ipl_datset.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 237,
   "id": "bb306115-1d2c-4d75-9c69-ab1dce5c654f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from matplotlib import pyplot as plt\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import plotly\n",
    "import plotly.express as px\n",
    "import plotly.graph_objs as go\n",
    "from plotly.offline import init_notebook_mode, plot, iplot\n",
    "from plotly import tools\n",
    "from warnings import filterwarnings\n",
    "filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "id": "d200184c-8dfb-41f9-b2c5-8961216ec244",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data is ready for exploration\n"
     ]
    }
   ],
   "source": [
    "ipl = pd.read_csv('ipl_dataset.csv')\n",
    "print('Data is ready for exploration')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "id": "1299d55f-e67d-443e-b7a0-81159c6aa699",
   "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>season</th>\n",
       "      <th>city</th>\n",
       "      <th>date</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>result</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>venue</th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "      <th>umpire3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2017</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>5/4/2017</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>Yuvraj Singh</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>AY Dandekar</td>\n",
       "      <td>NJ Llong</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2017</td>\n",
       "      <td>Pune</td>\n",
       "      <td>6/4/2017</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>SPD Smith</td>\n",
       "      <td>Maharashtra Cricket Association Stadium</td>\n",
       "      <td>A Nand Kishore</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2017</td>\n",
       "      <td>Rajkot</td>\n",
       "      <td>7/4/2017</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>CA Lynn</td>\n",
       "      <td>Saurashtra Cricket Association Stadium</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>CK Nandan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2017</td>\n",
       "      <td>Indore</td>\n",
       "      <td>8/4/2017</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>GJ Maxwell</td>\n",
       "      <td>Holkar Cricket Stadium</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2017</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>8/4/2017</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>KM Jadhav</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id  season       city      date                        team1  \\\n",
       "0   1    2017  Hyderabad  5/4/2017          Sunrisers Hyderabad   \n",
       "1   2    2017       Pune  6/4/2017               Mumbai Indians   \n",
       "2   3    2017     Rajkot  7/4/2017                Gujarat Lions   \n",
       "3   4    2017     Indore  8/4/2017       Rising Pune Supergiant   \n",
       "4   5    2017  Bangalore  8/4/2017  Royal Challengers Bangalore   \n",
       "\n",
       "                         team2                  toss_winner toss_decision  \\\n",
       "0  Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
       "1       Rising Pune Supergiant       Rising Pune Supergiant         field   \n",
       "2        Kolkata Knight Riders        Kolkata Knight Riders         field   \n",
       "3              Kings XI Punjab              Kings XI Punjab         field   \n",
       "4             Delhi Daredevils  Royal Challengers Bangalore           bat   \n",
       "\n",
       "   result  dl_applied                       winner  win_by_runs  \\\n",
       "0  normal           0          Sunrisers Hyderabad           35   \n",
       "1  normal           0       Rising Pune Supergiant            0   \n",
       "2  normal           0        Kolkata Knight Riders            0   \n",
       "3  normal           0              Kings XI Punjab            0   \n",
       "4  normal           0  Royal Challengers Bangalore           15   \n",
       "\n",
       "   win_by_wickets player_of_match                                      venue  \\\n",
       "0               0    Yuvraj Singh  Rajiv Gandhi International Stadium, Uppal   \n",
       "1               7       SPD Smith    Maharashtra Cricket Association Stadium   \n",
       "2              10         CA Lynn     Saurashtra Cricket Association Stadium   \n",
       "3               6      GJ Maxwell                     Holkar Cricket Stadium   \n",
       "4               0       KM Jadhav                      M Chinnaswamy Stadium   \n",
       "\n",
       "          umpire1        umpire2  umpire3  \n",
       "0     AY Dandekar       NJ Llong      NaN  \n",
       "1  A Nand Kishore         S Ravi      NaN  \n",
       "2     Nitin Menon      CK Nandan      NaN  \n",
       "3    AK Chaudhary  C Shamshuddin      NaN  \n",
       "4             NaN            NaN      NaN  "
      ]
     },
     "execution_count": 239,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "id": "a9647b76-7ba4-4c85-8825-acf8f2a52ef2",
   "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>season</th>\n",
       "      <th>city</th>\n",
       "      <th>date</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>result</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>venue</th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "      <th>umpire3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>631</th>\n",
       "      <td>632</td>\n",
       "      <td>2016</td>\n",
       "      <td>Raipur</td>\n",
       "      <td>22/05/16</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>V Kohli</td>\n",
       "      <td>Shaheed Veer Narayan Singh International Stadium</td>\n",
       "      <td>A Nand Kishore</td>\n",
       "      <td>BNJ Oxenford</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>632</th>\n",
       "      <td>633</td>\n",
       "      <td>2016</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>24/05/16</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>AB de Villiers</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>633</th>\n",
       "      <td>634</td>\n",
       "      <td>2016</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>25/05/16</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>MC Henriques</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>634</th>\n",
       "      <td>635</td>\n",
       "      <td>2016</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>27/05/16</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>CK Nandan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>635</th>\n",
       "      <td>636</td>\n",
       "      <td>2016</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>29/05/16</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>BCJ Cutting</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>BNJ Oxenford</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      id  season       city      date                team1  \\\n",
       "631  632    2016     Raipur  22/05/16     Delhi Daredevils   \n",
       "632  633    2016  Bangalore  24/05/16        Gujarat Lions   \n",
       "633  634    2016      Delhi  25/05/16  Sunrisers Hyderabad   \n",
       "634  635    2016      Delhi  27/05/16        Gujarat Lions   \n",
       "635  636    2016  Bangalore  29/05/16  Sunrisers Hyderabad   \n",
       "\n",
       "                           team2                  toss_winner toss_decision  \\\n",
       "631  Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
       "632  Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
       "633        Kolkata Knight Riders        Kolkata Knight Riders         field   \n",
       "634          Sunrisers Hyderabad          Sunrisers Hyderabad         field   \n",
       "635  Royal Challengers Bangalore          Sunrisers Hyderabad           bat   \n",
