[2]Dataframe.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PANDAS DATAFRAME"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Creating DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>iq</th>\n",
       "      <th>marks</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>90</td>\n",
       "      <td>70</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>120</td>\n",
       "      <td>100</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>80</td>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    iq  marks  package\n",
       "0  100     80       10\n",
       "1   90     70        7\n",
       "2  120    100       14\n",
       "3   80     50        0"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#using lists\n",
    "student_data = [\n",
    "    [100,80,10],\n",
    "    [90,70,7],\n",
    "    [120,100,14],\n",
    "    [80,50,0]\n",
    "]\n",
    "student = pd.DataFrame(student_data,columns=['iq','marks','package'])\n",
    "student"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>marks</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>90</td>\n",
       "      <td>70</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>120</td>\n",
       "      <td>100</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>80</td>\n",
       "      <td>50</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    id  marks  package\n",
       "0  100     80       10\n",
       "1   90     70        7\n",
       "2  120    100       14\n",
       "3   80     50        2"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#using dict\n",
    "student_dict={\n",
    "    'id':[100,90,120,80],\n",
    "    'marks':[80,70,100,50],\n",
    "    'package':[10,7,14,2]\n",
    "}\n",
    "pd.DataFrame(student_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>title_x</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>poster_path</th>\n",
       "      <th>wiki_link</th>\n",
       "      <th>title_y</th>\n",
       "      <th>original_title</th>\n",
       "      <th>is_adult</th>\n",
       "      <th>year_of_release</th>\n",
       "      <th>runtime</th>\n",
       "      <th>genres</th>\n",
       "      <th>imdb_rating</th>\n",
       "      <th>imdb_votes</th>\n",
       "      <th>story</th>\n",
       "      <th>summary</th>\n",
       "      <th>tagline</th>\n",
       "      <th>actors</th>\n",
       "      <th>wins_nominations</th>\n",
       "      <th>release_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>tt8291224</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Uri:_The_Surgica...</td>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>138</td>\n",
       "      <td>Action|Drama|War</td>\n",
       "      <td>8.4</td>\n",
       "      <td>35112</td>\n",
       "      <td>Divided over five chapters  the film chronicle...</td>\n",
       "      <td>Indian army special forces execute a covert op...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...</td>\n",
       "      <td>4 wins</td>\n",
       "      <td>11 January 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>tt9472208</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Battalion_609</td>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>131</td>\n",
       "      <td>War</td>\n",
       "      <td>4.1</td>\n",
       "      <td>73</td>\n",
       "      <td>The story revolves around a cricket match betw...</td>\n",
       "      <td>The story of Battalion 609 revolves around a c...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vicky Ahuja|Shoaib Ibrahim|Shrikant Kamat|Elen...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11 January 2019 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>The Accidental Prime Minister (film)</td>\n",
       "      <td>tt6986710</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/The_Accidental_P...</td>\n",
       "      <td>The Accidental Prime Minister</td>\n",
       "      <td>The Accidental Prime Minister</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>112</td>\n",
       "      <td>Biography|Drama</td>\n",
       "      <td>6.1</td>\n",
       "      <td>5549</td>\n",
       "      <td>Based on the memoir by Indian policy analyst S...</td>\n",
       "      <td>Explores Manmohan Singh's tenure as the Prime ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Anupam Kher|Akshaye Khanna|Aahana Kumra|Atul S...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11 January 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Why Cheat India</td>\n",
       "      <td>tt8108208</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Why_Cheat_India</td>\n",
       "      <td>Why Cheat India</td>\n",
       "      <td>Why Cheat India</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>121</td>\n",
       "      <td>Crime|Drama</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1891</td>\n",
       "      <td>The movie focuses on existing malpractices in ...</td>\n",
       "      <td>The movie focuses on existing malpractices in ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Emraan Hashmi|Shreya Dhanwanthary|Snighdadeep ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18 January 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Evening Shadows</td>\n",
       "      <td>tt6028796</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Evening_Shadows</td>\n",
       "      <td>Evening Shadows</td>\n",
       "      <td>Evening Shadows</td>\n",
       "      <td>0</td>\n",
       "      <td>2018</td>\n",
       "      <td>102</td>\n",
       "      <td>Drama</td>\n",
       "      <td>7.3</td>\n",
       "      <td>280</td>\n",
       "      <td>While gay rights and marriage equality has bee...</td>\n",
       "      <td>Under the 'Evening Shadows'  truth often plays...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mona Ambegaonkar|Ananth Narayan Mahadevan|Deva...</td>\n",
       "      <td>17 wins &amp; 1 nomination</td>\n",
       "      <td>11 January 2019 (India)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                title_x    imdb_id  \\\n",
       "0              Uri: The Surgical Strike  tt8291224   \n",
       "1                         Battalion 609  tt9472208   \n",
       "2  The Accidental Prime Minister (film)  tt6986710   \n",
       "3                       Why Cheat India  tt8108208   \n",
       "4                       Evening Shadows  tt6028796   \n",
       "\n",
       "                                         poster_path  \\\n",
       "0  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "1                                                NaN   \n",
       "2  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "3  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "4                                                NaN   \n",
       "\n",
       "                                           wiki_link  \\\n",
       "0  https://en.wikipedia.org/wiki/Uri:_The_Surgica...   \n",
       "1        https://en.wikipedia.org/wiki/Battalion_609   \n",
       "2  https://en.wikipedia.org/wiki/The_Accidental_P...   \n",
       "3      https://en.wikipedia.org/wiki/Why_Cheat_India   \n",
       "4      https://en.wikipedia.org/wiki/Evening_Shadows   \n",
       "\n",
       "                         title_y                 original_title  is_adult  \\\n",
       "0       Uri: The Surgical Strike       Uri: The Surgical Strike         0   \n",
       "1                  Battalion 609                  Battalion 609         0   \n",
       "2  The Accidental Prime Minister  The Accidental Prime Minister         0   \n",
       "3                Why Cheat India                Why Cheat India         0   \n",
       "4                Evening Shadows                Evening Shadows         0   \n",
       "\n",
       "   year_of_release runtime            genres  imdb_rating  imdb_votes  \\\n",
       "0             2019     138  Action|Drama|War          8.4       35112   \n",
       "1             2019     131               War          4.1          73   \n",
       "2             2019     112   Biography|Drama          6.1        5549   \n",
       "3             2019     121       Crime|Drama          6.0        1891   \n",
       "4             2018     102             Drama          7.3         280   \n",
       "\n",
       "                                               story  \\\n",
       "0  Divided over five chapters  the film chronicle...   \n",
       "1  The story revolves around a cricket match betw...   \n",
       "2  Based on the memoir by Indian policy analyst S...   \n",
       "3  The movie focuses on existing malpractices in ...   \n",
       "4  While gay rights and marriage equality has bee...   \n",
       "\n",
       "                                             summary tagline  \\\n",
       "0  Indian army special forces execute a covert op...     NaN   \n",
       "1  The story of Battalion 609 revolves around a c...     NaN   \n",
       "2  Explores Manmohan Singh's tenure as the Prime ...     NaN   \n",
       "3  The movie focuses on existing malpractices in ...     NaN   \n",
       "4  Under the 'Evening Shadows'  truth often plays...     NaN   \n",
       "\n",
       "                                              actors        wins_nominations  \\\n",
       "0  Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...                  4 wins   \n",
       "1  Vicky Ahuja|Shoaib Ibrahim|Shrikant Kamat|Elen...                     NaN   \n",
       "2  Anupam Kher|Akshaye Khanna|Aahana Kumra|Atul S...                     NaN   \n",
       "3  Emraan Hashmi|Shreya Dhanwanthary|Snighdadeep ...                     NaN   \n",
       "4  Mona Ambegaonkar|Ananth Narayan Mahadevan|Deva...  17 wins & 1 nomination   \n",
       "\n",
       "              release_date  \n",
       "0    11 January 2019 (USA)  \n",
       "1  11 January 2019 (India)  \n",
       "2    11 January 2019 (USA)  \n",
       "3    18 January 2019 (USA)  \n",
       "4  11 January 2019 (India)  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#using read_csv\n",
    "movies = pd.read_csv('movies.csv')\n",
    "movies.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>City</th>\n",
       "      <th>Date</th>\n",
       "      <th>Season</th>\n",
       "      <th>MatchNumber</th>\n",
       "      <th>Team1</th>\n",
       "      <th>Team2</th>\n",
       "      <th>Venue</th>\n",
       "      <th>TossWinner</th>\n",
       "      <th>TossDecision</th>\n",
       "      <th>SuperOver</th>\n",
       "      <th>WinningTeam</th>\n",
       "      <th>WonBy</th>\n",
       "      <th>Margin</th>\n",
       "      <th>method</th>\n",
       "      <th>Player_of_Match</th>\n",
       "      <th>Team1Players</th>\n",
       "      <th>Team2Players</th>\n",
       "      <th>Umpire1</th>\n",
       "      <th>Umpire2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1312200</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>2022-05-29</td>\n",
       "      <td>2022</td>\n",
       "      <td>Final</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>Narendra Modi Stadium, Ahmedabad</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>HH Pandya</td>\n",
       "      <td>['YBK Jaiswal', 'JC Buttler', 'SV Samson', 'D ...</td>\n",
       "      <td>['WP Saha', 'Shubman Gill', 'MS Wade', 'HH Pan...</td>\n",
       "      <td>CB Gaffaney</td>\n",
       "      <td>Nitin Menon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1312199</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>2022-05-27</td>\n",
       "      <td>2022</td>\n",
       "      <td>Qualifier 2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Narendra Modi Stadium, Ahmedabad</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>JC Buttler</td>\n",
       "      <td>['V Kohli', 'F du Plessis', 'RM Patidar', 'GJ ...</td>\n",
       "      <td>['YBK Jaiswal', 'JC Buttler', 'SV Samson', 'D ...</td>\n",
       "      <td>CB Gaffaney</td>\n",
       "      <td>Nitin Menon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1312198</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>2022-05-25</td>\n",
       "      <td>2022</td>\n",
       "      <td>Eliminator</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Lucknow Super Giants</td>\n",
       "      <td>Eden Gardens, Kolkata</td>\n",
       "      <td>Lucknow Super Giants</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Runs</td>\n",
       "      <td>14.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RM Patidar</td>\n",
       "      <td>['V Kohli', 'F du Plessis', 'RM Patidar', 'GJ ...</td>\n",
       "      <td>['Q de Kock', 'KL Rahul', 'M Vohra', 'DJ Hooda...</td>\n",
       "      <td>J Madanagopal</td>\n",
       "      <td>MA Gough</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1312197</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>2022-05-24</td>\n",
       "      <td>2022</td>\n",
       "      <td>Qualifier 1</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>Eden Gardens, Kolkata</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DA Miller</td>\n",
       "      <td>['YBK Jaiswal', 'JC Buttler', 'SV Samson', 'D ...</td>\n",
       "      <td>['WP Saha', 'Shubman Gill', 'MS Wade', 'HH Pan...</td>\n",
       "      <td>BNJ Oxenford</td>\n",
       "      <td>VK Sharma</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1304116</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2022-05-22</td>\n",
       "      <td>2022</td>\n",
       "      <td>70</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Punjab Kings</td>\n",
       "      <td>Wankhede Stadium, Mumbai</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Punjab Kings</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Harpreet Brar</td>\n",
       "      <td>['PK Garg', 'Abhishek Sharma', 'RA Tripathi', ...</td>\n",
       "      <td>['JM Bairstow', 'S Dhawan', 'M Shahrukh Khan',...</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>NA Patwardhan</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        ID       City        Date Season  MatchNumber  \\\n",
       "0  1312200  Ahmedabad  2022-05-29   2022        Final   \n",
       "1  1312199  Ahmedabad  2022-05-27   2022  Qualifier 2   \n",
       "2  1312198    Kolkata  2022-05-25   2022   Eliminator   \n",
       "3  1312197    Kolkata  2022-05-24   2022  Qualifier 1   \n",
       "4  1304116     Mumbai  2022-05-22   2022           70   \n",
       "\n",
       "                         Team1                 Team2  \\\n",
       "0             Rajasthan Royals        Gujarat Titans   \n",
       "1  Royal Challengers Bangalore      Rajasthan Royals   \n",
       "2  Royal Challengers Bangalore  Lucknow Super Giants   \n",
       "3             Rajasthan Royals        Gujarat Titans   \n",
       "4          Sunrisers Hyderabad          Punjab Kings   \n",
       "\n",
       "                              Venue            TossWinner TossDecision  \\\n",
       "0  Narendra Modi Stadium, Ahmedabad      Rajasthan Royals          bat   \n",
       "1  Narendra Modi Stadium, Ahmedabad      Rajasthan Royals        field   \n",
       "2             Eden Gardens, Kolkata  Lucknow Super Giants        field   \n",
       "3             Eden Gardens, Kolkata        Gujarat Titans        field   \n",
       "4          Wankhede Stadium, Mumbai   Sunrisers Hyderabad          bat   \n",
       "\n",
       "  SuperOver                  WinningTeam    WonBy  Margin method  \\\n",
       "0         N               Gujarat Titans  Wickets     7.0    NaN   \n",
       "1         N             Rajasthan Royals  Wickets     7.0    NaN   \n",
       "2         N  Royal Challengers Bangalore     Runs    14.0    NaN   \n",
       "3         N               Gujarat Titans  Wickets     7.0    NaN   \n",
       "4         N                 Punjab Kings  Wickets     5.0    NaN   \n",
       "\n",
       "  Player_of_Match                                       Team1Players  \\\n",
       "0       HH Pandya  ['YBK Jaiswal', 'JC Buttler', 'SV Samson', 'D ...   \n",
       "1      JC Buttler  ['V Kohli', 'F du Plessis', 'RM Patidar', 'GJ ...   \n",
       "2      RM Patidar  ['V Kohli', 'F du Plessis', 'RM Patidar', 'GJ ...   \n",
       "3       DA Miller  ['YBK Jaiswal', 'JC Buttler', 'SV Samson', 'D ...   \n",
       "4   Harpreet Brar  ['PK Garg', 'Abhishek Sharma', 'RA Tripathi', ...   \n",
       "\n",
       "                                        Team2Players        Umpire1  \\\n",
       "0  ['WP Saha', 'Shubman Gill', 'MS Wade', 'HH Pan...    CB Gaffaney   \n",
       "1  ['YBK Jaiswal', 'JC Buttler', 'SV Samson', 'D ...    CB Gaffaney   \n",
       "2  ['Q de Kock', 'KL Rahul', 'M Vohra', 'DJ Hooda...  J Madanagopal   \n",
       "3  ['WP Saha', 'Shubman Gill', 'MS Wade', 'HH Pan...   BNJ Oxenford   \n",
       "4  ['JM Bairstow', 'S Dhawan', 'M Shahrukh Khan',...   AK Chaudhary   \n",
       "\n",
       "         Umpire2  \n",
       "0    Nitin Menon  \n",
       "1    Nitin Menon  \n",
       "2       MA Gough  \n",
       "3      VK Sharma  \n",
       "4  NA Patwardhan  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl = pd.read_csv('ipl-matches.csv')\n",
    "ipl.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## DataFrame Attributes and Methods"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1629, 18)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#shape\n",
    "movies.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(950, 20)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "title_x              object\n",
       "imdb_id              object\n",
       "poster_path          object\n",
       "wiki_link            object\n",
       "title_y              object\n",
       "original_title       object\n",
       "is_adult              int64\n",
       "year_of_release       int64\n",
       "runtime              object\n",
       "genres               object\n",
       "imdb_rating         float64\n",
       "imdb_votes            int64\n",
       "story                object\n",
       "summary              object\n",
       "tagline              object\n",
       "actors               object\n",
       "wins_nominations     object\n",
       "release_date         object\n",
       "dtype: object"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#dtypes\n",
    "movies.dtypes                                                      #object=string"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RangeIndex(start=0, stop=1629, step=1)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#index\n",
    "movies.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['title_x', 'imdb_id', 'poster_path', 'wiki_link', 'title_y',\n",
       "       'original_title', 'is_adult', 'year_of_release', 'runtime', 'genres',\n",
       "       'imdb_rating', 'imdb_votes', 'story', 'summary', 'tagline', 'actors',\n",
       "       'wins_nominations', 'release_date'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#columns\n",
    "movies.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['ID', 'City', 'Date', 'Season', 'MatchNumber', 'Team1', 'Team2',\n",
       "       'Venue', 'TossWinner', 'TossDecision', 'SuperOver', 'WinningTeam',\n",
       "       'WonBy', 'Margin', 'method', 'Player_of_Match', 'Team1Players',\n",
       "       'Team2Players', 'Umpire1', 'Umpire2'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['iq', 'marks', 'package'], dtype='object')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "student.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[100,  80,  10],\n",
       "       [ 90,  70,   7],\n",
       "       [120, 100,  14],\n",
       "       [ 80,  50,   0]], dtype=int64)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#values\n",
    "student.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([['Uri: The Surgical Strike', 'tt8291224',\n",
       "        'https://upload.wikimedia.org/wikipedia/en/thumb/3/3b/URI_-_New_poster.jpg/220px-URI_-_New_poster.jpg',\n",
       "        ...,\n",
       "        'Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Gautam|Kirti Kulhari|Rajit Kapoor|Ivan Rodrigues|Manasi Parekh|Swaroop Sampat|Riva Arora|Yogesh Soman|Fareed Ahmed|Akashdeep Arora|Kallol Banerjee|',\n",
       "        '4 wins', '11 January 2019 (USA)'],\n",
       "       ['Battalion 609', 'tt9472208', nan, ...,\n",
       "        'Vicky Ahuja|Shoaib Ibrahim|Shrikant Kamat|Elena Kazan|Vishwas Kini|Major Kishore|Jashn Kohli|Rammy C. Pandey|Manish Sharma|Sparsh Sharma|Farnaz Shetty|Vikas Shrivastav|Chandraprakash Thakur|Brajesh Tiwari|',\n",
       "        nan, '11 January 2019 (India)'],\n",
       "       ['The Accidental Prime Minister (film)', 'tt6986710',\n",
       "        'https://upload.wikimedia.org/wikipedia/en/thumb/a/a1/The_Accidental_Prime_Minister_film.jpg/220px-The_Accidental_Prime_Minister_film.jpg',\n",
       "        ...,\n",
       "        'Anupam Kher|Akshaye Khanna|Aahana Kumra|Atul Sharma|Manoj Anand|Arjun Mathur|Suzanne Bernert|Abdul Quadir Amin|Bharat Mistri|Divya Seth|Anil Rastogi|Ramesh Bhatkar|Parrgash Kaur|Jess Kaur|',\n",
       "        nan, '11 January 2019 (USA)'],\n",
       "       ...,\n",
       "       ['Sabse Bada Sukh', 'tt0069204', nan, ...,\n",
       "        'Vijay Arora|Asrani|Rajni Bala|Kumud Damle|Utpal Dutt|Meeta Faiyyaz|Rabi Ghosh|Tarun Ghosh|Sanjeev Kumar|Keshto Mukherjee|Meena Rai|',\n",
       "        nan, nan],\n",
       "       ['Daaka', 'tt10833860',\n",
       "        'https://upload.wikimedia.org/wikipedia/en/thumb/4/45/Daaka.jpg/220px-Daaka.jpg',\n",
       "        ..., 'Gippy Grewal|Zareen Khan|', nan, '1 November 2019 (USA)'],\n",
       "       ['Humsafar', 'tt2403201',\n",
       "        'https://upload.wikimedia.org/wikipedia/en/thumb/4/41/Flag_of_India.svg/23px-Flag_of_India.svg.png',\n",
       "        ..., 'Fawad Khan|', nan, 'TV Series (2011–2012)']], dtype=object)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>title_x</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>poster_path</th>\n",
       "      <th>wiki_link</th>\n",
       "      <th>title_y</th>\n",
       "      <th>original_title</th>\n",
       "      <th>is_adult</th>\n",
       "      <th>year_of_release</th>\n",
       "      <th>runtime</th>\n",
       "      <th>genres</th>\n",
       "      <th>imdb_rating</th>\n",
       "      <th>imdb_votes</th>\n",
       "      <th>story</th>\n",
       "      <th>summary</th>\n",
       "      <th>tagline</th>\n",
       "      <th>actors</th>\n",
       "      <th>wins_nominations</th>\n",
       "      <th>release_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1627</th>\n",
       "      <td>Daaka</td>\n",
       "      <td>tt10833860</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Daaka</td>\n",
       "      <td>Daaka</td>\n",
       "      <td>Daaka</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>136</td>\n",
       "      <td>Action</td>\n",
       "      <td>7.4</td>\n",
       "      <td>38</td>\n",
       "      <td>Shinda tries robbing a bank so he can be wealt...</td>\n",
       "      <td>Shinda tries robbing a bank so he can be wealt...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Gippy Grewal|Zareen Khan|</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1 November 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1628</th>\n",
       "      <td>Humsafar</td>\n",
       "      <td>tt2403201</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Humsafar</td>\n",
       "      <td>Humsafar</td>\n",
       "      <td>Humsafar</td>\n",
       "      <td>0</td>\n",
       "      <td>2011</td>\n",
       "      <td>35</td>\n",
       "      <td>Drama|Romance</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2968</td>\n",
       "      <td>Sara and Ashar are childhood friends who share...</td>\n",
       "      <td>Ashar and Khirad are forced to get married due...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Fawad Khan|</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TV Series (2011–2012)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       title_x     imdb_id                                        poster_path  \\\n",
       "1627     Daaka  tt10833860  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "1628  Humsafar   tt2403201  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "\n",
       "                                   wiki_link   title_y original_title  \\\n",
       "1627     https://en.wikipedia.org/wiki/Daaka     Daaka          Daaka   \n",
       "1628  https://en.wikipedia.org/wiki/Humsafar  Humsafar       Humsafar   \n",
       "\n",
       "      is_adult  year_of_release runtime         genres  imdb_rating  \\\n",
       "1627         0             2019     136         Action          7.4   \n",
       "1628         0             2011      35  Drama|Romance          9.0   \n",
       "\n",
       "      imdb_votes                                              story  \\\n",
       "1627          38  Shinda tries robbing a bank so he can be wealt...   \n",
       "1628        2968  Sara and Ashar are childhood friends who share...   \n",
       "\n",
       "                                                summary tagline  \\\n",
       "1627  Shinda tries robbing a bank so he can be wealt...     NaN   \n",
       "1628  Ashar and Khirad are forced to get married due...     NaN   \n",
       "\n",
       "                         actors wins_nominations           release_date  \n",
       "1627  Gippy Grewal|Zareen Khan|              NaN  1 November 2019 (USA)  \n",
       "1628                Fawad Khan|              NaN  TV Series (2011–2012)  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#head,tail\n",
    "movies.tail(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>City</th>\n",
       "      <th>Date</th>\n",
       "      <th>Season</th>\n",
       "      <th>MatchNumber</th>\n",
       "      <th>Team1</th>\n",
       "      <th>Team2</th>\n",
       "      <th>Venue</th>\n",
       "      <th>TossWinner</th>\n",
       "      <th>TossDecision</th>\n",
       "      <th>SuperOver</th>\n",
       "      <th>WinningTeam</th>\n",
       "      <th>WonBy</th>\n",
       "      <th>Margin</th>\n",
       "      <th>method</th>\n",
       "      <th>Player_of_Match</th>\n",
       "      <th>Team1Players</th>\n",
       "      <th>Team2Players</th>\n",
       "      <th>Umpire1</th>\n",
       "      <th>Umpire2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>1178409</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>2019-04-18</td>\n",
       "      <td>2019</td>\n",
       "      <td>34</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Arun Jaitley Stadium</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Runs</td>\n",
       "      <td>40.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>HH Pandya</td>\n",
       "      <td>['RG Sharma', 'Q de Kock', 'BCJ Cutting', 'SA ...</td>\n",
       "      <td>['PP Shaw', 'S Dhawan', 'C Munro', 'SS Iyer', ...</td>\n",
       "      <td>BNJ Oxenford</td>\n",
       "      <td>NJ Llong</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>394</th>\n",
       "      <td>980977</td>\n",
       "      <td>Chandigarh</td>\n",
       "      <td>2016-05-09</td>\n",
       "      <td>2016</td>\n",
       "      <td>39</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Punjab Cricket Association IS Bindra Stadium, ...</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Runs</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SR Watson</td>\n",
       "      <td>['HM Amla', 'M Vijay', 'WP Saha', 'DA Miller',...</td>\n",
       "      <td>['V Kohli', 'KL Rahul', 'AB de Villiers', 'SR ...</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>429</th>\n",
       "      <td>980907</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>2016-04-12</td>\n",
       "      <td>2016</td>\n",
       "      <td>4</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Runs</td>\n",
       "      <td>45.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AB de Villiers</td>\n",
       "      <td>['CH Gayle', 'V Kohli', 'AB de Villiers', 'SR ...</td>\n",
       "      <td>['DA Warner', 'S Dhawan', 'MC Henriques', 'NV ...</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>VK Sharma</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          ID        City        Date Season MatchNumber  \\\n",
       "220  1178409       Delhi  2019-04-18   2019          34   \n",
       "394   980977  Chandigarh  2016-05-09   2016          39   \n",
       "429   980907   Bangalore  2016-04-12   2016           4   \n",
       "\n",
       "                           Team1                        Team2  \\\n",
       "220               Mumbai Indians               Delhi Capitals   \n",
       "394              Kings XI Punjab  Royal Challengers Bangalore   \n",
       "429  Royal Challengers Bangalore          Sunrisers Hyderabad   \n",
       "\n",
       "                                                 Venue           TossWinner  \\\n",
       "220                               Arun Jaitley Stadium       Mumbai Indians   \n",
       "394  Punjab Cricket Association IS Bindra Stadium, ...      Kings XI Punjab   \n",
       "429                              M Chinnaswamy Stadium  Sunrisers Hyderabad   \n",
       "\n",
       "    TossDecision SuperOver                  WinningTeam WonBy  Margin method  \\\n",
       "220          bat         N               Mumbai Indians  Runs    40.0    NaN   \n",
       "394        field         N  Royal Challengers Bangalore  Runs     1.0    NaN   \n",
       "429        field         N  Royal Challengers Bangalore  Runs    45.0    NaN   \n",
       "\n",
       "    Player_of_Match                                       Team1Players  \\\n",
       "220       HH Pandya  ['RG Sharma', 'Q de Kock', 'BCJ Cutting', 'SA ...   \n",
       "394       SR Watson  ['HM Amla', 'M Vijay', 'WP Saha', 'DA Miller',...   \n",
       "429  AB de Villiers  ['CH Gayle', 'V Kohli', 'AB de Villiers', 'SR ...   \n",
       "\n",
       "                                          Team2Players          Umpire1  \\\n",
       "220  ['PP Shaw', 'S Dhawan', 'C Munro', 'SS Iyer', ...     BNJ Oxenford   \n",
       "394  ['V Kohli', 'KL Rahul', 'AB de Villiers', 'SR ...     AK Chaudhary   \n",
       "429  ['DA Warner', 'S Dhawan', 'MC Henriques', 'NV ...  HDPK Dharmasena   \n",
       "\n",
       "             Umpire2  \n",
       "220         NJ Llong  \n",
       "394  HDPK Dharmasena  \n",
       "429        VK Sharma  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#sample\n",
    "ipl.sample(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1629 entries, 0 to 1628\n",
      "Data columns (total 18 columns):\n",
      " #   Column            Non-Null Count  Dtype  \n",
      "---  ------            --------------  -----  \n",
      " 0   title_x           1629 non-null   object \n",
      " 1   imdb_id           1629 non-null   object \n",
      " 2   poster_path       1526 non-null   object \n",
      " 3   wiki_link         1629 non-null   object \n",
      " 4   title_y           1629 non-null   object \n",
      " 5   original_title    1629 non-null   object \n",
      " 6   is_adult          1629 non-null   int64  \n",
      " 7   year_of_release   1629 non-null   int64  \n",
      " 8   runtime           1629 non-null   object \n",
      " 9   genres            1629 non-null   object \n",
      " 10  imdb_rating       1629 non-null   float64\n",
      " 11  imdb_votes        1629 non-null   int64  \n",
      " 12  story             1609 non-null   object \n",
      " 13  summary           1629 non-null   object \n",
      " 14  tagline           557 non-null    object \n",
      " 15  actors            1624 non-null   object \n",
      " 16  wins_nominations  707 non-null    object \n",
      " 17  release_date      1522 non-null   object \n",
      "dtypes: float64(1), int64(3), object(14)\n",
      "memory usage: 229.2+ KB\n"
     ]
    }
   ],
   "source": [
    "#info\n",
    "movies.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 950 entries, 0 to 949\n",
      "Data columns (total 20 columns):\n",
      " #   Column           Non-Null Count  Dtype  \n",
      "---  ------           --------------  -----  \n",
      " 0   ID               950 non-null    int64  \n",
      " 1   City             899 non-null    object \n",
      " 2   Date             950 non-null    object \n",
      " 3   Season           950 non-null    object \n",
      " 4   MatchNumber      950 non-null    object \n",
      " 5   Team1            950 non-null    object \n",
      " 6   Team2            950 non-null    object \n",
      " 7   Venue            950 non-null    object \n",
      " 8   TossWinner       950 non-null    object \n",
      " 9   TossDecision     950 non-null    object \n",
      " 10  SuperOver        946 non-null    object \n",
      " 11  WinningTeam      946 non-null    object \n",
      " 12  WonBy            950 non-null    object \n",
      " 13  Margin           932 non-null    float64\n",
      " 14  method           19 non-null     object \n",
      " 15  Player_of_Match  946 non-null    object \n",
      " 16  Team1Players     950 non-null    object \n",
      " 17  Team2Players     950 non-null    object \n",
      " 18  Umpire1          950 non-null    object \n",
      " 19  Umpire2          950 non-null    object \n",
      "dtypes: float64(1), int64(1), object(18)\n",
      "memory usage: 148.6+ KB\n"
     ]
    }
   ],
   "source": [
    "ipl.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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>is_adult</th>\n",
       "      <th>year_of_release</th>\n",
       "      <th>imdb_rating</th>\n",
       "      <th>imdb_votes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1629.0</td>\n",
       "      <td>1629.000000</td>\n",
       "      <td>1629.000000</td>\n",
       "      <td>1629.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.0</td>\n",
       "      <td>2010.263966</td>\n",
       "      <td>5.557459</td>\n",
       "      <td>5384.263352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.0</td>\n",
       "      <td>5.381542</td>\n",
       "      <td>1.567609</td>\n",
       "      <td>14552.103231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.0</td>\n",
       "      <td>2001.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.0</td>\n",
       "      <td>2005.000000</td>\n",
       "      <td>4.400000</td>\n",
       "      <td>233.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.0</td>\n",
       "      <td>2011.000000</td>\n",
       "      <td>5.600000</td>\n",
       "      <td>1000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.0</td>\n",
       "      <td>2015.000000</td>\n",
       "      <td>6.800000</td>\n",
       "      <td>4287.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.0</td>\n",
       "      <td>2019.000000</td>\n",
       "      <td>9.400000</td>\n",
       "      <td>310481.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       is_adult  year_of_release  imdb_rating     imdb_votes\n",
       "count    1629.0      1629.000000  1629.000000    1629.000000\n",
       "mean        0.0      2010.263966     5.557459    5384.263352\n",
       "std         0.0         5.381542     1.567609   14552.103231\n",
       "min         0.0      2001.000000     0.000000       0.000000\n",
       "25%         0.0      2005.000000     4.400000     233.000000\n",
       "50%         0.0      2011.000000     5.600000    1000.000000\n",
       "75%         0.0      2015.000000     6.800000    4287.000000\n",
       "max         0.0      2019.000000     9.400000  310481.000000"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#describe:a summary of numerical columns  .....automatically detect numerical columns and perform operations\n",
    "movies.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Margin</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>9.500000e+02</td>\n",
       "      <td>932.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>8.304852e+05</td>\n",
       "      <td>17.056867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.375678e+05</td>\n",
       "      <td>21.633109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>3.359820e+05</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>5.012612e+05</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>8.297380e+05</td>\n",
       "      <td>8.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.175372e+06</td>\n",
       "      <td>19.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.312200e+06</td>\n",
       "      <td>146.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 ID      Margin\n",
       "count  9.500000e+02  932.000000\n",
       "mean   8.304852e+05   17.056867\n",
       "std    3.375678e+05   21.633109\n",
       "min    3.359820e+05    1.000000\n",
       "25%    5.012612e+05    6.000000\n",
       "50%    8.297380e+05    8.000000\n",
       "75%    1.175372e+06   19.000000\n",
       "max    1.312200e+06  146.000000"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "title_x                0\n",
       "imdb_id                0\n",
       "poster_path          103\n",
       "wiki_link              0\n",
       "title_y                0\n",
       "original_title         0\n",
       "is_adult               0\n",
       "year_of_release        0\n",
       "runtime                0\n",
       "genres                 0\n",
       "imdb_rating            0\n",
       "imdb_votes             0\n",
       "story                 20\n",
       "summary                0\n",
       "tagline             1072\n",
       "actors                 5\n",
       "wins_nominations     922\n",
       "release_date         107\n",
       "dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#isnull\n",
    "movies.isnull()  #gives a boolean dataframe\n",
    "movies.isnull().sum() #specifies no of missing values in each columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ID                   0\n",
       "City                51\n",
       "Date                 0\n",
       "Season               0\n",
       "MatchNumber          0\n",
       "Team1                0\n",
       "Team2                0\n",
       "Venue                0\n",
       "TossWinner           0\n",
       "TossDecision         0\n",
       "SuperOver            4\n",
       "WinningTeam          4\n",
       "WonBy                0\n",
       "Margin              18\n",
       "method             931\n",
       "Player_of_Match      4\n",
       "Team1Players         0\n",
       "Team2Players         0\n",
       "Umpire1              0\n",
       "Umpire2              0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#duplicated:check duplicate values or not... gives no. of rows duplicated\n",
    "movies.duplicated()\n",
    "movies.duplicated().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>iq</th>\n",
       "      <th>marks</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>90</td>\n",
       "      <td>70</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>120</td>\n",
       "      <td>100</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>80</td>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    iq  marks  package\n",
       "0  100     80       10\n",
       "1   90     70        7\n",
       "2  120    100       14\n",
       "3   80     50        0"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#rename: rename column name\n",
    "student"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "student.rename(columns={'marks':'percent','package':'lpa'},inplace=True) #for permanant change, use inplace=true"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Math Methods"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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>iq</th>\n",
       "      <th>percent</th>\n",
       "      <th>lpa</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>90</td>\n",
       "      <td>70</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>120</td>\n",
       "      <td>100</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>80</td>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    iq  percent  lpa\n",
       "0  100       80   10\n",
       "1   90       70    7\n",
       "2  120      100   14\n",
       "3   80       50    0"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "student"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "iq         390\n",
       "percent    300\n",
       "lpa         31\n",
       "dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "student.sum() #by default,sum of each columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    190\n",
       "1    167\n",
       "2    234\n",
       "3    130\n",
       "dtype: int64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "student.sum(axis=1) #sum of each rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "iq         97.50\n",
       "percent    75.00\n",
       "lpa         7.75\n",
       "dtype: float64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "student.mean() #all can apply in rowwise & columnwise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "iq         95.0\n",
       "percent    75.0\n",
       "lpa         8.5\n",
       "dtype: float64"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "student.median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "iq         80\n",
       "percent    50\n",
       "lpa         0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "student.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "iq         120\n",
       "percent    100\n",
       "lpa         14\n",
       "dtype: int64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "student.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "iq         17.078251\n",
       "percent    20.816660\n",
       "lpa         5.909033\n",
       "dtype: float64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "student.std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "iq         291.666667\n",
       "percent    433.333333\n",
       "lpa         34.916667\n",
       "dtype: float64"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "student.var()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "#when we apply sum() to entire dataset, categorical data just concatenate.. there is no point in it.. so apply sum specific to numeric columns only "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Nithin\\AppData\\Local\\Temp\\ipykernel_17556\\2790600498.py:1: FutureWarning: The default value of numeric_only in DataFrame.sum is deprecated. In a future version, it will default to False. In addition, specifying 'numeric_only=None' is deprecated. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
      "  movies.sum()\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "title_x            Uri: The Surgical StrikeBattalion 609The Accid...\n",
       "imdb_id            tt8291224tt9472208tt6986710tt8108208tt6028796t...\n",
       "wiki_link          https://en.wikipedia.org/wiki/Uri:_The_Surgica...\n",
       "title_y            Uri: The Surgical StrikeBattalion 609The Accid...\n",
       "original_title     Uri: The Surgical StrikeBattalion 609The Accid...\n",
       "is_adult                                                           0\n",
       "year_of_release                                              3274720\n",
       "runtime            1381311121211029710910414812013415314313014311...\n",
       "genres             Action|Drama|WarWarBiography|DramaCrime|DramaD...\n",
       "imdb_rating                                                   9053.1\n",
       "imdb_votes                                                   8770965\n",
       "summary            Indian army special forces execute a covert op...\n",
       "dtype: object"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies.sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Selecting cols from a DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                   Uri: The Surgical Strike\n",
       "1                              Battalion 609\n",
       "2       The Accidental Prime Minister (film)\n",
       "3                            Why Cheat India\n",
       "4                            Evening Shadows\n",
       "                        ...                 \n",
       "1624                   Tera Mera Saath Rahen\n",
       "1625                    Yeh Zindagi Ka Safar\n",
       "1626                         Sabse Bada Sukh\n",
       "1627                                   Daaka\n",
       "1628                                Humsafar\n",
       "Name: title_x, Length: 1629, dtype: object"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# single cols\n",
    "movies['title_x']           #single column is a series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(movies['title_x'] )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0          HH Pandya\n",
       "1         JC Buttler\n",
       "2         RM Patidar\n",
       "3          DA Miller\n",
       "4      Harpreet Brar\n",
       "           ...      \n",
       "945        DJ Hussey\n",
       "946       MV Boucher\n",
       "947      MF Maharoof\n",
       "948       MEK Hussey\n",
       "949      BB McCullum\n",
       "Name: Player_of_Match, Length: 950, dtype: object"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl['Player_of_Match']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "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>title_x</th>\n",
       "      <th>year_of_release</th>\n",
       "      <th>actors</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>2019</td>\n",
       "      <td>Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>2019</td>\n",
       "      <td>Vicky Ahuja|Shoaib Ibrahim|Shrikant Kamat|Elen...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>The Accidental Prime Minister (film)</td>\n",
       "      <td>2019</td>\n",
       "      <td>Anupam Kher|Akshaye Khanna|Aahana Kumra|Atul S...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Why Cheat India</td>\n",
       "      <td>2019</td>\n",
       "      <td>Emraan Hashmi|Shreya Dhanwanthary|Snighdadeep ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Evening Shadows</td>\n",
       "      <td>2018</td>\n",
       "      <td>Mona Ambegaonkar|Ananth Narayan Mahadevan|Deva...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1624</th>\n",
       "      <td>Tera Mera Saath Rahen</td>\n",
       "      <td>2001</td>\n",
       "      <td>Ajay Devgn|Sonali Bendre|Namrata Shirodkar|Pre...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1625</th>\n",
       "      <td>Yeh Zindagi Ka Safar</td>\n",
       "      <td>2001</td>\n",
       "      <td>Ameesha Patel|Jimmy Sheirgill|Nafisa Ali|Gulsh...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1626</th>\n",
       "      <td>Sabse Bada Sukh</td>\n",
       "      <td>2018</td>\n",
       "      <td>Vijay Arora|Asrani|Rajni Bala|Kumud Damle|Utpa...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1627</th>\n",
       "      <td>Daaka</td>\n",
       "      <td>2019</td>\n",
       "      <td>Gippy Grewal|Zareen Khan|</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1628</th>\n",
       "      <td>Humsafar</td>\n",
       "      <td>2011</td>\n",
       "      <td>Fawad Khan|</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1629 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   title_x  year_of_release  \\\n",
       "0                 Uri: The Surgical Strike             2019   \n",
       "1                            Battalion 609             2019   \n",
       "2     The Accidental Prime Minister (film)             2019   \n",
       "3                          Why Cheat India             2019   \n",
       "4                          Evening Shadows             2018   \n",
       "...                                    ...              ...   \n",
       "1624                 Tera Mera Saath Rahen             2001   \n",
       "1625                  Yeh Zindagi Ka Safar             2001   \n",
       "1626                       Sabse Bada Sukh             2018   \n",
       "1627                                 Daaka             2019   \n",
       "1628                              Humsafar             2011   \n",
       "\n",
       "                                                 actors  \n",
       "0     Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...  \n",
       "1     Vicky Ahuja|Shoaib Ibrahim|Shrikant Kamat|Elen...  \n",
       "2     Anupam Kher|Akshaye Khanna|Aahana Kumra|Atul S...  \n",
