_58214_row3_col7\" class=\"data row3 col7\" >113781</td>\n",
       "      <td id=\"T_58214_row3_col8\" class=\"data row3 col8\" >151.550000</td>\n",
       "      <td id=\"T_58214_row3_col9\" class=\"data row3 col9\" >C22 C26</td>\n",
       "      <td id=\"T_58214_row3_col10\" class=\"data row3 col10\" >S</td>\n",
       "      <td id=\"T_58214_row3_col11\" class=\"data row3 col11\" >nan</td>\n",
       "      <td id=\"T_58214_row3_col12\" class=\"data row3 col12\" >135.000000</td>\n",
       "      <td id=\"T_58214_row3_col13\" class=\"data row3 col13\" >Montreal, PQ / Chesterville, ON</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td id=\"T_58214_row4_col0\" class=\"data row4 col0\" >1.000000</td>\n",
       "      <td id=\"T_58214_row4_col1\" class=\"data row4 col1\" >0.000000</td>\n",
       "      <td id=\"T_58214_row4_col2\" class=\"data row4 col2\" >Allison, Mrs. Hudson J C (Bessie Waldo Daniels)</td>\n",
       "      <td id=\"T_58214_row4_col3\" class=\"data row4 col3\" >female</td>\n",
       "      <td id=\"T_58214_row4_col4\" class=\"data row4 col4\" >25.000000</td>\n",
       "      <td id=\"T_58214_row4_col5\" class=\"data row4 col5\" >1.000000</td>\n",
       "      <td id=\"T_58214_row4_col6\" class=\"data row4 col6\" >2.000000</td>\n",
       "      <td id=\"T_58214_row4_col7\" class=\"data row4 col7\" >113781</td>\n",
       "      <td id=\"T_58214_row4_col8\" class=\"data row4 col8\" >151.550000</td>\n",
       "      <td id=\"T_58214_row4_col9\" class=\"data row4 col9\" >C22 C26</td>\n",
       "      <td id=\"T_58214_row4_col10\" class=\"data row4 col10\" >S</td>\n",
       "      <td id=\"T_58214_row4_col11\" class=\"data row4 col11\" >nan</td>\n",
       "      <td id=\"T_58214_row4_col12\" class=\"data row4 col12\" >nan</td>\n",
       "      <td id=\"T_58214_row4_col13\" class=\"data row4 col13\" >Montreal, PQ / Chesterville, ON</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td id=\"T_58214_row5_col0\" class=\"data row5 col0\" >1.000000</td>\n",
       "      <td id=\"T_58214_row5_col1\" class=\"data row5 col1\" >1.000000</td>\n",
       "      <td id=\"T_58214_row5_col2\" class=\"data row5 col2\" >Anderson, Mr. Harry</td>\n",
       "      <td id=\"T_58214_row5_col3\" class=\"data row5 col3\" >male</td>\n",
       "      <td id=\"T_58214_row5_col4\" class=\"data row5 col4\" >48.000000</td>\n",
       "      <td id=\"T_58214_row5_col5\" class=\"data row5 col5\" >0.000000</td>\n",
       "      <td id=\"T_58214_row5_col6\" class=\"data row5 col6\" >0.000000</td>\n",
       "      <td id=\"T_58214_row5_col7\" class=\"data row5 col7\" >19952</td>\n",
       "      <td id=\"T_58214_row5_col8\" class=\"data row5 col8\" >26.550000</td>\n",
       "      <td id=\"T_58214_row5_col9\" class=\"data row5 col9\" >E12</td>\n",
       "      <td id=\"T_58214_row5_col10\" class=\"data row5 col10\" >S</td>\n",
       "      <td id=\"T_58214_row5_col11\" class=\"data row5 col11\" >3</td>\n",
       "      <td id=\"T_58214_row5_col12\" class=\"data row5 col12\" >nan</td>\n",
       "      <td id=\"T_58214_row5_col13\" class=\"data row5 col13\" >New York, NY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td id=\"T_58214_row6_col0\" class=\"data row6 col0\" >1.000000</td>\n",
       "      <td id=\"T_58214_row6_col1\" class=\"data row6 col1\" >1.000000</td>\n",
       "      <td id=\"T_58214_row6_col2\" class=\"data row6 col2\" >Andrews, Miss. Kornelia Theodosia</td>\n",
       "      <td id=\"T_58214_row6_col3\" class=\"data row6 col3\" >female</td>\n",
       "      <td id=\"T_58214_row6_col4\" class=\"data row6 col4\" >63.000000</td>\n",
       "      <td id=\"T_58214_row6_col5\" class=\"data row6 col5\" >1.000000</td>\n",
       "      <td id=\"T_58214_row6_col6\" class=\"data row6 col6\" >0.000000</td>\n",
       "      <td id=\"T_58214_row6_col7\" class=\"data row6 col7\" >13502</td>\n",
       "      <td id=\"T_58214_row6_col8\" class=\"data row6 col8\" >77.958300</td>\n",
       "      <td id=\"T_58214_row6_col9\" class=\"data row6 col9\" >D7</td>\n",
       "      <td id=\"T_58214_row6_col10\" class=\"data row6 col10\" >S</td>\n",
       "      <td id=\"T_58214_row6_col11\" class=\"data row6 col11\" >10</td>\n",
       "      <td id=\"T_58214_row6_col12\" class=\"data row6 col12\" >nan</td>\n",
       "      <td id=\"T_58214_row6_col13\" class=\"data row6 col13\" >Hudson, NY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td id=\"T_58214_row7_col0\" class=\"data row7 col0\" >1.000000</td>\n",
       "      <td id=\"T_58214_row7_col1\" class=\"data row7 col1\" >0.000000</td>\n",