       "\n",
       "     result  dl_applied                       winner  win_by_runs  \\\n",
       "631  normal           0  Royal Challengers Bangalore            0   \n",
       "632  normal           0  Royal Challengers Bangalore            0   \n",
       "633  normal           0          Sunrisers Hyderabad           22   \n",
       "634  normal           0          Sunrisers Hyderabad            0   \n",
       "635  normal           0          Sunrisers Hyderabad            8   \n",
       "\n",
       "     win_by_wickets player_of_match  \\\n",
       "631               6         V Kohli   \n",
       "632               4  AB de Villiers   \n",
       "633               0    MC Henriques   \n",
       "634               4       DA Warner   \n",
       "635               0     BCJ Cutting   \n",
       "\n",
       "                                                venue          umpire1  \\\n",
       "631  Shaheed Veer Narayan Singh International Stadium   A Nand Kishore   \n",
       "632                             M Chinnaswamy Stadium     AK Chaudhary   \n",
       "633                                  Feroz Shah Kotla        M Erasmus   \n",
       "634                                  Feroz Shah Kotla        M Erasmus   \n",
       "635                             M Chinnaswamy Stadium  HDPK Dharmasena   \n",
       "\n",
       "             umpire2  umpire3  \n",
       "631     BNJ Oxenford      NaN  \n",
       "632  HDPK Dharmasena      NaN  \n",
       "633    C Shamshuddin      NaN  \n",
       "634        CK Nandan      NaN  \n",
       "635     BNJ Oxenford      NaN  "
      ]
     },
     "execution_count": 240,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "id": "28313933-e6c6-4fcb-b1e5-2a404088bc2a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'season', 'city', 'date', 'team1', 'team2', 'toss_winner',\n",
       "       'toss_decision', 'result', 'dl_applied', 'winner', 'win_by_runs',\n",
       "       'win_by_wickets', 'player_of_match', 'venue', 'umpire1', 'umpire2',\n",
       "       'umpire3'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 241,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 242,
   "id": "7afa3fed-ee29-417e-9175-4e829cc8c73d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                   0\n",
       "season               0\n",
       "city                 7\n",
       "date                 0\n",
       "team1                0\n",
       "team2                0\n",
       "toss_winner          0\n",
       "toss_decision        0\n",
       "result               0\n",
       "dl_applied           0\n",
       "winner               3\n",
       "win_by_runs          0\n",
       "win_by_wickets       0\n",
       "player_of_match      3\n",
       "venue                0\n",
       "umpire1              1\n",
       "umpire2              1\n",
       "umpire3            636\n",
       "dtype: int64"
      ]
     },
     "execution_count": 242,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "id": "bda1b3d3-4925-41bd-981a-eb37438b3b88",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(636, 18)"
      ]
     },
     "execution_count": 243,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "id": "ba68c978-ffcd-449f-8768-02aa2a8887f4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total Matches Played: 636\n",
      " \n",
      " Venues Played At: ['Hyderabad' 'Pune' 'Rajkot' 'Indore' 'Bangalore' 'Mumbai' 'Kolkata'\n",
      " 'Delhi' 'Chandigarh' 'Kanpur' 'Jaipur' 'Chennai' 'Cape Town'\n",
      " 'Port Elizabeth' 'Durban' 'Centurion' 'East London' 'Johannesburg'\n",
      " 'Kimberley' 'Bloemfontein' 'Ahmedabad' 'Cuttack' 'Nagpur' 'Dharamsala'\n",
      " 'Kochi' 'Visakhapatnam' 'Raipur' 'Ranchi' 'Abu Dhabi' 'Sharjah' nan]\n",
      " \n",
      " Teams : ['Sunrisers Hyderabad' 'Mumbai Indians' 'Gujarat Lions'\n",
      " 'Rising Pune Supergiant' 'Royal Challengers Bangalore'\n",
      " 'Kolkata Knight Riders' 'Delhi Daredevils' 'Kings XI Punjab'\n",
      " 'Chennai Super Kings' 'Rajasthan Royals' 'Deccan Chargers'\n",
      " 'Kochi Tuskers Kerala' 'Pune Warriors' 'Rising Pune Supergiants']\n"
     ]
    }
   ],
   "source": [
    "print('Total Matches Played:',ipl.shape[0])\n",
    "print(' \\n Venues Played At:',ipl['city'].unique())     \n",
    "print(' \\n Teams :',ipl['team1'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 245,
   "id": "fbdc68bf-f9c5-4149-b1d9-f6de1008ab2b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 636 entries, 0 to 635\n",
      "Data columns (total 18 columns):\n",
      " #   Column           Non-Null Count  Dtype  \n",
      "---  ------           --------------  -----  \n",
      " 0   id               636 non-null    int64  \n",
      " 1   season           636 non-null    int64  \n",
      " 2   city             629 non-null    object \n",
      " 3   date             636 non-null    object \n",
      " 4   team1            636 non-null    object \n",
      " 5   team2            636 non-null    object \n",
      " 6   toss_winner      636 non-null    object \n",
      " 7   toss_decision    636 non-null    object \n",
      " 8   result           636 non-null    object \n",
      " 9   dl_applied       636 non-null    int64  \n",
      " 10  winner           633 non-null    object \n",
      " 11  win_by_runs      636 non-null    int64  \n",
      " 12  win_by_wickets   636 non-null    int64  \n",
      " 13  player_of_match  633 non-null    object \n",
      " 14  venue            636 non-null    object \n",
      " 15  umpire1          635 non-null    object \n",
      " 16  umpire2          635 non-null    object \n",
      " 17  umpire3          0 non-null      float64\n",
      "dtypes: float64(1), int64(5), object(12)\n",
      "memory usage: 89.6+ KB\n"
     ]
    }
   ],
   "source": [
    "ipl.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "id": "c349e145-86ee-4f3d-84a9-a4a8fbc772bb",
   "metadata": {},
   "outputs": [],
   "source": [
    "#ipl['team1'] = ipl['team1'].astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 247,
   "id": "154c9340-aaea-4ebf-973e-763e0cb1460f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     NaN\n",
       "1     NaN\n",
       "2     NaN\n",
       "3     NaN\n",
       "4     NaN\n",
       "       ..\n",
       "631   NaN\n",
       "632   NaN\n",
       "633   NaN\n",
       "634   NaN\n",
       "635   NaN\n",
       "Name: team1, Length: 636, dtype: float64"
      ]
     },
     "execution_count": 247,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl['team1'] = pd.to_numeric(ipl['team1'], downcast='integer', errors='coerce')\n",
    "#print(ipl)\n",
    "ipl['team1'].dtype\n",
    "ipl['team1']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 248,
   "id": "affca272-df66-4b98-90ac-9a477392992e",
   "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>season</th>\n",
       "      <th>city</th>\n",
       "      <th>date</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>result</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>venue</th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "      <th>umpire3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2017</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>5/4/2017</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>Yuvraj Singh</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>AY Dandekar</td>\n",
       "      <td>NJ Llong</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2017</td>\n",
       "      <td>Pune</td>\n",
       "      <td>6/4/2017</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>SPD Smith</td>\n",
       "      <td>Maharashtra Cricket Association Stadium</td>\n",
       "      <td>A Nand Kishore</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2017</td>\n",
       "      <td>Rajkot</td>\n",