       "3     Emraan Hashmi|Shreya Dhanwanthary|Snighdadeep ...  \n",
       "4     Mona Ambegaonkar|Ananth Narayan Mahadevan|Deva...  \n",
       "...                                                 ...  \n",
       "1624  Ajay Devgn|Sonali Bendre|Namrata Shirodkar|Pre...  \n",
       "1625  Ameesha Patel|Jimmy Sheirgill|Nafisa Ali|Gulsh...  \n",
       "1626  Vijay Arora|Asrani|Rajni Bala|Kumud Damle|Utpa...  \n",
       "1627                          Gippy Grewal|Zareen Khan|  \n",
       "1628                                        Fawad Khan|  \n",
       "\n",
       "[1629 rows x 3 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#multiple cols................................a dataframe itself\n",
    "movies[['title_x','year_of_release','actors']]                             #fancy indexing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(movies[['title_x','year_of_release','actors']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "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>year_of_release</th>\n",
       "      <th>actors</th>\n",
       "      <th>title_x</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019</td>\n",
       "      <td>Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...</td>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019</td>\n",
       "      <td>Vicky Ahuja|Shoaib Ibrahim|Shrikant Kamat|Elen...</td>\n",
       "      <td>Battalion 609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019</td>\n",
       "      <td>Anupam Kher|Akshaye Khanna|Aahana Kumra|Atul S...</td>\n",
       "      <td>The Accidental Prime Minister (film)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019</td>\n",
       "      <td>Emraan Hashmi|Shreya Dhanwanthary|Snighdadeep ...</td>\n",
       "      <td>Why Cheat India</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018</td>\n",
       "      <td>Mona Ambegaonkar|Ananth Narayan Mahadevan|Deva...</td>\n",
       "      <td>Evening Shadows</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1624</th>\n",
       "      <td>2001</td>\n",
       "      <td>Ajay Devgn|Sonali Bendre|Namrata Shirodkar|Pre...</td>\n",
       "      <td>Tera Mera Saath Rahen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1625</th>\n",
       "      <td>2001</td>\n",
       "      <td>Ameesha Patel|Jimmy Sheirgill|Nafisa Ali|Gulsh...</td>\n",
       "      <td>Yeh Zindagi Ka Safar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1626</th>\n",
       "      <td>2018</td>\n",
       "      <td>Vijay Arora|Asrani|Rajni Bala|Kumud Damle|Utpa...</td>\n",
       "      <td>Sabse Bada Sukh</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1627</th>\n",
       "      <td>2019</td>\n",
       "      <td>Gippy Grewal|Zareen Khan|</td>\n",
       "      <td>Daaka</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1628</th>\n",
       "      <td>2011</td>\n",
       "      <td>Fawad Khan|</td>\n",
       "      <td>Humsafar</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1629 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      year_of_release                                             actors  \\\n",
       "0                2019  Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...   \n",
       "1                2019  Vicky Ahuja|Shoaib Ibrahim|Shrikant Kamat|Elen...   \n",
       "2                2019  Anupam Kher|Akshaye Khanna|Aahana Kumra|Atul S...   \n",
       "3                2019  Emraan Hashmi|Shreya Dhanwanthary|Snighdadeep ...   \n",
       "4                2018  Mona Ambegaonkar|Ananth Narayan Mahadevan|Deva...   \n",
       "...               ...                                                ...   \n",
       "1624             2001  Ajay Devgn|Sonali Bendre|Namrata Shirodkar|Pre...   \n",
       "1625             2001  Ameesha Patel|Jimmy Sheirgill|Nafisa Ali|Gulsh...   \n",
       "1626             2018  Vijay Arora|Asrani|Rajni Bala|Kumud Damle|Utpa...   \n",
       "1627             2019                          Gippy Grewal|Zareen Khan|   \n",
       "1628             2011                                        Fawad Khan|   \n",
       "\n",
       "                                   title_x  \n",
       "0                 Uri: The Surgical Strike  \n",
       "1                            Battalion 609  \n",
       "2     The Accidental Prime Minister (film)  \n",
       "3                          Why Cheat India  \n",
       "4                          Evening Shadows  \n",
       "...                                    ...  \n",
       "1624                 Tera Mera Saath Rahen  \n",
       "1625                  Yeh Zindagi Ka Safar  \n",
       "1626                       Sabse Bada Sukh  \n",
       "1627                                 Daaka  \n",
       "1628                              Humsafar  \n",
       "\n",
       "[1629 rows x 3 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies[['year_of_release','actors','title_x']]                             #order matters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "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>Team1</th>\n",
       "      <th>Team2</th>\n",
       "      <th>TossWinner</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Lucknow Super Giants</td>\n",
       "      <td>Lucknow Super Giants</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Punjab Kings</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>946</th>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>947</th>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>948</th>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>949</th>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>950 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Team1                        Team2  \\\n",
       "0               Rajasthan Royals               Gujarat Titans   \n",
       "1    Royal Challengers Bangalore             Rajasthan Royals   \n",
       "2    Royal Challengers Bangalore         Lucknow Super Giants   \n",
       "3               Rajasthan Royals               Gujarat Titans   \n",
       "4            Sunrisers Hyderabad                 Punjab Kings   \n",
       "..                           ...                          ...   \n",
       "945        Kolkata Knight Riders              Deccan Chargers   \n",
       "946               Mumbai Indians  Royal Challengers Bangalore   \n",
       "947             Delhi Daredevils             Rajasthan Royals   \n",
       "948              Kings XI Punjab          Chennai Super Kings   \n",
       "949  Royal Challengers Bangalore        Kolkata Knight Riders   \n",
       "\n",
       "                      TossWinner  \n",
       "0               Rajasthan Royals  \n",
       "1               Rajasthan Royals  \n",
       "2           Lucknow Super Giants  \n",
       "3                 Gujarat Titans  \n",
       "4            Sunrisers Hyderabad  \n",
       "..                           ...  \n",
       "945              Deccan Chargers  \n",
       "946               Mumbai Indians  \n",
       "947             Rajasthan Royals  \n",
       "948          Chennai Super Kings  \n",
       "949  Royal Challengers Bangalore  \n",
       "\n",
       "[950 rows x 3 columns]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl[['Team1','Team2','TossWinner']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Selecting rows from a DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "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>iq</th>\n",
       "      <th>marks</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>nitish</th>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ankit</th>\n",
       "      <td>90</td>\n",
       "      <td>70</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rupesh</th>\n",
       "      <td>120</td>\n",
       "      <td>100</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rishabh</th>\n",
       "      <td>80</td>\n",
       "      <td>50</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>amit</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ankita</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          iq  marks  package\n",
       "name                        \n",
       "nitish   100     80       10\n",
       "ankit     90     70        7\n",
       "rupesh   120    100       14\n",
       "rishabh   80     50        2\n",
       "amit       0      0        0\n",
       "ankita     0      0        0"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "student_dict = {\n",
    "    'name':['nitish','ankit','rupesh','rishabh','amit','ankita'],\n",
    "    'iq':[100,90,120,80,0,0],\n",
    "    'marks':[80,70,100,50,0,0],\n",
    "    'package':[10,7,14,2,0,0]\n",
    "}\n",
    "\n",
    "students=pd.DataFrame(student_dict)\n",
    "students.set_index('name',inplace=True)  #to set a specified column as index\n",
    "students"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### iloc - searches using index positions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "title_x                                      Uri: The Surgical Strike\n",
       "imdb_id                                                     tt8291224\n",
       "poster_path         https://upload.wikimedia.org/wikipedia/en/thum...\n",
       "wiki_link           https://en.wikipedia.org/wiki/Uri:_The_Surgica...\n",
       "title_y                                      Uri: The Surgical Strike\n",
       "original_title                               Uri: The Surgical Strike\n",
       "is_adult                                                            0\n",
       "year_of_release                                                  2019\n",
       "runtime                                                           138\n",
       "genres                                               Action|Drama|War\n",
       "imdb_rating                                                       8.4\n",
       "imdb_votes                                                      35112\n",
       "story               Divided over five chapters  the film chronicle...\n",
       "summary             Indian army special forces execute a covert op...\n",
       "tagline                                                           NaN\n",
       "actors              Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...\n",
       "wins_nominations                                               4 wins\n",
       "release_date                                    11 January 2019 (USA)\n",
       "Name: 0, dtype: object"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#single row\n",
    "movies.iloc[0]          #details of first movie.. output as series, as single row is a series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "title_x                                                   Soni (film)\n",
       "imdb_id                                                     tt6078866\n",
       "poster_path         https://upload.wikimedia.org/wikipedia/en/thum...\n",
       "wiki_link                   https://en.wikipedia.org/wiki/Soni_(film)\n",
       "title_y                                                          Soni\n",
       "original_title                                                   Soni\n",
       "is_adult                                                            0\n",
       "year_of_release                                                  2018\n",
       "runtime                                                            97\n",
       "genres                                                          Drama\n",
       "imdb_rating                                                       7.2\n",
       "imdb_votes                                                       1595\n",
       "story               Soni  a young policewoman in Delhi  and her su...\n",
       "summary             While fighting crimes against women in Delhi  ...\n",
       "tagline                                                           NaN\n",
       "actors              Geetika Vidya Ohlyan|Saloni Batra|Vikas Shukla...\n",
       "wins_nominations                               3 wins & 5 nominations\n",
       "release_date                                    18 January 2019 (USA)\n",
       "Name: 5, dtype: object"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies.iloc[5] #6th movie details"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "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>title_x</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>poster_path</th>\n",
       "      <th>wiki_link</th>\n",
       "      <th>title_y</th>\n",
       "      <th>original_title</th>\n",
       "      <th>is_adult</th>\n",
       "      <th>year_of_release</th>\n",
       "      <th>runtime</th>\n",
       "      <th>genres</th>\n",
       "      <th>imdb_rating</th>\n",
       "      <th>imdb_votes</th>\n",
       "      <th>story</th>\n",
       "      <th>summary</th>\n",
       "      <th>tagline</th>\n",
       "      <th>actors</th>\n",
       "      <th>wins_nominations</th>\n",
       "      <th>release_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>tt8291224</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Uri:_The_Surgica...</td>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>138</td>\n",
       "      <td>Action|Drama|War</td>\n",
       "      <td>8.4</td>\n",
       "      <td>35112</td>\n",
       "      <td>Divided over five chapters  the film chronicle...</td>\n",
       "      <td>Indian army special forces execute a covert op...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...</td>\n",
       "      <td>4 wins</td>\n",
       "      <td>11 January 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>tt9472208</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Battalion_609</td>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>131</td>\n",
       "      <td>War</td>\n",
       "      <td>4.1</td>\n",
       "      <td>73</td>\n",
       "      <td>The story revolves around a cricket match betw...</td>\n",
       "      <td>The story of Battalion 609 revolves around a c...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vicky Ahuja|Shoaib Ibrahim|Shrikant Kamat|Elen...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11 January 2019 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>The Accidental Prime Minister (film)</td>\n",
       "      <td>tt6986710</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/The_Accidental_P...</td>\n",
       "      <td>The Accidental Prime Minister</td>\n",
       "      <td>The Accidental Prime Minister</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>112</td>\n",
       "      <td>Biography|Drama</td>\n",
       "      <td>6.1</td>\n",
       "      <td>5549</td>\n",
       "      <td>Based on the memoir by Indian policy analyst S...</td>\n",
       "      <td>Explores Manmohan Singh's tenure as the Prime ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Anupam Kher|Akshaye Khanna|Aahana Kumra|Atul S...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11 January 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Why Cheat India</td>\n",
       "      <td>tt8108208</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Why_Cheat_India</td>\n",
       "      <td>Why Cheat India</td>\n",
       "      <td>Why Cheat India</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>121</td>\n",
       "      <td>Crime|Drama</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1891</td>\n",
       "      <td>The movie focuses on existing malpractices in ...</td>\n",
       "      <td>The movie focuses on existing malpractices in ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Emraan Hashmi|Shreya Dhanwanthary|Snighdadeep ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18 January 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Evening Shadows</td>\n",
       "      <td>tt6028796</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Evening_Shadows</td>\n",
       "      <td>Evening Shadows</td>\n",
       "      <td>Evening Shadows</td>\n",
       "      <td>0</td>\n",
       "      <td>2018</td>\n",
       "      <td>102</td>\n",
       "      <td>Drama</td>\n",
       "      <td>7.3</td>\n",
       "      <td>280</td>\n",
       "      <td>While gay rights and marriage equality has bee...</td>\n",
       "      <td>Under the 'Evening Shadows'  truth often plays...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mona Ambegaonkar|Ananth Narayan Mahadevan|Deva...</td>\n",
       "      <td>17 wins &amp; 1 nomination</td>\n",
       "      <td>11 January 2019 (India)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                title_x    imdb_id  \\\n",
       "0              Uri: The Surgical Strike  tt8291224   \n",
       "1                         Battalion 609  tt9472208   \n",
       "2  The Accidental Prime Minister (film)  tt6986710   \n",
       "3                       Why Cheat India  tt8108208   \n",
       "4                       Evening Shadows  tt6028796   \n",
       "\n",
       "                                         poster_path  \\\n",
       "0  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "1                                                NaN   \n",
       "2  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "3  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "4                                                NaN   \n",
       "\n",
       "                                           wiki_link  \\\n",
       "0  https://en.wikipedia.org/wiki/Uri:_The_Surgica...   \n",
       "1        https://en.wikipedia.org/wiki/Battalion_609   \n",
       "2  https://en.wikipedia.org/wiki/The_Accidental_P...   \n",
       "3      https://en.wikipedia.org/wiki/Why_Cheat_India   \n",
       "4      https://en.wikipedia.org/wiki/Evening_Shadows   \n",
       "\n",
       "                         title_y                 original_title  is_adult  \\\n",
       "0       Uri: The Surgical Strike       Uri: The Surgical Strike         0   \n",
       "1                  Battalion 609                  Battalion 609         0   \n",
       "2  The Accidental Prime Minister  The Accidental Prime Minister         0   \n",
       "3                Why Cheat India                Why Cheat India         0   \n",
       "4                Evening Shadows                Evening Shadows         0   \n",
       "\n",
       "   year_of_release runtime            genres  imdb_rating  imdb_votes  \\\n",
       "0             2019     138  Action|Drama|War          8.4       35112   \n",
       "1             2019     131               War          4.1          73   \n",
       "2             2019     112   Biography|Drama          6.1        5549   \n",
       "3             2019     121       Crime|Drama          6.0        1891   \n",
       "4             2018     102             Drama          7.3         280   \n",
       "\n",
       "                                               story  \\\n",
       "0  Divided over five chapters  the film chronicle...   \n",
       "1  The story revolves around a cricket match betw...   \n",
       "2  Based on the memoir by Indian policy analyst S...   \n",
       "3  The movie focuses on existing malpractices in ...   \n",
       "4  While gay rights and marriage equality has bee...   \n",
       "\n",
       "                                             summary tagline  \\\n",
       "0  Indian army special forces execute a covert op...     NaN   \n",
       "1  The story of Battalion 609 revolves around a c...     NaN   \n",
       "2  Explores Manmohan Singh's tenure as the Prime ...     NaN   \n",
       "3  The movie focuses on existing malpractices in ...     NaN   \n",
       "4  Under the 'Evening Shadows'  truth often plays...     NaN   \n",
       "\n",
       "                                              actors        wins_nominations  \\\n",
       "0  Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...                  4 wins   \n",
       "1  Vicky Ahuja|Shoaib Ibrahim|Shrikant Kamat|Elen...                     NaN   \n",
       "2  Anupam Kher|Akshaye Khanna|Aahana Kumra|Atul S...                     NaN   \n",
       "3  Emraan Hashmi|Shreya Dhanwanthary|Snighdadeep ...                     NaN   \n",
       "4  Mona Ambegaonkar|Ananth Narayan Mahadevan|Deva...  17 wins & 1 nomination   \n",
       "\n",
       "              release_date  \n",
       "0    11 January 2019 (USA)  \n",
       "1  11 January 2019 (India)  \n",
       "2    11 January 2019 (USA)  \n",
       "3    18 January 2019 (USA)  \n",
       "4  11 January 2019 (India)  "
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#multiple rows\n",
    "movies.iloc[0:5]    #first 5 movies.... a dataframe "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title_x</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>poster_path</th>\n",
       "      <th>wiki_link</th>\n",
       "      <th>title_y</th>\n",
       "      <th>original_title</th>\n",
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       "      <th>genres</th>\n",
       "      <th>imdb_rating</th>\n",
       "      <th>imdb_votes</th>\n",
       "      <th>story</th>\n",
       "      <th>summary</th>\n",
       "      <th>tagline</th>\n",
       "      <th>actors</th>\n",
       "      <th>wins_nominations</th>\n",
       "      <th>release_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Soni (film)</td>\n",
       "      <td>tt6078866</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Soni_(film)</td>\n",
       "      <td>Soni</td>\n",
       "      <td>Soni</td>\n",
       "      <td>0</td>\n",
       "      <td>2018</td>\n",
       "      <td>97</td>\n",
       "      <td>Drama</td>\n",
       "      <td>7.2</td>\n",
       "      <td>1595</td>\n",
       "      <td>Soni  a young policewoman in Delhi  and her su...</td>\n",
       "      <td>While fighting crimes against women in Delhi  ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Geetika Vidya Ohlyan|Saloni Batra|Vikas Shukla...</td>\n",
       "      <td>3 wins &amp; 5 nominations</td>\n",
       "      <td>18 January 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Fraud Saiyaan</td>\n",
       "      <td>tt5013008</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Fraud_Saiyaan</td>\n",
       "      <td>Fraud Saiyaan</td>\n",
       "      <td>Fraud Saiyyan</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>109</td>\n",
       "      <td>Comedy|Drama</td>\n",
       "      <td>4.2</td>\n",
       "      <td>504</td>\n",
       "      <td>Fraud Saiyyan is the story of a con artist in ...</td>\n",
       "      <td>Fraud Saiyyan is the story of a con artist in ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Arshad Warsi|Saurabh Shukla|Flora Saini|Sara L...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18 January 2019 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Bombairiya</td>\n",
       "      <td>tt4971258</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Bombairiya</td>\n",
       "      <td>Bombairiya</td>\n",
       "      <td>Bombairiya</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>104</td>\n",
       "      <td>Comedy|Crime|Drama</td>\n",
       "      <td>4.3</td>\n",
       "      <td>295</td>\n",
       "      <td>It follows the story of Meghna  who gets embro...</td>\n",
       "      <td>It follows the story of Meghna  who gets embro...</td>\n",
       "      <td>They didn't mean to change the world.</td>\n",
       "      <td>Radhika Apte|Akshay Oberoi|Siddhanth Kapoor|Ra...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18 January 2019 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Manikarnika: The Queen of Jhansi</td>\n",
       "      <td>tt6903440</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Manikarnika:_The...</td>\n",
       "      <td>Manikarnika: The Queen of Jhansi</td>\n",
       "      <td>Manikarnika: The Queen of Jhansi</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>148</td>\n",
       "      <td>Action|Biography|Drama</td>\n",
       "      <td>6.5</td>\n",
       "      <td>7361</td>\n",
       "      <td>Manikarnika born in Varanasi when Dixt a minis...</td>\n",
       "      <td>Story of Rani Lakshmibai  one of the leading f...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kangana Ranaut|Rimi Sen|Atul Kulkarni|Nalneesh...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25 January 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Thackeray (film)</td>\n",
       "      <td>tt7777196</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Thackeray_(film)</td>\n",
       "      <td>Thackeray</td>\n",
       "      <td>Thackeray</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>120</td>\n",
       "      <td>Biography|Drama</td>\n",
       "      <td>5.1</td>\n",
       "      <td>2301</td>\n",
       "      <td>Balasaheb Thackrey works as a cartoonist for a...</td>\n",
       "      <td>Biographical account of Shiv Sena Supremo  Bal...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Nawazuddin Siddiqui|Amrita Rao|Abdul Quadir Am...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25 January 2019 (India)</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1624</th>\n",
       "      <td>Tera Mera Saath Rahen</td>\n",
       "      <td>tt0301250</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/2/2b...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Tera_Mera_Saath_...</td>\n",
       "      <td>Tera Mera Saath Rahen</td>\n",
       "      <td>Tera Mera Saath Rahen</td>\n",
       "      <td>0</td>\n",
       "      <td>2001</td>\n",
       "      <td>148</td>\n",
       "      <td>Drama</td>\n",
       "      <td>4.9</td>\n",
       "      <td>278</td>\n",
       "      <td>Raj Dixit lives with his younger brother  Rahu...</td>\n",
       "      <td>A man is torn between his handicapped brother ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ajay Devgn|Sonali Bendre|Namrata Shirodkar|Pre...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7 November 2001 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1625</th>\n",
       "      <td>Yeh Zindagi Ka Safar</td>\n",
       "      <td>tt0298607</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Yeh_Zindagi_Ka_S...</td>\n",
       "      <td>Yeh Zindagi Ka Safar</td>\n",
       "      <td>Yeh Zindagi Ka Safar</td>\n",
       "      <td>0</td>\n",
       "      <td>2001</td>\n",
       "      <td>146</td>\n",
       "      <td>Drama</td>\n",
       "      <td>3.0</td>\n",
       "      <td>133</td>\n",
       "      <td>Hindi pop-star  Sarina Devan  lives a wealthy ...</td>\n",
       "      <td>A singer finds out she was adopted when the ed...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ameesha Patel|Jimmy Sheirgill|Nafisa Ali|Gulsh...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16 November 2001 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1626</th>\n",
       "      <td>Sabse Bada Sukh</td>\n",
       "      <td>tt0069204</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Sabse_Bada_Sukh</td>\n",
       "      <td>Sabse Bada Sukh</td>\n",
       "      <td>Sabse Bada Sukh</td>\n",
       "      <td>0</td>\n",
       "      <td>2018</td>\n",
       "      <td>\\N</td>\n",
       "      <td>Comedy|Drama</td>\n",
       "      <td>6.1</td>\n",
       "      <td>13</td>\n",
       "      <td>Village born Lalloo re-locates to Bombay  and ...</td>\n",
       "      <td>Village born Lalloo re-locates to Bombay  and ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vijay Arora|Asrani|Rajni Bala|Kumud Damle|Utpa...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1627</th>\n",
       "      <td>Daaka</td>\n",
       "      <td>tt10833860</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Daaka</td>\n",
       "      <td>Daaka</td>\n",
       "      <td>Daaka</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>136</td>\n",
       "      <td>Action</td>\n",
       "      <td>7.4</td>\n",
       "      <td>38</td>\n",
       "      <td>Shinda tries robbing a bank so he can be wealt...</td>\n",
       "      <td>Shinda tries robbing a bank so he can be wealt...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Gippy Grewal|Zareen Khan|</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1 November 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1628</th>\n",
       "      <td>Humsafar</td>\n",
       "      <td>tt2403201</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Humsafar</td>\n",
       "      <td>Humsafar</td>\n",
       "      <td>Humsafar</td>\n",
       "      <td>0</td>\n",
       "      <td>2011</td>\n",
       "      <td>35</td>\n",
       "      <td>Drama|Romance</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2968</td>\n",
       "      <td>Sara and Ashar are childhood friends who share...</td>\n",
       "      <td>Ashar and Khirad are forced to get married due...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Fawad Khan|</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TV Series (2011–2012)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1624 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                               title_x     imdb_id  \\\n",
       "5                          Soni (film)   tt6078866   \n",
       "6                        Fraud Saiyaan   tt5013008   \n",
       "7                           Bombairiya   tt4971258   \n",
       "8     Manikarnika: The Queen of Jhansi   tt6903440   \n",
       "9                     Thackeray (film)   tt7777196   \n",
       "...                                ...         ...   \n",
       "1624             Tera Mera Saath Rahen   tt0301250   \n",
       "1625              Yeh Zindagi Ka Safar   tt0298607   \n",
       "1626                   Sabse Bada Sukh   tt0069204   \n",
       "1627                             Daaka  tt10833860   \n",
       "1628                          Humsafar   tt2403201   \n",
       "\n",
       "                                            poster_path  \\\n",
       "5     https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "6     https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "7     https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "8     https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "9     https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "...                                                 ...   \n",
       "1624  https://upload.wikimedia.org/wikipedia/en/2/2b...   \n",
       "1625  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "1626                                                NaN   \n",
       "1627  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "1628  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "\n",
       "                                              wiki_link  \\\n",
       "5             https://en.wikipedia.org/wiki/Soni_(film)   \n",
       "6           https://en.wikipedia.org/wiki/Fraud_Saiyaan   \n",
       "7              https://en.wikipedia.org/wiki/Bombairiya   \n",
       "8     https://en.wikipedia.org/wiki/Manikarnika:_The...   \n",
       "9        https://en.wikipedia.org/wiki/Thackeray_(film)   \n",
       "...                                                 ...   \n",
       "1624  https://en.wikipedia.org/wiki/Tera_Mera_Saath_...   \n",
       "1625  https://en.wikipedia.org/wiki/Yeh_Zindagi_Ka_S...   \n",
       "1626      https://en.wikipedia.org/wiki/Sabse_Bada_Sukh   \n",
       "1627                https://en.wikipedia.org/wiki/Daaka   \n",
       "1628             https://en.wikipedia.org/wiki/Humsafar   \n",
       "\n",
       "                               title_y                    original_title  \\\n",
       "5                                 Soni                              Soni   \n",
       "6                        Fraud Saiyaan                     Fraud Saiyyan   \n",
       "7                           Bombairiya                        Bombairiya   \n",
       "8     Manikarnika: The Queen of Jhansi  Manikarnika: The Queen of Jhansi   \n",
       "9                            Thackeray                         Thackeray   \n",
       "...                                ...                               ...   \n",
       "1624             Tera Mera Saath Rahen             Tera Mera Saath Rahen   \n",
       "1625              Yeh Zindagi Ka Safar              Yeh Zindagi Ka Safar   \n",
       "1626                   Sabse Bada Sukh                   Sabse Bada Sukh   \n",
       "1627                             Daaka                             Daaka   \n",
       "1628                          Humsafar                          Humsafar   \n",
       "\n",
       "      is_adult  year_of_release runtime                  genres  imdb_rating  \\\n",
       "5            0             2018      97                   Drama          7.2   \n",
       "6            0             2019     109            Comedy|Drama          4.2   \n",
       "7            0             2019     104      Comedy|Crime|Drama          4.3   \n",
       "8            0             2019     148  Action|Biography|Drama          6.5   \n",
       "9            0             2019     120         Biography|Drama          5.1   \n",
       "...        ...              ...     ...                     ...          ...   \n",
       "1624         0             2001     148                   Drama          4.9   \n",
       "1625         0             2001     146                   Drama          3.0   \n",
       "1626         0             2018      \\N            Comedy|Drama          6.1   \n",
       "1627         0             2019     136                  Action          7.4   \n",
       "1628         0             2011      35           Drama|Romance          9.0   \n",
       "\n",
       "      imdb_votes                                              story  \\\n",
       "5           1595  Soni  a young policewoman in Delhi  and her su...   \n",
       "6            504  Fraud Saiyyan is the story of a con artist in ...   \n",
       "7            295  It follows the story of Meghna  who gets embro...   \n",
       "8           7361  Manikarnika born in Varanasi when Dixt a minis...   \n",
       "9           2301  Balasaheb Thackrey works as a cartoonist for a...   \n",
       "...          ...                                                ...   \n",
       "1624         278  Raj Dixit lives with his younger brother  Rahu...   \n",
       "1625         133  Hindi pop-star  Sarina Devan  lives a wealthy ...   \n",
       "1626          13  Village born Lalloo re-locates to Bombay  and ...   \n",
       "1627          38  Shinda tries robbing a bank so he can be wealt...   \n",
       "1628        2968  Sara and Ashar are childhood friends who share...   \n",
       "\n",
       "                                                summary  \\\n",
       "5     While fighting crimes against women in Delhi  ...   \n",
       "6     Fraud Saiyyan is the story of a con artist in ...   \n",
       "7     It follows the story of Meghna  who gets embro...   \n",
       "8     Story of Rani Lakshmibai  one of the leading f...   \n",
       "9     Biographical account of Shiv Sena Supremo  Bal...   \n",
       "...                                                 ...   \n",
       "1624  A man is torn between his handicapped brother ...   \n",
       "1625  A singer finds out she was adopted when the ed...   \n",
       "1626  Village born Lalloo re-locates to Bombay  and ...   \n",
       "1627  Shinda tries robbing a bank so he can be wealt...   \n",
       "1628  Ashar and Khirad are forced to get married due...   \n",
       "\n",
       "                                    tagline  \\\n",
       "5                                       NaN   \n",
       "6                                       NaN   \n",
       "7     They didn't mean to change the world.   \n",
       "8                                       NaN   \n",
       "9                                       NaN   \n",
       "...                                     ...   \n",
       "1624                                    NaN   \n",
       "1625                                    NaN   \n",
       "1626                                    NaN   \n",
       "1627                                    NaN   \n",
       "1628                                    NaN   \n",
       "\n",
       "                                                 actors  \\\n",
       "5     Geetika Vidya Ohlyan|Saloni Batra|Vikas Shukla...   \n",
       "6     Arshad Warsi|Saurabh Shukla|Flora Saini|Sara L...   \n",
       "7     Radhika Apte|Akshay Oberoi|Siddhanth Kapoor|Ra...   \n",
       "8     Kangana Ranaut|Rimi Sen|Atul Kulkarni|Nalneesh...   \n",
       "9     Nawazuddin Siddiqui|Amrita Rao|Abdul Quadir Am...   \n",
       "...                                                 ...   \n",
       "1624  Ajay Devgn|Sonali Bendre|Namrata Shirodkar|Pre...   \n",
       "1625  Ameesha Patel|Jimmy Sheirgill|Nafisa Ali|Gulsh...   \n",
       "1626  Vijay Arora|Asrani|Rajni Bala|Kumud Damle|Utpa...   \n",
       "1627                          Gippy Grewal|Zareen Khan|   \n",
       "1628                                        Fawad Khan|   \n",
       "\n",
       "            wins_nominations              release_date  \n",
       "5     3 wins & 5 nominations     18 January 2019 (USA)  \n",
       "6                        NaN   18 January 2019 (India)  \n",
       "7                        NaN   18 January 2019 (India)  \n",
       "8                        NaN     25 January 2019 (USA)  \n",
       "9                        NaN   25 January 2019 (India)  \n",
       "...                      ...                       ...  \n",
       "1624                     NaN   7 November 2001 (India)  \n",
       "1625                     NaN  16 November 2001 (India)  \n",
       "1626                     NaN                       NaN  \n",
       "1627                     NaN     1 November 2019 (USA)  \n",
       "1628                     NaN     TV Series (2011–2012)  \n",
       "\n",
       "[1624 rows x 18 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies.iloc[5:16]  #5 to 15 movies\n",
    "movies.iloc[5:16:2] #alternate movies from 5 to 15\n",
    "movies.iloc[:5] #from starting to 5\n",
    "movies.iloc[5:] #from 5 to end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "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>title_x</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>poster_path</th>\n",
       "      <th>wiki_link</th>\n",
       "      <th>title_y</th>\n",
       "      <th>original_title</th>\n",
       "      <th>is_adult</th>\n",
       "      <th>year_of_release</th>\n",
       "      <th>runtime</th>\n",
       "      <th>genres</th>\n",
       "      <th>imdb_rating</th>\n",
       "      <th>imdb_votes</th>\n",
       "      <th>story</th>\n",
       "      <th>summary</th>\n",
       "      <th>tagline</th>\n",
       "      <th>actors</th>\n",
       "      <th>wins_nominations</th>\n",
       "      <th>release_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>tt8291224</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Uri:_The_Surgica...</td>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>138</td>\n",
       "      <td>Action|Drama|War</td>\n",
       "      <td>8.4</td>\n",
       "      <td>35112</td>\n",
       "      <td>Divided over five chapters  the film chronicle...</td>\n",
       "      <td>Indian army special forces execute a covert op...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...</td>\n",
       "      <td>4 wins</td>\n",
       "      <td>11 January 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Evening Shadows</td>\n",
       "      <td>tt6028796</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Evening_Shadows</td>\n",
       "      <td>Evening Shadows</td>\n",
       "      <td>Evening Shadows</td>\n",
       "      <td>0</td>\n",
       "      <td>2018</td>\n",
       "      <td>102</td>\n",
       "      <td>Drama</td>\n",
       "      <td>7.3</td>\n",
       "      <td>280</td>\n",
       "      <td>While gay rights and marriage equality has bee...</td>\n",
       "      <td>Under the 'Evening Shadows'  truth often plays...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mona Ambegaonkar|Ananth Narayan Mahadevan|Deva...</td>\n",
       "      <td>17 wins &amp; 1 nomination</td>\n",
       "      <td>11 January 2019 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Soni (film)</td>\n",
       "      <td>tt6078866</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Soni_(film)</td>\n",
       "      <td>Soni</td>\n",
       "      <td>Soni</td>\n",
       "      <td>0</td>\n",
       "      <td>2018</td>\n",
       "      <td>97</td>\n",
       "      <td>Drama</td>\n",
       "      <td>7.2</td>\n",
       "      <td>1595</td>\n",
       "      <td>Soni  a young policewoman in Delhi  and her su...</td>\n",
       "      <td>While fighting crimes against women in Delhi  ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Geetika Vidya Ohlyan|Saloni Batra|Vikas Shukla...</td>\n",
       "      <td>3 wins &amp; 5 nominations</td>\n",
       "      <td>18 January 2019 (USA)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    title_x    imdb_id  \\\n",
       "0  Uri: The Surgical Strike  tt8291224   \n",
       "4           Evening Shadows  tt6028796   \n",
       "5               Soni (film)  tt6078866   \n",
       "\n",
       "                                         poster_path  \\\n",
       "0  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "4                                                NaN   \n",
       "5  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "\n",
       "                                           wiki_link  \\\n",
       "0  https://en.wikipedia.org/wiki/Uri:_The_Surgica...   \n",
       "4      https://en.wikipedia.org/wiki/Evening_Shadows   \n",
       "5          https://en.wikipedia.org/wiki/Soni_(film)   \n",
       "\n",
       "                    title_y            original_title  is_adult  \\\n",
       "0  Uri: The Surgical Strike  Uri: The Surgical Strike         0   \n",
       "4           Evening Shadows           Evening Shadows         0   \n",
       "5                      Soni                      Soni         0   \n",
       "\n",
       "   year_of_release runtime            genres  imdb_rating  imdb_votes  \\\n",
       "0             2019     138  Action|Drama|War          8.4       35112   \n",
       "4             2018     102             Drama          7.3         280   \n",
       "5             2018      97             Drama          7.2        1595   \n",
       "\n",
       "                                               story  \\\n",
       "0  Divided over five chapters  the film chronicle...   \n",
       "4  While gay rights and marriage equality has bee...   \n",
       "5  Soni  a young policewoman in Delhi  and her su...   \n",
       "\n",
       "                                             summary tagline  \\\n",
       "0  Indian army special forces execute a covert op...     NaN   \n",
       "4  Under the 'Evening Shadows'  truth often plays...     NaN   \n",
       "5  While fighting crimes against women in Delhi  ...     NaN   \n",
       "\n",
       "                                              actors        wins_nominations  \\\n",
       "0  Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...                  4 wins   \n",
       "4  Mona Ambegaonkar|Ananth Narayan Mahadevan|Deva...  17 wins & 1 nomination   \n",
       "5  Geetika Vidya Ohlyan|Saloni Batra|Vikas Shukla...  3 wins & 5 nominations   \n",
       "\n",
       "              release_date  \n",
       "0    11 January 2019 (USA)  \n",
       "4  11 January 2019 (India)  \n",
       "5    18 January 2019 (USA)  "
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies.iloc[[0,4,5]]            #fancy indexing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### loc - searches using index labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "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>iq</th>\n",
       "      <th>marks</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>nitish</th>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ankit</th>\n",
       "      <td>90</td>\n",
       "      <td>70</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rupesh</th>\n",
       "      <td>120</td>\n",
       "      <td>100</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rishabh</th>\n",
       "      <td>80</td>\n",
       "      <td>50</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>amit</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ankita</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          iq  marks  package\n",
       "name                        \n",
       "nitish   100     80       10\n",
       "ankit     90     70        7\n",
       "rupesh   120    100       14\n",
       "rishabh   80     50        2\n",
       "amit       0      0        0\n",
       "ankita     0      0        0"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "students"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "iq         100\n",
       "marks       80\n",
       "package     10\n",
       "Name: nitish, dtype: int64"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#single row\n",
    "students.loc['nitish']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "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>iq</th>\n",
       "      <th>marks</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>nitish</th>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ankit</th>\n",
       "      <td>90</td>\n",
       "      <td>70</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rupesh</th>\n",
       "      <td>120</td>\n",
       "      <td>100</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rishabh</th>\n",
       "      <td>80</td>\n",
       "      <td>50</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          iq  marks  package\n",
       "name                        \n",
       "nitish   100     80       10\n",
       "ankit     90     70        7\n",
       "rupesh   120    100       14\n",
       "rishabh   80     50        2"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#multiple rows\n",
    "students.loc['nitish':'rishabh']"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "when u provide range for multiple rows,in 'iloc',last value is excluded.. but in 'loc',last value is included"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "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>iq</th>\n",
       "      <th>marks</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>nitish</th>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rupesh</th>\n",
       "      <td>120</td>\n",
       "      <td>100</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         iq  marks  package\n",
       "name                       \n",
       "nitish  100     80       10\n",
       "rupesh  120    100       14"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "students.loc['nitish':'rishabh':2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "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>iq</th>\n",
       "      <th>marks</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>nitish</th>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rishabh</th>\n",
       "      <td>80</td>\n",
       "      <td>50</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ankita</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          iq  marks  package\n",
       "name                        \n",
       "nitish   100     80       10\n",
       "rishabh   80     50        2\n",
       "ankita     0      0        0"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "students.loc[['nitish','rishabh','ankita']]            #fancy indexing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "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>iq</th>\n",
       "      <th>marks</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>nitish</th>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ankit</th>\n",
       "      <td>90</td>\n",
       "      <td>70</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rupesh</th>\n",
       "      <td>120</td>\n",
       "      <td>100</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         iq  marks  package\n",
       "name                       \n",
       "nitish  100     80       10\n",
       "ankit    90     70        7\n",
       "rupesh  120    100       14"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#even though there are labeled index, we can also extract rows using iloc\n",