       "      <td id=\"T_58214_row7_col2\" class=\"data row7 col2\" >Andrews, Mr. Thomas Jr</td>\n",
       "      <td id=\"T_58214_row7_col3\" class=\"data row7 col3\" >male</td>\n",
       "      <td id=\"T_58214_row7_col4\" class=\"data row7 col4\" >39.000000</td>\n",
       "      <td id=\"T_58214_row7_col5\" class=\"data row7 col5\" >0.000000</td>\n",
       "      <td id=\"T_58214_row7_col6\" class=\"data row7 col6\" >0.000000</td>\n",
       "      <td id=\"T_58214_row7_col7\" class=\"data row7 col7\" >112050</td>\n",
       "      <td id=\"T_58214_row7_col8\" class=\"data row7 col8\" >0.000000</td>\n",
       "      <td id=\"T_58214_row7_col9\" class=\"data row7 col9\" >A36</td>\n",
       "      <td id=\"T_58214_row7_col10\" class=\"data row7 col10\" >S</td>\n",
       "      <td id=\"T_58214_row7_col11\" class=\"data row7 col11\" >nan</td>\n",
       "      <td id=\"T_58214_row7_col12\" class=\"data row7 col12\" >nan</td>\n",
       "      <td id=\"T_58214_row7_col13\" class=\"data row7 col13\" >Belfast, NI</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td id=\"T_58214_row8_col0\" class=\"data row8 col0\" >1.000000</td>\n",
       "      <td id=\"T_58214_row8_col1\" class=\"data row8 col1\" >1.000000</td>\n",
       "      <td id=\"T_58214_row8_col2\" class=\"data row8 col2\" >Appleton, Mrs. Edward Dale (Charlotte Lamson)</td>\n",
       "      <td id=\"T_58214_row8_col3\" class=\"data row8 col3\" >female</td>\n",
       "      <td id=\"T_58214_row8_col4\" class=\"data row8 col4\" >53.000000</td>\n",
       "      <td id=\"T_58214_row8_col5\" class=\"data row8 col5\" >2.000000</td>\n",
       "      <td id=\"T_58214_row8_col6\" class=\"data row8 col6\" >0.000000</td>\n",
       "      <td id=\"T_58214_row8_col7\" class=\"data row8 col7\" >11769</td>\n",
       "      <td id=\"T_58214_row8_col8\" class=\"data row8 col8\" >51.479200</td>\n",
       "      <td id=\"T_58214_row8_col9\" class=\"data row8 col9\" >C101</td>\n",
       "      <td id=\"T_58214_row8_col10\" class=\"data row8 col10\" >S</td>\n",
       "      <td id=\"T_58214_row8_col11\" class=\"data row8 col11\" >D</td>\n",
       "      <td id=\"T_58214_row8_col12\" class=\"data row8 col12\" >nan</td>\n",
       "      <td id=\"T_58214_row8_col13\" class=\"data row8 col13\" >Bayside, Queens, NY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td id=\"T_58214_row9_col0\" class=\"data row9 col0\" >1.000000</td>\n",
       "      <td id=\"T_58214_row9_col1\" class=\"data row9 col1\" >0.000000</td>\n",
       "      <td id=\"T_58214_row9_col2\" class=\"data row9 col2\" >Artagaveytia, Mr. Ramon</td>\n",
       "      <td id=\"T_58214_row9_col3\" class=\"data row9 col3\" >male</td>\n",
       "      <td id=\"T_58214_row9_col4\" class=\"data row9 col4\" >71.000000</td>\n",
       "      <td id=\"T_58214_row9_col5\" class=\"data row9 col5\" >0.000000</td>\n",
       "      <td id=\"T_58214_row9_col6\" class=\"data row9 col6\" >0.000000</td>\n",
       "      <td id=\"T_58214_row9_col7\" class=\"data row9 col7\" >PC 17609</td>\n",
       "      <td id=\"T_58214_row9_col8\" class=\"data row9 col8\" >49.504200</td>\n",
       "      <td id=\"T_58214_row9_col9\" class=\"data row9 col9\" >nan</td>\n",
       "      <td id=\"T_58214_row9_col10\" class=\"data row9 col10\" >C</td>\n",
       "      <td id=\"T_58214_row9_col11\" class=\"data row9 col11\" >nan</td>\n",
       "      <td id=\"T_58214_row9_col12\" class=\"data row9 col12\" >22.000000</td>\n",
       "      <td id=\"T_58214_row9_col13\" class=\"data row9 col13\" >Montevideo, Uruguay</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fb7afbb8bb0>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_titanic.head(10).style.set_table_styles(\n",
    "[{'selector': 'th',\n",
    "  'props': [('background', '#7CAE00'), \n",
    "            ('color', 'white'),\n",
    "            ('font-family', 'verdana')]},\n",
    " \n",
    " {'selector': 'td',\n",
    "  'props': [('font-family', 'verdana')]},\n",
    "\n",
    " {'selector': 'tr:nth-of-type(odd)',\n",
    "  'props': [('background', '#DCDCDC')]}, \n",
    " \n",
    " {'selector': 'tr:nth-of-type(even)',\n",
    "  'props': [('background', 'white')]},\n",
    " \n",
    " {'selector': 'tr:hover',\n",
    "  'props': [('background', 'pink')]},\n",
    " \n",
    "]\n",
    ").hide_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "40e34e74",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "61ad0d05",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e7d464d4",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}