       "      <td>7/4/2017</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>CA Lynn</td>\n",
       "      <td>Saurashtra Cricket Association Stadium</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>CK Nandan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2017</td>\n",
       "      <td>Indore</td>\n",
       "      <td>8/4/2017</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>GJ Maxwell</td>\n",
       "      <td>Holkar Cricket Stadium</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2017</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>8/4/2017</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>KM Jadhav</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id  season       city      date  team1                        team2  \\\n",
       "0   1    2017  Hyderabad  5/4/2017    NaN  Royal Challengers Bangalore   \n",
       "1   2    2017       Pune  6/4/2017    NaN       Rising Pune Supergiant   \n",
       "2   3    2017     Rajkot  7/4/2017    NaN        Kolkata Knight Riders   \n",
       "3   4    2017     Indore  8/4/2017    NaN              Kings XI Punjab   \n",
       "4   5    2017  Bangalore  8/4/2017    NaN             Delhi Daredevils   \n",
       "\n",
       "                   toss_winner toss_decision  result  dl_applied  \\\n",
       "0  Royal Challengers Bangalore         field  normal           0   \n",
       "1       Rising Pune Supergiant         field  normal           0   \n",
       "2        Kolkata Knight Riders         field  normal           0   \n",
       "3              Kings XI Punjab         field  normal           0   \n",
       "4  Royal Challengers Bangalore           bat  normal           0   \n",
       "\n",
       "                        winner  win_by_runs  win_by_wickets player_of_match  \\\n",
       "0          Sunrisers Hyderabad           35               0    Yuvraj Singh   \n",
       "1       Rising Pune Supergiant            0               7       SPD Smith   \n",
       "2        Kolkata Knight Riders            0              10         CA Lynn   \n",
       "3              Kings XI Punjab            0               6      GJ Maxwell   \n",
       "4  Royal Challengers Bangalore           15               0       KM Jadhav   \n",
       "\n",
       "                                       venue         umpire1        umpire2  \\\n",
       "0  Rajiv Gandhi International Stadium, Uppal     AY Dandekar       NJ Llong   \n",
       "1    Maharashtra Cricket Association Stadium  A Nand Kishore         S Ravi   \n",
       "2     Saurashtra Cricket Association Stadium     Nitin Menon      CK Nandan   \n",
       "3                     Holkar Cricket Stadium    AK Chaudhary  C Shamshuddin   \n",
       "4                      M Chinnaswamy Stadium             NaN            NaN   \n",
       "\n",
       "   umpire3  \n",
       "0      NaN  \n",
       "1      NaN  \n",
       "2      NaN  \n",
       "3      NaN  \n",
       "4      NaN  "
      ]
     },
     "execution_count": 248,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 249,
   "id": "92f2474d-d696-43bc-961c-44070a49d477",
   "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>season</th>\n",
       "      <th>city</th>\n",
       "      <th>date</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>result</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>venue</th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "      <th>umpire3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2017</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>5/4/2017</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
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       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>Yuvraj Singh</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>AY Dandekar</td>\n",
       "      <td>NJ Llong</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2017</td>\n",
       "      <td>Pune</td>\n",
       "      <td>6/4/2017</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>SPD Smith</td>\n",
       "      <td>Maharashtra Cricket Association Stadium</td>\n",
       "      <td>A Nand Kishore</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2017</td>\n",
       "      <td>Rajkot</td>\n",
       "      <td>7/4/2017</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>CA Lynn</td>\n",
       "      <td>Saurashtra Cricket Association Stadium</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>CK Nandan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2017</td>\n",
       "      <td>Indore</td>\n",
       "      <td>8/4/2017</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>GJ Maxwell</td>\n",
       "      <td>Holkar Cricket Stadium</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2017</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>8/4/2017</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>KM Jadhav</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>631</th>\n",
       "      <td>632</td>\n",
       "      <td>2016</td>\n",
       "      <td>Raipur</td>\n",
       "      <td>22/05/16</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>V Kohli</td>\n",
       "      <td>Shaheed Veer Narayan Singh International Stadium</td>\n",
       "      <td>A Nand Kishore</td>\n",
       "      <td>BNJ Oxenford</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>632</th>\n",
       "      <td>633</td>\n",
       "      <td>2016</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>24/05/16</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>AB de Villiers</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>633</th>\n",
       "      <td>634</td>\n",
       "      <td>2016</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>25/05/16</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>MC Henriques</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>634</th>\n",
       "      <td>635</td>\n",
       "      <td>2016</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>27/05/16</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>CK Nandan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>635</th>\n",
       "      <td>636</td>\n",
       "      <td>2016</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>29/05/16</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>BCJ Cutting</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>BNJ Oxenford</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>636 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      id  season       city      date                        team1  \\\n",
       "0      1    2017  Hyderabad  5/4/2017          Sunrisers Hyderabad   \n",
       "1      2    2017       Pune  6/4/2017               Mumbai Indians   \n",
       "2      3    2017     Rajkot  7/4/2017                Gujarat Lions   \n",
       "3      4    2017     Indore  8/4/2017       Rising Pune Supergiant   \n",
       "4      5    2017  Bangalore  8/4/2017  Royal Challengers Bangalore   \n",
       "..   ...     ...        ...       ...                          ...   \n",
       "631  632    2016     Raipur  22/05/16             Delhi Daredevils   \n",
       "632  633    2016  Bangalore  24/05/16                Gujarat Lions   \n",
       "633  634    2016      Delhi  25/05/16          Sunrisers Hyderabad   \n",
       "634  635    2016      Delhi  27/05/16                Gujarat Lions   \n",
       "635  636    2016  Bangalore  29/05/16          Sunrisers Hyderabad   \n",
       "\n",
       "                           team2                  toss_winner toss_decision  \\\n",
       "0    Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
       "1         Rising Pune Supergiant       Rising Pune Supergiant         field   \n",
       "2          Kolkata Knight Riders        Kolkata Knight Riders         field   \n",
       "3                Kings XI Punjab              Kings XI Punjab         field   \n",