    "students.iloc[0]\n",
    "students.iloc[0:3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# #Selecting both rows and cols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "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>title_x</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>poster_path</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>tt8291224</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>tt9472208</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>The Accidental Prime Minister (film)</td>\n",
       "      <td>tt6986710</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                title_x    imdb_id  \\\n",
       "0              Uri: The Surgical Strike  tt8291224   \n",
       "1                         Battalion 609  tt9472208   \n",
       "2  The Accidental Prime Minister (film)  tt6986710   \n",
       "\n",
       "                                         poster_path  \n",
       "0  https://upload.wikimedia.org/wikipedia/en/thum...  \n",
       "1                                                NaN  \n",
       "2  https://upload.wikimedia.org/wikipedia/en/thum...  "
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies.iloc[0:3,0:3]#using iloc (by index positions). pandas internally give index nos starting from 0 to both rows and columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "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>title_x</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>poster_path</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>tt8291224</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>tt9472208</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>The Accidental Prime Minister (film)</td>\n",
       "      <td>tt6986710</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                title_x    imdb_id  \\\n",
       "0              Uri: The Surgical Strike  tt8291224   \n",
       "1                         Battalion 609  tt9472208   \n",
       "2  The Accidental Prime Minister (film)  tt6986710   \n",
       "\n",
       "                                         poster_path  \n",
       "0  https://upload.wikimedia.org/wikipedia/en/thum...  \n",
       "1                                                NaN  \n",
       "2  https://upload.wikimedia.org/wikipedia/en/thum...  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies.loc[0:2,'title_x':'poster_path']     #using loc (by index labels)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filtering a DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>City</th>\n",
       "      <th>Date</th>\n",
       "      <th>Season</th>\n",
       "      <th>MatchNumber</th>\n",
       "      <th>Team1</th>\n",
       "      <th>Team2</th>\n",
       "      <th>Venue</th>\n",
       "      <th>TossWinner</th>\n",
       "      <th>TossDecision</th>\n",
       "      <th>SuperOver</th>\n",
       "      <th>WinningTeam</th>\n",
       "      <th>WonBy</th>\n",
       "      <th>Margin</th>\n",
       "      <th>method</th>\n",
       "      <th>Player_of_Match</th>\n",
       "      <th>Team1Players</th>\n",
       "      <th>Team2Players</th>\n",
       "      <th>Umpire1</th>\n",
       "      <th>Umpire2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1312200</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>2022-05-29</td>\n",
       "      <td>2022</td>\n",
       "      <td>Final</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>Narendra Modi Stadium, Ahmedabad</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>HH Pandya</td>\n",
       "      <td>['YBK Jaiswal', 'JC Buttler', 'SV Samson', 'D ...</td>\n",
       "      <td>['WP Saha', 'Shubman Gill', 'MS Wade', 'HH Pan...</td>\n",
       "      <td>CB Gaffaney</td>\n",
       "      <td>Nitin Menon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1312199</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>2022-05-27</td>\n",
       "      <td>2022</td>\n",
       "      <td>Qualifier 2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Narendra Modi Stadium, Ahmedabad</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>JC Buttler</td>\n",
       "      <td>['V Kohli', 'F du Plessis', 'RM Patidar', 'GJ ...</td>\n",
       "      <td>['YBK Jaiswal', 'JC Buttler', 'SV Samson', 'D ...</td>\n",
       "      <td>CB Gaffaney</td>\n",
       "      <td>Nitin Menon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1312198</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>2022-05-25</td>\n",
       "      <td>2022</td>\n",
       "      <td>Eliminator</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Lucknow Super Giants</td>\n",
       "      <td>Eden Gardens, Kolkata</td>\n",
       "      <td>Lucknow Super Giants</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Runs</td>\n",
       "      <td>14.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RM Patidar</td>\n",
       "      <td>['V Kohli', 'F du Plessis', 'RM Patidar', 'GJ ...</td>\n",
       "      <td>['Q de Kock', 'KL Rahul', 'M Vohra', 'DJ Hooda...</td>\n",
       "      <td>J Madanagopal</td>\n",
       "      <td>MA Gough</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1312197</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>2022-05-24</td>\n",
       "      <td>2022</td>\n",
       "      <td>Qualifier 1</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>Eden Gardens, Kolkata</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DA Miller</td>\n",
       "      <td>['YBK Jaiswal', 'JC Buttler', 'SV Samson', 'D ...</td>\n",
       "      <td>['WP Saha', 'Shubman Gill', 'MS Wade', 'HH Pan...</td>\n",
       "      <td>BNJ Oxenford</td>\n",
       "      <td>VK Sharma</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1304116</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2022-05-22</td>\n",
       "      <td>2022</td>\n",
       "      <td>70</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Punjab Kings</td>\n",
       "      <td>Wankhede Stadium, Mumbai</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Punjab Kings</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Harpreet Brar</td>\n",
       "      <td>['PK Garg', 'Abhishek Sharma', 'RA Tripathi', ...</td>\n",
       "      <td>['JM Bairstow', 'S Dhawan', 'M Shahrukh Khan',...</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>NA Patwardhan</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945</th>\n",
       "      <td>335986</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>2008-04-20</td>\n",
       "      <td>2007/08</td>\n",
       "      <td>4</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DJ Hussey</td>\n",
       "      <td>['WP Saha', 'BB McCullum', 'RT Ponting', 'SC G...</td>\n",
       "      <td>['AC Gilchrist', 'Y Venugopal Rao', 'VVS Laxma...</td>\n",
       "      <td>BF Bowden</td>\n",
       "      <td>K Hariharan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>946</th>\n",
       "      <td>335985</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2008-04-20</td>\n",
       "      <td>2007/08</td>\n",
       "      <td>5</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MV Boucher</td>\n",
       "      <td>['L Ronchi', 'ST Jayasuriya', 'DJ Thornely', '...</td>\n",
       "      <td>['S Chanderpaul', 'R Dravid', 'LRPL Taylor', '...</td>\n",
       "      <td>SJ Davis</td>\n",
       "      <td>DJ Harper</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>947</th>\n",
       "      <td>335984</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>2008-04-19</td>\n",
       "      <td>2007/08</td>\n",
       "      <td>3</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MF Maharoof</td>\n",
       "      <td>['G Gambhir', 'V Sehwag', 'S Dhawan', 'MK Tiwa...</td>\n",
       "      <td>['T Kohli', 'YK Pathan', 'SR Watson', 'M Kaif'...</td>\n",
       "      <td>Aleem Dar</td>\n",
       "      <td>GA Pratapkumar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>948</th>\n",
       "      <td>335983</td>\n",
       "      <td>Chandigarh</td>\n",
       "      <td>2008-04-19</td>\n",
       "      <td>2007/08</td>\n",
       "      <td>2</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Punjab Cricket Association Stadium, Mohali</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Runs</td>\n",
       "      <td>33.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MEK Hussey</td>\n",
       "      <td>['K Goel', 'JR Hopes', 'KC Sangakkara', 'Yuvra...</td>\n",
       "      <td>['PA Patel', 'ML Hayden', 'MEK Hussey', 'MS Dh...</td>\n",
       "      <td>MR Benson</td>\n",
       "      <td>SL Shastri</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>949</th>\n",
       "      <td>335982</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>2007/08</td>\n",
       "      <td>1</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Runs</td>\n",
       "      <td>140.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>['R Dravid', 'W Jaffer', 'V Kohli', 'JH Kallis...</td>\n",
       "      <td>['SC Ganguly', 'BB McCullum', 'RT Ponting', 'D...</td>\n",
       "      <td>Asad Rauf</td>\n",
       "      <td>RE Koertzen</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>950 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          ID        City        Date   Season  MatchNumber  \\\n",
       "0    1312200   Ahmedabad  2022-05-29     2022        Final   \n",
       "1    1312199   Ahmedabad  2022-05-27     2022  Qualifier 2   \n",
       "2    1312198     Kolkata  2022-05-25     2022   Eliminator   \n",
       "3    1312197     Kolkata  2022-05-24     2022  Qualifier 1   \n",
       "4    1304116      Mumbai  2022-05-22     2022           70   \n",
       "..       ...         ...         ...      ...          ...   \n",
       "945   335986     Kolkata  2008-04-20  2007/08            4   \n",
       "946   335985      Mumbai  2008-04-20  2007/08            5   \n",
       "947   335984       Delhi  2008-04-19  2007/08            3   \n",
       "948   335983  Chandigarh  2008-04-19  2007/08            2   \n",
       "949   335982   Bangalore  2008-04-18  2007/08            1   \n",
       "\n",
       "                           Team1                        Team2  \\\n",
       "0               Rajasthan Royals               Gujarat Titans   \n",
       "1    Royal Challengers Bangalore             Rajasthan Royals   \n",
       "2    Royal Challengers Bangalore         Lucknow Super Giants   \n",
       "3               Rajasthan Royals               Gujarat Titans   \n",
       "4            Sunrisers Hyderabad                 Punjab Kings   \n",
       "..                           ...                          ...   \n",
       "945        Kolkata Knight Riders              Deccan Chargers   \n",
       "946               Mumbai Indians  Royal Challengers Bangalore   \n",
       "947             Delhi Daredevils             Rajasthan Royals   \n",
       "948              Kings XI Punjab          Chennai Super Kings   \n",
       "949  Royal Challengers Bangalore        Kolkata Knight Riders   \n",
       "\n",
       "                                          Venue                   TossWinner  \\\n",
       "0              Narendra Modi Stadium, Ahmedabad             Rajasthan Royals   \n",
       "1              Narendra Modi Stadium, Ahmedabad             Rajasthan Royals   \n",
       "2                         Eden Gardens, Kolkata         Lucknow Super Giants   \n",
       "3                         Eden Gardens, Kolkata               Gujarat Titans   \n",
       "4                      Wankhede Stadium, Mumbai          Sunrisers Hyderabad   \n",
       "..                                          ...                          ...   \n",
       "945                                Eden Gardens              Deccan Chargers   \n",
       "946                            Wankhede Stadium               Mumbai Indians   \n",
       "947                            Feroz Shah Kotla             Rajasthan Royals   \n",
       "948  Punjab Cricket Association Stadium, Mohali          Chennai Super Kings   \n",
       "949                       M Chinnaswamy Stadium  Royal Challengers Bangalore   \n",
       "\n",
       "    TossDecision SuperOver                  WinningTeam    WonBy  Margin  \\\n",
       "0            bat         N               Gujarat Titans  Wickets     7.0   \n",
       "1          field         N             Rajasthan Royals  Wickets     7.0   \n",
       "2          field         N  Royal Challengers Bangalore     Runs    14.0   \n",
       "3          field         N               Gujarat Titans  Wickets     7.0   \n",
       "4            bat         N                 Punjab Kings  Wickets     5.0   \n",
       "..           ...       ...                          ...      ...     ...   \n",
       "945          bat         N        Kolkata Knight Riders  Wickets     5.0   \n",
       "946          bat         N  Royal Challengers Bangalore  Wickets     5.0   \n",
       "947          bat         N             Delhi Daredevils  Wickets     9.0   \n",
       "948          bat         N          Chennai Super Kings     Runs    33.0   \n",
       "949        field         N        Kolkata Knight Riders     Runs   140.0   \n",
       "\n",
       "    method Player_of_Match                                       Team1Players  \\\n",
       "0      NaN       HH Pandya  ['YBK Jaiswal', 'JC Buttler', 'SV Samson', 'D ...   \n",
       "1      NaN      JC Buttler  ['V Kohli', 'F du Plessis', 'RM Patidar', 'GJ ...   \n",
       "2      NaN      RM Patidar  ['V Kohli', 'F du Plessis', 'RM Patidar', 'GJ ...   \n",
       "3      NaN       DA Miller  ['YBK Jaiswal', 'JC Buttler', 'SV Samson', 'D ...   \n",
       "4      NaN   Harpreet Brar  ['PK Garg', 'Abhishek Sharma', 'RA Tripathi', ...   \n",
       "..     ...             ...                                                ...   \n",
       "945    NaN       DJ Hussey  ['WP Saha', 'BB McCullum', 'RT Ponting', 'SC G...   \n",
       "946    NaN      MV Boucher  ['L Ronchi', 'ST Jayasuriya', 'DJ Thornely', '...   \n",
       "947    NaN     MF Maharoof  ['G Gambhir', 'V Sehwag', 'S Dhawan', 'MK Tiwa...   \n",
       "948    NaN      MEK Hussey  ['K Goel', 'JR Hopes', 'KC Sangakkara', 'Yuvra...   \n",
       "949    NaN     BB McCullum  ['R Dravid', 'W Jaffer', 'V Kohli', 'JH Kallis...   \n",
       "\n",
       "                                          Team2Players        Umpire1  \\\n",
       "0    ['WP Saha', 'Shubman Gill', 'MS Wade', 'HH Pan...    CB Gaffaney   \n",
       "1    ['YBK Jaiswal', 'JC Buttler', 'SV Samson', 'D ...    CB Gaffaney   \n",
       "2    ['Q de Kock', 'KL Rahul', 'M Vohra', 'DJ Hooda...  J Madanagopal   \n",
       "3    ['WP Saha', 'Shubman Gill', 'MS Wade', 'HH Pan...   BNJ Oxenford   \n",
       "4    ['JM Bairstow', 'S Dhawan', 'M Shahrukh Khan',...   AK Chaudhary   \n",
       "..                                                 ...            ...   \n",
       "945  ['AC Gilchrist', 'Y Venugopal Rao', 'VVS Laxma...      BF Bowden   \n",
       "946  ['S Chanderpaul', 'R Dravid', 'LRPL Taylor', '...       SJ Davis   \n",
       "947  ['T Kohli', 'YK Pathan', 'SR Watson', 'M Kaif'...      Aleem Dar   \n",
       "948  ['PA Patel', 'ML Hayden', 'MEK Hussey', 'MS Dh...      MR Benson   \n",
       "949  ['SC Ganguly', 'BB McCullum', 'RT Ponting', 'D...      Asad Rauf   \n",
       "\n",
       "            Umpire2  \n",
       "0       Nitin Menon  \n",
       "1       Nitin Menon  \n",
       "2          MA Gough  \n",
       "3         VK Sharma  \n",
       "4     NA Patwardhan  \n",
       "..              ...  \n",
       "945     K Hariharan  \n",
       "946       DJ Harper  \n",
       "947  GA Pratapkumar  \n",
       "948      SL Shastri  \n",
       "949     RE Koertzen  \n",
       "\n",
       "[950 rows x 20 columns]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Season</th>\n",
       "      <th>WinningTeam</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>2021</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>2020/21</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>2019</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>254</th>\n",
       "      <td>2018</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>314</th>\n",
       "      <td>2017</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>373</th>\n",
       "      <td>2016</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>433</th>\n",
       "      <td>2015</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>492</th>\n",
       "      <td>2014</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>552</th>\n",
       "      <td>2013</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>628</th>\n",
       "      <td>2012</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>702</th>\n",
       "      <td>2011</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>775</th>\n",
       "      <td>2009/10</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>835</th>\n",
       "      <td>2009</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>892</th>\n",
       "      <td>2007/08</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Season            WinningTeam\n",
       "0       2022         Gujarat Titans\n",
       "74      2021    Chennai Super Kings\n",
       "134  2020/21         Mumbai Indians\n",
       "194     2019         Mumbai Indians\n",
       "254     2018    Chennai Super Kings\n",
       "314     2017         Mumbai Indians\n",
       "373     2016    Sunrisers Hyderabad\n",
       "433     2015         Mumbai Indians\n",
       "492     2014  Kolkata Knight Riders\n",
       "552     2013         Mumbai Indians\n",
       "628     2012  Kolkata Knight Riders\n",
       "702     2011    Chennai Super Kings\n",
       "775  2009/10    Chennai Super Kings\n",
       "835     2009        Deccan Chargers\n",
       "892  2007/08       Rajasthan Royals"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Q) fing all the finalwinners in each season\n",
    "new_df = ipl[ipl['MatchNumber']=='Final']          #or\n",
    "                                          # mask = ipl['MatchNumber']=='Final'\n",
    "                                          # ipl[mask]\n",
    "new_df[['Season','WinningTeam']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>Season</th>\n",
       "      <th>WinningTeam</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>2021</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>2020/21</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>2019</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>254</th>\n",
       "      <td>2018</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>314</th>\n",
       "      <td>2017</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>373</th>\n",
       "      <td>2016</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>433</th>\n",
       "      <td>2015</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>492</th>\n",
       "      <td>2014</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>552</th>\n",
       "      <td>2013</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>628</th>\n",
       "      <td>2012</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>702</th>\n",
       "      <td>2011</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>775</th>\n",
       "      <td>2009/10</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>835</th>\n",
       "      <td>2009</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>892</th>\n",
       "      <td>2007/08</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Season            WinningTeam\n",
       "0       2022         Gujarat Titans\n",
       "74      2021    Chennai Super Kings\n",
       "134  2020/21         Mumbai Indians\n",
       "194     2019         Mumbai Indians\n",
       "254     2018    Chennai Super Kings\n",
       "314     2017         Mumbai Indians\n",
       "373     2016    Sunrisers Hyderabad\n",
       "433     2015         Mumbai Indians\n",
       "492     2014  Kolkata Knight Riders\n",
       "552     2013         Mumbai Indians\n",
       "628     2012  Kolkata Knight Riders\n",
       "702     2011    Chennai Super Kings\n",
       "775  2009/10    Chennai Super Kings\n",
       "835     2009        Deccan Chargers\n",
       "892  2007/08       Rajasthan Royals"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl[ipl['MatchNumber']=='Final'][['Season','WinningTeam']] #in single line"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(14, 20)"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Q)how many super over finishes have occured\n",
    "ipl[ipl['SuperOver'] == 'Y'].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl[ipl['SuperOver'] == 'Y'].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Q) how many matches has csk won in kolkata\n",
    "ipl[(ipl['City'] == 'Kolkata') & (ipl['WinningTeam'] =='Chennai Super Kings')]             # & -> bitwise and\n",
    "ipl[(ipl['City'] == 'Kolkata') & (ipl['WinningTeam'] =='Chennai Super Kings')].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "51.473684210526315"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Q) toss winner is match winner in percentage\n",
    "(ipl[ipl['TossWinner'] == ipl['WinningTeam']].shape[0])/(ipl.shape[0]) * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ipl['TossWinner'] == ipl['WinningTeam']\n",
    "# ipl[ipl['TossWinner'] == ipl['WinningTeam']]\n",
    "# ipl[ipl['TossWinner'] == ipl['WinningTeam']].shape[0]\n",
    "# ipl.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "43"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Q) movies with rating higher than 8 and votes>10000\n",
    "movies[(movies['imdb_rating'] > 8) & (movies['imdb_votes'] > 10000)].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pandas.core.strings.accessor.StringMethods at 0x21276bc7850>"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Q) Action movies with rating higher than 7.5\n",
    "movies['genres'].str"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       [Action, Drama, War]\n",
       "1                      [War]\n",
       "2         [Biography, Drama]\n",
       "3             [Crime, Drama]\n",
       "4                    [Drama]\n",
       "                ...         \n",
       "1624                 [Drama]\n",
       "1625                 [Drama]\n",
       "1626         [Comedy, Drama]\n",
       "1627                [Action]\n",
       "1628        [Drama, Romance]\n",
       "Name: genres, Length: 1629, dtype: object"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies['genres'].str.split('|')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "mask1 = movies['genres'].str.split('|').apply(lambda x:'Action' in x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "33"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mask2 = movies['imdb_rating'] > 7.5\n",
    "movies[mask1 & mask2].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "33"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#in one line\n",
    "movies[(movies['genres'].str.contains('Action')) & (movies['imdb_rating'] > 7.5)].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Q) write a function that can return the track record of 2 teams against each other"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Adding new cols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "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>title_x</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>poster_path</th>\n",
       "      <th>wiki_link</th>\n",
       "      <th>title_y</th>\n",
       "      <th>original_title</th>\n",
       "      <th>is_adult</th>\n",
       "      <th>year_of_release</th>\n",
       "      <th>runtime</th>\n",
       "      <th>genres</th>\n",
       "      <th>imdb_rating</th>\n",
       "      <th>imdb_votes</th>\n",
       "      <th>story</th>\n",
       "      <th>summary</th>\n",
       "      <th>tagline</th>\n",
       "      <th>actors</th>\n",
       "      <th>wins_nominations</th>\n",
       "      <th>release_date</th>\n",
       "      <th>country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>tt8291224</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Uri:_The_Surgica...</td>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>138</td>\n",
       "      <td>Action|Drama|War</td>\n",
       "      <td>8.4</td>\n",
       "      <td>35112</td>\n",
       "      <td>Divided over five chapters  the film chronicle...</td>\n",
       "      <td>Indian army special forces execute a covert op...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...</td>\n",
       "      <td>4 wins</td>\n",
       "      <td>11 January 2019 (USA)</td>\n",
       "      <td>india</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>tt9472208</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Battalion_609</td>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>131</td>\n",
       "      <td>War</td>\n",
       "      <td>4.1</td>\n",
       "      <td>73</td>\n",
       "      <td>The story revolves around a cricket match betw...</td>\n",
       "      <td>The story of Battalion 609 revolves around a c...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vicky Ahuja|Shoaib Ibrahim|Shrikant Kamat|Elen...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11 January 2019 (India)</td>\n",
       "      <td>india</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    title_x    imdb_id  \\\n",
       "0  Uri: The Surgical Strike  tt8291224   \n",
       "1             Battalion 609  tt9472208   \n",
       "\n",
       "                                         poster_path  \\\n",
       "0  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "1                                                NaN   \n",
       "\n",
       "                                           wiki_link  \\\n",
       "0  https://en.wikipedia.org/wiki/Uri:_The_Surgica...   \n",
       "1        https://en.wikipedia.org/wiki/Battalion_609   \n",
       "\n",
       "                    title_y            original_title  is_adult  \\\n",
       "0  Uri: The Surgical Strike  Uri: The Surgical Strike         0   \n",
       "1             Battalion 609             Battalion 609         0   \n",
       "\n",
       "   year_of_release runtime            genres  imdb_rating  imdb_votes  \\\n",
       "0             2019     138  Action|Drama|War          8.4       35112   \n",
       "1             2019     131               War          4.1          73   \n",
       "\n",
       "                                               story  \\\n",
       "0  Divided over five chapters  the film chronicle...   \n",
       "1  The story revolves around a cricket match betw...   \n",
       "\n",
       "                                             summary tagline  \\\n",
       "0  Indian army special forces execute a covert op...     NaN   \n",
       "1  The story of Battalion 609 revolves around a c...     NaN   \n",
       "\n",
       "                                              actors wins_nominations  \\\n",
       "0  Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...           4 wins   \n",
       "1  Vicky Ahuja|Shoaib Ibrahim|Shrikant Kamat|Elen...              NaN   \n",
       "\n",
       "              release_date country  \n",
       "0    11 January 2019 (USA)   india  \n",
       "1  11 January 2019 (India)   india  "
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#completely new\n",
    "movies['country'] = 'india'\n",
    "movies.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "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>title_x</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>poster_path</th>\n",
       "      <th>wiki_link</th>\n",
       "      <th>title_y</th>\n",
       "      <th>original_title</th>\n",
       "      <th>is_adult</th>\n",
       "      <th>year_of_release</th>\n",
       "      <th>runtime</th>\n",
       "      <th>genres</th>\n",
       "      <th>imdb_rating</th>\n",
       "      <th>imdb_votes</th>\n",
       "      <th>story</th>\n",
       "      <th>summary</th>\n",
       "      <th>tagline</th>\n",
       "      <th>actors</th>\n",
       "      <th>wins_nominations</th>\n",
       "      <th>release_date</th>\n",
       "      <th>country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Gully Boy</td>\n",
       "      <td>tt2395469</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Gully_Boy</td>\n",
       "      <td>Gully Boy</td>\n",
       "      <td>Gully Boy</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>153</td>\n",
       "      <td>Drama|Music</td>\n",
       "      <td>8.2</td>\n",
       "      <td>22440</td>\n",
       "      <td>Gully Boy is a film about a 22-year-old boy \"M...</td>\n",
       "      <td>A coming-of-age story based on the lives of st...</td>\n",
       "      <td>Apna Time Aayega!</td>\n",
       "      <td>Ranveer Singh|Alia Bhatt|Siddhant Chaturvedi|V...</td>\n",
       "      <td>6 wins &amp; 3 nominations</td>\n",
       "      <td>14 February 2019 (USA)</td>\n",
       "      <td>india</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Yeh Hai India</td>\n",
       "      <td>tt5525846</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Yeh_Hai_India</td>\n",
       "      <td>Yeh Hai India</td>\n",
       "      <td>Yeh Hai India</td>\n",
       "      <td>0</td>\n",
       "      <td>2017</td>\n",
       "      <td>128</td>\n",
       "      <td>Action|Adventure|Drama</td>\n",
       "      <td>5.7</td>\n",
       "      <td>169</td>\n",
       "      <td>Yeh Hai India  follows the story of a 25 years...</td>\n",
       "      <td>Yeh Hai India  follows the story of a 25 years...</td>\n",
       "      <td>A Film for Every Indian</td>\n",
       "      <td>Gavie Chahal|Mohan Agashe|Mohan Joshi|Lom Harsh|</td>\n",
       "      <td>2 wins &amp; 1 nomination</td>\n",
       "      <td>24 May 2019 (India)</td>\n",
       "      <td>india</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          title_x    imdb_id  \\\n",
       "11      Gully Boy  tt2395469   \n",
       "34  Yeh Hai India  tt5525846   \n",
       "\n",
       "                                          poster_path  \\\n",
       "11  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "34  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "\n",
       "                                      wiki_link        title_y original_title  \\\n",
       "11      https://en.wikipedia.org/wiki/Gully_Boy      Gully Boy      Gully Boy   \n",
       "34  https://en.wikipedia.org/wiki/Yeh_Hai_India  Yeh Hai India  Yeh Hai India   \n",
       "\n",
       "    is_adult  year_of_release runtime                  genres  imdb_rating  \\\n",
       "11         0             2019     153             Drama|Music          8.2   \n",
       "34         0             2017     128  Action|Adventure|Drama          5.7   \n",
       "\n",
       "    imdb_votes                                              story  \\\n",
       "11       22440  Gully Boy is a film about a 22-year-old boy \"M...   \n",
       "34         169  Yeh Hai India  follows the story of a 25 years...   \n",
       "\n",
       "                                              summary  \\\n",
       "11  A coming-of-age story based on the lives of st...   \n",
       "34  Yeh Hai India  follows the story of a 25 years...   \n",
       "\n",
       "                    tagline  \\\n",
       "11        Apna Time Aayega!   \n",
       "34  A Film for Every Indian   \n",
       "\n",
       "                                               actors        wins_nominations  \\\n",
       "11  Ranveer Singh|Alia Bhatt|Siddhant Chaturvedi|V...  6 wins & 3 nominations   \n",
       "34   Gavie Chahal|Mohan Agashe|Mohan Joshi|Lom Harsh|   2 wins & 1 nomination   \n",
       "\n",
       "              release_date country  \n",
       "11  14 February 2019 (USA)   india  \n",
       "34     24 May 2019 (India)   india  "
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# from existing ones\n",
    "mmovies = movies.dropna()                                            #pandas treat missing value as float\n",
    "movies['lead actor'] = mmovies['actors'].str.split('|').apply(lambda x:x[0])\n",
    "mmovies.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Important DataFrame Functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 950 entries, 0 to 949\n",
      "Data columns (total 20 columns):\n",
      " #   Column           Non-Null Count  Dtype  \n",
      "---  ------           --------------  -----  \n",
      " 0   ID               950 non-null    int64  \n",
      " 1   City             899 non-null    object \n",
      " 2   Date             950 non-null    object \n",
      " 3   Season           950 non-null    object \n",
      " 4   MatchNumber      950 non-null    object \n",
      " 5   Team1            950 non-null    object \n",
      " 6   Team2            950 non-null    object \n",
      " 7   Venue            950 non-null    object \n",
      " 8   TossWinner       950 non-null    object \n",
      " 9   TossDecision     950 non-null    object \n",
      " 10  SuperOver        946 non-null    object \n",
      " 11  WinningTeam      946 non-null    object \n",
      " 12  WonBy            950 non-null    object \n",
      " 13  Margin           932 non-null    float64\n",
      " 14  method           19 non-null     object \n",
      " 15  Player_of_Match  946 non-null    object \n",
      " 16  Team1Players     950 non-null    object \n",
      " 17  Team2Players     950 non-null    object \n",
      " 18  Umpire1          950 non-null    object \n",
      " 19  Umpire2          950 non-null    object \n",
      "dtypes: float64(1), int64(1), object(18)\n",
      "memory usage: 148.6+ KB\n"
     ]
    }
   ],
   "source": [
    "# astype\n",
    "ipl.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "ipl['ID'] = ipl['ID'].astype('int32')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 950 entries, 0 to 949\n",
      "Data columns (total 20 columns):\n",
      " #   Column           Non-Null Count  Dtype  \n",
      "---  ------           --------------  -----  \n",
      " 0   ID               950 non-null    int32  \n",
      " 1   City             899 non-null    object \n",
      " 2   Date             950 non-null    object \n",
      " 3   Season           950 non-null    object \n",
      " 4   MatchNumber      950 non-null    object \n",
      " 5   Team1            950 non-null    object \n",
      " 6   Team2            950 non-null    object \n",
      " 7   Venue            950 non-null    object \n",
      " 8   TossWinner       950 non-null    object \n",
      " 9   TossDecision     950 non-null    object \n",
      " 10  SuperOver        946 non-null    object \n",
      " 11  WinningTeam      946 non-null    object \n",
      " 12  WonBy            950 non-null    object \n",
      " 13  Margin           932 non-null    float64\n",
      " 14  method           19 non-null     object \n",
      " 15  Player_of_Match  946 non-null    object \n",
      " 16  Team1Players     950 non-null    object \n",
      " 17  Team2Players     950 non-null    object \n",
      " 18  Umpire1          950 non-null    object \n",
      " 19  Umpire2          950 non-null    object \n",
      "dtypes: float64(1), int32(1), object(18)\n",
      "memory usage: 144.9+ KB\n"
     ]
    }
   ],
   "source": [
    "ipl.info()                             #memory usage reduced"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "ipl['Season'] = ipl['Season'].astype('category')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 950 entries, 0 to 949\n",
      "Data columns (total 20 columns):\n",
      " #   Column           Non-Null Count  Dtype   \n",
      "---  ------           --------------  -----   \n",
      " 0   ID               950 non-null    int32   \n",
      " 1   City             899 non-null    object  \n",
      " 2   Date             950 non-null    object  \n",
      " 3   Season           950 non-null    category\n",
      " 4   MatchNumber      950 non-null    object  \n",
      " 5   Team1            950 non-null    object  \n",
      " 6   Team2            950 non-null    object  \n",
      " 7   Venue            950 non-null    object  \n",
      " 8   TossWinner       950 non-null    object  \n",
      " 9   TossDecision     950 non-null    object  \n",
      " 10  SuperOver        946 non-null    object  \n",
      " 11  WinningTeam      946 non-null    object  \n",
      " 12  WonBy            950 non-null    object  \n",
      " 13  Margin           932 non-null    float64 \n",
      " 14  method           19 non-null     object  \n",
      " 15  Player_of_Match  946 non-null    object  \n",
      " 16  Team1Players     950 non-null    object  \n",
      " 17  Team2Players     950 non-null    object  \n",
      " 18  Umpire1          950 non-null    object  \n",
      " 19  Umpire2          950 non-null    object  \n",
      "dtypes: category(1), float64(1), int32(1), object(17)\n",
      "memory usage: 139.0+ KB\n"
     ]
    }
   ],
   "source": [
    "ipl.info()                            #again memory usuage reduced"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 950 entries, 0 to 949\n",
      "Data columns (total 20 columns):\n",
      " #   Column           Non-Null Count  Dtype   \n",
      "---  ------           --------------  -----   \n",
      " 0   ID               950 non-null    int32   \n",
      " 1   City             899 non-null    object  \n",
      " 2   Date             950 non-null    object  \n",
      " 3   Season           950 non-null    category\n",
      " 4   MatchNumber      950 non-null    object  \n",
      " 5   Team1            950 non-null    category\n",
      " 6   Team2            950 non-null    category\n",
      " 7   Venue            950 non-null    object  \n",
      " 8   TossWinner       950 non-null    object  \n",
      " 9   TossDecision     950 non-null    object  \n",
      " 10  SuperOver        946 non-null    object  \n",
      " 11  WinningTeam      946 non-null    object  \n",
      " 12  WonBy            950 non-null    object  \n",
      " 13  Margin           932 non-null    float64 \n",
      " 14  method           19 non-null     object  \n",
      " 15  Player_of_Match  946 non-null    object  \n",
      " 16  Team1Players     950 non-null    object  \n",
      " 17  Team2Players     950 non-null    object  \n",
      " 18  Umpire1          950 non-null    object  \n",
      " 19  Umpire2          950 non-null    object  \n",
      "dtypes: category(3), float64(1), int32(1), object(15)\n",
      "memory usage: 127.4+ KB\n"
     ]
    }
   ],
   "source": [
    "ipl['Team1'] = ipl['Team1'].astype('category')\n",
    "ipl['Team2'] = ipl['Team2'].astype('category')\n",
    "ipl.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# DATAFRAME METHODS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "# value_counts\n",
    "# sort_values\n",
    "# rank\n",
    "# sort index\n",
    "# set index\n",
    "# rename index -> rename\n",
    "# reset index\n",
    "# unique & nunique\n",
    "# isnull/notnull/hasnans\n",
    "# dropna\n",
    "# fillna\n",
    "# drop_duplicates\n",
    "# drop\n",
    "# apply\n",
    "# isin\n",
    "# corr\n",
    "# nlargest -> nsmallest\n",
    "# insert\n",
    "# copy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### value_counts:give frequency count of each unique items(Applicable to both series and dataframe)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DS    3\n",
       "ML    2\n",
       "DA    1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = pd.Series(['DS','ML','DA','DS','DS','ML']) #series\n",
    "a.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "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>iq</th>\n",
       "      <th>marks</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>90</td>\n",
       "      <td>70</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>120</td>\n",
       "      <td>100</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>80</td>\n",
       "      <td>70</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>80</td>\n",
       "      <td>70</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    iq  marks  package\n",
       "0  100     80       10\n",
       "1   90     70        7\n",
       "2  120    100       14\n",
       "3   80     70       14\n",
       "4   80     70       14"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "marks = pd.DataFrame([\n",
    "    [100,80,10],\n",
    "    [90,70,7],\n",
    "    [120,100,14],\n",
    "    [80,70,14],\n",
    "    [80,70,14]\n",
    "],columns=['iq','marks','package'])\n",
    "\n",
    "marks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "iq   marks  package\n",
       "80   70     14         2\n",
       "90   70     7          1\n",
       "100  80     10         1\n",
       "120  100    14         1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "marks.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14    3\n",
       "10    1\n",
       "7     1\n",
       "Name: package, dtype: int64"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "marks['package'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2014    110\n",
       "2015    105\n",
       "2003     99\n",
       "2005     97\n",
       "2017     96\n",
       "2016     94\n",
       "2013     94\n",
       "2010     92\n",
       "2006     85\n",
       "2011     84\n",
       "2007     84\n",
       "2012     83\n",
       "2018     79\n",
       "2004     79\n",
       "2002     76\n",
       "2019     75\n",
       "2008     73\n",
       "2009     63\n",
       "2001     61\n",
       "Name: year_of_release, dtype: int64"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies = pd.read_csv('movies.csv')\n",
    "movies['year_of_release'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>City</th>\n",
       "      <th>Date</th>\n",
       "      <th>Season</th>\n",
       "      <th>MatchNumber</th>\n",
       "      <th>Team1</th>\n",
       "      <th>Team2</th>\n",
       "      <th>Venue</th>\n",
       "      <th>TossWinner</th>\n",
       "      <th>TossDecision</th>\n",
       "      <th>SuperOver</th>\n",
       "      <th>WinningTeam</th>\n",
       "      <th>WonBy</th>\n",
       "      <th>Margin</th>\n",
       "      <th>method</th>\n",
       "      <th>Player_of_Match</th>\n",
       "      <th>Team1Players</th>\n",
       "      <th>Team2Players</th>\n",
       "      <th>Umpire1</th>\n",
       "      <th>Umpire2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1312200</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>2022-05-29</td>\n",
       "      <td>2022</td>\n",
       "      <td>Final</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>Narendra Modi Stadium, Ahmedabad</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>HH Pandya</td>\n",
       "      <td>['YBK Jaiswal', 'JC Buttler', 'SV Samson', 'D ...</td>\n",
       "      <td>['WP Saha', 'Shubman Gill', 'MS Wade', 'HH Pan...</td>\n",
       "      <td>CB Gaffaney</td>\n",
       "      <td>Nitin Menon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1312199</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>2022-05-27</td>\n",
       "      <td>2022</td>\n",
       "      <td>Qualifier 2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Narendra Modi Stadium, Ahmedabad</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>JC Buttler</td>\n",
       "      <td>['V Kohli', 'F du Plessis', 'RM Patidar', 'GJ ...</td>\n",
       "      <td>['YBK Jaiswal', 'JC Buttler', 'SV Samson', 'D ...</td>\n",
       "      <td>CB Gaffaney</td>\n",
       "      <td>Nitin Menon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1312198</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>2022-05-25</td>\n",
       "      <td>2022</td>\n",
       "      <td>Eliminator</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Lucknow Super Giants</td>\n",
       "      <td>Eden Gardens, Kolkata</td>\n",
       "      <td>Lucknow Super Giants</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Runs</td>\n",
       "      <td>14.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RM Patidar</td>\n",
       "      <td>['V Kohli', 'F du Plessis', 'RM Patidar', 'GJ ...</td>\n",
       "      <td>['Q de Kock', 'KL Rahul', 'M Vohra', 'DJ Hooda...</td>\n",
       "      <td>J Madanagopal</td>\n",
       "      <td>MA Gough</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1312197</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>2022-05-24</td>\n",
       "      <td>2022</td>\n",
       "      <td>Qualifier 1</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>Eden Gardens, Kolkata</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DA Miller</td>\n",
       "      <td>['YBK Jaiswal', 'JC Buttler', 'SV Samson', 'D ...</td>\n",
       "      <td>['WP Saha', 'Shubman Gill', 'MS Wade', 'HH Pan...</td>\n",
       "      <td>BNJ Oxenford</td>\n",
       "      <td>VK Sharma</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>1254117</td>\n",
       "      <td>Dubai</td>\n",
       "      <td>2021-10-15</td>\n",
       "      <td>2021</td>\n",
       "      <td>Final</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Dubai International Cricket Stadium</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Runs</td>\n",
       "      <td>27.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>F du Plessis</td>\n",
       "      <td>['RD Gaikwad', 'F du Plessis', 'RV Uthappa', '...</td>\n",
       "      <td>['Shubman Gill', 'VR Iyer', 'N Rana', 'SP Nari...</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>RK Illingworth</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>1254116</td>\n",
       "      <td>Sharjah</td>\n",
       "      <td>2021-10-13</td>\n",
       "      <td>2021</td>\n",
       "      <td>Qualifier 2</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Sharjah Cricket Stadium</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>VR Iyer</td>\n",
       "      <td>['PP Shaw', 'S Dhawan', 'MP Stoinis', 'SS Iyer...</td>\n",
       "      <td>['Shubman Gill', 'VR Iyer', 'N Rana', 'RA Trip...</td>\n",
       "      <td>KN Ananthapadmanabhan</td>\n",
       "      <td>MA Gough</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>1254115</td>\n",
       "      <td>Sharjah</td>\n",
       "      <td>2021-10-11</td>\n",
       "      <td>2021</td>\n",
       "      <td>Eliminator</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Sharjah Cricket Stadium</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SP Narine</td>\n",
       "      <td>['D Padikkal', 'V Kohli', 'KS Bharat', 'GJ Max...</td>\n",
       "      <td>['Shubman Gill', 'VR Iyer', 'RA Tripathi', 'N ...</td>\n",
       "      <td>CB Gaffaney</td>\n",
       "      <td>VK Sharma</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>1254114</td>\n",
       "      <td>Dubai</td>\n",
       "      <td>2021-10-10</td>\n",
       "      <td>2021</td>\n",
       "      <td>Qualifier 1</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Dubai International Cricket Stadium</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RD Gaikwad</td>\n",
       "      <td>['PP Shaw', 'S Dhawan', 'SS Iyer', 'AR Patel',...</td>\n",
       "      <td>['RD Gaikwad', 'F du Plessis', 'RV Uthappa', '...</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>RK Illingworth</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>1237181</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-11-10</td>\n",
       "      <td>2020/21</td>\n",
       "      <td>Final</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Dubai International Cricket Stadium</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TA Boult</td>\n",
       "      <td>['MP Stoinis', 'S Dhawan', 'AM Rahane', 'SS Iy...</td>\n",
       "      <td>['RG Sharma', 'Q de Kock', 'SA Yadav', 'Ishan ...</td>\n",
       "      <td>CB Gaffaney</td>\n",
       "      <td>Nitin Menon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>1237180</td>\n",
       "      <td>Abu Dhabi</td>\n",
       "      <td>2020-11-08</td>\n",
       "      <td>2020/21</td>\n",
       "      <td>Qualifier 2</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Sheikh Zayed Stadium</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Runs</td>\n",
       "      <td>17.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MP Stoinis</td>\n",
       "      <td>['MP Stoinis', 'S Dhawan', 'SS Iyer', 'SO Hetm...</td>\n",
       "      <td>['PK Garg', 'DA Warner', 'MK Pandey', 'KS Will...</td>\n",
       "      <td>PR Reiffel</td>\n",
       "      <td>S Ravi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>1237178</td>\n",
       "      <td>Abu Dhabi</td>\n",
       "      <td>2020-11-06</td>\n",
       "      <td>2020/21</td>\n",
       "      <td>Eliminator</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Sheikh Zayed Stadium</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>KS Williamson</td>\n",
       "      <td>['V Kohli', 'D Padikkal', 'AJ Finch', 'AB de V...</td>\n",
       "      <td>['DA Warner', 'SP Goswami', 'MK Pandey', 'KS W...</td>\n",
       "      <td>PR Reiffel</td>\n",
       "      <td>S Ravi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>1237177</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-11-05</td>\n",
       "      <td>2020/21</td>\n",
       "      <td>Qualifier 1</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Dubai International Cricket Stadium</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Runs</td>\n",
       "      <td>57.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>JJ Bumrah</td>\n",
       "      <td>['Q de Kock', 'RG Sharma', 'SA Yadav', 'Ishan ...</td>\n",
       "      <td>['PP Shaw', 'S Dhawan', 'AM Rahane', 'SS Iyer'...</td>\n",
       "      <td>CB Gaffaney</td>\n",
       "      <td>Nitin Menon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>1181768</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>2019-05-12</td>\n",
       "      <td>2019</td>\n",
       "      <td>Final</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Rajiv Gandhi International Stadium</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Runs</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>JJ Bumrah</td>\n",
       "      <td>['Q de Kock', 'RG Sharma', 'SA Yadav', 'Ishan ...</td>\n",
       "      <td>['F du Plessis', 'SR Watson', 'SK Raina', 'AT ...</td>\n",
       "      <td>IJ Gould</td>\n",
       "      <td>Nitin Menon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>1181767</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>2019-05-10</td>\n",
       "      <td>2019</td>\n",
       "      <td>Qualifier</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket St...</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>F du Plessis</td>\n",
       "      <td>['PP Shaw', 'S Dhawan', 'C Munro', 'SS Iyer', ...</td>\n",
       "      <td>['F du Plessis', 'SR Watson', 'SK Raina', 'AT ...</td>\n",
       "      <td>BNJ Oxenford</td>\n",
       "      <td>S Ravi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>1181766</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>2019-05-08</td>\n",
       "      <td>2019</td>\n",
       "      <td>Eliminator</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket St...</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RR Pant</td>\n",
       "      <td>['WP Saha', 'MJ Guptill', 'MK Pandey', 'KS Wil...</td>\n",
       "      <td>['PP Shaw', 'S Dhawan', 'SS Iyer', 'RR Pant', ...</td>\n",
       "      <td>BNJ Oxenford</td>\n",
       "      <td>S Ravi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>1181764</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>2019-05-07</td>\n",
       "      <td>2019</td>\n",
       "      <td>Qualifier</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>MA Chidambaram Stadium</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SA Yadav</td>\n",
       "      <td>['F du Plessis', 'SR Watson', 'SK Raina', 'M V...</td>\n",
       "      <td>['RG Sharma', 'Q de Kock', 'SA Yadav', 'Ishan ...</td>\n",
       "      <td>NJ Llong</td>\n",
       "      <td>Nitin Menon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>254</th>\n",
       "      <td>1136620</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2018-05-27</td>\n",
       "      <td>2018</td>\n",
       "      <td>Final</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SR Watson</td>\n",
       "      <td>['SP Goswami', 'S Dhawan', 'KS Williamson', 'S...</td>\n",
       "      <td>['SR Watson', 'F du Plessis', 'SK Raina', 'AT ...</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>S Ravi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>255</th>\n",
       "      <td>1136619</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>2018-05-25</td>\n",
       "      <td>2018</td>\n",
       "      <td>Qualifier</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Runs</td>\n",
       "      <td>14.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rashid Khan</td>\n",
       "      <td>['WP Saha', 'S Dhawan', 'KS Williamson', 'Shak...</td>\n",
       "      <td>['CA Lynn', 'SP Narine', 'N Rana', 'RV Uthappa...</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>Nitin Menon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256</th>\n",
       "      <td>1136618</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>2018-05-23</td>\n",
       "      <td>2018</td>\n",
       "      <td>Eliminator</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Runs</td>\n",
       "      <td>25.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AD Russell</td>\n",
       "      <td>['SP Narine', 'CA Lynn', 'RV Uthappa', 'N Rana...</td>\n",
       "      <td>['AM Rahane', 'RA Tripathi', 'SV Samson', 'H K...</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>Nitin Menon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>257</th>\n",
       "      <td>1136617</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2018-05-22</td>\n",
       "      <td>2018</td>\n",
       "      <td>Qualifier</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>F du Plessis</td>\n",
       "      <td>['S Dhawan', 'SP Goswami', 'KS Williamson', 'M...</td>\n",
       "      <td>['SR Watson', 'F du Plessis', 'SK Raina', 'AT ...</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>M Erasmus</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>314</th>\n",
       "      <td>1082650</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>2017-05-21</td>\n",
       "      <td>2017</td>\n",
       "      <td>Final</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Runs</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>KH Pandya</td>\n",
       "      <td>['LMP Simmons', 'PA Patel', 'AT Rayudu', 'RG S...</td>\n",
       "      <td>['AM Rahane', 'RA Tripathi', 'SPD Smith', 'MS ...</td>\n",
       "      <td>NJ Llong</td>\n",
       "      <td>S Ravi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>315</th>\n",
       "      <td>1082649</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>2017-05-19</td>\n",
       "      <td>2017</td>\n",
       "      <td>Qualifier 2</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>KV Sharma</td>\n",
       "      <td>['LMP Simmons', 'PA Patel', 'AT Rayudu', 'RG S...</td>\n",
       "      <td>['CA Lynn', 'SP Narine', 'G Gambhir', 'RV Utha...</td>\n",
       "      <td>NJ Llong</td>\n",
       "      <td>Nitin Menon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>316</th>\n",
       "      <td>1082648</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>2017-05-17</td>\n",
       "      <td>2017</td>\n",
       "      <td>Eliminator</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>7.0</td>\n",
       "      <td>D/L</td>\n",
       "      <td>NM Coulter-Nile</td>\n",
       "      <td>['DA Warner', 'S Dhawan', 'KS Williamson', 'Yu...</td>\n",
       "      <td>['RV Uthappa', 'CA Lynn', 'YK Pathan', 'G Gamb...</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>Nitin Menon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>317</th>\n",
       "      <td>1082647</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2017-05-16</td>\n",
       "      <td>2017</td>\n",
       "      <td>Qualifier 1</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Runs</td>\n",
       "      <td>20.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Washington Sundar</td>\n",
       "      <td>['LMP Simmons', 'PA Patel', 'RG Sharma', 'AT R...</td>\n",
       "      <td>['AM Rahane', 'RA Tripathi', 'SPD Smith', 'MK ...</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>373</th>\n",
       "      <td>981019</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>2016-05-29</td>\n",
       "      <td>2016</td>\n",
       "      <td>Final</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Runs</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BCJ Cutting</td>\n",
       "      <td>['CH Gayle', 'V Kohli', 'AB de Villiers', 'KL ...</td>\n",
       "      <td>['DA Warner', 'S Dhawan', 'MC Henriques', 'Yuv...</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>BNJ Oxenford</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>374</th>\n",
       "      <td>981017</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>2016-05-27</td>\n",
       "      <td>2016</td>\n",
       "      <td>Qualifier 2</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>['ER Dwivedi', 'BB McCullum', 'SK Raina', 'KD ...</td>\n",
       "      <td>['DA Warner', 'S Dhawan', 'MC Henriques', 'Yuv...</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>CK Nandan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>375</th>\n",
       "      <td>981015</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>2016-05-25</td>\n",
       "      <td>2016</td>\n",
       "      <td>Elimination Final</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Runs</td>\n",
       "      <td>22.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MC Henriques</td>\n",
       "      <td>['DA Warner', 'S Dhawan', 'MC Henriques', 'Yuv...</td>\n",
       "      <td>['RV Uthappa', 'G Gambhir', 'C Munro', 'MK Pan...</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>376</th>\n",
       "      <td>981013</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>2016-05-24</td>\n",
       "      <td>2016</td>\n",
       "      <td>Qualifier 1</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AB de Villiers</td>\n",
       "      <td>['AJ Finch', 'BB McCullum', 'SK Raina', 'KD Ka...</td>\n",
       "      <td>['CH Gayle', 'V Kohli', 'AB de Villiers', 'KL ...</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>433</th>\n",
       "      <td>829823</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>2015-05-24</td>\n",
       "      <td>2015</td>\n",
       "      <td>Final</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Runs</td>\n",
       "      <td>41.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RG Sharma</td>\n",
       "      <td>['LMP Simmons', 'PA Patel', 'RG Sharma', 'KA P...</td>\n",
       "      <td>['DR Smith', 'MEK Hussey', 'SK Raina', 'MS Dho...</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>RK Illingworth</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>434</th>\n",
       "      <td>829821</td>\n",
       "      <td>Ranchi</td>\n",
       "      <td>2015-05-22</td>\n",
       "      <td>2015</td>\n",
       "      <td>Qualifier 2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>JSCA International Stadium Complex</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A Nehra</td>\n",
       "      <td>['DR Smith', 'MEK Hussey', 'F du Plessis', 'SK...</td>\n",
       "      <td>['CH Gayle', 'V Kohli', 'AB de Villiers', 'Man...</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>CB Gaffaney</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>435</th>\n",
       "      <td>829819</td>\n",
       "      <td>Pune</td>\n",
       "      <td>2015-05-20</td>\n",
       "      <td>2015</td>\n",
       "      <td>Eliminator</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Maharashtra Cricket Association Stadium</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Runs</td>\n",
       "      <td>71.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AB de Villiers</td>\n",
       "      <td>['CH Gayle', 'V Kohli', 'AB de Villiers', 'Man...</td>\n",
       "      <td>['AM Rahane', 'SR Watson', 'SV Samson', 'SPD S...</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>829817</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2015-05-19</td>\n",
       "      <td>2015</td>\n",
       "      <td>Qualifier 1</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Runs</td>\n",
       "      <td>25.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>KA Pollard</td>\n",
       "      <td>['DR Smith', 'MEK Hussey', 'F du Plessis', 'SK...</td>\n",
       "      <td>['LMP Simmons', 'PA Patel', 'RG Sharma', 'KA P...</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>RK Illingworth</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>492</th>\n",
       "      <td>734049</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>2014-06-01</td>\n",
       "      <td>2014</td>\n",
       "      <td>Final</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MK Pandey</td>\n",
       "      <td>['RV Uthappa', 'G Gambhir', 'MK Pandey', 'YK P...</td>\n",
       "      <td>['V Sehwag', 'M Vohra', 'GJ Bailey', 'WP Saha'...</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>BNJ Oxenford</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>734047</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2014-05-30</td>\n",
       "      <td>2014</td>\n",
       "      <td>Qualifier 2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Runs</td>\n",
       "      <td>24.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>V Sehwag</td>\n",
       "      <td>['DR Smith', 'F du Plessis', 'SK Raina', 'BB M...</td>\n",
       "      <td>['V Sehwag', 'M Vohra', 'GJ Maxwell', 'DA Mill...</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>RJ Tucker</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>494</th>\n",
       "      <td>734045</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2014-05-28</td>\n",
       "      <td>2014</td>\n",
       "      <td>Eliminator</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Brabourne Stadium</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SK Raina</td>\n",
       "      <td>['DR Smith', 'F du Plessis', 'SK Raina', 'BB M...</td>\n",
       "      <td>['LMP Simmons', 'MEK Hussey', 'CJ Anderson', '...</td>\n",
       "      <td>VA Kulkarni</td>\n",
       "      <td>BNJ Oxenford</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>495</th>\n",
       "      <td>734043</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>2014-05-27</td>\n",
       "      <td>2014</td>\n",
       "      <td>Qualifier 1</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Runs</td>\n",
       "      <td>28.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UT Yadav</td>\n",
       "      <td>['V Sehwag', 'M Vohra', 'WP Saha', 'GJ Maxwell...</td>\n",
       "      <td>['RV Uthappa', 'G Gambhir', 'MK Pandey', 'Shak...</td>\n",
       "      <td>NJ Llong</td>\n",
       "      <td>S Ravi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>552</th>\n",
       "      <td>598073</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>2013-05-26</td>\n",
       "      <td>2013</td>\n",
       "      <td>Final</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Runs</td>\n",
       "      <td>23.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>KA Pollard</td>\n",
       "      <td>['MEK Hussey', 'M Vijay', 'SK Raina', 'S Badri...</td>\n",
       "      <td>['DR Smith', 'AP Tare', 'KD Karthik', 'RG Shar...</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>SJA Taufel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>553</th>\n",
       "      <td>598072</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>2013-05-24</td>\n",
       "      <td>2013</td>\n",
       "      <td>Qualifier 2</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Harbhajan Singh</td>\n",
       "      <td>['DR Smith', 'AP Tare', 'KD Karthik', 'RG Shar...</td>\n",
       "      <td>['R Dravid', 'AM Rahane', 'SR Watson', 'SV Sam...</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>SJA Taufel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>554</th>\n",
       "      <td>598071</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>2013-05-22</td>\n",
       "      <td>2013</td>\n",
       "      <td>Eliminator</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BJ Hodge</td>\n",
       "      <td>['R Dravid', 'AM Rahane', 'SR Watson', 'DH Yag...</td>\n",
       "      <td>['PA Patel', 'S Dhawan', 'GH Vihari', 'CL Whit...</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>RJ Tucker</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>555</th>\n",
       "      <td>598070</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>2013-05-21</td>\n",
       "      <td>2013</td>\n",
       "      <td>Qualifier 1</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Runs</td>\n",
       "      <td>48.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MEK Hussey</td>\n",
       "      <td>['MEK Hussey', 'M Vijay', 'SK Raina', 'MS Dhon...</td>\n",
       "      <td>['DR Smith', 'AP Tare', 'KD Karthik', 'RG Shar...</td>\n",
       "      <td>NJ Llong</td>\n",
       "      <td>RJ Tucker</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>628</th>\n",
       "      <td>548381</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>2012-05-27</td>\n",
       "      <td>2012</td>\n",
       "      <td>Final</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>MA Chidambaram Stadium, Chepauk</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MS Bisla</td>\n",
       "      <td>['MS Bisla', 'G Gambhir', 'JH Kallis', 'LR Shu...</td>\n",
       "      <td>['MEK Hussey', 'M Vijay', 'SK Raina', 'MS Dhon...</td>\n",
       "      <td>BF Bowden</td>\n",
       "      <td>SJA Taufel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>629</th>\n",
       "      <td>548380</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>2012-05-25</td>\n",
       "      <td>2012</td>\n",
       "      <td>Qualifier 2</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>MA Chidambaram Stadium, Chepauk</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Runs</td>\n",
       "      <td>86.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>M Vijay</td>\n",
       "      <td>['DPMD Jayawardene', 'DA Warner', 'V Sehwag', ...</td>\n",
       "      <td>['M Vijay', 'MEK Hussey', 'SK Raina', 'MS Dhon...</td>\n",
       "      <td>BR Doctrove</td>\n",
       "      <td>SJA Taufel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>630</th>\n",
       "      <td>548379</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>2012-05-23</td>\n",
       "      <td>2012</td>\n",
       "      <td>Elimination Final</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Runs</td>\n",
       "      <td>38.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MS Dhoni</td>\n",
       "      <td>['M Vijay', 'MEK Hussey', 'SK Raina', 'S Badri...</td>\n",
       "      <td>['SR Tendulkar', 'DR Smith', 'RG Sharma', 'KD ...</td>\n",
       "      <td>BF Bowden</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>631</th>\n",
       "      <td>548378</td>\n",
       "      <td>Pune</td>\n",
       "      <td>2012-05-22</td>\n",
       "      <td>2012</td>\n",
       "      <td>Qualifier 1</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Subrata Roy Sahara Stadium</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Runs</td>\n",
       "      <td>18.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>YK Pathan</td>\n",
       "      <td>['DA Warner', 'V Sehwag', 'NV Ojha', 'DPMD Jay...</td>\n",
       "      <td>['BB McCullum', 'G Gambhir', 'JH Kallis', 'Sha...</td>\n",
       "      <td>BR Doctrove</td>\n",
       "      <td>SJA Taufel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>702</th>\n",
       "      <td>501271</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>2011-05-28</td>\n",
       "      <td>2011</td>\n",
       "      <td>Final</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>MA Chidambaram Stadium, Chepauk</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Runs</td>\n",
       "      <td>58.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>M Vijay</td>\n",
       "      <td>['MEK Hussey', 'M Vijay', 'MS Dhoni', 'SK Rain...</td>\n",
       "      <td>['MA Agarwal', 'CH Gayle', 'V Kohli', 'AB de V...</td>\n",
       "      <td>Asad Rauf</td>\n",
       "      <td>SJA Taufel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>703</th>\n",
       "      <td>501270</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>2011-05-27</td>\n",
       "      <td>2011</td>\n",
       "      <td>Qualifier 2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>MA Chidambaram Stadium, Chepauk</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Runs</td>\n",
       "      <td>43.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CH Gayle</td>\n",
       "      <td>['MA Agarwal', 'CH Gayle', 'V Kohli', 'AB de V...</td>\n",
       "      <td>['AC Blizzard', 'SR Tendulkar', 'Harbhajan Sin...</td>\n",
       "      <td>Asad Rauf</td>\n",
       "      <td>SJA Taufel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>704</th>\n",
       "      <td>501269</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2011-05-25</td>\n",
       "      <td>2011</td>\n",
       "      <td>Elimination Final</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MM Patel</td>\n",
       "      <td>['AC Blizzard', 'SR Tendulkar', 'RG Sharma', '...</td>\n",
       "      <td>['G Gambhir', 'JH Kallis', 'SP Goswami', 'MK T...</td>\n",
       "      <td>Asad Rauf</td>\n",
       "      <td>SJA Taufel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>705</th>\n",
       "      <td>501268</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2011-05-24</td>\n",
       "      <td>2011</td>\n",
       "      <td>Qualifier 1</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SK Raina</td>\n",
       "      <td>['MA Agarwal', 'CH Gayle', 'V Kohli', 'AB de V...</td>\n",
       "      <td>['MEK Hussey', 'M Vijay', 'SK Raina', 'S Badri...</td>\n",
       "      <td>Asad Rauf</td>\n",
       "      <td>SJA Taufel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>775</th>\n",
       "      <td>419165</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2010-04-25</td>\n",
       "      <td>2009/10</td>\n",
       "      <td>Final</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Dr DY Patil Sports Academy</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Runs</td>\n",
       "      <td>22.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SK Raina</td>\n",
       "      <td>['M Vijay', 'ML Hayden', 'SK Raina', 'S Badrin...</td>\n",
       "      <td>['S Dhawan', 'SR Tendulkar', 'AM Nayar', 'Harb...</td>\n",
       "      <td>RE Koertzen</td>\n",
       "      <td>SJA Taufel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>776</th>\n",
       "      <td>419164</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2010-04-24</td>\n",
       "      <td>2009/10</td>\n",
       "      <td>3rd Place Play-Off</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>Dr DY Patil Sports Academy</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A Kumble</td>\n",
       "      <td>['JH Kallis', 'R Dravid', 'KP Pietersen', 'RV ...</td>\n",
       "      <td>['AC Gilchrist', 'MD Mishra', 'Anirudh Singh',...</td>\n",
       "      <td>RE Koertzen</td>\n",
       "      <td>SJA Taufel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>777</th>\n",
       "      <td>419163</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2010-04-22</td>\n",
       "      <td>2009/10</td>\n",
       "      <td>Semi Final</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>Dr DY Patil Sports Academy</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Runs</td>\n",
       "      <td>38.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DE Bollinger</td>\n",
       "      <td>['M Vijay', 'ML Hayden', 'SK Raina', 'S Badrin...</td>\n",
       "      <td>['AC Gilchrist', 'HH Gibbs', 'TL Suman', 'RG S...</td>\n",
       "      <td>BR Doctrove</td>\n",
       "      <td>RB Tiffin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>778</th>\n",
       "      <td>419162</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2010-04-21</td>\n",
       "      <td>2009/10</td>\n",
       "      <td>Semi Final</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Dr DY Patil Sports Academy</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Runs</td>\n",
       "      <td>35.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>KA Pollard</td>\n",
       "      <td>['JH Kallis', 'R Dravid', 'KP Pietersen', 'RV ...</td>\n",
       "      <td>['S Dhawan', 'SR Tendulkar', 'AM Nayar', 'AT R...</td>\n",
       "      <td>BR Doctrove</td>\n",
       "      <td>RB Tiffin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>835</th>\n",
       "      <td>392239</td>\n",
       "      <td>Johannesburg</td>\n",
       "      <td>2009-05-24</td>\n",
       "      <td>2009</td>\n",
       "      <td>Final</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>New Wanderers Stadium</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>Runs</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A Kumble</td>\n",
       "      <td>['JH Kallis', 'MK Pandey', 'RE van der Merwe',...</td>\n",
       "      <td>['AC Gilchrist', 'HH Gibbs', 'TL Suman', 'A Sy...</td>\n",
       "      <td>RE Koertzen</td>\n",
       "      <td>SJA Taufel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>836</th>\n",
       "      <td>392238</td>\n",
       "      <td>Johannesburg</td>\n",
       "      <td>2009-05-23</td>\n",
       "      <td>2009</td>\n",
       "      <td>Semi Final</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>New Wanderers Stadium</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MK Pandey</td>\n",
       "      <td>['JH Kallis', 'MK Pandey', 'RE van der Merwe',...</td>\n",
       "      <td>['PA Patel', 'ML Hayden', 'MS Dhoni', 'SK Rain...</td>\n",
       "      <td>RE Koertzen</td>\n",
       "      <td>SJA Taufel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>837</th>\n",
       "      <td>392237</td>\n",
       "      <td>Centurion</td>\n",
       "      <td>2009-05-22</td>\n",
       "      <td>2009</td>\n",
       "      <td>Semi Final</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>SuperSport Park</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AC Gilchrist</td>\n",
       "      <td>['G Gambhir', 'DA Warner', 'V Sehwag', 'TM Dil...</td>\n",
       "      <td>['AC Gilchrist', 'HH Gibbs', 'AA Bilakhia', 'T...</td>\n",
       "      <td>BR Doctrove</td>\n",
       "      <td>DJ Harper</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>892</th>\n",
       "      <td>336040</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2008-06-01</td>\n",
       "      <td>2007/08</td>\n",
       "      <td>Final</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Dr DY Patil Sports Academy</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>YK Pathan</td>\n",
       "      <td>['PA Patel', 'S Vidyut', 'SK Raina', 'JA Morke...</td>\n",
       "      <td>['NK Patel', 'SA Asnodkar', 'Kamran Akmal', 'S...</td>\n",
       "      <td>BF Bowden</td>\n",
       "      <td>RE Koertzen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>893</th>\n",
       "      <td>336039</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2008-05-31</td>\n",
       "      <td>2007/08</td>\n",
       "      <td>Semi Final</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>bat</td>\n",
       "      <td>N</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Wickets</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>M Ntini</td>\n",
       "      <td>['PA Patel', 'S Vidyut', 'SK Raina', 'MS Dhoni...</td>\n",
       "      <td>['SE Marsh', 'JR Hopes', 'KC Sangakkara', 'Yuv...</td>\n",
       "      <td>Asad Rauf</td>\n",
       "      <td>DJ Harper</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>894</th>\n",
       "      <td>336038</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2008-05-30</td>\n",
       "      <td>2007/08</td>\n",
       "      <td>Semi Final</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>field</td>\n",
       "      <td>N</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Runs</td>\n",
       "      <td>105.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SR Watson</td>\n",
       "      <td>['G Gambhir', 'V Sehwag', 'S Dhawan', 'MK Tiwa...</td>\n",
       "      <td>['GC Smith', 'SA Asnodkar', 'Sohail Tanvir', '...</td>\n",
       "      <td>BF Bowden</td>\n",
       "      <td>RE Koertzen</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          ID           City        Date   Season         MatchNumber  \\\n",
       "0    1312200      Ahmedabad  2022-05-29     2022               Final   \n",
       "1    1312199      Ahmedabad  2022-05-27     2022         Qualifier 2   \n",
       "2    1312198        Kolkata  2022-05-25     2022          Eliminator   \n",
       "3    1312197        Kolkata  2022-05-24     2022         Qualifier 1   \n",
       "74   1254117          Dubai  2021-10-15     2021               Final   \n",
       "75   1254116        Sharjah  2021-10-13     2021         Qualifier 2   \n",
       "76   1254115        Sharjah  2021-10-11     2021          Eliminator   \n",
       "77   1254114          Dubai  2021-10-10     2021         Qualifier 1   \n",
       "134  1237181            NaN  2020-11-10  2020/21               Final   \n",
       "135  1237180      Abu Dhabi  2020-11-08  2020/21         Qualifier 2   \n",
       "136  1237178      Abu Dhabi  2020-11-06  2020/21          Eliminator   \n",
       "137  1237177            NaN  2020-11-05  2020/21         Qualifier 1   \n",
       "194  1181768      Hyderabad  2019-05-12     2019               Final   \n",
       "195  1181767  Visakhapatnam  2019-05-10     2019           Qualifier   \n",
       "196  1181766  Visakhapatnam  2019-05-08     2019          Eliminator   \n",
       "197  1181764        Chennai  2019-05-07     2019           Qualifier   \n",
       "254  1136620         Mumbai  2018-05-27     2018               Final   \n",
       "255  1136619        Kolkata  2018-05-25     2018           Qualifier   \n",
       "256  1136618        Kolkata  2018-05-23     2018          Eliminator   \n",
       "257  1136617         Mumbai  2018-05-22     2018           Qualifier   \n",
       "314  1082650      Hyderabad  2017-05-21     2017               Final   \n",
       "315  1082649      Bangalore  2017-05-19     2017         Qualifier 2   \n",
       "316  1082648      Bangalore  2017-05-17     2017          Eliminator   \n",
       "317  1082647         Mumbai  2017-05-16     2017         Qualifier 1   \n",
       "373   981019      Bangalore  2016-05-29     2016               Final   \n",
       "374   981017          Delhi  2016-05-27     2016         Qualifier 2   \n",
       "375   981015          Delhi  2016-05-25     2016   Elimination Final   \n",
       "376   981013      Bangalore  2016-05-24     2016         Qualifier 1   \n",
       "433   829823        Kolkata  2015-05-24     2015               Final   \n",
       "434   829821         Ranchi  2015-05-22     2015         Qualifier 2   \n",
       "435   829819           Pune  2015-05-20     2015          Eliminator   \n",
       "436   829817         Mumbai  2015-05-19     2015         Qualifier 1   \n",
       "492   734049      Bangalore  2014-06-01     2014               Final   \n",
       "493   734047         Mumbai  2014-05-30     2014         Qualifier 2   \n",
       "494   734045         Mumbai  2014-05-28     2014          Eliminator   \n",
       "495   734043        Kolkata  2014-05-27     2014         Qualifier 1   \n",
       "552   598073        Kolkata  2013-05-26     2013               Final   \n",
       "553   598072        Kolkata  2013-05-24     2013         Qualifier 2   \n",
       "554   598071          Delhi  2013-05-22     2013          Eliminator   \n",
       "555   598070          Delhi  2013-05-21     2013         Qualifier 1   \n",
       "628   548381        Chennai  2012-05-27     2012               Final   \n",
       "629   548380        Chennai  2012-05-25     2012         Qualifier 2   \n",
       "630   548379      Bangalore  2012-05-23     2012   Elimination Final   \n",
       "631   548378           Pune  2012-05-22     2012         Qualifier 1   \n",
       "702   501271        Chennai  2011-05-28     2011               Final   \n",
       "703   501270        Chennai  2011-05-27     2011         Qualifier 2   \n",
       "704   501269         Mumbai  2011-05-25     2011   Elimination Final   \n",
       "705   501268         Mumbai  2011-05-24     2011         Qualifier 1   \n",
       "775   419165         Mumbai  2010-04-25  2009/10               Final   \n",
       "776   419164         Mumbai  2010-04-24  2009/10  3rd Place Play-Off   \n",
       "777   419163         Mumbai  2010-04-22  2009/10          Semi Final   \n",
       "778   419162         Mumbai  2010-04-21  2009/10          Semi Final   \n",
       "835   392239   Johannesburg  2009-05-24     2009               Final   \n",
       "836   392238   Johannesburg  2009-05-23     2009          Semi Final   \n",
       "837   392237      Centurion  2009-05-22     2009          Semi Final   \n",
       "892   336040         Mumbai  2008-06-01  2007/08               Final   \n",
       "893   336039         Mumbai  2008-05-31  2007/08          Semi Final   \n",
       "894   336038         Mumbai  2008-05-30  2007/08          Semi Final   \n",
       "\n",
       "                           Team1                        Team2  \\\n",
       "0               Rajasthan Royals               Gujarat Titans   \n",
       "1    Royal Challengers Bangalore             Rajasthan Royals   \n",
       "2    Royal Challengers Bangalore         Lucknow Super Giants   \n",
       "3               Rajasthan Royals               Gujarat Titans   \n",
       "74           Chennai Super Kings        Kolkata Knight Riders   \n",
       "75                Delhi Capitals        Kolkata Knight Riders   \n",
       "76   Royal Challengers Bangalore        Kolkata Knight Riders   \n",
       "77                Delhi Capitals          Chennai Super Kings   \n",
       "134               Delhi Capitals               Mumbai Indians   \n",
       "135               Delhi Capitals          Sunrisers Hyderabad   \n",
       "136  Royal Challengers Bangalore          Sunrisers Hyderabad   \n",
       "137               Mumbai Indians               Delhi Capitals   \n",
       "194               Mumbai Indians          Chennai Super Kings   \n",
       "195               Delhi Capitals          Chennai Super Kings   \n",
       "196          Sunrisers Hyderabad               Delhi Capitals   \n",
       "197          Chennai Super Kings               Mumbai Indians   \n",
       "254          Sunrisers Hyderabad          Chennai Super Kings   \n",
       "255          Sunrisers Hyderabad        Kolkata Knight Riders   \n",
       "256        Kolkata Knight Riders             Rajasthan Royals   \n",
       "257          Sunrisers Hyderabad          Chennai Super Kings   \n",
       "314               Mumbai Indians       Rising Pune Supergiant   \n",
       "315               Mumbai Indians        Kolkata Knight Riders   \n",
       "316          Sunrisers Hyderabad        Kolkata Knight Riders   \n",
       "317               Mumbai Indians       Rising Pune Supergiant   \n",
       "373  Royal Challengers Bangalore          Sunrisers Hyderabad   \n",
       "374                Gujarat Lions          Sunrisers Hyderabad   \n",
       "375          Sunrisers Hyderabad        Kolkata Knight Riders   \n",
       "376                Gujarat Lions  Royal Challengers Bangalore   \n",
       "433               Mumbai Indians          Chennai Super Kings   \n",
       "434          Chennai Super Kings  Royal Challengers Bangalore   \n",
       "435  Royal Challengers Bangalore             Rajasthan Royals   \n",
       "436          Chennai Super Kings               Mumbai Indians   \n",
       "492        Kolkata Knight Riders              Kings XI Punjab   \n",
       "493          Chennai Super Kings              Kings XI Punjab   \n",
       "494          Chennai Super Kings               Mumbai Indians   \n",
       "495              Kings XI Punjab        Kolkata Knight Riders   \n",
       "552          Chennai Super Kings               Mumbai Indians   \n",
       "553               Mumbai Indians             Rajasthan Royals   \n",
       "554             Rajasthan Royals          Sunrisers Hyderabad   \n",
       "555          Chennai Super Kings               Mumbai Indians   \n",
       "628        Kolkata Knight Riders          Chennai Super Kings   \n",
       "629             Delhi Daredevils          Chennai Super Kings   \n",
       "630          Chennai Super Kings               Mumbai Indians   \n",
       "631             Delhi Daredevils        Kolkata Knight Riders   \n",
       "702          Chennai Super Kings  Royal Challengers Bangalore   \n",
       "703  Royal Challengers Bangalore               Mumbai Indians   \n",
       "704               Mumbai Indians        Kolkata Knight Riders   \n",
       "705  Royal Challengers Bangalore          Chennai Super Kings   \n",
       "775          Chennai Super Kings               Mumbai Indians   \n",
       "776  Royal Challengers Bangalore              Deccan Chargers   \n",
       "777          Chennai Super Kings              Deccan Chargers   \n",
       "778  Royal Challengers Bangalore               Mumbai Indians   \n",
       "835  Royal Challengers Bangalore              Deccan Chargers   \n",
       "836  Royal Challengers Bangalore          Chennai Super Kings   \n",
       "837             Delhi Daredevils              Deccan Chargers   \n",
       "892          Chennai Super Kings             Rajasthan Royals   \n",
       "893          Chennai Super Kings              Kings XI Punjab   \n",
       "894             Delhi Daredevils             Rajasthan Royals   \n",
       "\n",
       "                                                 Venue  \\\n",
       "0                     Narendra Modi Stadium, Ahmedabad   \n",
       "1                     Narendra Modi Stadium, Ahmedabad   \n",
       "2                                Eden Gardens, Kolkata   \n",
       "3                                Eden Gardens, Kolkata   \n",
       "74                 Dubai International Cricket Stadium   \n",
       "75                             Sharjah Cricket Stadium   \n",
       "76                             Sharjah Cricket Stadium   \n",
       "77                 Dubai International Cricket Stadium   \n",
       "134                Dubai International Cricket Stadium   \n",
       "135                               Sheikh Zayed Stadium   \n",
       "136                               Sheikh Zayed Stadium   \n",
       "137                Dubai International Cricket Stadium   \n",
       "194                 Rajiv Gandhi International Stadium   \n",
       "195  Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket St...   \n",
       "196  Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket St...   \n",
       "197                             MA Chidambaram Stadium   \n",
       "254                                   Wankhede Stadium   \n",
       "255                                       Eden Gardens   \n",
       "256                                       Eden Gardens   \n",
       "257                                   Wankhede Stadium   \n",
       "314          Rajiv Gandhi International Stadium, Uppal   \n",
       "315                              M Chinnaswamy Stadium   \n",
       "316                              M Chinnaswamy Stadium   \n",
       "317                                   Wankhede Stadium   \n",
       "373                              M Chinnaswamy Stadium   \n",
       "374                                   Feroz Shah Kotla   \n",
       "375                                   Feroz Shah Kotla   \n",
       "376                              M Chinnaswamy Stadium   \n",
       "433                                       Eden Gardens   \n",
       "434                 JSCA International Stadium Complex   \n",
       "435            Maharashtra Cricket Association Stadium   \n",
       "436                                   Wankhede Stadium   \n",
       "492                              M Chinnaswamy Stadium   \n",
       "493                                   Wankhede Stadium   \n",
       "494                                  Brabourne Stadium   \n",
       "495                                       Eden Gardens   \n",
       "552                                       Eden Gardens   \n",
       "553                                       Eden Gardens   \n",
       "554                                   Feroz Shah Kotla   \n",
       "555                                   Feroz Shah Kotla   \n",
       "628                    MA Chidambaram Stadium, Chepauk   \n",
       "629                    MA Chidambaram Stadium, Chepauk   \n",
       "630                              M Chinnaswamy Stadium   \n",
       "631                         Subrata Roy Sahara Stadium   \n",
       "702                    MA Chidambaram Stadium, Chepauk   \n",
       "703                    MA Chidambaram Stadium, Chepauk   \n",
       "704                                   Wankhede Stadium   \n",
       "705                                   Wankhede Stadium   \n",
       "775                         Dr DY Patil Sports Academy   \n",
       "776                         Dr DY Patil Sports Academy   \n",
       "777                         Dr DY Patil Sports Academy   \n",
       "778                         Dr DY Patil Sports Academy   \n",
       "835                              New Wanderers Stadium   \n",
       "836                              New Wanderers Stadium   \n",
       "837                                    SuperSport Park   \n",
       "892                         Dr DY Patil Sports Academy   \n",
       "893                                   Wankhede Stadium   \n",
       "894                                   Wankhede Stadium   \n",
       "\n",
       "                      TossWinner TossDecision SuperOver  \\\n",
       "0               Rajasthan Royals          bat         N   \n",
       "1               Rajasthan Royals        field         N   \n",
       "2           Lucknow Super Giants        field         N   \n",
       "3                 Gujarat Titans        field         N   \n",
       "74         Kolkata Knight Riders        field         N   \n",
       "75         Kolkata Knight Riders        field         N   \n",
       "76   Royal Challengers Bangalore          bat         N   \n",
       "77           Chennai Super Kings        field         N   \n",
       "134               Delhi Capitals          bat         N   \n",
       "135               Delhi Capitals          bat         N   \n",
       "136          Sunrisers Hyderabad        field         N   \n",
       "137               Delhi Capitals        field         N   \n",
       "194               Mumbai Indians          bat         N   \n",
       "195          Chennai Super Kings        field         N   \n",
       "196               Delhi Capitals        field         N   \n",
       "197          Chennai Super Kings          bat         N   \n",
       "254          Chennai Super Kings        field         N   \n",
       "255        Kolkata Knight Riders        field         N   \n",
       "256             Rajasthan Royals        field         N   \n",
       "257          Chennai Super Kings        field         N   \n",
       "314               Mumbai Indians          bat         N   \n",
       "315               Mumbai Indians        field         N   \n",
       "316        Kolkata Knight Riders        field         N   \n",
       "317               Mumbai Indians        field         N   \n",
       "373          Sunrisers Hyderabad          bat         N   \n",
       "374          Sunrisers Hyderabad        field         N   \n",
       "375        Kolkata Knight Riders        field         N   \n",
       "376  Royal Challengers Bangalore        field         N   \n",
       "433          Chennai Super Kings        field         N   \n",
       "434          Chennai Super Kings        field         N   \n",
       "435  Royal Challengers Bangalore          bat         N   \n",
       "436               Mumbai Indians          bat         N   \n",
       "492        Kolkata Knight Riders        field         N   \n",
       "493          Chennai Super Kings        field         N   \n",
       "494          Chennai Super Kings        field         N   \n",
       "495              Kings XI Punjab        field         N   \n",
       "552               Mumbai Indians          bat         N   \n",
       "553             Rajasthan Royals          bat         N   \n",
       "554          Sunrisers Hyderabad          bat         N   \n",
       "555          Chennai Super Kings          bat         N   \n",
       "628          Chennai Super Kings          bat         N   \n",
       "629             Delhi Daredevils        field         N   \n",
       "630               Mumbai Indians        field         N   \n",
       "631        Kolkata Knight Riders          bat         N   \n",
       "702          Chennai Super Kings          bat         N   \n",
       "703               Mumbai Indians        field         N   \n",
       "704               Mumbai Indians        field         N   \n",
       "705          Chennai Super Kings        field         N   \n",
       "775          Chennai Super Kings          bat         N   \n",
       "776              Deccan Chargers          bat         N   \n",
       "777          Chennai Super Kings          bat         N   \n",
       "778               Mumbai Indians          bat         N   \n",
       "835  Royal Challengers Bangalore        field         N   \n",
       "836  Royal Challengers Bangalore        field         N   \n",
       "837              Deccan Chargers        field         N   \n",
       "892             Rajasthan Royals        field         N   \n",
       "893              Kings XI Punjab          bat         N   \n",
       "894             Delhi Daredevils        field         N   \n",
       "\n",
       "                     WinningTeam    WonBy  Margin method    Player_of_Match  \\\n",
       "0                 Gujarat Titans  Wickets     7.0    NaN          HH Pandya   \n",
       "1               Rajasthan Royals  Wickets     7.0    NaN         JC Buttler   \n",
       "2    Royal Challengers Bangalore     Runs    14.0    NaN         RM Patidar   \n",
       "3                 Gujarat Titans  Wickets     7.0    NaN          DA Miller   \n",
       "74           Chennai Super Kings     Runs    27.0    NaN       F du Plessis   \n",
       "75         Kolkata Knight Riders  Wickets     3.0    NaN            VR Iyer   \n",
       "76         Kolkata Knight Riders  Wickets     4.0    NaN          SP Narine   \n",
       "77           Chennai Super Kings  Wickets     4.0    NaN         RD Gaikwad   \n",
       "134               Mumbai Indians  Wickets     5.0    NaN           TA Boult   \n",
       "135               Delhi Capitals     Runs    17.0    NaN         MP Stoinis   \n",
       "136          Sunrisers Hyderabad  Wickets     6.0    NaN      KS Williamson   \n",
       "137               Mumbai Indians     Runs    57.0    NaN          JJ Bumrah   \n",
       "194               Mumbai Indians     Runs     1.0    NaN          JJ Bumrah   \n",
       "195          Chennai Super Kings  Wickets     6.0    NaN       F du Plessis   \n",
       "196               Delhi Capitals  Wickets     2.0    NaN            RR Pant   \n",
       "197               Mumbai Indians  Wickets     6.0    NaN           SA Yadav   \n",
       "254          Chennai Super Kings  Wickets     8.0    NaN          SR Watson   \n",
       "255          Sunrisers Hyderabad     Runs    14.0    NaN        Rashid Khan   \n",
       "256        Kolkata Knight Riders     Runs    25.0    NaN         AD Russell   \n",
       "257          Chennai Super Kings  Wickets     2.0    NaN       F du Plessis   \n",
       "314               Mumbai Indians     Runs     1.0    NaN          KH Pandya   \n",
       "315               Mumbai Indians  Wickets     6.0    NaN          KV Sharma   \n",
       "316        Kolkata Knight Riders  Wickets     7.0    D/L    NM Coulter-Nile   \n",
       "317       Rising Pune Supergiant     Runs    20.0    NaN  Washington Sundar   \n",