       "4               Delhi Daredevils  Royal Challengers Bangalore           bat   \n",
       "..                           ...                          ...           ...   \n",
       "631  Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
       "632  Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
       "633        Kolkata Knight Riders        Kolkata Knight Riders         field   \n",
       "634          Sunrisers Hyderabad          Sunrisers Hyderabad         field   \n",
       "635  Royal Challengers Bangalore          Sunrisers Hyderabad           bat   \n",
       "\n",
       "     result  dl_applied                       winner  win_by_runs  \\\n",
       "0    normal           0          Sunrisers Hyderabad           35   \n",
       "1    normal           0       Rising Pune Supergiant            0   \n",
       "2    normal           0        Kolkata Knight Riders            0   \n",
       "3    normal           0              Kings XI Punjab            0   \n",
       "4    normal           0  Royal Challengers Bangalore           15   \n",
       "..      ...         ...                          ...          ...   \n",
       "631  normal           0  Royal Challengers Bangalore            0   \n",
       "632  normal           0  Royal Challengers Bangalore            0   \n",
       "633  normal           0          Sunrisers Hyderabad           22   \n",
       "634  normal           0          Sunrisers Hyderabad            0   \n",
       "635  normal           0          Sunrisers Hyderabad            8   \n",
       "\n",
       "     win_by_wickets player_of_match  \\\n",
       "0                 0    Yuvraj Singh   \n",
       "1                 7       SPD Smith   \n",
       "2                10         CA Lynn   \n",
       "3                 6      GJ Maxwell   \n",
       "4                 0       KM Jadhav   \n",
       "..              ...             ...   \n",
       "631               6         V Kohli   \n",
       "632               4  AB de Villiers   \n",
       "633               0    MC Henriques   \n",
       "634               4       DA Warner   \n",
       "635               0     BCJ Cutting   \n",
       "\n",
       "                                                venue          umpire1  \\\n",
       "0           Rajiv Gandhi International Stadium, Uppal      AY Dandekar   \n",
       "1             Maharashtra Cricket Association Stadium   A Nand Kishore   \n",
       "2              Saurashtra Cricket Association Stadium      Nitin Menon   \n",
       "3                              Holkar Cricket Stadium     AK Chaudhary   \n",
       "4                               M Chinnaswamy Stadium              NaN   \n",
       "..                                                ...              ...   \n",
       "631  Shaheed Veer Narayan Singh International Stadium   A Nand Kishore   \n",
       "632                             M Chinnaswamy Stadium     AK Chaudhary   \n",
       "633                                  Feroz Shah Kotla        M Erasmus   \n",
       "634                                  Feroz Shah Kotla        M Erasmus   \n",
       "635                             M Chinnaswamy Stadium  HDPK Dharmasena   \n",
       "\n",
       "             umpire2  umpire3  \n",
       "0           NJ Llong      NaN  \n",
       "1             S Ravi      NaN  \n",
       "2          CK Nandan      NaN  \n",
       "3      C Shamshuddin      NaN  \n",
       "4                NaN      NaN  \n",
       "..               ...      ...  \n",
       "631     BNJ Oxenford      NaN  \n",
       "632  HDPK Dharmasena      NaN  \n",
       "633    C Shamshuddin      NaN  \n",
       "634        CK Nandan      NaN  \n",
       "635     BNJ Oxenford      NaN  \n",
       "\n",
       "[636 rows x 18 columns]"
      ]
     },
     "execution_count": 249,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl = pd.read_csv('ipl_dataset.csv')\n",
    "ipl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "id": "8e610d6e-23d0-4771-b221-0f94eb1f3752",
   "metadata": {},
   "outputs": [],
   "source": [
    "#ipl['team1'] = int(ipl['team1'].strip())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 251,
   "id": "f0915793-9997-4ee1-9b62-98d77219a4f3",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "##ipl['team1'] = ipl['team1'].apply(lambda x: int(x))\n",
    "#print(ipl)\n",
    "#df['team1'].dtype\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "id": "5e778340-0b83-48ce-bba7-909d7a2867d5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total Matches Played: 636\n",
      " \n",
      " Venues Played At: ['Hyderabad' 'Pune' 'Rajkot' 'Indore' 'Bangalore' 'Mumbai' 'Kolkata'\n",
      " 'Delhi' 'Chandigarh' 'Kanpur' 'Jaipur' 'Chennai' 'Cape Town'\n",
      " 'Port Elizabeth' 'Durban' 'Centurion' 'East London' 'Johannesburg'\n",
      " 'Kimberley' 'Bloemfontein' 'Ahmedabad' 'Cuttack' 'Nagpur' 'Dharamsala'\n",
      " 'Kochi' 'Visakhapatnam' 'Raipur' 'Ranchi' 'Abu Dhabi' 'Sharjah' nan]\n",
      " \n",
      " Teams : ['Sunrisers Hyderabad' 'Mumbai Indians' 'Gujarat Lions'\n",
      " 'Rising Pune Supergiant' 'Royal Challengers Bangalore'\n",
      " 'Kolkata Knight Riders' 'Delhi Daredevils' 'Kings XI Punjab'\n",
      " 'Chennai Super Kings' 'Rajasthan Royals' 'Deccan Chargers'\n",
      " 'Kochi Tuskers Kerala' 'Pune Warriors' 'Rising Pune Supergiants']\n"
     ]
    }
   ],
   "source": [
    "print('Total Matches Played:',ipl.shape[0])\n",
    "print(' \\n Venues Played At:',ipl['city'].unique())     \n",
    "print(' \\n Teams :',ipl['team1'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 253,
   "id": "1ca41509-cb45-42b9-aac6-4ad2c5ab2723",
   "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>season</th>\n",
       "      <th>city</th>\n",
       "      <th>date</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>result</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>venue</th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "      <th>umpire3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2017</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>5/4/2017</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>Yuvraj Singh</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>AY Dandekar</td>\n",
       "      <td>NJ Llong</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2017</td>\n",
       "      <td>Pune</td>\n",
       "      <td>6/4/2017</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>SPD Smith</td>\n",
       "      <td>Maharashtra Cricket Association Stadium</td>\n",
       "      <td>A Nand Kishore</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2017</td>\n",
       "      <td>Rajkot</td>\n",
       "      <td>7/4/2017</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>CA Lynn</td>\n",
       "      <td>Saurashtra Cricket Association Stadium</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>CK Nandan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2017</td>\n",
       "      <td>Indore</td>\n",
       "      <td>8/4/2017</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>GJ Maxwell</td>\n",
       "      <td>Holkar Cricket Stadium</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2017</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>8/4/2017</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>KM Jadhav</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>631</th>\n",
       "      <td>632</td>\n",
       "      <td>2016</td>\n",
       "      <td>Raipur</td>\n",
       "      <td>22/05/16</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>V Kohli</td>\n",
       "      <td>Shaheed Veer Narayan Singh International Stadium</td>\n",
       "      <td>A Nand Kishore</td>\n",
       "      <td>BNJ Oxenford</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>632</th>\n",
       "      <td>633</td>\n",