       "373          Sunrisers Hyderabad     Runs     8.0    NaN        BCJ Cutting   \n",
       "374          Sunrisers Hyderabad  Wickets     4.0    NaN          DA Warner   \n",
       "375          Sunrisers Hyderabad     Runs    22.0    NaN       MC Henriques   \n",
       "376  Royal Challengers Bangalore  Wickets     4.0    NaN     AB de Villiers   \n",
       "433               Mumbai Indians     Runs    41.0    NaN          RG Sharma   \n",
       "434          Chennai Super Kings  Wickets     3.0    NaN            A Nehra   \n",
       "435  Royal Challengers Bangalore     Runs    71.0    NaN     AB de Villiers   \n",
       "436               Mumbai Indians     Runs    25.0    NaN         KA Pollard   \n",
       "492        Kolkata Knight Riders  Wickets     3.0    NaN          MK Pandey   \n",
       "493              Kings XI Punjab     Runs    24.0    NaN           V Sehwag   \n",
       "494          Chennai Super Kings  Wickets     7.0    NaN           SK Raina   \n",
       "495        Kolkata Knight Riders     Runs    28.0    NaN           UT Yadav   \n",
       "552               Mumbai Indians     Runs    23.0    NaN         KA Pollard   \n",
       "553               Mumbai Indians  Wickets     4.0    NaN    Harbhajan Singh   \n",
       "554             Rajasthan Royals  Wickets     4.0    NaN           BJ Hodge   \n",
       "555          Chennai Super Kings     Runs    48.0    NaN         MEK Hussey   \n",
       "628        Kolkata Knight Riders  Wickets     5.0    NaN           MS Bisla   \n",
       "629          Chennai Super Kings     Runs    86.0    NaN            M Vijay   \n",
       "630          Chennai Super Kings     Runs    38.0    NaN           MS Dhoni   \n",
       "631        Kolkata Knight Riders     Runs    18.0    NaN          YK Pathan   \n",
       "702          Chennai Super Kings     Runs    58.0    NaN            M Vijay   \n",
       "703  Royal Challengers Bangalore     Runs    43.0    NaN           CH Gayle   \n",
       "704               Mumbai Indians  Wickets     4.0    NaN           MM Patel   \n",
       "705          Chennai Super Kings  Wickets     6.0    NaN           SK Raina   \n",
       "775          Chennai Super Kings     Runs    22.0    NaN           SK Raina   \n",
       "776  Royal Challengers Bangalore  Wickets     9.0    NaN           A Kumble   \n",
       "777          Chennai Super Kings     Runs    38.0    NaN       DE Bollinger   \n",
       "778               Mumbai Indians     Runs    35.0    NaN         KA Pollard   \n",
       "835              Deccan Chargers     Runs     6.0    NaN           A Kumble   \n",
       "836  Royal Challengers Bangalore  Wickets     6.0    NaN          MK Pandey   \n",
       "837              Deccan Chargers  Wickets     6.0    NaN       AC Gilchrist   \n",
       "892             Rajasthan Royals  Wickets     3.0    NaN          YK Pathan   \n",
       "893          Chennai Super Kings  Wickets     9.0    NaN            M Ntini   \n",
       "894             Rajasthan Royals     Runs   105.0    NaN          SR Watson   \n",
       "\n",
       "                                          Team1Players  \\\n",
       "0    ['YBK Jaiswal', 'JC Buttler', 'SV Samson', 'D ...   \n",
       "1    ['V Kohli', 'F du Plessis', 'RM Patidar', 'GJ ...   \n",
       "2    ['V Kohli', 'F du Plessis', 'RM Patidar', 'GJ ...   \n",
       "3    ['YBK Jaiswal', 'JC Buttler', 'SV Samson', 'D ...   \n",
       "74   ['RD Gaikwad', 'F du Plessis', 'RV Uthappa', '...   \n",
       "75   ['PP Shaw', 'S Dhawan', 'MP Stoinis', 'SS Iyer...   \n",
       "76   ['D Padikkal', 'V Kohli', 'KS Bharat', 'GJ Max...   \n",
       "77   ['PP Shaw', 'S Dhawan', 'SS Iyer', 'AR Patel',...   \n",
       "134  ['MP Stoinis', 'S Dhawan', 'AM Rahane', 'SS Iy...   \n",
       "135  ['MP Stoinis', 'S Dhawan', 'SS Iyer', 'SO Hetm...   \n",
       "136  ['V Kohli', 'D Padikkal', 'AJ Finch', 'AB de V...   \n",
       "137  ['Q de Kock', 'RG Sharma', 'SA Yadav', 'Ishan ...   \n",
       "194  ['Q de Kock', 'RG Sharma', 'SA Yadav', 'Ishan ...   \n",
       "195  ['PP Shaw', 'S Dhawan', 'C Munro', 'SS Iyer', ...   \n",
       "196  ['WP Saha', 'MJ Guptill', 'MK Pandey', 'KS Wil...   \n",
       "197  ['F du Plessis', 'SR Watson', 'SK Raina', 'M V...   \n",
       "254  ['SP Goswami', 'S Dhawan', 'KS Williamson', 'S...   \n",
       "255  ['WP Saha', 'S Dhawan', 'KS Williamson', 'Shak...   \n",
       "256  ['SP Narine', 'CA Lynn', 'RV Uthappa', 'N Rana...   \n",
       "257  ['S Dhawan', 'SP Goswami', 'KS Williamson', 'M...   \n",
       "314  ['LMP Simmons', 'PA Patel', 'AT Rayudu', 'RG S...   \n",
       "315  ['LMP Simmons', 'PA Patel', 'AT Rayudu', 'RG S...   \n",
       "316  ['DA Warner', 'S Dhawan', 'KS Williamson', 'Yu...   \n",
       "317  ['LMP Simmons', 'PA Patel', 'RG Sharma', 'AT R...   \n",
       "373  ['CH Gayle', 'V Kohli', 'AB de Villiers', 'KL ...   \n",
       "374  ['ER Dwivedi', 'BB McCullum', 'SK Raina', 'KD ...   \n",
       "375  ['DA Warner', 'S Dhawan', 'MC Henriques', 'Yuv...   \n",
       "376  ['AJ Finch', 'BB McCullum', 'SK Raina', 'KD Ka...   \n",
       "433  ['LMP Simmons', 'PA Patel', 'RG Sharma', 'KA P...   \n",
       "434  ['DR Smith', 'MEK Hussey', 'F du Plessis', 'SK...   \n",
       "435  ['CH Gayle', 'V Kohli', 'AB de Villiers', 'Man...   \n",
       "436  ['DR Smith', 'MEK Hussey', 'F du Plessis', 'SK...   \n",
       "492  ['RV Uthappa', 'G Gambhir', 'MK Pandey', 'YK P...   \n",
       "493  ['DR Smith', 'F du Plessis', 'SK Raina', 'BB M...   \n",
       "494  ['DR Smith', 'F du Plessis', 'SK Raina', 'BB M...   \n",
       "495  ['V Sehwag', 'M Vohra', 'WP Saha', 'GJ Maxwell...   \n",
       "552  ['MEK Hussey', 'M Vijay', 'SK Raina', 'S Badri...   \n",
       "553  ['DR Smith', 'AP Tare', 'KD Karthik', 'RG Shar...   \n",
       "554  ['R Dravid', 'AM Rahane', 'SR Watson', 'DH Yag...   \n",
       "555  ['MEK Hussey', 'M Vijay', 'SK Raina', 'MS Dhon...   \n",
       "628  ['MS Bisla', 'G Gambhir', 'JH Kallis', 'LR Shu...   \n",
       "629  ['DPMD Jayawardene', 'DA Warner', 'V Sehwag', ...   \n",
       "630  ['M Vijay', 'MEK Hussey', 'SK Raina', 'S Badri...   \n",
       "631  ['DA Warner', 'V Sehwag', 'NV Ojha', 'DPMD Jay...   \n",
       "702  ['MEK Hussey', 'M Vijay', 'MS Dhoni', 'SK Rain...   \n",
       "703  ['MA Agarwal', 'CH Gayle', 'V Kohli', 'AB de V...   \n",
       "704  ['AC Blizzard', 'SR Tendulkar', 'RG Sharma', '...   \n",
       "705  ['MA Agarwal', 'CH Gayle', 'V Kohli', 'AB de V...   \n",
       "775  ['M Vijay', 'ML Hayden', 'SK Raina', 'S Badrin...   \n",
       "776  ['JH Kallis', 'R Dravid', 'KP Pietersen', 'RV ...   \n",
       "777  ['M Vijay', 'ML Hayden', 'SK Raina', 'S Badrin...   \n",
       "778  ['JH Kallis', 'R Dravid', 'KP Pietersen', 'RV ...   \n",
       "835  ['JH Kallis', 'MK Pandey', 'RE van der Merwe',...   \n",
       "836  ['JH Kallis', 'MK Pandey', 'RE van der Merwe',...   \n",
       "837  ['G Gambhir', 'DA Warner', 'V Sehwag', 'TM Dil...   \n",
       "892  ['PA Patel', 'S Vidyut', 'SK Raina', 'JA Morke...   \n",
       "893  ['PA Patel', 'S Vidyut', 'SK Raina', 'MS Dhoni...   \n",
       "894  ['G Gambhir', 'V Sehwag', 'S Dhawan', 'MK Tiwa...   \n",
       "\n",
       "                                          Team2Players                Umpire1  \\\n",
       "0    ['WP Saha', 'Shubman Gill', 'MS Wade', 'HH Pan...            CB Gaffaney   \n",
       "1    ['YBK Jaiswal', 'JC Buttler', 'SV Samson', 'D ...            CB Gaffaney   \n",
       "2    ['Q de Kock', 'KL Rahul', 'M Vohra', 'DJ Hooda...          J Madanagopal   \n",
       "3    ['WP Saha', 'Shubman Gill', 'MS Wade', 'HH Pan...           BNJ Oxenford   \n",
       "74   ['Shubman Gill', 'VR Iyer', 'N Rana', 'SP Nari...            Nitin Menon   \n",
       "75   ['Shubman Gill', 'VR Iyer', 'N Rana', 'RA Trip...  KN Ananthapadmanabhan   \n",
       "76   ['Shubman Gill', 'VR Iyer', 'RA Tripathi', 'N ...            CB Gaffaney   \n",
       "77   ['RD Gaikwad', 'F du Plessis', 'RV Uthappa', '...            Nitin Menon   \n",
       "134  ['RG Sharma', 'Q de Kock', 'SA Yadav', 'Ishan ...            CB Gaffaney   \n",
       "135  ['PK Garg', 'DA Warner', 'MK Pandey', 'KS Will...             PR Reiffel   \n",
       "136  ['DA Warner', 'SP Goswami', 'MK Pandey', 'KS W...             PR Reiffel   \n",
       "137  ['PP Shaw', 'S Dhawan', 'AM Rahane', 'SS Iyer'...            CB Gaffaney   \n",
       "194  ['F du Plessis', 'SR Watson', 'SK Raina', 'AT ...               IJ Gould   \n",
       "195  ['F du Plessis', 'SR Watson', 'SK Raina', 'AT ...           BNJ Oxenford   \n",
       "196  ['PP Shaw', 'S Dhawan', 'SS Iyer', 'RR Pant', ...           BNJ Oxenford   \n",
       "197  ['RG Sharma', 'Q de Kock', 'SA Yadav', 'Ishan ...               NJ Llong   \n",
       "254  ['SR Watson', 'F du Plessis', 'SK Raina', 'AT ...              M Erasmus   \n",
       "255  ['CA Lynn', 'SP Narine', 'N Rana', 'RV Uthappa...        HDPK Dharmasena   \n",
       "256  ['AM Rahane', 'RA Tripathi', 'SV Samson', 'H K...           AK Chaudhary   \n",
       "257  ['SR Watson', 'F du Plessis', 'SK Raina', 'AT ...          C Shamshuddin   \n",
       "314  ['AM Rahane', 'RA Tripathi', 'SPD Smith', 'MS ...               NJ Llong   \n",
       "315  ['CA Lynn', 'SP Narine', 'G Gambhir', 'RV Utha...               NJ Llong   \n",
       "316  ['RV Uthappa', 'CA Lynn', 'YK Pathan', 'G Gamb...           AK Chaudhary   \n",
       "317  ['AM Rahane', 'RA Tripathi', 'SPD Smith', 'MK ...                 S Ravi   \n",
       "373  ['DA Warner', 'S Dhawan', 'MC Henriques', 'Yuv...        HDPK Dharmasena   \n",
       "374  ['DA Warner', 'S Dhawan', 'MC Henriques', 'Yuv...              M Erasmus   \n",
       "375  ['RV Uthappa', 'G Gambhir', 'C Munro', 'MK Pan...              M Erasmus   \n",
       "376  ['CH Gayle', 'V Kohli', 'AB de Villiers', 'KL ...           AK Chaudhary   \n",
       "433  ['DR Smith', 'MEK Hussey', 'SK Raina', 'MS Dho...        HDPK Dharmasena   \n",
       "434  ['CH Gayle', 'V Kohli', 'AB de Villiers', 'Man...           AK Chaudhary   \n",
       "435  ['AM Rahane', 'SR Watson', 'SV Samson', 'SPD S...           AK Chaudhary   \n",
       "436  ['LMP Simmons', 'PA Patel', 'RG Sharma', 'KA P...        HDPK Dharmasena   \n",
       "492  ['V Sehwag', 'M Vohra', 'GJ Bailey', 'WP Saha'...        HDPK Dharmasena   \n",
       "493  ['V Sehwag', 'M Vohra', 'GJ Maxwell', 'DA Mill...        HDPK Dharmasena   \n",
       "494  ['LMP Simmons', 'MEK Hussey', 'CJ Anderson', '...            VA Kulkarni   \n",
       "495  ['RV Uthappa', 'G Gambhir', 'MK Pandey', 'Shak...               NJ Llong   \n",
       "552  ['DR Smith', 'AP Tare', 'KD Karthik', 'RG Shar...        HDPK Dharmasena   \n",
       "553  ['R Dravid', 'AM Rahane', 'SR Watson', 'SV Sam...          C Shamshuddin   \n",
       "554  ['PA Patel', 'S Dhawan', 'GH Vihari', 'CL Whit...                 S Ravi   \n",
       "555  ['DR Smith', 'AP Tare', 'KD Karthik', 'RG Shar...               NJ Llong   \n",
       "628  ['MEK Hussey', 'M Vijay', 'SK Raina', 'MS Dhon...              BF Bowden   \n",
       "629  ['M Vijay', 'MEK Hussey', 'SK Raina', 'MS Dhon...            BR Doctrove   \n",
       "630  ['SR Tendulkar', 'DR Smith', 'RG Sharma', 'KD ...              BF Bowden   \n",
       "631  ['BB McCullum', 'G Gambhir', 'JH Kallis', 'Sha...            BR Doctrove   \n",
       "702  ['MA Agarwal', 'CH Gayle', 'V Kohli', 'AB de V...              Asad Rauf   \n",
       "703  ['AC Blizzard', 'SR Tendulkar', 'Harbhajan Sin...              Asad Rauf   \n",
       "704  ['G Gambhir', 'JH Kallis', 'SP Goswami', 'MK T...              Asad Rauf   \n",
       "705  ['MEK Hussey', 'M Vijay', 'SK Raina', 'S Badri...              Asad Rauf   \n",
       "775  ['S Dhawan', 'SR Tendulkar', 'AM Nayar', 'Harb...            RE Koertzen   \n",
       "776  ['AC Gilchrist', 'MD Mishra', 'Anirudh Singh',...            RE Koertzen   \n",
       "777  ['AC Gilchrist', 'HH Gibbs', 'TL Suman', 'RG S...            BR Doctrove   \n",
       "778  ['S Dhawan', 'SR Tendulkar', 'AM Nayar', 'AT R...            BR Doctrove   \n",
       "835  ['AC Gilchrist', 'HH Gibbs', 'TL Suman', 'A Sy...            RE Koertzen   \n",
       "836  ['PA Patel', 'ML Hayden', 'MS Dhoni', 'SK Rain...            RE Koertzen   \n",
       "837  ['AC Gilchrist', 'HH Gibbs', 'AA Bilakhia', 'T...            BR Doctrove   \n",
       "892  ['NK Patel', 'SA Asnodkar', 'Kamran Akmal', 'S...              BF Bowden   \n",
       "893  ['SE Marsh', 'JR Hopes', 'KC Sangakkara', 'Yuv...              Asad Rauf   \n",
       "894  ['GC Smith', 'SA Asnodkar', 'Sohail Tanvir', '...              BF Bowden   \n",
       "\n",
       "             Umpire2  \n",
       "0        Nitin Menon  \n",
       "1        Nitin Menon  \n",
       "2           MA Gough  \n",
       "3          VK Sharma  \n",
       "74    RK Illingworth  \n",
       "75          MA Gough  \n",
       "76         VK Sharma  \n",
       "77    RK Illingworth  \n",
       "134      Nitin Menon  \n",
       "135           S Ravi  \n",
       "136           S Ravi  \n",
       "137      Nitin Menon  \n",
       "194      Nitin Menon  \n",
       "195           S Ravi  \n",
       "196           S Ravi  \n",
       "197      Nitin Menon  \n",
       "254           S Ravi  \n",
       "255      Nitin Menon  \n",
       "256      Nitin Menon  \n",
       "257        M Erasmus  \n",
       "314           S Ravi  \n",
       "315      Nitin Menon  \n",
       "316      Nitin Menon  \n",
       "317    C Shamshuddin  \n",
       "373     BNJ Oxenford  \n",
       "374        CK Nandan  \n",
       "375    C Shamshuddin  \n",
       "376  HDPK Dharmasena  \n",
       "433   RK Illingworth  \n",
       "434      CB Gaffaney  \n",
       "435    C Shamshuddin  \n",
       "436   RK Illingworth  \n",
       "492     BNJ Oxenford  \n",
       "493        RJ Tucker  \n",
       "494     BNJ Oxenford  \n",
       "495           S Ravi  \n",
       "552       SJA Taufel  \n",
       "553       SJA Taufel  \n",
       "554        RJ Tucker  \n",
       "555        RJ Tucker  \n",
       "628       SJA Taufel  \n",
       "629       SJA Taufel  \n",
       "630  HDPK Dharmasena  \n",
       "631       SJA Taufel  \n",
       "702       SJA Taufel  \n",
       "703       SJA Taufel  \n",
       "704       SJA Taufel  \n",
       "705       SJA Taufel  \n",
       "775       SJA Taufel  \n",
       "776       SJA Taufel  \n",
       "777        RB Tiffin  \n",
       "778        RB Tiffin  \n",
       "835       SJA Taufel  \n",
       "836       SJA Taufel  \n",
       "837        DJ Harper  \n",
       "892      RE Koertzen  \n",
       "893        DJ Harper  \n",
       "894      RE Koertzen  "
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl = pd.read_csv('ipl-matches.csv')\n",
    "# Q) find which player has won most player of the match -> in finals and qualifiers\n",
    "ipl[~ipl['MatchNumber'].str.isdigit()]  #details of special matches"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KA Pollard           3\n",
       "F du Plessis         3\n",
       "SK Raina             3\n",
       "A Kumble             2\n",
       "MK Pandey            2\n",
       "YK Pathan            2\n",
       "M Vijay              2\n",
       "JJ Bumrah            2\n",
       "AB de Villiers       2\n",
       "SR Watson            2\n",
       "HH Pandya            1\n",
       "Harbhajan Singh      1\n",
       "A Nehra              1\n",
       "V Sehwag             1\n",
       "UT Yadav             1\n",
       "MS Bisla             1\n",
       "BJ Hodge             1\n",
       "MEK Hussey           1\n",
       "MS Dhoni             1\n",
       "CH Gayle             1\n",
       "MM Patel             1\n",
       "DE Bollinger         1\n",
       "AC Gilchrist         1\n",
       "RG Sharma            1\n",
       "DA Warner            1\n",
       "MC Henriques         1\n",
       "JC Buttler           1\n",
       "RM Patidar           1\n",
       "DA Miller            1\n",
       "VR Iyer              1\n",
       "SP Narine            1\n",
       "RD Gaikwad           1\n",
       "TA Boult             1\n",
       "MP Stoinis           1\n",
       "KS Williamson        1\n",
       "RR Pant              1\n",
       "SA Yadav             1\n",
       "Rashid Khan          1\n",
       "AD Russell           1\n",
       "KH Pandya            1\n",
       "KV Sharma            1\n",
       "NM Coulter-Nile      1\n",
       "Washington Sundar    1\n",
       "BCJ Cutting          1\n",
       "M Ntini              1\n",
       "Name: Player_of_Match, dtype: int64"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl[~ipl['MatchNumber'].str.isdigit()]['Player_of_Match'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "field    599\n",
       "bat      351\n",
       "Name: TossDecision, dtype: int64"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Toss decision plot\n",
    "ipl['TossDecision'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: ylabel='TossDecision'>"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ipl['TossDecision'].value_counts().plot(kind='pie')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Royal Challengers Bangalore    126\n",
       "Mumbai Indians                 112\n",
       "Chennai Super Kings            111\n",
       "Kolkata Knight Riders          105\n",
       "Kings XI Punjab                 92\n",
       "Rajasthan Royals                89\n",
       "Delhi Daredevils                85\n",
       "Sunrisers Hyderabad             69\n",
       "Deccan Chargers                 39\n",
       "Delhi Capitals                  29\n",
       "Pune Warriors                   23\n",
       "Punjab Kings                    18\n",
       "Gujarat Lions                   16\n",
       "Lucknow Super Giants             8\n",
       "Gujarat Titans                   7\n",
       "Rising Pune Supergiant           7\n",
       "Rising Pune Supergiants          7\n",
       "Kochi Tuskers Kerala             7\n",
       "Name: Team1, dtype: int64"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# how many matches each team has played\n",
    "ipl['Team1'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Mumbai Indians                 119\n",
       "Kolkata Knight Riders          118\n",
       "Rajasthan Royals               103\n",
       "Royal Challengers Bangalore    100\n",
       "Kings XI Punjab                 98\n",
       "Chennai Super Kings             97\n",
       "Sunrisers Hyderabad             83\n",
       "Delhi Daredevils                76\n",
       "Deccan Chargers                 36\n",
       "Delhi Capitals                  34\n",
       "Pune Warriors                   23\n",
       "Gujarat Lions                   14\n",
       "Punjab Kings                    10\n",
       "Gujarat Titans                   9\n",
       "Rising Pune Supergiant           9\n",
       "Rising Pune Supergiants          7\n",
       "Lucknow Super Giants             7\n",
       "Kochi Tuskers Kerala             7\n",
       "Name: Team2, dtype: int64"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl['Team2'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Chennai Super Kings            208\n",
       "Deccan Chargers                 75\n",
       "Delhi Capitals                  63\n",
       "Delhi Daredevils               161\n",
       "Gujarat Lions                   30\n",
       "Gujarat Titans                  16\n",
       "Kings XI Punjab                190\n",
       "Kochi Tuskers Kerala            14\n",
       "Kolkata Knight Riders          223\n",
       "Lucknow Super Giants            15\n",
       "Mumbai Indians                 231\n",
       "Pune Warriors                   46\n",
       "Punjab Kings                    28\n",
       "Rajasthan Royals               192\n",
       "Rising Pune Supergiant          16\n",
       "Rising Pune Supergiants         14\n",
       "Royal Challengers Bangalore    226\n",
       "Sunrisers Hyderabad            152\n",
       "dtype: int64"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl['Team1'].value_counts() + ipl['Team2'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Mumbai Indians                 231\n",
       "Royal Challengers Bangalore    226\n",
       "Kolkata Knight Riders          223\n",
       "Chennai Super Kings            208\n",
       "Rajasthan Royals               192\n",
       "Kings XI Punjab                190\n",
       "Delhi Daredevils               161\n",
       "Sunrisers Hyderabad            152\n",
       "Deccan Chargers                 75\n",
       "Delhi Capitals                  63\n",
       "Pune Warriors                   46\n",
       "Gujarat Lions                   30\n",
       "Punjab Kings                    28\n",
       "Gujarat Titans                  16\n",
       "Rising Pune Supergiant          16\n",
       "Lucknow Super Giants            15\n",
       "Kochi Tuskers Kerala            14\n",
       "Rising Pune Supergiants         14\n",
       "dtype: int64"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(ipl['Team2'].value_counts() + ipl['Team1'].value_counts()).sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Kochi Tuskers Kerala            14\n",
       "Rising Pune Supergiants         14\n",
       "Lucknow Super Giants            15\n",
       "Gujarat Titans                  16\n",
       "Rising Pune Supergiant          16\n",
       "Punjab Kings                    28\n",
       "Gujarat Lions                   30\n",
       "Pune Warriors                   46\n",
       "Delhi Capitals                  63\n",
       "Deccan Chargers                 75\n",
       "Sunrisers Hyderabad            152\n",
       "Delhi Daredevils               161\n",
       "Kings XI Punjab                190\n",
       "Rajasthan Royals               192\n",
       "Chennai Super Kings            208\n",
       "Kolkata Knight Riders          223\n",
       "Royal Challengers Bangalore    226\n",
       "Mumbai Indians                 231\n",
       "dtype: int64"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(ipl['Team2'].value_counts() + ipl['Team1'].value_counts()).sort_values() #default=ascending"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### sort_values(series and dataframe) -> ascending -> na_position -> inplace -> multiple cols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    54\n",
       "1     7\n",
       "2    87\n",
       "3    23\n",
       "4    53\n",
       "dtype: int64"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#series\n",
    "x = pd.Series([54,7,87,23,53])\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1     7\n",
       "3    23\n",
       "4    53\n",
       "0    54\n",
       "2    87\n",
       "dtype: int64"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x.sort_values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2    87\n",
       "0    54\n",
       "4    53\n",
       "3    23\n",
       "1     7\n",
       "dtype: int64"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x.sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "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>title_x</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>poster_path</th>\n",
       "      <th>wiki_link</th>\n",
       "      <th>title_y</th>\n",
       "      <th>original_title</th>\n",
       "      <th>is_adult</th>\n",
       "      <th>year_of_release</th>\n",
       "      <th>runtime</th>\n",
       "      <th>genres</th>\n",
       "      <th>imdb_rating</th>\n",
       "      <th>imdb_votes</th>\n",
       "      <th>story</th>\n",
       "      <th>summary</th>\n",
       "      <th>tagline</th>\n",
       "      <th>actors</th>\n",
       "      <th>wins_nominations</th>\n",
       "      <th>release_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>tt8291224</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Uri:_The_Surgica...</td>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>138</td>\n",
       "      <td>Action|Drama|War</td>\n",
       "      <td>8.4</td>\n",
       "      <td>35112</td>\n",
       "      <td>Divided over five chapters  the film chronicle...</td>\n",
       "      <td>Indian army special forces execute a covert op...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...</td>\n",
       "      <td>4 wins</td>\n",
       "      <td>11 January 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>tt9472208</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Battalion_609</td>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>131</td>\n",
       "      <td>War</td>\n",
       "      <td>4.1</td>\n",
       "      <td>73</td>\n",
       "      <td>The story revolves around a cricket match betw...</td>\n",
       "      <td>The story of Battalion 609 revolves around a c...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vicky Ahuja|Shoaib Ibrahim|Shrikant Kamat|Elen...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11 January 2019 (India)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    title_x    imdb_id  \\\n",
       "0  Uri: The Surgical Strike  tt8291224   \n",
       "1             Battalion 609  tt9472208   \n",
       "\n",
       "                                         poster_path  \\\n",
       "0  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "1                                                NaN   \n",
       "\n",
       "                                           wiki_link  \\\n",
       "0  https://en.wikipedia.org/wiki/Uri:_The_Surgica...   \n",
       "1        https://en.wikipedia.org/wiki/Battalion_609   \n",
       "\n",
       "                    title_y            original_title  is_adult  \\\n",
       "0  Uri: The Surgical Strike  Uri: The Surgical Strike         0   \n",
       "1             Battalion 609             Battalion 609         0   \n",
       "\n",
       "   year_of_release runtime            genres  imdb_rating  imdb_votes  \\\n",
       "0             2019     138  Action|Drama|War          8.4       35112   \n",
       "1             2019     131               War          4.1          73   \n",
       "\n",
       "                                               story  \\\n",
       "0  Divided over five chapters  the film chronicle...   \n",
       "1  The story revolves around a cricket match betw...   \n",
       "\n",
       "                                             summary tagline  \\\n",
       "0  Indian army special forces execute a covert op...     NaN   \n",
       "1  The story of Battalion 609 revolves around a c...     NaN   \n",
       "\n",
       "                                              actors wins_nominations  \\\n",
       "0  Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...           4 wins   \n",
       "1  Vicky Ahuja|Shoaib Ibrahim|Shrikant Kamat|Elen...              NaN   \n",
       "\n",
       "              release_date  \n",
       "0    11 January 2019 (USA)  \n",
       "1  11 January 2019 (India)  "
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#dataframe\n",
    "movies.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "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>title_x</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>poster_path</th>\n",
       "      <th>wiki_link</th>\n",
       "      <th>title_y</th>\n",
       "      <th>original_title</th>\n",
       "      <th>is_adult</th>\n",
       "      <th>year_of_release</th>\n",
       "      <th>runtime</th>\n",
       "      <th>genres</th>\n",
       "      <th>imdb_rating</th>\n",
       "      <th>imdb_votes</th>\n",
       "      <th>story</th>\n",
       "      <th>summary</th>\n",
       "      <th>tagline</th>\n",
       "      <th>actors</th>\n",
       "      <th>wins_nominations</th>\n",
       "      <th>release_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1623</th>\n",
       "      <td>Zubeidaa</td>\n",
       "      <td>tt0255713</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Zubeidaa</td>\n",
       "      <td>Zubeidaa</td>\n",
       "      <td>Zubeidaa</td>\n",
       "      <td>0</td>\n",
       "      <td>2001</td>\n",
       "      <td>153</td>\n",
       "      <td>Biography|Drama|History</td>\n",
       "      <td>6.2</td>\n",
       "      <td>1384</td>\n",
       "      <td>The film begins with Riyaz (Rajat Kapoor)  Zub...</td>\n",
       "      <td>Zubeidaa  an aspiring Muslim actress  marries ...</td>\n",
       "      <td>The Story of a Princess</td>\n",
       "      <td>Karisma Kapoor|Rekha|Manoj Bajpayee|Rajit Kapo...</td>\n",
       "      <td>3 wins &amp; 13 nominations</td>\n",
       "      <td>19 January 2001 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>939</th>\n",
       "      <td>Zor Lagaa Ke...Haiya!</td>\n",
       "      <td>tt1479857</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Zor_Lagaa_Ke...H...</td>\n",
       "      <td>Zor Lagaa Ke... Haiya!</td>\n",
       "      <td>Zor Lagaa Ke... Haiya!</td>\n",
       "      <td>0</td>\n",
       "      <td>2009</td>\n",
       "      <td>\\N</td>\n",
       "      <td>Comedy|Drama|Family</td>\n",
       "      <td>6.4</td>\n",
       "      <td>46</td>\n",
       "      <td>A tree narrates the story of four Mumbai-based...</td>\n",
       "      <td>Children build a tree-house to spy on a beggar...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Meghan Jadhav|Mithun Chakraborty|Riya Sen|Seem...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>756</th>\n",
       "      <td>Zokkomon</td>\n",
       "      <td>tt1605790</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Zokkomon</td>\n",
       "      <td>Zokkomon</td>\n",
       "      <td>Zokkomon</td>\n",
       "      <td>0</td>\n",
       "      <td>2011</td>\n",
       "      <td>109</td>\n",
       "      <td>Action|Adventure</td>\n",
       "      <td>4.0</td>\n",
       "      <td>274</td>\n",
       "      <td>After the passing of his parents in an acciden...</td>\n",
       "      <td>An orphan is abused and abandoned  believed to...</td>\n",
       "      <td>Betrayal. Friendship. Bravery.</td>\n",
       "      <td>Darsheel Safary|Anupam Kher|Manjari Fadnnis|Ti...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22 April 2011 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>670</th>\n",
       "      <td>Zindagi Tere Naam</td>\n",
       "      <td>tt2164702</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Zindagi_Tere_Naam</td>\n",
       "      <td>Zindagi Tere Naam</td>\n",
       "      <td>Zindagi Tere Naam</td>\n",
       "      <td>0</td>\n",
       "      <td>2012</td>\n",
       "      <td>120</td>\n",
       "      <td>Romance</td>\n",
       "      <td>4.7</td>\n",
       "      <td>27</td>\n",
       "      <td>Mr. Singh  an elderly gentleman  relates to hi...</td>\n",
       "      <td>Mr. Singh  an elderly gentleman  relates to hi...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mithun Chakraborty|Ranjeeta Kaur|Priyanka Meht...</td>\n",
       "      <td>1 win</td>\n",
       "      <td>16 March 2012 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>778</th>\n",
       "      <td>Zindagi Na Milegi Dobara</td>\n",
       "      <td>tt1562872</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Zindagi_Na_Mileg...</td>\n",
       "      <td>Zindagi Na Milegi Dobara</td>\n",
       "      <td>Zindagi Na Milegi Dobara</td>\n",
       "      <td>0</td>\n",
       "      <td>2011</td>\n",
       "      <td>155</td>\n",
       "      <td>Comedy|Drama</td>\n",
       "      <td>8.1</td>\n",
       "      <td>60826</td>\n",
       "      <td>Three friends decide to turn their fantasy vac...</td>\n",
       "      <td>Three friends decide to turn their fantasy vac...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Hrithik Roshan|Farhan Akhtar|Abhay Deol|Katrin...</td>\n",
       "      <td>30 wins &amp; 22 nominations</td>\n",
       "      <td>15 July 2011 (India)</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1039</th>\n",
       "      <td>1971 (2007 film)</td>\n",
       "      <td>tt0983990</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/1971_(2007_film)</td>\n",
       "      <td>1971</td>\n",
       "      <td>1971</td>\n",
       "      <td>0</td>\n",
       "      <td>2007</td>\n",
       "      <td>160</td>\n",
       "      <td>Action|Drama|War</td>\n",
       "      <td>7.9</td>\n",
       "      <td>1121</td>\n",
       "      <td>Based on true facts  the film revolves around ...</td>\n",
       "      <td>Based on true facts  the film revolves around ...</td>\n",
       "      <td>Honor the heroes.......</td>\n",
       "      <td>Manoj Bajpayee|Ravi Kishan|Deepak Dobriyal|</td>\n",
       "      <td>1 win</td>\n",
       "      <td>9 March 2007 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>723</th>\n",
       "      <td>1920: The Evil Returns</td>\n",
       "      <td>tt2222550</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/e/e7...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/1920:_The_Evil_R...</td>\n",
       "      <td>1920: Evil Returns</td>\n",
       "      <td>1920: Evil Returns</td>\n",
       "      <td>0</td>\n",
       "      <td>2012</td>\n",
       "      <td>124</td>\n",
       "      <td>Drama|Horror|Romance</td>\n",
       "      <td>4.8</td>\n",
       "      <td>1587</td>\n",
       "      <td>This story revolves around a famous poet who m...</td>\n",
       "      <td>This story revolves around a famous poet who m...</td>\n",
       "      <td>Possession is back</td>\n",
       "      <td>Vicky Ahuja|Tia Bajpai|Irma Jämhammar|Sharad K...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2 November 2012 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>287</th>\n",
       "      <td>1920: London</td>\n",
       "      <td>tt5638500</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/1920_London</td>\n",
       "      <td>1920 London</td>\n",
       "      <td>1920 London</td>\n",
       "      <td>0</td>\n",
       "      <td>2016</td>\n",
       "      <td>120</td>\n",
       "      <td>Horror|Mystery</td>\n",
       "      <td>4.1</td>\n",
       "      <td>1373</td>\n",
       "      <td>Shivangi (Meera Chopra) lives in London with h...</td>\n",
       "      <td>After her husband is possessed by an evil spir...</td>\n",
       "      <td>Fear strikes again</td>\n",
       "      <td>Sharman Joshi|Meera Chopra|Vishal Karwal|Suren...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6 May 2016 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1021</th>\n",
       "      <td>1920 (film)</td>\n",
       "      <td>tt1301698</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/1920_(film)</td>\n",
       "      <td>1920</td>\n",
       "      <td>1920</td>\n",
       "      <td>0</td>\n",
       "      <td>2008</td>\n",
       "      <td>138</td>\n",
       "      <td>Horror|Mystery|Romance</td>\n",
       "      <td>6.4</td>\n",
       "      <td>2588</td>\n",
       "      <td>A devotee of Bhagwan Shri Hanuman  Arjun Singh...</td>\n",
       "      <td>After forsaking his family and religion  a hus...</td>\n",
       "      <td>A Love Made in Heaven...A Revenge Born in Hell...</td>\n",
       "      <td>Rajniesh Duggall|Adah Sharma|Anjori Alagh|Raj ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12 September 2008 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1498</th>\n",
       "      <td>16 December (film)</td>\n",
       "      <td>tt0313844</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/16_December_(film)</td>\n",
       "      <td>16-Dec</td>\n",
       "      <td>16-Dec</td>\n",
       "      <td>0</td>\n",
       "      <td>2002</td>\n",
       "      <td>158</td>\n",
       "      <td>Action|Thriller</td>\n",
       "      <td>6.9</td>\n",
       "      <td>1091</td>\n",
       "      <td>16 December  1971 was the day when India won t...</td>\n",
       "      <td>Indian intelligence agents race against time t...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Danny Denzongpa|Gulshan Grover|Milind Soman|Di...</td>\n",
       "      <td>2 nominations</td>\n",
       "      <td>22 March 2002 (India)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1629 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       title_x    imdb_id  \\\n",
       "1623                  Zubeidaa  tt0255713   \n",
       "939      Zor Lagaa Ke...Haiya!  tt1479857   \n",
       "756                   Zokkomon  tt1605790   \n",
       "670          Zindagi Tere Naam  tt2164702   \n",
       "778   Zindagi Na Milegi Dobara  tt1562872   \n",
       "...                        ...        ...   \n",
       "1039          1971 (2007 film)  tt0983990   \n",
       "723     1920: The Evil Returns  tt2222550   \n",
       "287               1920: London  tt5638500   \n",
       "1021               1920 (film)  tt1301698   \n",
       "1498        16 December (film)  tt0313844   \n",
       "\n",
       "                                            poster_path  \\\n",
       "1623  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "939   https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "756   https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "670   https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "778   https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "...                                                 ...   \n",
       "1039  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "723   https://upload.wikimedia.org/wikipedia/en/e/e7...   \n",
       "287   https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "1021  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "1498  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "\n",
       "                                              wiki_link  \\\n",
       "1623             https://en.wikipedia.org/wiki/Zubeidaa   \n",
       "939   https://en.wikipedia.org/wiki/Zor_Lagaa_Ke...H...   \n",
       "756              https://en.wikipedia.org/wiki/Zokkomon   \n",
       "670     https://en.wikipedia.org/wiki/Zindagi_Tere_Naam   \n",
       "778   https://en.wikipedia.org/wiki/Zindagi_Na_Mileg...   \n",
       "...                                                 ...   \n",
       "1039     https://en.wikipedia.org/wiki/1971_(2007_film)   \n",
       "723   https://en.wikipedia.org/wiki/1920:_The_Evil_R...   \n",
       "287           https://en.wikipedia.org/wiki/1920_London   \n",
       "1021          https://en.wikipedia.org/wiki/1920_(film)   \n",
       "1498   https://en.wikipedia.org/wiki/16_December_(film)   \n",
       "\n",
       "                       title_y            original_title  is_adult  \\\n",
       "1623                  Zubeidaa                  Zubeidaa         0   \n",
       "939     Zor Lagaa Ke... Haiya!    Zor Lagaa Ke... Haiya!         0   \n",
       "756                   Zokkomon                  Zokkomon         0   \n",
       "670          Zindagi Tere Naam         Zindagi Tere Naam         0   \n",
       "778   Zindagi Na Milegi Dobara  Zindagi Na Milegi Dobara         0   \n",
       "...                        ...                       ...       ...   \n",
       "1039                      1971                      1971         0   \n",
       "723         1920: Evil Returns        1920: Evil Returns         0   \n",
       "287                1920 London               1920 London         0   \n",
       "1021                      1920                      1920         0   \n",
       "1498                    16-Dec                    16-Dec         0   \n",
       "\n",
       "      year_of_release runtime                   genres  imdb_rating  \\\n",
       "1623             2001     153  Biography|Drama|History          6.2   \n",
       "939              2009      \\N      Comedy|Drama|Family          6.4   \n",
       "756              2011     109         Action|Adventure          4.0   \n",
       "670              2012     120                  Romance          4.7   \n",
       "778              2011     155             Comedy|Drama          8.1   \n",
       "...               ...     ...                      ...          ...   \n",
       "1039             2007     160         Action|Drama|War          7.9   \n",
       "723              2012     124     Drama|Horror|Romance          4.8   \n",
       "287              2016     120           Horror|Mystery          4.1   \n",
       "1021             2008     138   Horror|Mystery|Romance          6.4   \n",
       "1498             2002     158          Action|Thriller          6.9   \n",
       "\n",
       "      imdb_votes                                              story  \\\n",
       "1623        1384  The film begins with Riyaz (Rajat Kapoor)  Zub...   \n",
       "939           46  A tree narrates the story of four Mumbai-based...   \n",
       "756          274  After the passing of his parents in an acciden...   \n",
       "670           27  Mr. Singh  an elderly gentleman  relates to hi...   \n",
       "778        60826  Three friends decide to turn their fantasy vac...   \n",
       "...          ...                                                ...   \n",
       "1039        1121  Based on true facts  the film revolves around ...   \n",
       "723         1587  This story revolves around a famous poet who m...   \n",
       "287         1373  Shivangi (Meera Chopra) lives in London with h...   \n",
       "1021        2588  A devotee of Bhagwan Shri Hanuman  Arjun Singh...   \n",
       "1498        1091  16 December  1971 was the day when India won t...   \n",
       "\n",
       "                                                summary  \\\n",
       "1623  Zubeidaa  an aspiring Muslim actress  marries ...   \n",
       "939   Children build a tree-house to spy on a beggar...   \n",
       "756   An orphan is abused and abandoned  believed to...   \n",
       "670   Mr. Singh  an elderly gentleman  relates to hi...   \n",
       "778   Three friends decide to turn their fantasy vac...   \n",
       "...                                                 ...   \n",
       "1039  Based on true facts  the film revolves around ...   \n",
       "723   This story revolves around a famous poet who m...   \n",
       "287   After her husband is possessed by an evil spir...   \n",
       "1021  After forsaking his family and religion  a hus...   \n",
       "1498  Indian intelligence agents race against time t...   \n",
       "\n",
       "                                                tagline  \\\n",
       "1623                            The Story of a Princess   \n",
       "939                                                 NaN   \n",
       "756                      Betrayal. Friendship. Bravery.   \n",
       "670                                                 NaN   \n",
       "778                                                 NaN   \n",
       "...                                                 ...   \n",
       "1039                            Honor the heroes.......   \n",
       "723                                  Possession is back   \n",
       "287                                  Fear strikes again   \n",
       "1021  A Love Made in Heaven...A Revenge Born in Hell...   \n",
       "1498                                                NaN   \n",
       "\n",
       "                                                 actors  \\\n",
       "1623  Karisma Kapoor|Rekha|Manoj Bajpayee|Rajit Kapo...   \n",
       "939   Meghan Jadhav|Mithun Chakraborty|Riya Sen|Seem...   \n",
       "756   Darsheel Safary|Anupam Kher|Manjari Fadnnis|Ti...   \n",
       "670   Mithun Chakraborty|Ranjeeta Kaur|Priyanka Meht...   \n",
       "778   Hrithik Roshan|Farhan Akhtar|Abhay Deol|Katrin...   \n",
       "...                                                 ...   \n",
       "1039        Manoj Bajpayee|Ravi Kishan|Deepak Dobriyal|   \n",
       "723   Vicky Ahuja|Tia Bajpai|Irma Jämhammar|Sharad K...   \n",
       "287   Sharman Joshi|Meera Chopra|Vishal Karwal|Suren...   \n",
       "1021  Rajniesh Duggall|Adah Sharma|Anjori Alagh|Raj ...   \n",
       "1498  Danny Denzongpa|Gulshan Grover|Milind Soman|Di...   \n",
       "\n",
       "              wins_nominations               release_date  \n",
       "1623   3 wins & 13 nominations    19 January 2001 (India)  \n",
       "939                        NaN                        NaN  \n",
       "756                        NaN      22 April 2011 (India)  \n",
       "670                      1 win      16 March 2012 (India)  \n",
       "778   30 wins & 22 nominations       15 July 2011 (India)  \n",
       "...                        ...                        ...  \n",
       "1039                     1 win       9 March 2007 (India)  \n",
       "723                        NaN    2 November 2012 (India)  \n",
       "287                        NaN           6 May 2016 (USA)  \n",
       "1021                       NaN  12 September 2008 (India)  \n",
       "1498             2 nominations      22 March 2002 (India)  \n",
       "\n",
       "[1629 rows x 18 columns]"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies.sort_values('title_x',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>college</th>\n",
       "      <th>branch</th>\n",
       "      <th>cgpa</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>nitish</td>\n",
       "      <td>bit</td>\n",
       "      <td>eee</td>\n",
       "      <td>6.66</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ankit</td>\n",
       "      <td>iit</td>\n",
       "      <td>it</td>\n",
       "      <td>8.25</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>rupesh</td>\n",
       "      <td>vit</td>\n",
       "      <td>cse</td>\n",
       "      <td>6.41</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</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>mrityunjay</td>\n",
       "      <td>NaN</td>\n",
       "      <td>me</td>\n",
       "      <td>5.60</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NaN</td>\n",
       "      <td>vlsi</td>\n",
       "      <td>ce</td>\n",
       "      <td>9.00</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>rishabh</td>\n",
       "      <td>ssit</td>\n",
       "      <td>civ</td>\n",
       "      <td>7.40</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>cse</td>\n",
       "      <td>10.00</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>aditya</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bio</td>\n",
       "      <td>7.40</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>NaN</td>\n",
       "      <td>git</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         name college branch   cgpa  package\n",
       "0      nitish     bit    eee   6.66      4.0\n",
       "1       ankit     iit     it   8.25      5.0\n",
       "2      rupesh     vit    cse   6.41      6.0\n",
       "3         NaN     NaN    NaN    NaN      NaN\n",
       "4  mrityunjay     NaN     me   5.60      6.0\n",
       "5         NaN    vlsi     ce   9.00      7.0\n",
       "6     rishabh    ssit    civ   7.40      8.0\n",
       "7         NaN     NaN    cse  10.00      9.0\n",
       "8      aditya     NaN    bio   7.40      NaN\n",
       "9         NaN     git    NaN    NaN      NaN"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "students = pd.DataFrame(\n",
    "    {\n",
    "        'name':['nitish','ankit','rupesh',np.nan,'mrityunjay',np.nan,'rishabh',np.nan,'aditya',np.nan],\n",
    "        'college':['bit','iit','vit',np.nan,np.nan,'vlsi','ssit',np.nan,np.nan,'git'],\n",
    "        'branch':['eee','it','cse',np.nan,'me','ce','civ','cse','bio',np.nan],\n",
    "        'cgpa':[6.66,8.25,6.41,np.nan,5.6,9.0,7.4,10,7.4,np.nan],\n",
    "        'package':[4,5,6,np.nan,6,7,8,9,np.nan,np.nan]\n",
    "\n",
    "    }\n",
    ")\n",
    "\n",
    "students"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>aditya</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ankit</td>\n",
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       "      <th>4</th>\n",
       "      <td>mrityunjay</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>nitish</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>rishabh</td>\n",
       "      <td>ssit</td>\n",
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       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>rupesh</td>\n",
       "      <td>vit</td>\n",
       "      <td>cse</td>\n",
       "      <td>6.41</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</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>NaN</td>\n",
       "      <td>vlsi</td>\n",
       "      <td>ce</td>\n",
       "      <td>9.00</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>cse</td>\n",
       "      <td>10.00</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>NaN</td>\n",
       "      <td>git</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         name college branch   cgpa  package\n",
       "8      aditya     NaN    bio   7.40      NaN\n",
       "1       ankit     iit     it   8.25      5.0\n",
       "4  mrityunjay     NaN     me   5.60      6.0\n",
       "0      nitish     bit    eee   6.66      4.0\n",
       "6     rishabh    ssit    civ   7.40      8.0\n",
       "2      rupesh     vit    cse   6.41      6.0\n",
       "3         NaN     NaN    NaN    NaN      NaN\n",
       "5         NaN    vlsi     ce   9.00      7.0\n",
       "7         NaN     NaN    cse  10.00      9.0\n",
       "9         NaN     git    NaN    NaN      NaN"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#sort_values when there are missing values............... NaN values goes to bottam defaulty\n",
    "students.sort_values('name')            #By default, (na_position ='last')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ankit</td>\n",
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       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>mrityunjay</td>\n",
       "      <td>NaN</td>\n",
       "      <td>me</td>\n",
       "      <td>5.60</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>nitish</td>\n",
       "      <td>bit</td>\n",
       "      <td>eee</td>\n",
       "      <td>6.66</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>rishabh</td>\n",
       "      <td>ssit</td>\n",
       "      <td>civ</td>\n",
       "      <td>7.40</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>rupesh</td>\n",
       "      <td>vit</td>\n",
       "      <td>cse</td>\n",
       "      <td>6.41</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         name college branch   cgpa  package\n",
       "3         NaN     NaN    NaN    NaN      NaN\n",
       "5         NaN    vlsi     ce   9.00      7.0\n",
       "7         NaN     NaN    cse  10.00      9.0\n",
       "9         NaN     git    NaN    NaN      NaN\n",
       "8      aditya     NaN    bio   7.40      NaN\n",
       "1       ankit     iit     it   8.25      5.0\n",
       "4  mrityunjay     NaN     me   5.60      6.0\n",
       "0      nitish     bit    eee   6.66      4.0\n",
       "6     rishabh    ssit    civ   7.40      8.0\n",
       "2      rupesh     vit    cse   6.41      6.0"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "students.sort_values('name',na_position='first')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
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       "      <th>6</th>\n",
       "      <td>rishabh</td>\n",
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       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>mrityunjay</td>\n",
       "      <td>NaN</td>\n",
       "      <td>me</td>\n",
       "      <td>5.60</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ankit</td>\n",
       "      <td>iit</td>\n",
       "      <td>it</td>\n",
       "      <td>8.25</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>aditya</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bio</td>\n",
       "      <td>7.40</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         name college branch   cgpa  package\n",
       "3         NaN     NaN    NaN    NaN      NaN\n",
       "5         NaN    vlsi     ce   9.00      7.0\n",
       "7         NaN     NaN    cse  10.00      9.0\n",
       "9         NaN     git    NaN    NaN      NaN\n",
       "2      rupesh     vit    cse   6.41      6.0\n",
       "6     rishabh    ssit    civ   7.40      8.0\n",
       "0      nitish     bit    eee   6.66      4.0\n",
       "4  mrityunjay     NaN     me   5.60      6.0\n",
       "1       ankit     iit     it   8.25      5.0\n",
       "8      aditya     NaN    bio   7.40      NaN"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "students.sort_values('name',na_position='first',ascending=False)          #Z to A"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "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",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>college</th>\n",
       "      <th>branch</th>\n",
       "      <th>cgpa</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</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>NaN</td>\n",
       "      <td>vlsi</td>\n",
       "      <td>ce</td>\n",
       "      <td>9.00</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>cse</td>\n",
       "      <td>10.00</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>NaN</td>\n",
       "      <td>git</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>rupesh</td>\n",
       "      <td>vit</td>\n",
       "      <td>cse</td>\n",
       "      <td>6.41</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>rishabh</td>\n",
       "      <td>ssit</td>\n",
       "      <td>civ</td>\n",
       "      <td>7.40</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>nitish</td>\n",
       "      <td>bit</td>\n",
       "      <td>eee</td>\n",
       "      <td>6.66</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>mrityunjay</td>\n",
       "      <td>NaN</td>\n",
       "      <td>me</td>\n",
       "      <td>5.60</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ankit</td>\n",
       "      <td>iit</td>\n",
       "      <td>it</td>\n",
       "      <td>8.25</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>aditya</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bio</td>\n",
       "      <td>7.40</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         name college branch   cgpa  package\n",
       "3         NaN     NaN    NaN    NaN      NaN\n",
       "5         NaN    vlsi     ce   9.00      7.0\n",
       "7         NaN     NaN    cse  10.00      9.0\n",
       "9         NaN     git    NaN    NaN      NaN\n",
       "2      rupesh     vit    cse   6.41      6.0\n",
       "6     rishabh    ssit    civ   7.40      8.0\n",
       "0      nitish     bit    eee   6.66      4.0\n",
       "4  mrityunjay     NaN     me   5.60      6.0\n",
       "1       ankit     iit     it   8.25      5.0\n",
       "8      aditya     NaN    bio   7.40      NaN"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "students.sort_values('name',na_position='first',ascending=False,inplace=True)  #permanant change\n",
    "students"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>title_x</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>poster_path</th>\n",
       "      <th>wiki_link</th>\n",
       "      <th>title_y</th>\n",
       "      <th>original_title</th>\n",
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       "      <th>year_of_release</th>\n",
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       "      <th>genres</th>\n",
       "      <th>imdb_rating</th>\n",
       "      <th>imdb_votes</th>\n",
       "      <th>story</th>\n",
       "      <th>summary</th>\n",
       "      <th>tagline</th>\n",
       "      <th>actors</th>\n",
       "      <th>wins_nominations</th>\n",
       "      <th>release_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1575</th>\n",
       "      <td>Aalavandhan</td>\n",
       "      <td>tt0294264</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Aalavandhan</td>\n",
       "      <td>Aalavandhan</td>\n",
       "      <td>Aalavandhan</td>\n",
       "      <td>0</td>\n",
       "      <td>2001</td>\n",
       "      <td>177</td>\n",
       "      <td>Action|Thriller</td>\n",
       "      <td>7.1</td>\n",
       "      <td>1746</td>\n",
       "      <td>The story follows Abhay (Haasan) who has a dis...</td>\n",
       "      <td>A psychopath tries to protect his twin brother...</td>\n",
       "      <td>The Fearless</td>\n",
       "      <td>Kamal Haasan|Raveena Tandon|Manisha Koirala|Ki...</td>\n",
       "      <td>1 win &amp; 1 nomination</td>\n",
       "      <td>16 November 2001 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1576</th>\n",
       "      <td>Aamdani Atthanni Kharcha Rupaiya</td>\n",
       "      <td>tt0305173</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Aamdani_Atthanni...</td>\n",
       "      <td>Aamdani Atthanni Kharcha Rupaiya</td>\n",
       "      <td>Aamdani Atthanni Kharcha Rupaiya</td>\n",
       "      <td>0</td>\n",
       "      <td>2001</td>\n",
       "      <td>150</td>\n",
       "      <td>Comedy|Drama|Family</td>\n",
       "      <td>4.7</td>\n",
       "      <td>1026</td>\n",
       "      <td>Jhoomri and her husband  Bhimsha  move into a ...</td>\n",
       "      <td>In order to make ends meet  three women steps ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Govinda|Juhi Chawla|Tabu|Chandrachur Singh|Joh...</td>\n",
       "      <td>1 nomination</td>\n",
       "      <td>21 December 2001 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1577</th>\n",
       "      <td>Aashiq (2001 film)</td>\n",
       "      <td>tt0273406</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/c/c6...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Aashiq_(2001_film)</td>\n",
       "      <td>Aashiq</td>\n",
       "      <td>Aashiq</td>\n",
       "      <td>0</td>\n",
       "      <td>2001</td>\n",
       "      <td>160</td>\n",
       "      <td>Action|Drama|Romance</td>\n",
       "      <td>3.8</td>\n",
       "      <td>357</td>\n",
       "      <td>Pooja and Chander Kapoor have a heart-to-heart...</td>\n",
       "      <td>Pooja and Chander Kapoor have a heart-to-heart...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bobby Deol|Karisma Kapoor|</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26 January 2001 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1579</th>\n",
       "      <td>Ajnabee (2001 film)</td>\n",
       "      <td>tt0278291</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Ajnabee_(2001_film)</td>\n",
       "      <td>Ajnabee</td>\n",
       "      <td>Ajnabee</td>\n",
       "      <td>0</td>\n",
       "      <td>2001</td>\n",
       "      <td>165</td>\n",
       "      <td>Action|Crime|Drama</td>\n",
       "      <td>6.3</td>\n",
       "      <td>7480</td>\n",
       "      <td>A new couple get married and move to Switzerla...</td>\n",
       "      <td>Bobby Deol and Kareena Kapoor play a new coupl...</td>\n",
       "      <td>Trust no one</td>\n",
       "      <td>Akshay Kumar|Bobby Deol|Kareena Kapoor|Bipasha...</td>\n",
       "      <td>3 wins &amp; 9 nominations</td>\n",
       "      <td>21 September 2001 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1578</th>\n",
       "      <td>Aks (2001 film)</td>\n",
       "      <td>tt0289845</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Aks_(2001_film)</td>\n",
       "      <td>Aks</td>\n",
       "      <td>Aks</td>\n",
       "      <td>0</td>\n",
       "      <td>2001</td>\n",
       "      <td>184</td>\n",
       "      <td>Action|Crime|Horror</td>\n",
       "      <td>5.9</td>\n",
       "      <td>1518</td>\n",
       "      <td>Aks is the story of a hunter and his prey. A c...</td>\n",
       "      <td>Raghavan Ghatge  a psychotic terrorist  and Ma...</td>\n",
       "      <td>There is a stranger in your mirror</td>\n",
       "      <td>Amitabh Bachchan|Raveena Tandon|Manoj Bajpayee...</td>\n",
       "      <td>9 wins &amp; 14 nominations</td>\n",
       "      <td>13 July 2001 (India)</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",
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       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>Ujda Chaman</td>\n",
       "      <td>tt11046300</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Ujda_Chaman</td>\n",
       "      <td>Ujda Chaman</td>\n",
       "      <td>Ujda Chaman</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>120</td>\n",
       "      <td>Comedy</td>\n",
       "      <td>8.1</td>\n",
       "      <td>1440</td>\n",
       "      <td>Ujda Chaman is about a 30 -year-old bachelor C...</td>\n",
       "      <td>Ujda Chaman is about a 30 -year-old bachelor C...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sunny Singh Nijjar|Maanvi Gagroo|Saurabh Shukl...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1 November 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>tt8291224</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Uri:_The_Surgica...</td>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>138</td>\n",
       "      <td>Action|Drama|War</td>\n",
       "      <td>8.4</td>\n",
       "      <td>35112</td>\n",
       "      <td>Divided over five chapters  the film chronicle...</td>\n",
       "      <td>Indian army special forces execute a covert op...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...</td>\n",
       "      <td>4 wins</td>\n",
       "      <td>11 January 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Why Cheat India</td>\n",
       "      <td>tt8108208</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Why_Cheat_India</td>\n",
       "      <td>Why Cheat India</td>\n",
       "      <td>Why Cheat India</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>121</td>\n",
       "      <td>Crime|Drama</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1891</td>\n",
       "      <td>The movie focuses on existing malpractices in ...</td>\n",
       "      <td>The movie focuses on existing malpractices in ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Emraan Hashmi|Shreya Dhanwanthary|Snighdadeep ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18 January 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>Yaaram (2019 film)</td>\n",
       "      <td>tt11007050</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Yaaram_(2019_film)</td>\n",
       "      <td>#Yaaram</td>\n",
       "      <td>#Yaaram</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>\\N</td>\n",
       "      <td>Comedy|Romance</td>\n",
       "      <td>5.7</td>\n",
       "      <td>7</td>\n",
       "      <td>All set for an arranged marriage  Rohit Bajaj ...</td>\n",
       "      <td>All set for an arranged marriage  Rohit Bajaj ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Siddhanth Kapoor|Prateik|Anita Raj|Ishita Raj|...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>Yeh Saali Aashiqui</td>\n",
       "      <td>tt10443846</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Yeh_Saali_Aashiqui</td>\n",
       "      <td>Yeh Saali Aashiqui</td>\n",
       "      <td>Yeh Saali Aashiqui</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>137</td>\n",
       "      <td>Thriller</td>\n",
       "      <td>7.9</td>\n",
       "      <td>3200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Add a Plot »</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vardhan Puri|Jessey Lever|</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1629 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                               title_x     imdb_id  \\\n",
       "1575                       Aalavandhan   tt0294264   \n",
       "1576  Aamdani Atthanni Kharcha Rupaiya   tt0305173   \n",
       "1577                Aashiq (2001 film)   tt0273406   \n",
       "1579               Ajnabee (2001 film)   tt0278291   \n",
       "1578                   Aks (2001 film)   tt0289845   \n",
       "...                                ...         ...   \n",
       "64                         Ujda Chaman  tt11046300   \n",
       "0             Uri: The Surgical Strike   tt8291224   \n",
       "3                      Why Cheat India   tt8108208   \n",
       "60                  Yaaram (2019 film)  tt11007050   \n",
       "73                  Yeh Saali Aashiqui  tt10443846   \n",
       "\n",
       "                                            poster_path  \\\n",
       "1575  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "1576  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "1577  https://upload.wikimedia.org/wikipedia/en/c/c6...   \n",
       "1579  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "1578  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "...                                                 ...   \n",
       "64    https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "0     https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "3     https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "60    https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "73    https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "\n",
       "                                              wiki_link  \\\n",
       "1575          https://en.wikipedia.org/wiki/Aalavandhan   \n",
       "1576  https://en.wikipedia.org/wiki/Aamdani_Atthanni...   \n",
       "1577   https://en.wikipedia.org/wiki/Aashiq_(2001_film)   \n",
       "1579  https://en.wikipedia.org/wiki/Ajnabee_(2001_film)   \n",
       "1578      https://en.wikipedia.org/wiki/Aks_(2001_film)   \n",
       "...                                                 ...   \n",
       "64            https://en.wikipedia.org/wiki/Ujda_Chaman   \n",
       "0     https://en.wikipedia.org/wiki/Uri:_The_Surgica...   \n",
       "3         https://en.wikipedia.org/wiki/Why_Cheat_India   \n",
       "60     https://en.wikipedia.org/wiki/Yaaram_(2019_film)   \n",
       "73     https://en.wikipedia.org/wiki/Yeh_Saali_Aashiqui   \n",
       "\n",
       "                               title_y                    original_title  \\\n",
       "1575                       Aalavandhan                       Aalavandhan   \n",
       "1576  Aamdani Atthanni Kharcha Rupaiya  Aamdani Atthanni Kharcha Rupaiya   \n",
       "1577                            Aashiq                            Aashiq   \n",
       "1579                           Ajnabee                           Ajnabee   \n",
       "1578                               Aks                               Aks   \n",
       "...                                ...                               ...   \n",
       "64                         Ujda Chaman                       Ujda Chaman   \n",
       "0             Uri: The Surgical Strike          Uri: The Surgical Strike   \n",
       "3                      Why Cheat India                   Why Cheat India   \n",
       "60                             #Yaaram                           #Yaaram   \n",
       "73                  Yeh Saali Aashiqui                Yeh Saali Aashiqui   \n",
       "\n",
       "      is_adult  year_of_release runtime                genres  imdb_rating  \\\n",
       "1575         0             2001     177       Action|Thriller          7.1   \n",
       "1576         0             2001     150   Comedy|Drama|Family          4.7   \n",
       "1577         0             2001     160  Action|Drama|Romance          3.8   \n",
       "1579         0             2001     165    Action|Crime|Drama          6.3   \n",
       "1578         0             2001     184   Action|Crime|Horror          5.9   \n",
       "...        ...              ...     ...                   ...          ...   \n",
       "64           0             2019     120                Comedy          8.1   \n",
       "0            0             2019     138      Action|Drama|War          8.4   \n",
       "3            0             2019     121           Crime|Drama          6.0   \n",
       "60           0             2019      \\N        Comedy|Romance          5.7   \n",
       "73           0             2019     137              Thriller          7.9   \n",
       "\n",
       "      imdb_votes                                              story  \\\n",
       "1575        1746  The story follows Abhay (Haasan) who has a dis...   \n",
       "1576        1026  Jhoomri and her husband  Bhimsha  move into a ...   \n",
       "1577         357  Pooja and Chander Kapoor have a heart-to-heart...   \n",
       "1579        7480  A new couple get married and move to Switzerla...   \n",
       "1578        1518  Aks is the story of a hunter and his prey. A c...   \n",
       "...          ...                                                ...   \n",
       "64          1440  Ujda Chaman is about a 30 -year-old bachelor C...   \n",
       "0          35112  Divided over five chapters  the film chronicle...   \n",
       "3           1891  The movie focuses on existing malpractices in ...   \n",
       "60             7  All set for an arranged marriage  Rohit Bajaj ...   \n",
       "73          3200                                                NaN   \n",
       "\n",
       "                                                summary  \\\n",
       "1575  A psychopath tries to protect his twin brother...   \n",
       "1576  In order to make ends meet  three women steps ...   \n",
       "1577  Pooja and Chander Kapoor have a heart-to-heart...   \n",
       "1579  Bobby Deol and Kareena Kapoor play a new coupl...   \n",
       "1578  Raghavan Ghatge  a psychotic terrorist  and Ma...   \n",
       "...                                                 ...   \n",
       "64    Ujda Chaman is about a 30 -year-old bachelor C...   \n",
       "0     Indian army special forces execute a covert op...   \n",
       "3     The movie focuses on existing malpractices in ...   \n",
       "60    All set for an arranged marriage  Rohit Bajaj ...   \n",
       "73                                         Add a Plot »   \n",
       "\n",
       "                                 tagline  \\\n",
       "1575                        The Fearless   \n",
       "1576                                 NaN   \n",
       "1577                                 NaN   \n",
       "1579                        Trust no one   \n",
       "1578  There is a stranger in your mirror   \n",
       "...                                  ...   \n",
       "64                                   NaN   \n",
       "0                                    NaN   \n",
       "3                                    NaN   \n",
       "60                                   NaN   \n",
       "73                                   NaN   \n",
       "\n",
       "                                                 actors  \\\n",
       "1575  Kamal Haasan|Raveena Tandon|Manisha Koirala|Ki...   \n",
       "1576  Govinda|Juhi Chawla|Tabu|Chandrachur Singh|Joh...   \n",
       "1577                         Bobby Deol|Karisma Kapoor|   \n",
       "1579  Akshay Kumar|Bobby Deol|Kareena Kapoor|Bipasha...   \n",
       "1578  Amitabh Bachchan|Raveena Tandon|Manoj Bajpayee...   \n",
       "...                                                 ...   \n",
       "64    Sunny Singh Nijjar|Maanvi Gagroo|Saurabh Shukl...   \n",
       "0     Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...   \n",
       "3     Emraan Hashmi|Shreya Dhanwanthary|Snighdadeep ...   \n",
       "60    Siddhanth Kapoor|Prateik|Anita Raj|Ishita Raj|...   \n",
       "73                           Vardhan Puri|Jessey Lever|   \n",
       "\n",
       "             wins_nominations               release_date  \n",
       "1575     1 win & 1 nomination   16 November 2001 (India)  \n",
       "1576             1 nomination   21 December 2001 (India)  \n",
       "1577                      NaN    26 January 2001 (India)  \n",
       "1579   3 wins & 9 nominations  21 September 2001 (India)  \n",
       "1578  9 wins & 14 nominations       13 July 2001 (India)  \n",
       "...                       ...                        ...  \n",
       "64                        NaN      1 November 2019 (USA)  \n",
       "0                      4 wins      11 January 2019 (USA)  \n",
       "3                         NaN      18 January 2019 (USA)  \n",
       "60                        NaN                        NaN  \n",
       "73                        NaN                        NaN  \n",
       "\n",
       "[1629 rows x 18 columns]"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#sorting with multiple columns\n",
    "movies.sort_values(['year_of_release','title_x'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "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>title_x</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>poster_path</th>\n",
       "      <th>wiki_link</th>\n",
       "      <th>title_y</th>\n",
       "      <th>original_title</th>\n",
       "      <th>is_adult</th>\n",
       "      <th>year_of_release</th>\n",
       "      <th>runtime</th>\n",
       "      <th>genres</th>\n",
       "      <th>imdb_rating</th>\n",
       "      <th>imdb_votes</th>\n",
       "      <th>story</th>\n",
       "      <th>summary</th>\n",
       "      <th>tagline</th>\n",
       "      <th>actors</th>\n",
       "      <th>wins_nominations</th>\n",
       "      <th>release_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1623</th>\n",
       "      <td>Zubeidaa</td>\n",
       "      <td>tt0255713</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Zubeidaa</td>\n",
       "      <td>Zubeidaa</td>\n",
       "      <td>Zubeidaa</td>\n",
       "      <td>0</td>\n",
       "      <td>2001</td>\n",
       "      <td>153</td>\n",
       "      <td>Biography|Drama|History</td>\n",
       "      <td>6.2</td>\n",
       "      <td>1384</td>\n",
       "      <td>The film begins with Riyaz (Rajat Kapoor)  Zub...</td>\n",
       "      <td>Zubeidaa  an aspiring Muslim actress  marries ...</td>\n",
       "      <td>The Story of a Princess</td>\n",
       "      <td>Karisma Kapoor|Rekha|Manoj Bajpayee|Rajit Kapo...</td>\n",
       "      <td>3 wins &amp; 13 nominations</td>\n",
       "      <td>19 January 2001 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1625</th>\n",
       "      <td>Yeh Zindagi Ka Safar</td>\n",
       "      <td>tt0298607</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Yeh_Zindagi_Ka_S...</td>\n",
       "      <td>Yeh Zindagi Ka Safar</td>\n",
       "      <td>Yeh Zindagi Ka Safar</td>\n",
       "      <td>0</td>\n",
       "      <td>2001</td>\n",
       "      <td>146</td>\n",
       "      <td>Drama</td>\n",
       "      <td>3.0</td>\n",
       "      <td>133</td>\n",
       "      <td>Hindi pop-star  Sarina Devan  lives a wealthy ...</td>\n",
       "      <td>A singer finds out she was adopted when the ed...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ameesha Patel|Jimmy Sheirgill|Nafisa Ali|Gulsh...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16 November 2001 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1622</th>\n",
       "      <td>Yeh Teraa Ghar Yeh Meraa Ghar</td>\n",
       "      <td>tt0298606</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Yeh_Teraa_Ghar_Y...</td>\n",
       "      <td>Yeh Teraa Ghar Yeh Meraa Ghar</td>\n",
       "      <td>Yeh Teraa Ghar Yeh Meraa Ghar</td>\n",
       "      <td>0</td>\n",
       "      <td>2001</td>\n",
       "      <td>175</td>\n",
       "      <td>Comedy|Drama</td>\n",
       "      <td>5.7</td>\n",
       "      <td>704</td>\n",
       "      <td>In debt; Dayashankar Pandey is forced to go to...</td>\n",
       "      <td>In debt; Dayashankar Pandey is forced to go to...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sunil Shetty|Mahima Chaudhry|Paresh Rawal|Saur...</td>\n",
       "      <td>1 nomination</td>\n",
       "      <td>12 October 2001 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1620</th>\n",
       "      <td>Yeh Raaste Hain Pyaar Ke</td>\n",
       "      <td>tt0292740</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Yeh_Raaste_Hain_...</td>\n",
       "      <td>Yeh Raaste Hain Pyaar Ke</td>\n",
       "      <td>Yeh Raaste Hain Pyaar Ke</td>\n",
       "      <td>0</td>\n",
       "      <td>2001</td>\n",
       "      <td>149</td>\n",
       "      <td>Drama|Romance</td>\n",
       "      <td>4.0</td>\n",
       "      <td>607</td>\n",
       "      <td>Two con artistes and car thieves  Vicky (Ajay ...</td>\n",
       "      <td>Two con artistes and car thieves  Vicky (Ajay ...</td>\n",
       "      <td>Love is a journey... not a destination</td>\n",
       "      <td>Ajay Devgn|Madhuri Dixit|Preity Zinta|Vikram G...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10 August 2001 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1573</th>\n",
       "      <td>Yaadein (2001 film)</td>\n",
       "      <td>tt0248617</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Yaadein_(2001_film)</td>\n",
       "      <td>Yaadein...</td>\n",
       "      <td>Yaadein...</td>\n",
       "      <td>0</td>\n",
       "      <td>2001</td>\n",
       "      <td>171</td>\n",
       "      <td>Drama|Musical|Romance</td>\n",
       "      <td>4.4</td>\n",
       "      <td>3034</td>\n",
       "      <td>Raj Singh Puri is best friends with L.K. Malho...</td>\n",
       "      <td>Raj Singh Puri is best friends with L.K. Malho...</td>\n",
       "      <td>memories to cherish...</td>\n",
       "      <td>Jackie Shroff|Hrithik Roshan|Kareena Kapoor|Am...</td>\n",
       "      <td>1 nomination</td>\n",
       "      <td>27 June 2001 (India)</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Article 15 (film)</td>\n",
       "      <td>tt10324144</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Article_15_(film)</td>\n",
       "      <td>Article 15</td>\n",
       "      <td>Article 15</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>130</td>\n",
       "      <td>Crime|Drama</td>\n",
       "      <td>8.3</td>\n",
       "      <td>13417</td>\n",
       "      <td>In the rural heartlands of India  an upright p...</td>\n",
       "      <td>In the rural heartlands of India  an upright p...</td>\n",
       "      <td>Farq Bahut Kar Liya| Ab Farq Laayenge.</td>\n",
       "      <td>Ayushmann Khurrana|Nassar|Manoj Pahwa|Kumud Mi...</td>\n",
       "      <td>1 win</td>\n",
       "      <td>28 June 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Arjun Patiala</td>\n",
       "      <td>tt7881524</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Arjun_Patiala</td>\n",
       "      <td>Arjun Patiala</td>\n",
       "      <td>Arjun Patiala</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>107</td>\n",
       "      <td>Action|Comedy</td>\n",
       "      <td>4.1</td>\n",
       "      <td>676</td>\n",
       "      <td>Arjun Patiala(Diljit Dosanjh)has recently been...</td>\n",
       "      <td>This spoof comedy narrates the story of a cop ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Diljit Dosanjh|Kriti Sanon|Varun Sharma|Ronit ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26 July 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Amavas</td>\n",
       "      <td>tt8396186</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Amavas</td>\n",
       "      <td>Amavas</td>\n",
       "      <td>Amavas</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>134</td>\n",
       "      <td>Horror|Thriller</td>\n",
       "      <td>2.8</td>\n",
       "      <td>235</td>\n",
       "      <td>Far away from the bustle of the city  a young ...</td>\n",
       "      <td>The lives of a couple turn into a nightmare  a...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ali Asgar|Vivan Bhatena|Nargis Fakhri|Sachiin ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8 February 2019 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Albert Pinto Ko Gussa Kyun Aata Hai?</td>\n",
       "      <td>tt4355838</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Albert_Pinto_Ko_...</td>\n",
       "      <td>Albert Pinto Ko Gussa Kyun Aata Hai?</td>\n",
       "      <td>Albert Pinto Ko Gussa Kyun Aata Hai?</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>100</td>\n",
       "      <td>Drama</td>\n",
       "      <td>4.8</td>\n",
       "      <td>56</td>\n",
       "      <td>Albert leaves his house one morning without te...</td>\n",
       "      <td>Albert Pinto goes missing one day and his girl...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Manav Kaul|Nandita Das|</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12 April 2019 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22 Yards</td>\n",
       "      <td>tt9496212</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/22_Yards</td>\n",
       "      <td>22 Yards</td>\n",
       "      <td>22 Yards</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>126</td>\n",
       "      <td>Sport</td>\n",
       "      <td>5.3</td>\n",
       "      <td>124</td>\n",
       "      <td>A dramatic portrayal of a victorious tale of a...</td>\n",
       "      <td>A dramatic portrayal of a victorious tale of a...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Barun Sobti|Rajit Kapur|Panchhi Bora|Kartikey ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15 March 2019 (India)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1629 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   title_x     imdb_id  \\\n",
       "1623                              Zubeidaa   tt0255713   \n",
       "1625                  Yeh Zindagi Ka Safar   tt0298607   \n",
       "1622         Yeh Teraa Ghar Yeh Meraa Ghar   tt0298606   \n",
       "1620              Yeh Raaste Hain Pyaar Ke   tt0292740   \n",
       "1573                   Yaadein (2001 film)   tt0248617   \n",
       "...                                    ...         ...   \n",
       "37                       Article 15 (film)  tt10324144   \n",
       "46                           Arjun Patiala   tt7881524   \n",
       "10                                  Amavas   tt8396186   \n",
       "26    Albert Pinto Ko Gussa Kyun Aata Hai?   tt4355838   \n",
       "21                                22 Yards   tt9496212   \n",
       "\n",
       "                                            poster_path  \\\n",
       "1623  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "1625  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "1622  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "1620  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "1573  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "...                                                 ...   \n",
       "37    https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "46    https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "10    https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "26    https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "21    https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "\n",
       "                                              wiki_link  \\\n",
       "1623             https://en.wikipedia.org/wiki/Zubeidaa   \n",
       "1625  https://en.wikipedia.org/wiki/Yeh_Zindagi_Ka_S...   \n",
       "1622  https://en.wikipedia.org/wiki/Yeh_Teraa_Ghar_Y...   \n",
       "1620  https://en.wikipedia.org/wiki/Yeh_Raaste_Hain_...   \n",
       "1573  https://en.wikipedia.org/wiki/Yaadein_(2001_film)   \n",
       "...                                                 ...   \n",
       "37      https://en.wikipedia.org/wiki/Article_15_(film)   \n",
       "46          https://en.wikipedia.org/wiki/Arjun_Patiala   \n",
       "10                 https://en.wikipedia.org/wiki/Amavas   \n",
       "26    https://en.wikipedia.org/wiki/Albert_Pinto_Ko_...   \n",
       "21               https://en.wikipedia.org/wiki/22_Yards   \n",
       "\n",
       "                                   title_y  \\\n",
       "1623                              Zubeidaa   \n",
       "1625                  Yeh Zindagi Ka Safar   \n",
       "1622         Yeh Teraa Ghar Yeh Meraa Ghar   \n",
       "1620              Yeh Raaste Hain Pyaar Ke   \n",
       "1573                            Yaadein...   \n",
       "...                                    ...   \n",
       "37                              Article 15   \n",
       "46                           Arjun Patiala   \n",
       "10                                  Amavas   \n",
       "26    Albert Pinto Ko Gussa Kyun Aata Hai?   \n",
       "21                                22 Yards   \n",
       "\n",
       "                            original_title  is_adult  year_of_release runtime  \\\n",
       "1623                              Zubeidaa         0             2001     153   \n",
       "1625                  Yeh Zindagi Ka Safar         0             2001     146   \n",
       "1622         Yeh Teraa Ghar Yeh Meraa Ghar         0             2001     175   \n",
       "1620              Yeh Raaste Hain Pyaar Ke         0             2001     149   \n",
       "1573                            Yaadein...         0             2001     171   \n",
       "...                                    ...       ...              ...     ...   \n",
       "37                              Article 15         0             2019     130   \n",
       "46                           Arjun Patiala         0             2019     107   \n",
       "10                                  Amavas         0             2019     134   \n",
       "26    Albert Pinto Ko Gussa Kyun Aata Hai?         0             2019     100   \n",
       "21                                22 Yards         0             2019     126   \n",
       "\n",
       "                       genres  imdb_rating  imdb_votes  \\\n",
       "1623  Biography|Drama|History          6.2        1384   \n",
       "1625                    Drama          3.0         133   \n",
       "1622             Comedy|Drama          5.7         704   \n",
       "1620            Drama|Romance          4.0         607   \n",
       "1573    Drama|Musical|Romance          4.4        3034   \n",
       "...                       ...          ...         ...   \n",
       "37                Crime|Drama          8.3       13417   \n",
       "46              Action|Comedy          4.1         676   \n",
       "10            Horror|Thriller          2.8         235   \n",
       "26                      Drama          4.8          56   \n",
       "21                      Sport          5.3         124   \n",
       "\n",
       "                                                  story  \\\n",
       "1623  The film begins with Riyaz (Rajat Kapoor)  Zub...   \n",
       "1625  Hindi pop-star  Sarina Devan  lives a wealthy ...   \n",
       "1622  In debt; Dayashankar Pandey is forced to go to...   \n",
       "1620  Two con artistes and car thieves  Vicky (Ajay ...   \n",
       "1573  Raj Singh Puri is best friends with L.K. Malho...   \n",
       "...                                                 ...   \n",
       "37    In the rural heartlands of India  an upright p...   \n",
       "46    Arjun Patiala(Diljit Dosanjh)has recently been...   \n",
       "10    Far away from the bustle of the city  a young ...   \n",
       "26    Albert leaves his house one morning without te...   \n",
       "21    A dramatic portrayal of a victorious tale of a...   \n",
       "\n",
       "                                                summary  \\\n",
       "1623  Zubeidaa  an aspiring Muslim actress  marries ...   \n",
       "1625  A singer finds out she was adopted when the ed...   \n",
       "1622  In debt; Dayashankar Pandey is forced to go to...   \n",
       "1620  Two con artistes and car thieves  Vicky (Ajay ...   \n",
       "1573  Raj Singh Puri is best friends with L.K. Malho...   \n",
       "...                                                 ...   \n",
       "37    In the rural heartlands of India  an upright p...   \n",
       "46    This spoof comedy narrates the story of a cop ...   \n",
       "10    The lives of a couple turn into a nightmare  a...   \n",
       "26    Albert Pinto goes missing one day and his girl...   \n",
       "21    A dramatic portrayal of a victorious tale of a...   \n",
       "\n",
       "                                     tagline  \\\n",
       "1623                 The Story of a Princess   \n",
       "1625                                     NaN   \n",
       "1622                                     NaN   \n",
       "1620  Love is a journey... not a destination   \n",
       "1573                  memories to cherish...   \n",
       "...                                      ...   \n",
       "37    Farq Bahut Kar Liya| Ab Farq Laayenge.   \n",
       "46                                       NaN   \n",
       "10                                       NaN   \n",
       "26                                       NaN   \n",
       "21                                       NaN   \n",
       "\n",
       "                                                 actors  \\\n",
       "1623  Karisma Kapoor|Rekha|Manoj Bajpayee|Rajit Kapo...   \n",
       "1625  Ameesha Patel|Jimmy Sheirgill|Nafisa Ali|Gulsh...   \n",
       "1622  Sunil Shetty|Mahima Chaudhry|Paresh Rawal|Saur...   \n",
       "1620  Ajay Devgn|Madhuri Dixit|Preity Zinta|Vikram G...   \n",
       "1573  Jackie Shroff|Hrithik Roshan|Kareena Kapoor|Am...   \n",
       "...                                                 ...   \n",
       "37    Ayushmann Khurrana|Nassar|Manoj Pahwa|Kumud Mi...   \n",
       "46    Diljit Dosanjh|Kriti Sanon|Varun Sharma|Ronit ...   \n",
       "10    Ali Asgar|Vivan Bhatena|Nargis Fakhri|Sachiin ...   \n",
       "26                              Manav Kaul|Nandita Das|   \n",
       "21    Barun Sobti|Rajit Kapur|Panchhi Bora|Kartikey ...   \n",
       "\n",
       "             wins_nominations              release_date  \n",
       "1623  3 wins & 13 nominations   19 January 2001 (India)  \n",
       "1625                      NaN  16 November 2001 (India)  \n",
       "1622             1 nomination   12 October 2001 (India)  \n",
       "1620                      NaN    10 August 2001 (India)  \n",
       "1573             1 nomination      27 June 2001 (India)  \n",
       "...                       ...                       ...  \n",
       "37                      1 win        28 June 2019 (USA)  \n",
       "46                        NaN        26 July 2019 (USA)  \n",
       "10                        NaN   8 February 2019 (India)  \n",
       "26                        NaN     12 April 2019 (India)  \n",
       "21                        NaN     15 March 2019 (India)  \n",
       "\n",
       "[1629 rows x 18 columns]"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies.sort_values(['year_of_release','title_x'],ascending=[True,False])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### rank(series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "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>batter</th>\n",
       "      <th>batsman_run</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A Ashish Reddy</td>\n",
       "      <td>280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A Badoni</td>\n",
       "      <td>161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A Chandila</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A Chopra</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>A Choudhary</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           batter  batsman_run\n",
       "0  A Ashish Reddy          280\n",
       "1        A Badoni          161\n",
       "2      A Chandila            4\n",
       "3        A Chopra           53\n",
       "4     A Choudhary           25"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "batsman = pd.read_csv('batsman_runs_ipl.csv')\n",
    "batsman.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      166.5\n",
       "1      226.0\n",
       "2      535.0\n",
       "3      329.0\n",
       "4      402.5\n",
       "       ...  \n",
       "600    594.0\n",
       "601    343.0\n",
       "602    547.5\n",
       "603     27.0\n",
       "604    256.0\n",
       "Name: batsman_run, Length: 605, dtype: float64"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "batsman['batsman_run'].rank(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "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>batter</th>\n",
       "      <th>batsman_run</th>\n",
       "      <th>batting_rank</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A Ashish Reddy</td>\n",
       "      <td>280</td>\n",
       "      <td>166.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A Badoni</td>\n",
       "      <td>161</td>\n",
       "      <td>226.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A Chandila</td>\n",
       "      <td>4</td>\n",
       "      <td>535.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A Chopra</td>\n",
       "      <td>53</td>\n",
       "      <td>329.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>A Choudhary</td>\n",
       "      <td>25</td>\n",
       "      <td>402.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           batter  batsman_run  batting_rank\n",
       "0  A Ashish Reddy          280         166.5\n",
       "1        A Badoni          161         226.0\n",
       "2      A Chandila            4         535.0\n",
       "3        A Chopra           53         329.0\n",
       "4     A Choudhary           25         402.5"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "batsman['batting_rank'] = batsman['batsman_run'].rank(ascending=False)\n",
    "batsman.head()            "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "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>batter</th>\n",
       "      <th>batsman_run</th>\n",
       "      <th>batting_rank</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>569</th>\n",
       "      <td>V Kohli</td>\n",
       "      <td>6634</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>462</th>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>6244</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>DA Warner</td>\n",
       "      <td>5883</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>430</th>\n",
       "      <td>RG Sharma</td>\n",
       "      <td>5881</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>SK Raina</td>\n",
       "      <td>5536</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        batter  batsman_run  batting_rank\n",
       "569    V Kohli         6634           1.0\n",
       "462   S Dhawan         6244           2.0\n",
       "130  DA Warner         5883           3.0\n",
       "430  RG Sharma         5881           4.0\n",
       "493   SK Raina         5536           5.0"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "batsman.sort_values('batting_rank').head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### sort_index(series and dataframe)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "maths       67\n",
       "english     57\n",
       "science     89\n",
       "hindi      100\n",
       "dtype: int64"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#sort_index in series\n",
    "marks = {\n",
    "    'maths':67,\n",
    "    'english':57,\n",
    "    'science':89,\n",
    "    'hindi':100\n",
    "}\n",
    "\n",
    "marks_series = pd.Series(marks)\n",
    "marks_series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "english     57\n",
       "hindi      100\n",
       "maths       67\n",
       "science     89\n",
       "dtype: int64"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "marks_series.sort_index()            #index sorted alphabetically"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "science     89\n",
       "maths       67\n",
       "hindi      100\n",
       "english     57\n",
       "dtype: int64"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "marks_series.sort_index(ascending=False) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title_x</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>poster_path</th>\n",
       "      <th>wiki_link</th>\n",
       "      <th>title_y</th>\n",
       "      <th>original_title</th>\n",
       "      <th>is_adult</th>\n",
       "      <th>year_of_release</th>\n",
       "      <th>runtime</th>\n",
       "      <th>genres</th>\n",
       "      <th>imdb_rating</th>\n",
       "      <th>imdb_votes</th>\n",
       "      <th>story</th>\n",
       "      <th>summary</th>\n",
       "      <th>tagline</th>\n",
       "      <th>actors</th>\n",
       "      <th>wins_nominations</th>\n",
       "      <th>release_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1628</th>\n",
       "      <td>Humsafar</td>\n",
       "      <td>tt2403201</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Humsafar</td>\n",
       "      <td>Humsafar</td>\n",
       "      <td>Humsafar</td>\n",
       "      <td>0</td>\n",
       "      <td>2011</td>\n",
       "      <td>35</td>\n",
       "      <td>Drama|Romance</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2968</td>\n",