       "      <td>2016</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>24/05/16</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>AB de Villiers</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>633</th>\n",
       "      <td>634</td>\n",
       "      <td>2016</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>25/05/16</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>MC Henriques</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>634</th>\n",
       "      <td>635</td>\n",
       "      <td>2016</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>27/05/16</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>CK Nandan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>635</th>\n",
       "      <td>636</td>\n",
       "      <td>2016</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>29/05/16</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>BCJ Cutting</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>BNJ Oxenford</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>636 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      id  season       city      date                        team1  \\\n",
       "0      1    2017  Hyderabad  5/4/2017          Sunrisers Hyderabad   \n",
       "1      2    2017       Pune  6/4/2017               Mumbai Indians   \n",
       "2      3    2017     Rajkot  7/4/2017                Gujarat Lions   \n",
       "3      4    2017     Indore  8/4/2017       Rising Pune Supergiant   \n",
       "4      5    2017  Bangalore  8/4/2017  Royal Challengers Bangalore   \n",
       "..   ...     ...        ...       ...                          ...   \n",
       "631  632    2016     Raipur  22/05/16             Delhi Daredevils   \n",
       "632  633    2016  Bangalore  24/05/16                Gujarat Lions   \n",
       "633  634    2016      Delhi  25/05/16          Sunrisers Hyderabad   \n",
       "634  635    2016      Delhi  27/05/16                Gujarat Lions   \n",
       "635  636    2016  Bangalore  29/05/16          Sunrisers Hyderabad   \n",
       "\n",
       "                           team2                  toss_winner toss_decision  \\\n",
       "0    Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
       "1         Rising Pune Supergiant       Rising Pune Supergiant         field   \n",
       "2          Kolkata Knight Riders        Kolkata Knight Riders         field   \n",
       "3                Kings XI Punjab              Kings XI Punjab         field   \n",
       "4               Delhi Daredevils  Royal Challengers Bangalore           bat   \n",
       "..                           ...                          ...           ...   \n",
       "631  Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
       "632  Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
       "633        Kolkata Knight Riders        Kolkata Knight Riders         field   \n",
       "634          Sunrisers Hyderabad          Sunrisers Hyderabad         field   \n",
       "635  Royal Challengers Bangalore          Sunrisers Hyderabad           bat   \n",
       "\n",
       "     result  dl_applied                       winner  win_by_runs  \\\n",
       "0    normal           0          Sunrisers Hyderabad           35   \n",
       "1    normal           0       Rising Pune Supergiant            0   \n",
       "2    normal           0        Kolkata Knight Riders            0   \n",
       "3    normal           0              Kings XI Punjab            0   \n",
       "4    normal           0  Royal Challengers Bangalore           15   \n",
       "..      ...         ...                          ...          ...   \n",
       "631  normal           0  Royal Challengers Bangalore            0   \n",
       "632  normal           0  Royal Challengers Bangalore            0   \n",
       "633  normal           0          Sunrisers Hyderabad           22   \n",
       "634  normal           0          Sunrisers Hyderabad            0   \n",
       "635  normal           0          Sunrisers Hyderabad            8   \n",
       "\n",
       "     win_by_wickets player_of_match  \\\n",
       "0                 0    Yuvraj Singh   \n",
       "1                 7       SPD Smith   \n",
       "2                10         CA Lynn   \n",
       "3                 6      GJ Maxwell   \n",
       "4                 0       KM Jadhav   \n",
       "..              ...             ...   \n",
       "631               6         V Kohli   \n",
       "632               4  AB de Villiers   \n",
       "633               0    MC Henriques   \n",
       "634               4       DA Warner   \n",
       "635               0     BCJ Cutting   \n",
       "\n",
       "                                                venue          umpire1  \\\n",
       "0           Rajiv Gandhi International Stadium, Uppal      AY Dandekar   \n",
       "1             Maharashtra Cricket Association Stadium   A Nand Kishore   \n",
       "2              Saurashtra Cricket Association Stadium      Nitin Menon   \n",
       "3                              Holkar Cricket Stadium     AK Chaudhary   \n",
       "4                               M Chinnaswamy Stadium              NaN   \n",
       "..                                                ...              ...   \n",
       "631  Shaheed Veer Narayan Singh International Stadium   A Nand Kishore   \n",
       "632                             M Chinnaswamy Stadium     AK Chaudhary   \n",
       "633                                  Feroz Shah Kotla        M Erasmus   \n",
       "634                                  Feroz Shah Kotla        M Erasmus   \n",
       "635                             M Chinnaswamy Stadium  HDPK Dharmasena   \n",
       "\n",
       "             umpire2  umpire3  \n",
       "0           NJ Llong      NaN  \n",
       "1             S Ravi      NaN  \n",
       "2          CK Nandan      NaN  \n",
       "3      C Shamshuddin      NaN  \n",
       "4                NaN      NaN  \n",
       "..               ...      ...  \n",
       "631     BNJ Oxenford      NaN  \n",
       "632  HDPK Dharmasena      NaN  \n",
       "633    C Shamshuddin      NaN  \n",
       "634        CK Nandan      NaN  \n",
       "635     BNJ Oxenford      NaN  \n",
       "\n",
       "[636 rows x 18 columns]"
      ]
     },
     "execution_count": 253,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "id": "3a772070-f652-452b-a7b7-c8467d0341c0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "player_of_match\n",
       "CH Gayle          18\n",
       "YK Pathan         16\n",
       "DA Warner         15\n",
       "AB de Villiers    15\n",
       "RG Sharma         14\n",
       "                  ..\n",
       "AD Mathews         1\n",
       "LR Shukla          1\n",
       "R Bhatia           1\n",
       "A Singh            1\n",
       "BCJ Cutting        1\n",
       "Name: count, Length: 201, dtype: int64"
      ]
     },
     "execution_count": 254,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl['player_of_match'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 255,
   "id": "6d366f00-f6db-409d-bd4e-1614d79dbeed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "player_of_match\n",
       "CH Gayle          18\n",
       "YK Pathan         16\n",
       "DA Warner         15\n",
       "AB de Villiers    15\n",
       "RG Sharma         14\n",
       "SK Raina          14\n",
       "MS Dhoni          13\n",
       "G Gambhir         13\n",
       "AM Rahane         12\n",
       "MEK Hussey        12\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 255,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl['player_of_match'].value_counts()[0:10]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 256,
   "id": "d6b2fbfc-b2b6-4c6e-8a76-a1990f1f91b0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "player_of_match\n",
       "CH Gayle          18\n",
       "YK Pathan         16\n",
       "DA Warner         15\n",