       "      <td>Sara and Ashar are childhood friends who share...</td>\n",
       "      <td>Ashar and Khirad are forced to get married due...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Fawad Khan|</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TV Series (2011–2012)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1627</th>\n",
       "      <td>Daaka</td>\n",
       "      <td>tt10833860</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Daaka</td>\n",
       "      <td>Daaka</td>\n",
       "      <td>Daaka</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>136</td>\n",
       "      <td>Action</td>\n",
       "      <td>7.4</td>\n",
       "      <td>38</td>\n",
       "      <td>Shinda tries robbing a bank so he can be wealt...</td>\n",
       "      <td>Shinda tries robbing a bank so he can be wealt...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Gippy Grewal|Zareen Khan|</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1 November 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1626</th>\n",
       "      <td>Sabse Bada Sukh</td>\n",
       "      <td>tt0069204</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Sabse_Bada_Sukh</td>\n",
       "      <td>Sabse Bada Sukh</td>\n",
       "      <td>Sabse Bada Sukh</td>\n",
       "      <td>0</td>\n",
       "      <td>2018</td>\n",
       "      <td>\\N</td>\n",
       "      <td>Comedy|Drama</td>\n",
       "      <td>6.1</td>\n",
       "      <td>13</td>\n",
       "      <td>Village born Lalloo re-locates to Bombay  and ...</td>\n",
       "      <td>Village born Lalloo re-locates to Bombay  and ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vijay Arora|Asrani|Rajni Bala|Kumud Damle|Utpa...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1625</th>\n",
       "      <td>Yeh Zindagi Ka Safar</td>\n",
       "      <td>tt0298607</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Yeh_Zindagi_Ka_S...</td>\n",
       "      <td>Yeh Zindagi Ka Safar</td>\n",
       "      <td>Yeh Zindagi Ka Safar</td>\n",
       "      <td>0</td>\n",
       "      <td>2001</td>\n",
       "      <td>146</td>\n",
       "      <td>Drama</td>\n",
       "      <td>3.0</td>\n",
       "      <td>133</td>\n",
       "      <td>Hindi pop-star  Sarina Devan  lives a wealthy ...</td>\n",
       "      <td>A singer finds out she was adopted when the ed...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ameesha Patel|Jimmy Sheirgill|Nafisa Ali|Gulsh...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16 November 2001 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1624</th>\n",
       "      <td>Tera Mera Saath Rahen</td>\n",
       "      <td>tt0301250</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/2/2b...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Tera_Mera_Saath_...</td>\n",
       "      <td>Tera Mera Saath Rahen</td>\n",
       "      <td>Tera Mera Saath Rahen</td>\n",
       "      <td>0</td>\n",
       "      <td>2001</td>\n",
       "      <td>148</td>\n",
       "      <td>Drama</td>\n",
       "      <td>4.9</td>\n",
       "      <td>278</td>\n",
       "      <td>Raj Dixit lives with his younger brother  Rahu...</td>\n",
       "      <td>A man is torn between his handicapped brother ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ajay Devgn|Sonali Bendre|Namrata Shirodkar|Pre...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7 November 2001 (India)</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Evening Shadows</td>\n",
       "      <td>tt6028796</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Evening_Shadows</td>\n",
       "      <td>Evening Shadows</td>\n",
       "      <td>Evening Shadows</td>\n",
       "      <td>0</td>\n",
       "      <td>2018</td>\n",
       "      <td>102</td>\n",
       "      <td>Drama</td>\n",
       "      <td>7.3</td>\n",
       "      <td>280</td>\n",
       "      <td>While gay rights and marriage equality has bee...</td>\n",
       "      <td>Under the 'Evening Shadows'  truth often plays...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mona Ambegaonkar|Ananth Narayan Mahadevan|Deva...</td>\n",
       "      <td>17 wins &amp; 1 nomination</td>\n",
       "      <td>11 January 2019 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Why Cheat India</td>\n",
       "      <td>tt8108208</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Why_Cheat_India</td>\n",
       "      <td>Why Cheat India</td>\n",
       "      <td>Why Cheat India</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>121</td>\n",
       "      <td>Crime|Drama</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1891</td>\n",
       "      <td>The movie focuses on existing malpractices in ...</td>\n",
       "      <td>The movie focuses on existing malpractices in ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Emraan Hashmi|Shreya Dhanwanthary|Snighdadeep ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18 January 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>The Accidental Prime Minister (film)</td>\n",
       "      <td>tt6986710</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/The_Accidental_P...</td>\n",
       "      <td>The Accidental Prime Minister</td>\n",
       "      <td>The Accidental Prime Minister</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>112</td>\n",
       "      <td>Biography|Drama</td>\n",
       "      <td>6.1</td>\n",
       "      <td>5549</td>\n",
       "      <td>Based on the memoir by Indian policy analyst S...</td>\n",
       "      <td>Explores Manmohan Singh's tenure as the Prime ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Anupam Kher|Akshaye Khanna|Aahana Kumra|Atul S...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11 January 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>tt9472208</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Battalion_609</td>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>131</td>\n",
       "      <td>War</td>\n",
       "      <td>4.1</td>\n",
       "      <td>73</td>\n",
       "      <td>The story revolves around a cricket match betw...</td>\n",
       "      <td>The story of Battalion 609 revolves around a c...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vicky Ahuja|Shoaib Ibrahim|Shrikant Kamat|Elen...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11 January 2019 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>tt8291224</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Uri:_The_Surgica...</td>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>138</td>\n",
       "      <td>Action|Drama|War</td>\n",
       "      <td>8.4</td>\n",
       "      <td>35112</td>\n",
       "      <td>Divided over five chapters  the film chronicle...</td>\n",
       "      <td>Indian army special forces execute a covert op...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...</td>\n",
       "      <td>4 wins</td>\n",
       "      <td>11 January 2019 (USA)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1629 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   title_x     imdb_id  \\\n",
       "1628                              Humsafar   tt2403201   \n",
       "1627                                 Daaka  tt10833860   \n",
       "1626                       Sabse Bada Sukh   tt0069204   \n",
       "1625                  Yeh Zindagi Ka Safar   tt0298607   \n",
       "1624                 Tera Mera Saath Rahen   tt0301250   \n",
       "...                                    ...         ...   \n",
       "4                          Evening Shadows   tt6028796   \n",
       "3                          Why Cheat India   tt8108208   \n",
       "2     The Accidental Prime Minister (film)   tt6986710   \n",
       "1                            Battalion 609   tt9472208   \n",
       "0                 Uri: The Surgical Strike   tt8291224   \n",
       "\n",
       "                                            poster_path  \\\n",
       "1628  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "1627  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "1626                                                NaN   \n",
       "1625  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "1624  https://upload.wikimedia.org/wikipedia/en/2/2b...   \n",
       "...                                                 ...   \n",
       "4                                                   NaN   \n",
       "3     https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "2     https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "1                                                   NaN   \n",
       "0     https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "\n",
       "                                              wiki_link  \\\n",
       "1628             https://en.wikipedia.org/wiki/Humsafar   \n",
       "1627                https://en.wikipedia.org/wiki/Daaka   \n",
       "1626      https://en.wikipedia.org/wiki/Sabse_Bada_Sukh   \n",
       "1625  https://en.wikipedia.org/wiki/Yeh_Zindagi_Ka_S...   \n",
       "1624  https://en.wikipedia.org/wiki/Tera_Mera_Saath_...   \n",
       "...                                                 ...   \n",
       "4         https://en.wikipedia.org/wiki/Evening_Shadows   \n",
       "3         https://en.wikipedia.org/wiki/Why_Cheat_India   \n",
       "2     https://en.wikipedia.org/wiki/The_Accidental_P...   \n",
       "1           https://en.wikipedia.org/wiki/Battalion_609   \n",
       "0     https://en.wikipedia.org/wiki/Uri:_The_Surgica...   \n",
       "\n",
       "                            title_y                 original_title  is_adult  \\\n",
       "1628                       Humsafar                       Humsafar         0   \n",
       "1627                          Daaka                          Daaka         0   \n",
       "1626                Sabse Bada Sukh                Sabse Bada Sukh         0   \n",
       "1625           Yeh Zindagi Ka Safar           Yeh Zindagi Ka Safar         0   \n",
       "1624          Tera Mera Saath Rahen          Tera Mera Saath Rahen         0   \n",
       "...                             ...                            ...       ...   \n",
       "4                   Evening Shadows                Evening Shadows         0   \n",
       "3                   Why Cheat India                Why Cheat India         0   \n",
       "2     The Accidental Prime Minister  The Accidental Prime Minister         0   \n",
       "1                     Battalion 609                  Battalion 609         0   \n",
       "0          Uri: The Surgical Strike       Uri: The Surgical Strike         0   \n",
       "\n",
       "      year_of_release runtime            genres  imdb_rating  imdb_votes  \\\n",
       "1628             2011      35     Drama|Romance          9.0        2968   \n",
       "1627             2019     136            Action          7.4          38   \n",
       "1626             2018      \\N      Comedy|Drama          6.1          13   \n",
       "1625             2001     146             Drama          3.0         133   \n",
       "1624             2001     148             Drama          4.9         278   \n",
       "...               ...     ...               ...          ...         ...   \n",
       "4                2018     102             Drama          7.3         280   \n",
       "3                2019     121       Crime|Drama          6.0        1891   \n",
       "2                2019     112   Biography|Drama          6.1        5549   \n",
       "1                2019     131               War          4.1          73   \n",
       "0                2019     138  Action|Drama|War          8.4       35112   \n",
       "\n",
       "                                                  story  \\\n",
       "1628  Sara and Ashar are childhood friends who share...   \n",
       "1627  Shinda tries robbing a bank so he can be wealt...   \n",
       "1626  Village born Lalloo re-locates to Bombay  and ...   \n",
       "1625  Hindi pop-star  Sarina Devan  lives a wealthy ...   \n",
       "1624  Raj Dixit lives with his younger brother  Rahu...   \n",
       "...                                                 ...   \n",
       "4     While gay rights and marriage equality has bee...   \n",
       "3     The movie focuses on existing malpractices in ...   \n",
       "2     Based on the memoir by Indian policy analyst S...   \n",
       "1     The story revolves around a cricket match betw...   \n",
       "0     Divided over five chapters  the film chronicle...   \n",
       "\n",
       "                                                summary tagline  \\\n",
       "1628  Ashar and Khirad are forced to get married due...     NaN   \n",
       "1627  Shinda tries robbing a bank so he can be wealt...     NaN   \n",
       "1626  Village born Lalloo re-locates to Bombay  and ...     NaN   \n",
       "1625  A singer finds out she was adopted when the ed...     NaN   \n",
       "1624  A man is torn between his handicapped brother ...     NaN   \n",
       "...                                                 ...     ...   \n",
       "4     Under the 'Evening Shadows'  truth often plays...     NaN   \n",
       "3     The movie focuses on existing malpractices in ...     NaN   \n",
       "2     Explores Manmohan Singh's tenure as the Prime ...     NaN   \n",
       "1     The story of Battalion 609 revolves around a c...     NaN   \n",
       "0     Indian army special forces execute a covert op...     NaN   \n",
       "\n",
       "                                                 actors  \\\n",
       "1628                                        Fawad Khan|   \n",
       "1627                          Gippy Grewal|Zareen Khan|   \n",
       "1626  Vijay Arora|Asrani|Rajni Bala|Kumud Damle|Utpa...   \n",
       "1625  Ameesha Patel|Jimmy Sheirgill|Nafisa Ali|Gulsh...   \n",
       "1624  Ajay Devgn|Sonali Bendre|Namrata Shirodkar|Pre...   \n",
       "...                                                 ...   \n",
       "4     Mona Ambegaonkar|Ananth Narayan Mahadevan|Deva...   \n",
       "3     Emraan Hashmi|Shreya Dhanwanthary|Snighdadeep ...   \n",
       "2     Anupam Kher|Akshaye Khanna|Aahana Kumra|Atul S...   \n",
       "1     Vicky Ahuja|Shoaib Ibrahim|Shrikant Kamat|Elen...   \n",
       "0     Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...   \n",
       "\n",
       "            wins_nominations              release_date  \n",
       "1628                     NaN     TV Series (2011–2012)  \n",
       "1627                     NaN     1 November 2019 (USA)  \n",
       "1626                     NaN                       NaN  \n",
       "1625                     NaN  16 November 2001 (India)  \n",
       "1624                     NaN   7 November 2001 (India)  \n",
       "...                      ...                       ...  \n",
       "4     17 wins & 1 nomination   11 January 2019 (India)  \n",
       "3                        NaN     18 January 2019 (USA)  \n",
       "2                        NaN     11 January 2019 (USA)  \n",
       "1                        NaN   11 January 2019 (India)  \n",
       "0                     4 wins     11 January 2019 (USA)  \n",
       "\n",
       "[1629 rows x 18 columns]"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#sort_index in dataframe\n",
    "movies.sort_index(ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### set_index(dataframe) -> inplace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [],
   "source": [
    "batsman.set_index('batter',inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### reset_index(series + dataframe) -> drop parameter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "#opposite of set.index()\n",
    "batsman.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>batter</th>\n",
       "      <th>batsman_run</th>\n",
       "      <th>batting_rank</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A Ashish Reddy</td>\n",
       "      <td>280</td>\n",
       "      <td>166.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A Badoni</td>\n",
       "      <td>161</td>\n",
       "      <td>226.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A Chandila</td>\n",
       "      <td>4</td>\n",
       "      <td>535.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A Chopra</td>\n",
       "      <td>53</td>\n",
       "      <td>329.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>A Choudhary</td>\n",
       "      <td>25</td>\n",
       "      <td>402.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           batter  batsman_run  batting_rank\n",
       "0  A Ashish Reddy          280         166.5\n",
       "1        A Badoni          161         226.0\n",
       "2      A Chandila            4         535.0\n",
       "3        A Chopra           53         329.0\n",
       "4     A Choudhary           25         402.5"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "batsman.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>batter</th>\n",
       "      <th>batsman_run</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>batting_rank</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>166.5</th>\n",
       "      <td>A Ashish Reddy</td>\n",
       "      <td>280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>226.0</th>\n",
       "      <td>A Badoni</td>\n",
       "      <td>161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>535.0</th>\n",
       "      <td>A Chandila</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>329.0</th>\n",
       "      <td>A Chopra</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>402.5</th>\n",
       "      <td>A Choudhary</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>594.0</th>\n",
       "      <td>Yash Dayal</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>343.0</th>\n",
       "      <td>Yashpal Singh</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>547.5</th>\n",
       "      <td>Younis Khan</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27.0</th>\n",
       "      <td>Yuvraj Singh</td>\n",
       "      <td>2754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256.0</th>\n",
       "      <td>Z Khan</td>\n",
       "      <td>117</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>605 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      batter  batsman_run\n",
       "batting_rank                             \n",
       "166.5         A Ashish Reddy          280\n",
       "226.0               A Badoni          161\n",
       "535.0             A Chandila            4\n",
       "329.0               A Chopra           53\n",
       "402.5            A Choudhary           25\n",
       "...                      ...          ...\n",
       "594.0             Yash Dayal            0\n",
       "343.0          Yashpal Singh           47\n",
       "547.5            Younis Khan            3\n",
       "27.0            Yuvraj Singh         2754\n",
       "256.0                 Z Khan          117\n",
       "\n",
       "[605 rows x 2 columns]"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "batsman.set_index('batting_rank')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>batter</th>\n",
       "      <th>batsman_run</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>batting_rank</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>166.5</th>\n",
       "      <td>0</td>\n",
       "      <td>A Ashish Reddy</td>\n",
       "      <td>280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>226.0</th>\n",
       "      <td>1</td>\n",
       "      <td>A Badoni</td>\n",
       "      <td>161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>535.0</th>\n",
       "      <td>2</td>\n",
       "      <td>A Chandila</td>\n",
       "      <td>4</td>\n",
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       "    <tr>\n",
       "      <th>329.0</th>\n",
       "      <td>3</td>\n",
       "      <td>A Chopra</td>\n",
       "      <td>53</td>\n",
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       "    <tr>\n",
       "      <th>402.5</th>\n",
       "      <td>4</td>\n",
       "      <td>A Choudhary</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>594.0</th>\n",
       "      <td>600</td>\n",
       "      <td>Yash Dayal</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>343.0</th>\n",
       "      <td>601</td>\n",
       "      <td>Yashpal Singh</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>547.5</th>\n",
       "      <td>602</td>\n",
       "      <td>Younis Khan</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27.0</th>\n",
       "      <td>603</td>\n",
       "      <td>Yuvraj Singh</td>\n",
       "      <td>2754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256.0</th>\n",
       "      <td>604</td>\n",
       "      <td>Z Khan</td>\n",
       "      <td>117</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>605 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              index          batter  batsman_run\n",
       "batting_rank                                    \n",
       "166.5             0  A Ashish Reddy          280\n",
       "226.0             1        A Badoni          161\n",
       "535.0             2      A Chandila            4\n",
       "329.0             3        A Chopra           53\n",
       "402.5             4     A Choudhary           25\n",
       "...             ...             ...          ...\n",
       "594.0           600      Yash Dayal            0\n",
       "343.0           601   Yashpal Singh           47\n",
       "547.5           602     Younis Khan            3\n",
       "27.0            603    Yuvraj Singh         2754\n",
       "256.0           604          Z Khan          117\n",
       "\n",
       "[605 rows x 3 columns]"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# how to replace existing index without loosing\n",
    "batsman.reset_index().set_index('batting_rank')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [],
   "source": [
    "#reset_index in series gives a dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "maths       67\n",
       "english     57\n",
       "science     89\n",
       "hindi      100\n",
       "dtype: int64"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "marks_series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "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>index</th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>maths</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>english</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>science</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>hindi</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     index    0\n",
       "0    maths   67\n",
       "1  english   57\n",
       "2  science   89\n",
       "3    hindi  100"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "marks_series.reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(marks_series.reset_index())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### rename(dataframe) -> index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "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>title_x</th>\n",
       "      <th>imdb</th>\n",
       "      <th>link</th>\n",
       "      <th>wiki_link</th>\n",
       "      <th>title_y</th>\n",
       "      <th>original_title</th>\n",
       "      <th>is_adult</th>\n",
       "      <th>year_of_release</th>\n",
       "      <th>runtime</th>\n",
       "      <th>genres</th>\n",
       "      <th>imdb_rating</th>\n",
       "      <th>imdb_votes</th>\n",
       "      <th>story</th>\n",
       "      <th>summary</th>\n",
       "      <th>tagline</th>\n",
       "      <th>actors</th>\n",
       "      <th>wins_nominations</th>\n",
       "      <th>release_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>tt8291224</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Uri:_The_Surgica...</td>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>138</td>\n",
       "      <td>Action|Drama|War</td>\n",
       "      <td>8.4</td>\n",
       "      <td>35112</td>\n",
       "      <td>Divided over five chapters  the film chronicle...</td>\n",
       "      <td>Indian army special forces execute a covert op...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...</td>\n",
       "      <td>4 wins</td>\n",
       "      <td>11 January 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>tt9472208</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Battalion_609</td>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>131</td>\n",
       "      <td>War</td>\n",
       "      <td>4.1</td>\n",
       "      <td>73</td>\n",
       "      <td>The story revolves around a cricket match betw...</td>\n",
       "      <td>The story of Battalion 609 revolves around a c...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vicky Ahuja|Shoaib Ibrahim|Shrikant Kamat|Elen...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11 January 2019 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>The Accidental Prime Minister (film)</td>\n",
       "      <td>tt6986710</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/The_Accidental_P...</td>\n",
       "      <td>The Accidental Prime Minister</td>\n",
       "      <td>The Accidental Prime Minister</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>112</td>\n",
       "      <td>Biography|Drama</td>\n",
       "      <td>6.1</td>\n",
       "      <td>5549</td>\n",
       "      <td>Based on the memoir by Indian policy analyst S...</td>\n",
       "      <td>Explores Manmohan Singh's tenure as the Prime ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Anupam Kher|Akshaye Khanna|Aahana Kumra|Atul S...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11 January 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Why Cheat India</td>\n",
       "      <td>tt8108208</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Why_Cheat_India</td>\n",
       "      <td>Why Cheat India</td>\n",
       "      <td>Why Cheat India</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>121</td>\n",
       "      <td>Crime|Drama</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1891</td>\n",
       "      <td>The movie focuses on existing malpractices in ...</td>\n",
       "      <td>The movie focuses on existing malpractices in ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Emraan Hashmi|Shreya Dhanwanthary|Snighdadeep ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18 January 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Evening Shadows</td>\n",
       "      <td>tt6028796</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Evening_Shadows</td>\n",
       "      <td>Evening Shadows</td>\n",
       "      <td>Evening Shadows</td>\n",
       "      <td>0</td>\n",
       "      <td>2018</td>\n",
       "      <td>102</td>\n",
       "      <td>Drama</td>\n",
       "      <td>7.3</td>\n",
       "      <td>280</td>\n",
       "      <td>While gay rights and marriage equality has bee...</td>\n",
       "      <td>Under the 'Evening Shadows'  truth often plays...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mona Ambegaonkar|Ananth Narayan Mahadevan|Deva...</td>\n",
       "      <td>17 wins &amp; 1 nomination</td>\n",
       "      <td>11 January 2019 (India)</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1624</th>\n",
       "      <td>Tera Mera Saath Rahen</td>\n",
       "      <td>tt0301250</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/2/2b...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Tera_Mera_Saath_...</td>\n",
       "      <td>Tera Mera Saath Rahen</td>\n",
       "      <td>Tera Mera Saath Rahen</td>\n",
       "      <td>0</td>\n",
       "      <td>2001</td>\n",
       "      <td>148</td>\n",
       "      <td>Drama</td>\n",
       "      <td>4.9</td>\n",
       "      <td>278</td>\n",
       "      <td>Raj Dixit lives with his younger brother  Rahu...</td>\n",
       "      <td>A man is torn between his handicapped brother ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ajay Devgn|Sonali Bendre|Namrata Shirodkar|Pre...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7 November 2001 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1625</th>\n",
       "      <td>Yeh Zindagi Ka Safar</td>\n",
       "      <td>tt0298607</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Yeh_Zindagi_Ka_S...</td>\n",
       "      <td>Yeh Zindagi Ka Safar</td>\n",
       "      <td>Yeh Zindagi Ka Safar</td>\n",
       "      <td>0</td>\n",
       "      <td>2001</td>\n",
       "      <td>146</td>\n",
       "      <td>Drama</td>\n",
       "      <td>3.0</td>\n",
       "      <td>133</td>\n",
       "      <td>Hindi pop-star  Sarina Devan  lives a wealthy ...</td>\n",
       "      <td>A singer finds out she was adopted when the ed...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ameesha Patel|Jimmy Sheirgill|Nafisa Ali|Gulsh...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16 November 2001 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1626</th>\n",
       "      <td>Sabse Bada Sukh</td>\n",
       "      <td>tt0069204</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Sabse_Bada_Sukh</td>\n",
       "      <td>Sabse Bada Sukh</td>\n",
       "      <td>Sabse Bada Sukh</td>\n",
       "      <td>0</td>\n",
       "      <td>2018</td>\n",
       "      <td>\\N</td>\n",
       "      <td>Comedy|Drama</td>\n",
       "      <td>6.1</td>\n",
       "      <td>13</td>\n",
       "      <td>Village born Lalloo re-locates to Bombay  and ...</td>\n",
       "      <td>Village born Lalloo re-locates to Bombay  and ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vijay Arora|Asrani|Rajni Bala|Kumud Damle|Utpa...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1627</th>\n",
       "      <td>Daaka</td>\n",
       "      <td>tt10833860</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Daaka</td>\n",
       "      <td>Daaka</td>\n",
       "      <td>Daaka</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>136</td>\n",
       "      <td>Action</td>\n",
       "      <td>7.4</td>\n",
       "      <td>38</td>\n",
       "      <td>Shinda tries robbing a bank so he can be wealt...</td>\n",
       "      <td>Shinda tries robbing a bank so he can be wealt...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Gippy Grewal|Zareen Khan|</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1 November 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1628</th>\n",
       "      <td>Humsafar</td>\n",
       "      <td>tt2403201</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Humsafar</td>\n",
       "      <td>Humsafar</td>\n",
       "      <td>Humsafar</td>\n",
       "      <td>0</td>\n",
       "      <td>2011</td>\n",
       "      <td>35</td>\n",
       "      <td>Drama|Romance</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2968</td>\n",
       "      <td>Sara and Ashar are childhood friends who share...</td>\n",
       "      <td>Ashar and Khirad are forced to get married due...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Fawad Khan|</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TV Series (2011–2012)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1629 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   title_x        imdb  \\\n",
       "0                 Uri: The Surgical Strike   tt8291224   \n",
       "1                            Battalion 609   tt9472208   \n",
       "2     The Accidental Prime Minister (film)   tt6986710   \n",
       "3                          Why Cheat India   tt8108208   \n",
       "4                          Evening Shadows   tt6028796   \n",
       "...                                    ...         ...   \n",
       "1624                 Tera Mera Saath Rahen   tt0301250   \n",
       "1625                  Yeh Zindagi Ka Safar   tt0298607   \n",
       "1626                       Sabse Bada Sukh   tt0069204   \n",
       "1627                                 Daaka  tt10833860   \n",
       "1628                              Humsafar   tt2403201   \n",
       "\n",
       "                                                   link  \\\n",
       "0     https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "1                                                   NaN   \n",
       "2     https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "3     https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "4                                                   NaN   \n",
       "...                                                 ...   \n",
       "1624  https://upload.wikimedia.org/wikipedia/en/2/2b...   \n",
       "1625  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "1626                                                NaN   \n",
       "1627  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "1628  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "\n",
       "                                              wiki_link  \\\n",
       "0     https://en.wikipedia.org/wiki/Uri:_The_Surgica...   \n",
       "1           https://en.wikipedia.org/wiki/Battalion_609   \n",
       "2     https://en.wikipedia.org/wiki/The_Accidental_P...   \n",
       "3         https://en.wikipedia.org/wiki/Why_Cheat_India   \n",
       "4         https://en.wikipedia.org/wiki/Evening_Shadows   \n",
       "...                                                 ...   \n",
       "1624  https://en.wikipedia.org/wiki/Tera_Mera_Saath_...   \n",
       "1625  https://en.wikipedia.org/wiki/Yeh_Zindagi_Ka_S...   \n",
       "1626      https://en.wikipedia.org/wiki/Sabse_Bada_Sukh   \n",
       "1627                https://en.wikipedia.org/wiki/Daaka   \n",
       "1628             https://en.wikipedia.org/wiki/Humsafar   \n",
       "\n",
       "                            title_y                 original_title  is_adult  \\\n",
       "0          Uri: The Surgical Strike       Uri: The Surgical Strike         0   \n",
       "1                     Battalion 609                  Battalion 609         0   \n",
       "2     The Accidental Prime Minister  The Accidental Prime Minister         0   \n",
       "3                   Why Cheat India                Why Cheat India         0   \n",
       "4                   Evening Shadows                Evening Shadows         0   \n",
       "...                             ...                            ...       ...   \n",
       "1624          Tera Mera Saath Rahen          Tera Mera Saath Rahen         0   \n",
       "1625           Yeh Zindagi Ka Safar           Yeh Zindagi Ka Safar         0   \n",
       "1626                Sabse Bada Sukh                Sabse Bada Sukh         0   \n",
       "1627                          Daaka                          Daaka         0   \n",
       "1628                       Humsafar                       Humsafar         0   \n",
       "\n",
       "      year_of_release runtime            genres  imdb_rating  imdb_votes  \\\n",
       "0                2019     138  Action|Drama|War          8.4       35112   \n",
       "1                2019     131               War          4.1          73   \n",
       "2                2019     112   Biography|Drama          6.1        5549   \n",
       "3                2019     121       Crime|Drama          6.0        1891   \n",
       "4                2018     102             Drama          7.3         280   \n",
       "...               ...     ...               ...          ...         ...   \n",
       "1624             2001     148             Drama          4.9         278   \n",
       "1625             2001     146             Drama          3.0         133   \n",
       "1626             2018      \\N      Comedy|Drama          6.1          13   \n",
       "1627             2019     136            Action          7.4          38   \n",
       "1628             2011      35     Drama|Romance          9.0        2968   \n",
       "\n",
       "                                                  story  \\\n",
       "0     Divided over five chapters  the film chronicle...   \n",
       "1     The story revolves around a cricket match betw...   \n",
       "2     Based on the memoir by Indian policy analyst S...   \n",
       "3     The movie focuses on existing malpractices in ...   \n",
       "4     While gay rights and marriage equality has bee...   \n",
       "...                                                 ...   \n",
       "1624  Raj Dixit lives with his younger brother  Rahu...   \n",
       "1625  Hindi pop-star  Sarina Devan  lives a wealthy ...   \n",
       "1626  Village born Lalloo re-locates to Bombay  and ...   \n",
       "1627  Shinda tries robbing a bank so he can be wealt...   \n",
       "1628  Sara and Ashar are childhood friends who share...   \n",
       "\n",
       "                                                summary tagline  \\\n",
       "0     Indian army special forces execute a covert op...     NaN   \n",
       "1     The story of Battalion 609 revolves around a c...     NaN   \n",
       "2     Explores Manmohan Singh's tenure as the Prime ...     NaN   \n",
       "3     The movie focuses on existing malpractices in ...     NaN   \n",
       "4     Under the 'Evening Shadows'  truth often plays...     NaN   \n",
       "...                                                 ...     ...   \n",
       "1624  A man is torn between his handicapped brother ...     NaN   \n",
       "1625  A singer finds out she was adopted when the ed...     NaN   \n",
       "1626  Village born Lalloo re-locates to Bombay  and ...     NaN   \n",
       "1627  Shinda tries robbing a bank so he can be wealt...     NaN   \n",
       "1628  Ashar and Khirad are forced to get married due...     NaN   \n",
       "\n",
       "                                                 actors  \\\n",
       "0     Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...   \n",
       "1     Vicky Ahuja|Shoaib Ibrahim|Shrikant Kamat|Elen...   \n",
       "2     Anupam Kher|Akshaye Khanna|Aahana Kumra|Atul S...   \n",
       "3     Emraan Hashmi|Shreya Dhanwanthary|Snighdadeep ...   \n",
       "4     Mona Ambegaonkar|Ananth Narayan Mahadevan|Deva...   \n",
       "...                                                 ...   \n",
       "1624  Ajay Devgn|Sonali Bendre|Namrata Shirodkar|Pre...   \n",
       "1625  Ameesha Patel|Jimmy Sheirgill|Nafisa Ali|Gulsh...   \n",
       "1626  Vijay Arora|Asrani|Rajni Bala|Kumud Damle|Utpa...   \n",
       "1627                          Gippy Grewal|Zareen Khan|   \n",
       "1628                                        Fawad Khan|   \n",
       "\n",
       "            wins_nominations              release_date  \n",
       "0                     4 wins     11 January 2019 (USA)  \n",
       "1                        NaN   11 January 2019 (India)  \n",
       "2                        NaN     11 January 2019 (USA)  \n",
       "3                        NaN     18 January 2019 (USA)  \n",
       "4     17 wins & 1 nomination   11 January 2019 (India)  \n",
       "...                      ...                       ...  \n",
       "1624                     NaN   7 November 2001 (India)  \n",
       "1625                     NaN  16 November 2001 (India)  \n",
       "1626                     NaN                       NaN  \n",
       "1627                     NaN     1 November 2019 (USA)  \n",
       "1628                     NaN     TV Series (2011–2012)  \n",
       "\n",
       "[1629 rows x 18 columns]"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies.rename(columns={'imdb_id':'imdb','poster_path':'link'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>poster_path</th>\n",
       "      <th>wiki_link</th>\n",
       "      <th>title_y</th>\n",
       "      <th>original_title</th>\n",
       "      <th>is_adult</th>\n",
       "      <th>year_of_release</th>\n",
       "      <th>runtime</th>\n",
       "      <th>genres</th>\n",
       "      <th>imdb_rating</th>\n",
       "      <th>imdb_votes</th>\n",
       "      <th>story</th>\n",
       "      <th>summary</th>\n",
       "      <th>tagline</th>\n",
       "      <th>actors</th>\n",
       "      <th>wins_nominations</th>\n",
       "      <th>release_date</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>title_x</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Uri</th>\n",
       "      <td>tt8291224</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Uri:_The_Surgica...</td>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>138</td>\n",
       "      <td>Action|Drama|War</td>\n",
       "      <td>8.4</td>\n",
       "      <td>35112</td>\n",
       "      <td>Divided over five chapters  the film chronicle...</td>\n",
       "      <td>Indian army special forces execute a covert op...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...</td>\n",
       "      <td>4 wins</td>\n",
       "      <td>11 January 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Battalion</th>\n",
       "      <td>tt9472208</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Battalion_609</td>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>131</td>\n",
       "      <td>War</td>\n",
       "      <td>4.1</td>\n",
       "      <td>73</td>\n",
       "      <td>The story revolves around a cricket match betw...</td>\n",
       "      <td>The story of Battalion 609 revolves around a c...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vicky Ahuja|Shoaib Ibrahim|Shrikant Kamat|Elen...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11 January 2019 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Accidental Prime Minister (film)</th>\n",
       "      <td>tt6986710</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/The_Accidental_P...</td>\n",
       "      <td>The Accidental Prime Minister</td>\n",
       "      <td>The Accidental Prime Minister</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>112</td>\n",
       "      <td>Biography|Drama</td>\n",
       "      <td>6.1</td>\n",
       "      <td>5549</td>\n",
       "      <td>Based on the memoir by Indian policy analyst S...</td>\n",
       "      <td>Explores Manmohan Singh's tenure as the Prime ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Anupam Kher|Akshaye Khanna|Aahana Kumra|Atul S...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11 January 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Why Cheat India</th>\n",
       "      <td>tt8108208</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Why_Cheat_India</td>\n",
       "      <td>Why Cheat India</td>\n",
       "      <td>Why Cheat India</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>121</td>\n",
       "      <td>Crime|Drama</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1891</td>\n",
       "      <td>The movie focuses on existing malpractices in ...</td>\n",
       "      <td>The movie focuses on existing malpractices in ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Emraan Hashmi|Shreya Dhanwanthary|Snighdadeep ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18 January 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Evening Shadows</th>\n",
       "      <td>tt6028796</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Evening_Shadows</td>\n",
       "      <td>Evening Shadows</td>\n",
       "      <td>Evening Shadows</td>\n",
       "      <td>0</td>\n",
       "      <td>2018</td>\n",
       "      <td>102</td>\n",
       "      <td>Drama</td>\n",
       "      <td>7.3</td>\n",
       "      <td>280</td>\n",
       "      <td>While gay rights and marriage equality has bee...</td>\n",
       "      <td>Under the 'Evening Shadows'  truth often plays...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mona Ambegaonkar|Ananth Narayan Mahadevan|Deva...</td>\n",
       "      <td>17 wins &amp; 1 nomination</td>\n",
       "      <td>11 January 2019 (India)</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tera Mera Saath Rahen</th>\n",
       "      <td>tt0301250</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/2/2b...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Tera_Mera_Saath_...</td>\n",
       "      <td>Tera Mera Saath Rahen</td>\n",
       "      <td>Tera Mera Saath Rahen</td>\n",
       "      <td>0</td>\n",
       "      <td>2001</td>\n",
       "      <td>148</td>\n",
       "      <td>Drama</td>\n",
       "      <td>4.9</td>\n",
       "      <td>278</td>\n",
       "      <td>Raj Dixit lives with his younger brother  Rahu...</td>\n",
       "      <td>A man is torn between his handicapped brother ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ajay Devgn|Sonali Bendre|Namrata Shirodkar|Pre...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7 November 2001 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yeh Zindagi Ka Safar</th>\n",
       "      <td>tt0298607</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Yeh_Zindagi_Ka_S...</td>\n",
       "      <td>Yeh Zindagi Ka Safar</td>\n",
       "      <td>Yeh Zindagi Ka Safar</td>\n",
       "      <td>0</td>\n",
       "      <td>2001</td>\n",
       "      <td>146</td>\n",
       "      <td>Drama</td>\n",
       "      <td>3.0</td>\n",
       "      <td>133</td>\n",
       "      <td>Hindi pop-star  Sarina Devan  lives a wealthy ...</td>\n",
       "      <td>A singer finds out she was adopted when the ed...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ameesha Patel|Jimmy Sheirgill|Nafisa Ali|Gulsh...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16 November 2001 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sabse Bada Sukh</th>\n",
       "      <td>tt0069204</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Sabse_Bada_Sukh</td>\n",
       "      <td>Sabse Bada Sukh</td>\n",
       "      <td>Sabse Bada Sukh</td>\n",
       "      <td>0</td>\n",
       "      <td>2018</td>\n",
       "      <td>\\N</td>\n",
       "      <td>Comedy|Drama</td>\n",
       "      <td>6.1</td>\n",
       "      <td>13</td>\n",
       "      <td>Village born Lalloo re-locates to Bombay  and ...</td>\n",
       "      <td>Village born Lalloo re-locates to Bombay  and ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vijay Arora|Asrani|Rajni Bala|Kumud Damle|Utpa...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Daaka</th>\n",
       "      <td>tt10833860</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Daaka</td>\n",
       "      <td>Daaka</td>\n",
       "      <td>Daaka</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>136</td>\n",
       "      <td>Action</td>\n",
       "      <td>7.4</td>\n",
       "      <td>38</td>\n",
       "      <td>Shinda tries robbing a bank so he can be wealt...</td>\n",
       "      <td>Shinda tries robbing a bank so he can be wealt...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Gippy Grewal|Zareen Khan|</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1 November 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Humsafar</th>\n",
       "      <td>tt2403201</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Humsafar</td>\n",
       "      <td>Humsafar</td>\n",
       "      <td>Humsafar</td>\n",
       "      <td>0</td>\n",
       "      <td>2011</td>\n",
       "      <td>35</td>\n",
       "      <td>Drama|Romance</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2968</td>\n",
       "      <td>Sara and Ashar are childhood friends who share...</td>\n",
       "      <td>Ashar and Khirad are forced to get married due...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Fawad Khan|</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TV Series (2011–2012)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1629 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         imdb_id  \\\n",
       "title_x                                            \n",
       "Uri                                    tt8291224   \n",
       "Battalion                              tt9472208   \n",
       "The Accidental Prime Minister (film)   tt6986710   \n",
       "Why Cheat India                        tt8108208   \n",
       "Evening Shadows                        tt6028796   \n",
       "...                                          ...   \n",
       "Tera Mera Saath Rahen                  tt0301250   \n",
       "Yeh Zindagi Ka Safar                   tt0298607   \n",
       "Sabse Bada Sukh                        tt0069204   \n",
       "Daaka                                 tt10833860   \n",
       "Humsafar                               tt2403201   \n",
       "\n",
       "                                                                            poster_path  \\\n",
       "title_x                                                                                   \n",
       "Uri                                   https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "Battalion                                                                           NaN   \n",
       "The Accidental Prime Minister (film)  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "Why Cheat India                       https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "Evening Shadows                                                                     NaN   \n",
       "...                                                                                 ...   \n",
       "Tera Mera Saath Rahen                 https://upload.wikimedia.org/wikipedia/en/2/2b...   \n",
       "Yeh Zindagi Ka Safar                  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "Sabse Bada Sukh                                                                     NaN   \n",
       "Daaka                                 https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "Humsafar                              https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "\n",
       "                                                                              wiki_link  \\\n",
       "title_x                                                                                   \n",
       "Uri                                   https://en.wikipedia.org/wiki/Uri:_The_Surgica...   \n",
       "Battalion                                   https://en.wikipedia.org/wiki/Battalion_609   \n",
       "The Accidental Prime Minister (film)  https://en.wikipedia.org/wiki/The_Accidental_P...   \n",
       "Why Cheat India                           https://en.wikipedia.org/wiki/Why_Cheat_India   \n",
       "Evening Shadows                           https://en.wikipedia.org/wiki/Evening_Shadows   \n",
       "...                                                                                 ...   \n",
       "Tera Mera Saath Rahen                 https://en.wikipedia.org/wiki/Tera_Mera_Saath_...   \n",
       "Yeh Zindagi Ka Safar                  https://en.wikipedia.org/wiki/Yeh_Zindagi_Ka_S...   \n",
       "Sabse Bada Sukh                           https://en.wikipedia.org/wiki/Sabse_Bada_Sukh   \n",
       "Daaka                                               https://en.wikipedia.org/wiki/Daaka   \n",
       "Humsafar                                         https://en.wikipedia.org/wiki/Humsafar   \n",
       "\n",
       "                                                            title_y  \\\n",
       "title_x                                                               \n",
       "Uri                                        Uri: The Surgical Strike   \n",
       "Battalion                                             Battalion 609   \n",
       "The Accidental Prime Minister (film)  The Accidental Prime Minister   \n",
       "Why Cheat India                                     Why Cheat India   \n",
       "Evening Shadows                                     Evening Shadows   \n",
       "...                                                             ...   \n",
       "Tera Mera Saath Rahen                         Tera Mera Saath Rahen   \n",
       "Yeh Zindagi Ka Safar                           Yeh Zindagi Ka Safar   \n",
       "Sabse Bada Sukh                                     Sabse Bada Sukh   \n",
       "Daaka                                                         Daaka   \n",
       "Humsafar                                                   Humsafar   \n",
       "\n",
       "                                                     original_title  is_adult  \\\n",
       "title_x                                                                         \n",
       "Uri                                        Uri: The Surgical Strike         0   \n",
       "Battalion                                             Battalion 609         0   \n",
       "The Accidental Prime Minister (film)  The Accidental Prime Minister         0   \n",
       "Why Cheat India                                     Why Cheat India         0   \n",
       "Evening Shadows                                     Evening Shadows         0   \n",
       "...                                                             ...       ...   \n",
       "Tera Mera Saath Rahen                         Tera Mera Saath Rahen         0   \n",
       "Yeh Zindagi Ka Safar                           Yeh Zindagi Ka Safar         0   \n",
       "Sabse Bada Sukh                                     Sabse Bada Sukh         0   \n",
       "Daaka                                                         Daaka         0   \n",
       "Humsafar                                                   Humsafar         0   \n",
       "\n",
       "                                      year_of_release runtime  \\\n",
       "title_x                                                         \n",
       "Uri                                              2019     138   \n",
       "Battalion                                        2019     131   \n",
       "The Accidental Prime Minister (film)             2019     112   \n",
       "Why Cheat India                                  2019     121   \n",
       "Evening Shadows                                  2018     102   \n",
       "...                                               ...     ...   \n",
       "Tera Mera Saath Rahen                            2001     148   \n",
       "Yeh Zindagi Ka Safar                             2001     146   \n",
       "Sabse Bada Sukh                                  2018      \\N   \n",
       "Daaka                                            2019     136   \n",
       "Humsafar                                         2011      35   \n",
       "\n",
       "                                                genres  imdb_rating  \\\n",
       "title_x                                                               \n",
       "Uri                                   Action|Drama|War          8.4   \n",
       "Battalion                                          War          4.1   \n",
       "The Accidental Prime Minister (film)   Biography|Drama          6.1   \n",
       "Why Cheat India                            Crime|Drama          6.0   \n",
       "Evening Shadows                                  Drama          7.3   \n",
       "...                                                ...          ...   \n",
       "Tera Mera Saath Rahen                            Drama          4.9   \n",
       "Yeh Zindagi Ka Safar                             Drama          3.0   \n",
       "Sabse Bada Sukh                           Comedy|Drama          6.1   \n",
       "Daaka                                           Action          7.4   \n",
       "Humsafar                                 Drama|Romance          9.0   \n",
       "\n",
       "                                      imdb_votes  \\\n",
       "title_x                                            \n",
       "Uri                                        35112   \n",
       "Battalion                                     73   \n",
       "The Accidental Prime Minister (film)        5549   \n",
       "Why Cheat India                             1891   \n",
       "Evening Shadows                              280   \n",
       "...                                          ...   \n",
       "Tera Mera Saath Rahen                        278   \n",
       "Yeh Zindagi Ka Safar                         133   \n",
       "Sabse Bada Sukh                               13   \n",
       "Daaka                                         38   \n",
       "Humsafar                                    2968   \n",
       "\n",
       "                                                                                  story  \\\n",
       "title_x                                                                                   \n",
       "Uri                                   Divided over five chapters  the film chronicle...   \n",
       "Battalion                             The story revolves around a cricket match betw...   \n",
       "The Accidental Prime Minister (film)  Based on the memoir by Indian policy analyst S...   \n",
       "Why Cheat India                       The movie focuses on existing malpractices in ...   \n",
       "Evening Shadows                       While gay rights and marriage equality has bee...   \n",
       "...                                                                                 ...   \n",
       "Tera Mera Saath Rahen                 Raj Dixit lives with his younger brother  Rahu...   \n",
       "Yeh Zindagi Ka Safar                  Hindi pop-star  Sarina Devan  lives a wealthy ...   \n",
       "Sabse Bada Sukh                       Village born Lalloo re-locates to Bombay  and ...   \n",
       "Daaka                                 Shinda tries robbing a bank so he can be wealt...   \n",
       "Humsafar                              Sara and Ashar are childhood friends who share...   \n",
       "\n",
       "                                                                                summary  \\\n",
       "title_x                                                                                   \n",
       "Uri                                   Indian army special forces execute a covert op...   \n",
       "Battalion                             The story of Battalion 609 revolves around a c...   \n",
       "The Accidental Prime Minister (film)  Explores Manmohan Singh's tenure as the Prime ...   \n",
       "Why Cheat India                       The movie focuses on existing malpractices in ...   \n",
       "Evening Shadows                       Under the 'Evening Shadows'  truth often plays...   \n",
       "...                                                                                 ...   \n",
       "Tera Mera Saath Rahen                 A man is torn between his handicapped brother ...   \n",
       "Yeh Zindagi Ka Safar                  A singer finds out she was adopted when the ed...   \n",
       "Sabse Bada Sukh                       Village born Lalloo re-locates to Bombay  and ...   \n",
       "Daaka                                 Shinda tries robbing a bank so he can be wealt...   \n",
       "Humsafar                              Ashar and Khirad are forced to get married due...   \n",
       "\n",
       "                                     tagline  \\\n",
       "title_x                                        \n",
       "Uri                                      NaN   \n",
       "Battalion                                NaN   \n",
       "The Accidental Prime Minister (film)     NaN   \n",
       "Why Cheat India                          NaN   \n",
       "Evening Shadows                          NaN   \n",
       "...                                      ...   \n",
       "Tera Mera Saath Rahen                    NaN   \n",
       "Yeh Zindagi Ka Safar                     NaN   \n",
       "Sabse Bada Sukh                          NaN   \n",
       "Daaka                                    NaN   \n",
       "Humsafar                                 NaN   \n",
       "\n",
       "                                                                                 actors  \\\n",
       "title_x                                                                                   \n",
       "Uri                                   Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...   \n",
       "Battalion                             Vicky Ahuja|Shoaib Ibrahim|Shrikant Kamat|Elen...   \n",
       "The Accidental Prime Minister (film)  Anupam Kher|Akshaye Khanna|Aahana Kumra|Atul S...   \n",
       "Why Cheat India                       Emraan Hashmi|Shreya Dhanwanthary|Snighdadeep ...   \n",
       "Evening Shadows                       Mona Ambegaonkar|Ananth Narayan Mahadevan|Deva...   \n",
       "...                                                                                 ...   \n",
       "Tera Mera Saath Rahen                 Ajay Devgn|Sonali Bendre|Namrata Shirodkar|Pre...   \n",
       "Yeh Zindagi Ka Safar                  Ameesha Patel|Jimmy Sheirgill|Nafisa Ali|Gulsh...   \n",
       "Sabse Bada Sukh                       Vijay Arora|Asrani|Rajni Bala|Kumud Damle|Utpa...   \n",
       "Daaka                                                         Gippy Grewal|Zareen Khan|   \n",
       "Humsafar                                                                    Fawad Khan|   \n",
       "\n",
       "                                            wins_nominations  \\\n",
       "title_x                                                        \n",
       "Uri                                                   4 wins   \n",
       "Battalion                                                NaN   \n",
       "The Accidental Prime Minister (film)                     NaN   \n",
       "Why Cheat India                                          NaN   \n",
       "Evening Shadows                       17 wins & 1 nomination   \n",
       "...                                                      ...   \n",
       "Tera Mera Saath Rahen                                    NaN   \n",
       "Yeh Zindagi Ka Safar                                     NaN   \n",
       "Sabse Bada Sukh                                          NaN   \n",
       "Daaka                                                    NaN   \n",
       "Humsafar                                                 NaN   \n",
       "\n",
       "                                                  release_date  \n",
       "title_x                                                         \n",
       "Uri                                      11 January 2019 (USA)  \n",
       "Battalion                              11 January 2019 (India)  \n",
       "The Accidental Prime Minister (film)     11 January 2019 (USA)  \n",
       "Why Cheat India                          18 January 2019 (USA)  \n",
       "Evening Shadows                        11 January 2019 (India)  \n",
       "...                                                        ...  \n",
       "Tera Mera Saath Rahen                  7 November 2001 (India)  \n",
       "Yeh Zindagi Ka Safar                  16 November 2001 (India)  \n",
       "Sabse Bada Sukh                                            NaN  \n",
       "Daaka                                    1 November 2019 (USA)  \n",
       "Humsafar                                 TV Series (2011–2012)  \n",
       "\n",
       "[1629 rows x 17 columns]"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies.set_index('title_x').rename(index={'Uri: The Surgical Strike':'Uri','Battalion 609':'Battalion'})\n",
    "#can rename columns as well as index"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### unique(series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0     1.0\n",
      "1     1.0\n",
      "2     2.0\n",
      "3     2.0\n",
      "4     3.0\n",
      "5     3.0\n",
      "6     4.0\n",
      "7     4.0\n",
      "8     5.0\n",
      "9     5.0\n",
      "10    NaN\n",
      "11    NaN\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "temp = pd.Series([1,1,2,2,3,3,4,4,5,5,np.nan,np.nan])\n",
    "print(temp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1.,  2.,  3.,  4.,  5., nan])"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6"
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(temp.unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['2022', '2021', '2020/21', '2019', '2018', '2017', '2016', '2015',\n",
       "       '2014', '2013', '2012', '2011', '2009/10', '2009', '2007/08'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl['Season'].unique()            #which are the unique values in column season"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#no of unique values\n",
    "len(ipl['Season'].unique())                              #or"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### nunique(series + dataframe) -> does not count nan -> dropna parameter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl['Season'].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp.nunique()      #unique() count missing values, but nunique wont"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### isnull(series + dataframe)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "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>college</th>\n",
       "      <th>branch</th>\n",
       "      <th>cgpa</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</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>NaN</td>\n",
       "      <td>vlsi</td>\n",
       "      <td>ce</td>\n",
       "      <td>9.00</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>cse</td>\n",
       "      <td>10.00</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>NaN</td>\n",
       "      <td>git</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>rupesh</td>\n",
       "      <td>vit</td>\n",
       "      <td>cse</td>\n",
       "      <td>6.41</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>rishabh</td>\n",
       "      <td>ssit</td>\n",
       "      <td>civ</td>\n",
       "      <td>7.40</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>nitish</td>\n",
       "      <td>bit</td>\n",
       "      <td>eee</td>\n",
       "      <td>6.66</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>mrityunjay</td>\n",
       "      <td>NaN</td>\n",
       "      <td>me</td>\n",
       "      <td>5.60</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ankit</td>\n",
       "      <td>iit</td>\n",
       "      <td>it</td>\n",
       "      <td>8.25</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>aditya</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bio</td>\n",
       "      <td>7.40</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         name college branch   cgpa  package\n",
       "3         NaN     NaN    NaN    NaN      NaN\n",
       "5         NaN    vlsi     ce   9.00      7.0\n",
       "7         NaN     NaN    cse  10.00      9.0\n",
       "9         NaN     git    NaN    NaN      NaN\n",
       "2      rupesh     vit    cse   6.41      6.0\n",
       "6     rishabh    ssit    civ   7.40      8.0\n",
       "0      nitish     bit    eee   6.66      4.0\n",
       "4  mrityunjay     NaN     me   5.60      6.0\n",
       "1       ankit     iit     it   8.25      5.0\n",
       "8      aditya     NaN    bio   7.40      NaN"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "students"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3           NaN\n",
       "5           NaN\n",
       "7           NaN\n",
       "9           NaN\n",
       "2        rupesh\n",
       "6       rishabh\n",
       "0        nitish\n",
       "4    mrityunjay\n",
       "1         ankit\n",
       "8        aditya\n",
       "Name: name, dtype: object"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#in series,\n",
    "students['name']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3    NaN\n",
       "5    NaN\n",
       "7    NaN\n",
       "9    NaN\n",
       "Name: name, dtype: object"
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "students['name'].isnull()      #just tell true,false\n",
    "students['name'][students['name'].isnull()] #on masking,it tell missing values only"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "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>college</th>\n",
       "      <th>branch</th>\n",
       "      <th>cgpa</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    name  college  branch   cgpa  package\n",
       "3   True     True    True   True     True\n",
       "5   True    False   False  False    False\n",
       "7   True     True   False  False    False\n",
       "9   True    False    True   True     True\n",
       "2  False    False   False  False    False\n",
       "6  False    False   False  False    False\n",
       "0  False    False   False  False    False\n",
       "4  False     True   False  False    False\n",
       "1  False    False   False  False    False\n",
       "8  False     True   False  False     True"
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#in dataframe,\n",
    "students.isnull()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### notnull(series + dataframe)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2        rupesh\n",
       "6       rishabh\n",
       "0        nitish\n",
       "4    mrityunjay\n",
       "1         ankit\n",
       "8        aditya\n",
       "Name: name, dtype: object"
      ]
     },
     "execution_count": 143,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#opp. of isnull()\n",
    "students['name'][students['name'].notnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "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>college</th>\n",
       "      <th>branch</th>\n",
       "      <th>cgpa</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    name  college  branch   cgpa  package\n",
       "3  False    False   False  False    False\n",
       "5  False     True    True   True     True\n",
       "7  False    False    True   True     True\n",
       "9  False     True   False  False    False\n",
       "2   True     True    True   True     True\n",
       "6   True     True    True   True     True\n",
       "0   True     True    True   True     True\n",
       "4   True    False    True   True     True\n",
       "1   True     True    True   True     True\n",
       "8   True    False    True   True    False"
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "students.notnull()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### hasnans(series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "students['name'].hasnans #just tell has nan values or not"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### dropna(series + dataframe) -> how parameter -> works like or"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2        rupesh\n",
       "6       rishabh\n",
       "0        nitish\n",
       "4    mrityunjay\n",
       "1         ankit\n",
       "8        aditya\n",
       "Name: name, dtype: object"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#if there are missing values, 'dropna' or 'fillna'\n",
    "students['name'].dropna()           #in series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "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",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>college</th>\n",
       "      <th>branch</th>\n",
       "      <th>cgpa</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>rupesh</td>\n",
       "      <td>vit</td>\n",
       "      <td>cse</td>\n",
       "      <td>6.41</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>rishabh</td>\n",
       "      <td>ssit</td>\n",
       "      <td>civ</td>\n",
       "      <td>7.40</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>nitish</td>\n",
       "      <td>bit</td>\n",
       "      <td>eee</td>\n",
       "      <td>6.66</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ankit</td>\n",
       "      <td>iit</td>\n",
       "      <td>it</td>\n",
       "      <td>8.25</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      name college branch  cgpa  package\n",
       "2   rupesh     vit    cse  6.41      6.0\n",
       "6  rishabh    ssit    civ  7.40      8.0\n",
       "0   nitish     bit    eee  6.66      4.0\n",
       "1    ankit     iit     it  8.25      5.0"
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "students.dropna() #by default, how = any  #drop all rows & columns with any nan... drawback:many data lost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "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>college</th>\n",
       "      <th>branch</th>\n",
       "      <th>cgpa</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NaN</td>\n",
       "      <td>vlsi</td>\n",
       "      <td>ce</td>\n",
       "      <td>9.00</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>cse</td>\n",
       "      <td>10.00</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>NaN</td>\n",
       "      <td>git</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>rupesh</td>\n",
       "      <td>vit</td>\n",
       "      <td>cse</td>\n",
       "      <td>6.41</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>rishabh</td>\n",
       "      <td>ssit</td>\n",
       "      <td>civ</td>\n",
       "      <td>7.40</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>nitish</td>\n",
       "      <td>bit</td>\n",
       "      <td>eee</td>\n",
       "      <td>6.66</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>mrityunjay</td>\n",
       "      <td>NaN</td>\n",
       "      <td>me</td>\n",
       "      <td>5.60</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ankit</td>\n",
       "      <td>iit</td>\n",
       "      <td>it</td>\n",
       "      <td>8.25</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>aditya</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bio</td>\n",
       "      <td>7.40</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         name college branch   cgpa  package\n",
       "5         NaN    vlsi     ce   9.00      7.0\n",
       "7         NaN     NaN    cse  10.00      9.0\n",
       "9         NaN     git    NaN    NaN      NaN\n",
       "2      rupesh     vit    cse   6.41      6.0\n",
       "6     rishabh    ssit    civ   7.40      8.0\n",
       "0      nitish     bit    eee   6.66      4.0\n",
       "4  mrityunjay     NaN     me   5.60      6.0\n",
       "1       ankit     iit     it   8.25      5.0\n",
       "8      aditya     NaN    bio   7.40      NaN"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "students.dropna(how='all') #drop only if all values in a row or column is missing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>college</th>\n",
       "      <th>branch</th>\n",
       "      <th>cgpa</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>rupesh</td>\n",
       "      <td>vit</td>\n",
       "      <td>cse</td>\n",
       "      <td>6.41</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>rishabh</td>\n",
       "      <td>ssit</td>\n",
       "      <td>civ</td>\n",
       "      <td>7.40</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>nitish</td>\n",
       "      <td>bit</td>\n",
       "      <td>eee</td>\n",
       "      <td>6.66</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>mrityunjay</td>\n",
       "      <td>NaN</td>\n",
       "      <td>me</td>\n",
       "      <td>5.60</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ankit</td>\n",
       "      <td>iit</td>\n",
       "      <td>it</td>\n",
       "      <td>8.25</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>aditya</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bio</td>\n",
       "      <td>7.40</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         name college branch  cgpa  package\n",
       "2      rupesh     vit    cse  6.41      6.0\n",
       "6     rishabh    ssit    civ  7.40      8.0\n",
       "0      nitish     bit    eee  6.66      4.0\n",
       "4  mrityunjay     NaN     me  5.60      6.0\n",
       "1       ankit     iit     it  8.25      5.0\n",
       "8      aditya     NaN    bio  7.40      NaN"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#droping based on some particular columns\n",
    "students.dropna(subset=['name']) #drop if there are missing values in name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "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>college</th>\n",
       "      <th>branch</th>\n",
       "      <th>cgpa</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>rupesh</td>\n",
       "      <td>vit</td>\n",
       "      <td>cse</td>\n",
       "      <td>6.41</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>rishabh</td>\n",
       "      <td>ssit</td>\n",
       "      <td>civ</td>\n",
       "      <td>7.40</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>nitish</td>\n",
       "      <td>bit</td>\n",
       "      <td>eee</td>\n",
       "      <td>6.66</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ankit</td>\n",
       "      <td>iit</td>\n",
       "      <td>it</td>\n",
       "      <td>8.25</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      name college branch  cgpa  package\n",
       "2   rupesh     vit    cse  6.41      6.0\n",
       "6  rishabh    ssit    civ  7.40      8.0\n",
       "0   nitish     bit    eee  6.66      4.0\n",
       "1    ankit     iit     it  8.25      5.0"
      ]
     },
     "execution_count": 150,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "students.dropna(subset=['name','college'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### fillna(series + dataframe)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3       unknown\n",
       "5       unknown\n",
       "7       unknown\n",
       "9       unknown\n",
       "2        rupesh\n",
       "6       rishabh\n",
       "0        nitish\n",
       "4    mrityunjay\n",
       "1         ankit\n",
       "8        aditya\n",
       "Name: name, dtype: object"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#in series, \n",
    "students['name'].fillna('unknown')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 152,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "students['name'].fillna('unknown').hasnans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
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       "      <th></th>\n",
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       "      <th>college</th>\n",
       "      <th>branch</th>\n",
       "      <th>cgpa</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>vlsi</td>\n",
       "      <td>ce</td>\n",
       "      <td>9.00</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>cse</td>\n",
       "      <td>10.00</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0</td>\n",
       "      <td>git</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>rupesh</td>\n",
       "      <td>vit</td>\n",
       "      <td>cse</td>\n",
       "      <td>6.41</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>rishabh</td>\n",
       "      <td>ssit</td>\n",
       "      <td>civ</td>\n",
       "      <td>7.40</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>nitish</td>\n",
       "      <td>bit</td>\n",
       "      <td>eee</td>\n",
       "      <td>6.66</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>mrityunjay</td>\n",
       "      <td>0</td>\n",
       "      <td>me</td>\n",
       "      <td>5.60</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ankit</td>\n",
       "      <td>iit</td>\n",
       "      <td>it</td>\n",
       "      <td>8.25</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>aditya</td>\n",
       "      <td>0</td>\n",
       "      <td>bio</td>\n",
       "      <td>7.40</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         name college branch   cgpa  package\n",
       "3           0       0      0   0.00      0.0\n",
       "5           0    vlsi     ce   9.00      7.0\n",
       "7           0       0    cse  10.00      9.0\n",
       "9           0     git      0   0.00      0.0\n",
       "2      rupesh     vit    cse   6.41      6.0\n",
       "6     rishabh    ssit    civ   7.40      8.0\n",
       "0      nitish     bit    eee   6.66      4.0\n",
       "4  mrityunjay       0     me   5.60      6.0\n",
       "1       ankit     iit     it   8.25      5.0\n",
       "8      aditya       0    bio   7.40      0.0"
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#in dataframe\n",
    "students.fillna(0)                #not recommended.. fill columnwise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3    6.428571\n",
       "5    7.000000\n",
       "7    9.000000\n",
       "9    6.428571\n",
       "2    6.000000\n",
       "6    8.000000\n",
       "0    4.000000\n",
       "4    6.000000\n",
       "1    5.000000\n",
       "8    6.428571\n",
       "Name: package, dtype: float64"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "students['package'].fillna(students['package'].mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3           NaN\n",
       "5           NaN\n",
       "7           NaN\n",
       "9           NaN\n",
       "2        rupesh\n",
       "6       rishabh\n",
       "0        nitish\n",
       "4    mrityunjay\n",
       "1         ankit\n",
       "8        aditya\n",
       "Name: name, dtype: object"
      ]
     },
     "execution_count": 155,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "students['name'].fillna(method='ffill') #forward fill  #method=bfill"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### drop_duplicates(series + dataframe) -> works like and -> duplicated()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1\n",
       "1    1\n",
       "2    1\n",
       "3    2\n",
       "4    3\n",
       "5    3\n",
       "6    4\n",
       "7    4\n",
       "dtype: int64"
      ]
     },
     "execution_count": 156,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp = pd.Series([1,1,1,2,3,3,4,4])\n",
    "temp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    False\n",
       "1     True\n",
       "2     True\n",
       "3    False\n",
       "4    False\n",
       "5     True\n",
       "6    False\n",
       "7     True\n",
       "dtype: bool"
      ]
     },
     "execution_count": 157,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp.duplicated()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 158,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp.duplicated().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1\n",
       "3    2\n",
       "4    3\n",
       "6    4\n",
       "dtype: int64"
      ]
     },
     "execution_count": 159,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp.drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "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>iq</th>\n",
       "      <th>marks</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>90</td>\n",
       "      <td>70</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>120</td>\n",
       "      <td>100</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>80</td>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>80</td>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    iq  marks  package\n",
       "0  100     80       10\n",
       "1   90     70        7\n",
       "2  120    100       14\n",
       "3   80     50        0\n",
       "4   80     50        0"
      ]
     },
     "execution_count": 160,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "student_data = [\n",
    "    [100,80,10],\n",
    "    [90,70,7],\n",
    "    [120,100,14],\n",
    "    [80,50,0],\n",
    "    [80,50,0]\n",
    "]\n",
    "student = pd.DataFrame(student_data,columns=['iq','marks','package'])\n",
    "student"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "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>iq</th>\n",
       "      <th>marks</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>90</td>\n",
       "      <td>70</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>120</td>\n",
       "      <td>100</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>80</td>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    iq  marks  package\n",
       "0  100     80       10\n",
       "1   90     70        7\n",
       "2  120    100       14\n",
       "3   80     50        0"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "student.drop_duplicates()               #keep=first"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "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>iq</th>\n",
       "      <th>marks</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>90</td>\n",
       "      <td>70</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>120</td>\n",
       "      <td>100</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>80</td>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    iq  marks  package\n",
       "0  100     80       10\n",
       "1   90     70        7\n",
       "2  120    100       14\n",
       "4   80     50        0"
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "student.drop_duplicates(keep='last')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [],
   "source": [
    "# find the last match played by virat kohli in Delhi"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### drop(series + dataframe)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    10\n",
       "1     2\n",
       "2     3\n",
       "3    16\n",
       "4    45\n",
       "5    78\n",
       "6    10\n",
       "dtype: int64"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp = pd.Series([10,2,3,16,45,78,10])\n",
    "temp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    10\n",
       "2     3\n",
       "3    16\n",
       "4    45\n",
       "5    78\n",
       "6    10\n",
       "dtype: int64"
      ]
     },
     "execution_count": 165,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp.drop([1])     #drop data of specified index positions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1     2\n",
       "2     3\n",
       "4    45\n",
       "5    78\n",
       "6    10\n",
       "dtype: int64"
      ]
     },
     "execution_count": 166,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp.drop([0,3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "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>college</th>\n",
       "      <th>branch</th>\n",
       "      <th>cgpa</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</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>NaN</td>\n",
       "      <td>vlsi</td>\n",
       "      <td>ce</td>\n",
       "      <td>9.00</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>cse</td>\n",
       "      <td>10.00</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>NaN</td>\n",
       "      <td>git</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>rupesh</td>\n",
       "      <td>vit</td>\n",
       "      <td>cse</td>\n",
       "      <td>6.41</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>rishabh</td>\n",
       "      <td>ssit</td>\n",
       "      <td>civ</td>\n",
       "      <td>7.40</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>nitish</td>\n",
       "      <td>bit</td>\n",
       "      <td>eee</td>\n",
       "      <td>6.66</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>mrityunjay</td>\n",
       "      <td>NaN</td>\n",
       "      <td>me</td>\n",
       "      <td>5.60</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ankit</td>\n",
       "      <td>iit</td>\n",
       "      <td>it</td>\n",
       "      <td>8.25</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>aditya</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bio</td>\n",
       "      <td>7.40</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         name college branch   cgpa  package\n",
       "3         NaN     NaN    NaN    NaN      NaN\n",
       "5         NaN    vlsi     ce   9.00      7.0\n",
       "7         NaN     NaN    cse  10.00      9.0\n",
       "9         NaN     git    NaN    NaN      NaN\n",
       "2      rupesh     vit    cse   6.41      6.0\n",
       "6     rishabh    ssit    civ   7.40      8.0\n",
       "0      nitish     bit    eee   6.66      4.0\n",
       "4  mrityunjay     NaN     me   5.60      6.0\n",
       "1       ankit     iit     it   8.25      5.0\n",
       "8      aditya     NaN    bio   7.40      NaN"
      ]
     },
     "execution_count": 167,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "students"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "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",
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       "    }\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>college</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NaN</td>\n",
       "      <td>vlsi</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>NaN</td>\n",
       "      <td>git</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>rupesh</td>\n",
       "      <td>vit</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>rishabh</td>\n",
       "      <td>ssit</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>nitish</td>\n",
       "      <td>bit</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>mrityunjay</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ankit</td>\n",
       "      <td>iit</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>aditya</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         name college  package\n",
       "3         NaN     NaN      NaN\n",
       "5         NaN    vlsi      7.0\n",
       "7         NaN     NaN      9.0\n",
       "9         NaN     git      NaN\n",
       "2      rupesh     vit      6.0\n",
       "6     rishabh    ssit      8.0\n",
       "0      nitish     bit      4.0\n",
       "4  mrityunjay     NaN      6.0\n",
       "1       ankit     iit      5.0\n",
       "8      aditya     NaN      NaN"
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "students.drop(columns=['branch','cgpa'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "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>college</th>\n",
       "      <th>branch</th>\n",
       "      <th>cgpa</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</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>NaN</td>\n",
       "      <td>vlsi</td>\n",
       "      <td>ce</td>\n",
       "      <td>9.00</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>cse</td>\n",
       "      <td>10.00</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>NaN</td>\n",
       "      <td>git</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>rishabh</td>\n",
       "      <td>ssit</td>\n",
       "      <td>civ</td>\n",
       "      <td>7.40</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>mrityunjay</td>\n",
       "      <td>NaN</td>\n",
       "      <td>me</td>\n",
       "      <td>5.60</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ankit</td>\n",
       "      <td>iit</td>\n",
       "      <td>it</td>\n",
       "      <td>8.25</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>aditya</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bio</td>\n",
       "      <td>7.40</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         name college branch   cgpa  package\n",
       "3         NaN     NaN    NaN    NaN      NaN\n",
       "5         NaN    vlsi     ce   9.00      7.0\n",
       "7         NaN     NaN    cse  10.00      9.0\n",
       "9         NaN     git    NaN    NaN      NaN\n",
       "6     rishabh    ssit    civ   7.40      8.0\n",
       "4  mrityunjay     NaN     me   5.60      6.0\n",
       "1       ankit     iit     it   8.25      5.0\n",
       "8      aditya     NaN    bio   7.40      NaN"
      ]
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "students.drop(index=[0,2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "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>college</th>\n",
       "      <th>branch</th>\n",
       "      <th>cgpa</th>\n",
       "      <th>package</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>vlsi</td>\n",
       "      <td>ce</td>\n",
       "      <td>9.00</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>NaN</td>\n",
       "      <td>cse</td>\n",
       "      <td>10.00</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>git</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rishabh</th>\n",
       "      <td>ssit</td>\n",
       "      <td>civ</td>\n",
       "      <td>7.40</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nitish</th>\n",
       "      <td>bit</td>\n",
       "      <td>eee</td>\n",
       "      <td>6.66</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mrityunjay</th>\n",
       "      <td>NaN</td>\n",
       "      <td>me</td>\n",
       "      <td>5.60</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           college branch   cgpa  package\n",
       "name                                     \n",
       "NaN            NaN    NaN    NaN      NaN\n",
       "NaN           vlsi     ce   9.00      7.0\n",
       "NaN            NaN    cse  10.00      9.0\n",
       "NaN            git    NaN    NaN      NaN\n",
       "rishabh       ssit    civ   7.40      8.0\n",
       "nitish         bit    eee   6.66      4.0\n",
       "mrityunjay     NaN     me   5.60      6.0"
      ]
     },
     "execution_count": 170,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "students.set_index('name').drop(index=['rupesh','ankit','aditya']) #can drop(row) based on labeled index also"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### apply(series + dataframe)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    10\n",
       "1    20\n",
       "2    30\n",
       "3    40\n",
       "4    50\n",
       "dtype: int64"
      ]
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp = pd.Series([10,20,30,40,50])\n",
    "temp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sigmoid(value):\n",
    "    return 1/(1+np.exp(-value))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    0.999955\n",
       "1    1.000000\n",
       "2    1.000000\n",
       "3    1.000000\n",
       "4    1.000000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp.apply(sigmoid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "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>1st point</th>\n",
       "      <th>2nd point</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>(3, 4)</td>\n",
       "      <td>(-3, 4)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>(-6, 5)</td>\n",
       "      <td>(0, 0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>(2, 2)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>(-10, 1)</td>\n",
       "      <td>(10, 10)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(4, 5)</td>\n",
       "      <td>(1, 1)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  1st point 2nd point\n",
       "0    (3, 4)   (-3, 4)\n",
       "1   (-6, 5)    (0, 0)\n",
       "2    (0, 0)    (2, 2)\n",
       "3  (-10, 1)  (10, 10)\n",
       "4    (4, 5)    (1, 1)"
      ]
     },
     "execution_count": 174,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#in dataframe\n",
    "points_df = pd.DataFrame(\n",
    "    {\n",
    "        '1st point':[(3,4),(-6,5),(0,0),(-10,1),(4,5)],\n",
    "        '2nd point':[(-3,4),(0,0),(2,2),(10,10),(1,1)]\n",
    "    }\n",
    ")\n",
    "\n",
    "points_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [],
   "source": [
    "def euclidean(row):\n",
    "  pt_A = row['1st point']\n",
    "  pt_B = row['2nd point']\n",
    "\n",
    "  return ((pt_A[0] - pt_B[0])**2 + (pt_A[1] - pt_B[1])**2)**0.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "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>1st point</th>\n",
       "      <th>2nd point</th>\n",
       "      <th>distance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>(3, 4)</td>\n",
       "      <td>(-3, 4)</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>(-6, 5)</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>7.810250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>(2, 2)</td>\n",
       "      <td>2.828427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>(-10, 1)</td>\n",
       "      <td>(10, 10)</td>\n",
       "      <td>21.931712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(4, 5)</td>\n",
       "      <td>(1, 1)</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  1st point 2nd point   distance\n",
       "0    (3, 4)   (-3, 4)   6.000000\n",
       "1   (-6, 5)    (0, 0)   7.810250\n",
       "2    (0, 0)    (2, 2)   2.828427\n",
       "3  (-10, 1)  (10, 10)  21.931712\n",
       "4    (4, 5)    (1, 1)   5.000000"
      ]
     },
     "execution_count": 176,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "points_df['distance'] = points_df.apply(euclidean,axis=1)\n",
    "points_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [],
   "source": [
    "# isin(series)\n",
    "#corr\n",
    "#nlargest and nsmallest\n",
    "#insert\n",
    "#copy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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