       "AB de Villiers    15\n",
       "RG Sharma         14\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 256,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl['player_of_match'].value_counts()[0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 257,
   "id": "57958eb4-7b2d-4331-810e-898ae8e4aa0c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['CH Gayle', 'YK Pathan', 'DA Warner', 'AB de Villiers', 'RG Sharma'], dtype='object', name='player_of_match')"
      ]
     },
     "execution_count": 257,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl['player_of_match'].value_counts()[0:5].keys()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 258,
   "id": "bdd7abd8-29ba-4dfd-af22-19fbceff46f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,5))\n",
    "plt.barh(ipl['player_of_match'].value_counts()[0:5].keys(),ipl['player_of_match'].value_counts()[0:5],color='g')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 259,
   "id": "b076cbf7-c104-4559-a629-d93a28f672b3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Hyderabad', 'Pune', 'Rajkot', 'Indore', 'Bangalore', 'Mumbai',\n",
       "       'Kolkata', 'Delhi', 'Chandigarh', 'Kanpur', 'Jaipur', 'Chennai',\n",
       "       'Cape Town', 'Port Elizabeth', 'Durban', 'Centurion',\n",
       "       'East London', 'Johannesburg', 'Kimberley', 'Bloemfontein',\n",
       "       'Ahmedabad', 'Cuttack', 'Nagpur', 'Dharamsala', 'Kochi',\n",
       "       'Visakhapatnam', 'Raipur', 'Ranchi', 'Abu Dhabi', 'Sharjah', nan],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 259,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cities = ipl['city'].unique()\n",
    "cities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 260,
   "id": "fd1dbfd1-f77b-45aa-8c40-aa01ee941196",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "win_by_runs\n",
       "0      349\n",
       "23       9\n",
       "10       9\n",
       "9        9\n",
       "7        9\n",
       "      ... \n",
       "67       1\n",
       "57       1\n",
       "76       1\n",
       "111      1\n",
       "80       1\n",
       "Name: count, Length: 86, dtype: int64"
      ]
     },
     "execution_count": 260,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "ipl['win_by_runs'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 261,
   "id": "db7c2e9b-f250-4ba2-89f7-3dcf412e7966",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "result\n",
       "normal       626\n",
       "tie            7\n",
       "no result      3\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 261,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl['result'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 262,
   "id": "6765c3df-7675-4d60-89c4-8af704d069ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['normal', 'tie', 'no result'], dtype=object)"
      ]
     },
     "execution_count": 262,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl['result'].unique()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 263,
   "id": "caccc4eb-a3de-4b13-8cfe-ff1731478c2e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "toss_winner\n",
       "Mumbai Indians                 85\n",
       "Kolkata Knight Riders          78\n",
       "Delhi Daredevils               72\n",
       "Royal Challengers Bangalore    70\n",
       "Kings XI Punjab                68\n",
       "Chennai Super Kings            66\n",
       "Rajasthan Royals               63\n",
       "Deccan Chargers                43\n",
       "Sunrisers Hyderabad            35\n",
       "Pune Warriors                  20\n",
       "Gujarat Lions                  15\n",
       "Kochi Tuskers Kerala            8\n",
       "Rising Pune Supergiants         7\n",
       "Rising Pune Supergiant          6\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 263,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl['toss_winner'].value_counts()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 264,
   "id": "d9c43dbf-f36b-4d07-9462-405e4b3200c0",
   "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>season</th>\n",
       "      <th>city</th>\n",
       "      <th>date</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>result</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>venue</th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "      <th>umpire3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2017</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>5/4/2017</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>Yuvraj Singh</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>AY Dandekar</td>\n",
       "      <td>NJ Llong</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2017</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>8/4/2017</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>KM Jadhav</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>2017</td>\n",
       "      <td>Pune</td>\n",
       "      <td>11/4/2017</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>97</td>\n",
       "      <td>0</td>\n",
       "      <td>SV Samson</td>\n",
       "      <td>Maharashtra Cricket Association Stadium</td>\n",
       "      <td>AY Dandekar</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>2017</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>15/04/17</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>RV Uthappa</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>AY Dandekar</td>\n",
       "      <td>NJ Llong</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>2017</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>15/04/17</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>51</td>\n",
       "      <td>0</td>\n",
       "      <td>CJ Anderson</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>YC Barde</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    id  season       city       date                        team1  \\\n",
       "0    1    2017  Hyderabad   5/4/2017          Sunrisers Hyderabad   \n",
       "4    5    2017  Bangalore   8/4/2017  Royal Challengers Bangalore   \n",
       "8    9    2017       Pune  11/4/2017             Delhi Daredevils   \n",
       "13  14    2017    Kolkata   15/04/17        Kolkata Knight Riders   \n",
       "14  15    2017      Delhi   15/04/17             Delhi Daredevils   \n",
       "\n",
       "                          team2                  toss_winner toss_decision  \\\n",
       "0   Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
       "4              Delhi Daredevils  Royal Challengers Bangalore           bat   \n",
       "8        Rising Pune Supergiant       Rising Pune Supergiant         field   \n",
       "13          Sunrisers Hyderabad          Sunrisers Hyderabad         field   \n",
       "14              Kings XI Punjab             Delhi Daredevils           bat   \n",
       "\n",
       "    result  dl_applied                       winner  win_by_runs  \\\n",
       "0   normal           0          Sunrisers Hyderabad           35   \n",
       "4   normal           0  Royal Challengers Bangalore           15   \n",
       "8   normal           0             Delhi Daredevils           97   \n",
       "13  normal           0        Kolkata Knight Riders           17   \n",
       "14  normal           0             Delhi Daredevils           51   \n",
       "\n",
       "    win_by_wickets player_of_match                                      venue  \\\n",
       "0                0    Yuvraj Singh  Rajiv Gandhi International Stadium, Uppal   \n",
       "4                0       KM Jadhav                      M Chinnaswamy Stadium   \n",
       "8                0       SV Samson    Maharashtra Cricket Association Stadium   \n",
       "13               0      RV Uthappa                               Eden Gardens   \n",
       "14               0     CJ Anderson                           Feroz Shah Kotla   \n",
       "\n",
       "        umpire1      umpire2  umpire3  \n",
       "0   AY Dandekar     NJ Llong      NaN  \n",
       "4           NaN          NaN      NaN  \n",
       "8   AY Dandekar       S Ravi      NaN  \n",
       "13  AY Dandekar     NJ Llong      NaN  \n",
       "14     YC Barde  Nitin Menon      NaN  "
      ]
     },
     "execution_count": 264,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "batting_first_win = ipl[ipl['win_by_runs'] != 0]\n",
    "batting_first_win.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 265,
   "id": "0a5ad902-3948-4d90-99d1-854f1dd36cbb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      35\n",
       "1       0\n",
       "2       0\n",
       "3       0\n",
       "4      15\n",
       "       ..\n",
       "631     0\n",
       "632     0\n",
       "633    22\n",
       "634     0\n",
       "635     8\n",
       "Name: win_by_runs, Length: 636, dtype: int64"
      ]
     },
     "execution_count": 265,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl['win_by_runs']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 266,
   "id": "9b8dd242-1b19-475e-9cdf-8931a1e98fd3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(5,5))\n",
    "plt.hist(batting_first_win['win_by_runs'],color='m')\n",
    "plt.title(\"Distribution of Runs\")\n",
    "plt.xlabel(\"Runs\")\n",
    "plt.ylabel(\"Matches\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 267,
   "id": "e6a6fb93-b54f-407a-934d-77b1eb3608fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "winner\n",
       "Mumbai Indians                 47\n",
       "Chennai Super Kings            46\n",
       "Kings XI Punjab                32\n",
       "Kolkata Knight Riders          31\n",
       "Royal Challengers Bangalore    30\n",
       "Sunrisers Hyderabad            23\n",
       "Rajasthan Royals               23\n",
       "Delhi Daredevils               21\n",
       "Deccan Chargers                18\n",
       "Pune Warriors                   6\n",
       "Rising Pune Supergiant          5\n",
       "Kochi Tuskers Kerala            2\n",
       "Rising Pune Supergiants         2\n",
       "Gujarat Lions                   1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 267,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "batting_first_win['winner'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 268,
   "id": "3f3889a6-ab96-4d5b-86a3-aa5c2a036e75",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Mumbai Indians', 'Chennai Super Kings', 'Kings XI Punjab',\n",
       "       'Kolkata Knight Riders', 'Royal Challengers Bangalore',\n",
       "       'Sunrisers Hyderabad', 'Rajasthan Royals', 'Delhi Daredevils',\n",
       "       'Deccan Chargers', 'Pune Warriors', 'Rising Pune Supergiant',\n",
       "       'Kochi Tuskers Kerala', 'Rising Pune Supergiants', 'Gujarat Lions'],\n",
       "      dtype='object', name='winner')"
      ]
     },
     "execution_count": 268,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "batting_first_win['winner'].value_counts().keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 269,
   "id": "2b895613-8b9e-453d-b400-321267acc96a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,5))\n",
    "plt.bar(list(batting_first_win['winner'].value_counts()[0:3].keys()),batting_first_win['winner'].value_counts()[0:3],color=['Blue','Yellow','Red'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 270,
   "id": "1612f2d0-fc77-4eea-9fca-15590758d0c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,5))\n",
    "plt.barh(batting_first_win['winner'].value_counts().keys(),batting_first_win['winner'].value_counts(),color=['Red'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 271,
   "id": "e86c7d1d-f14c-4adc-9e56-607b27e6b63b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "plt.pie(list(batting_first_win['winner'].value_counts()),labels = list(batting_first_win['winner'].value_counts().keys()),autopct = '%0.1f%%',pctdistance=0.9)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 272,
   "id": "bd5d4feb-dd15-498a-a0e9-d257a3c650f7",
   "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>season</th>\n",
       "      <th>city</th>\n",
       "      <th>date</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>result</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>venue</th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "      <th>umpire3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2017</td>\n",
       "      <td>Pune</td>\n",
       "      <td>6/4/2017</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>SPD Smith</td>\n",
       "      <td>Maharashtra Cricket Association Stadium</td>\n",
       "      <td>A Nand Kishore</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2017</td>\n",
       "      <td>Rajkot</td>\n",
       "      <td>7/4/2017</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>CA Lynn</td>\n",
       "      <td>Saurashtra Cricket Association Stadium</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>CK Nandan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2017</td>\n",
       "      <td>Indore</td>\n",
       "      <td>8/4/2017</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>GJ Maxwell</td>\n",
       "      <td>Holkar Cricket Stadium</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>2017</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>9/4/2017</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>Rashid Khan</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>A Deshmukh</td>\n",
       "      <td>NJ Llong</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>2017</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>9/4/2017</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>N Rana</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>CK Nandan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id  season       city      date                   team1  \\\n",
       "1   2    2017       Pune  6/4/2017          Mumbai Indians   \n",
       "2   3    2017     Rajkot  7/4/2017           Gujarat Lions   \n",
       "3   4    2017     Indore  8/4/2017  Rising Pune Supergiant   \n",
       "5   6    2017  Hyderabad  9/4/2017           Gujarat Lions   \n",
       "6   7    2017     Mumbai  9/4/2017   Kolkata Knight Riders   \n",
       "\n",
       "                    team2             toss_winner toss_decision  result  \\\n",
       "1  Rising Pune Supergiant  Rising Pune Supergiant         field  normal   \n",
       "2   Kolkata Knight Riders   Kolkata Knight Riders         field  normal   \n",
       "3         Kings XI Punjab         Kings XI Punjab         field  normal   \n",
       "5     Sunrisers Hyderabad     Sunrisers Hyderabad         field  normal   \n",
       "6          Mumbai Indians          Mumbai Indians         field  normal   \n",
       "\n",
       "   dl_applied                  winner  win_by_runs  win_by_wickets  \\\n",
       "1           0  Rising Pune Supergiant            0               7   \n",
       "2           0   Kolkata Knight Riders            0              10   \n",
       "3           0         Kings XI Punjab            0               6   \n",
       "5           0     Sunrisers Hyderabad            0               9   \n",
       "6           0          Mumbai Indians            0               4   \n",
       "\n",
       "  player_of_match                                      venue         umpire1  \\\n",
       "1       SPD Smith    Maharashtra Cricket Association Stadium  A Nand Kishore   \n",
       "2         CA Lynn     Saurashtra Cricket Association Stadium     Nitin Menon   \n",
       "3      GJ Maxwell                     Holkar Cricket Stadium    AK Chaudhary   \n",
       "5     Rashid Khan  Rajiv Gandhi International Stadium, Uppal      A Deshmukh   \n",
       "6          N Rana                           Wankhede Stadium     Nitin Menon   \n",
       "\n",
       "         umpire2  umpire3  \n",
       "1         S Ravi      NaN  \n",
       "2      CK Nandan      NaN  \n",
       "3  C Shamshuddin      NaN  \n",
       "5       NJ Llong      NaN  \n",
       "6      CK Nandan      NaN  "
      ]
     },
     "execution_count": 272,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "batting_second_win = ipl[ipl['win_by_wickets'] != 0]\n",
    "batting_second_win.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 273,
   "id": "fec8389d-9990-4cbc-b215-acef47fcb06a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(5,5))\n",
    "plt.hist(batting_second_win['win_by_wickets'],bins=20, color='skyblue',histtype='stepfilled')\n",
    "plt.title(\"Distribution of wickets\")\n",
    "plt.xlabel(\"wickets\")\n",
    "plt.ylabel(\"Nos of Matches\")\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 274,
   "id": "9cc5930f-5831-4283-ac85-81d9617e1f4d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "winner\n",
       "Kolkata Knight Riders          46\n",
       "Mumbai Indians                 44\n",
       "Royal Challengers Bangalore    42\n",
       "Delhi Daredevils               41\n",
       "Rajasthan Royals               38\n",
       "Kings XI Punjab                36\n",
       "Chennai Super Kings            33\n",
       "Sunrisers Hyderabad            18\n",
       "Gujarat Lions                  12\n",
       "Deccan Chargers                11\n",
       "Pune Warriors                   6\n",
       "Rising Pune Supergiant          5\n",
       "Kochi Tuskers Kerala            4\n",
       "Rising Pune Supergiants         3\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 274,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "batting_second_win['winner'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 275,
   "id": "601b4773-5275-415f-bcb3-38a811b53bd8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "plt.pie(list(batting_second_win['winner'].value_counts()),labels = list(batting_second_win['winner'].value_counts().keys()),autopct = '%0.1f%%',pctdistance=0.9)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 276,
   "id": "ad0d489a-d54e-43d2-962f-459f86d2d598",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,5))\n",
    "plt.barh(batting_second_win['winner'].value_counts().keys(),batting_second_win['winner'].value_counts(),color=['pink'])\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 277,
   "id": "130dc758-2351-481d-84a9-aaca3e9e250d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(5,5))\n",
    "plt.bar(list(batting_second_win['winner'].value_counts()[0:3].keys()),list(batting_second_win['winner'].value_counts()[0:3]),color=['purple','blue','Red'])\n",
    "plt.xticks(rotation ='vertical')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 278,
   "id": "8cd4a6da-06df-4d9f-9ea4-9bb1c774c11d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "season\n",
       "2013    76\n",
       "2012    74\n",
       "2011    73\n",
       "2010    60\n",
       "2014    60\n",
       "2016    60\n",
       "2017    59\n",
       "2015    59\n",
       "2008    58\n",
       "2009    57\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 278,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl['season'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 279,
   "id": "79a1bd69-e3d2-470f-a259-b6f2d84066f9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "city\n",
       "Mumbai            85\n",
       "Bangalore         66\n",
       "Kolkata           61\n",
       "Delhi             60\n",
       "Hyderabad         49\n",
       "Chennai           48\n",
       "Chandigarh        46\n",
       "Jaipur            33\n",
       "Pune              32\n",
       "Durban            15\n",
       "Ahmedabad         12\n",
       "Centurion         12\n",
       "Visakhapatnam     11\n",
       "Rajkot            10\n",
       "Dharamsala         9\n",
       "Johannesburg       8\n",
       "Cape Town          7\n",
       "Abu Dhabi          7\n",
       "Ranchi             7\n",
       "Port Elizabeth     7\n",
       "Cuttack            7\n",
       "Raipur             6\n",
       "Sharjah            6\n",
       "Kochi              5\n",
       "Indore             5\n",
       "Kanpur             4\n",
       "Nagpur             3\n",
       "Kimberley          3\n",
       "East London        3\n",
       "Bloemfontein       2\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 279,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl['city'].value_counts()\n"
   ]
  },
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      ]
     },
     "execution_count": 280,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sum(ipl['toss_winner'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 281,
   "id": "08a44aef-4db6-42ed-9866-b641967e6e8a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      False\n",
       "1       True\n",
       "2       True\n",
       "3       True\n",
       "4       True\n",
       "       ...  \n",
       "631     True\n",
       "632     True\n",
       "633    False\n",
       "634     True\n",
       "635     True\n",
       "Length: 636, dtype: bool"
      ]
     },
     "execution_count": 281,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipl['toss_winner'] == ipl['winner']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 282,
   "id": "a403f7e8-53ba-4136-8a1a-fc6296e0f3e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "325"
      ]
     },
     "execution_count": 282,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sum(ipl['toss_winner'] == ipl['winner'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 283,
   "id": "3a65aeb9-97a5-43e3-87b2-3a53ee0ad2ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "51.100628930817614"
      ]
     },
     "execution_count": 283,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(325/636)*100"
   ]
  },
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   "cell_type": "code",
   "execution_count": 284,
   "id": "90dd3df3-2dc6-4c18-b00e-0f384a5ecccb",
   "metadata": {},
   "outputs": [
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       "      <th></th>\n",
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       "      <th>is_wicket</th>\n",
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       "      <td>335982</td>\n",
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       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>260915</th>\n",
       "      <td>1426312</td>\n",
       "      <td>2</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
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       "      <td>AK Markram</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>260916</th>\n",
       "      <td>1426312</td>\n",
       "      <td>2</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
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       "      <td>6</td>\n",
       "      <td>VR Iyer</td>\n",
       "      <td>AK Markram</td>\n",
       "      <td>SS Iyer</td>\n",
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       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>260917</th>\n",
       "      <td>1426312</td>\n",
       "      <td>2</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
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       "      <td>VR Iyer</td>\n",
       "      <td>Shahbaz Ahmed</td>\n",
       "      <td>SS Iyer</td>\n",
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       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>260918</th>\n",
       "      <td>1426312</td>\n",
       "      <td>2</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>SS Iyer</td>\n",
       "      <td>Shahbaz Ahmed</td>\n",
       "      <td>VR Iyer</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260919</th>\n",
       "      <td>1426312</td>\n",
       "      <td>2</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>VR Iyer</td>\n",
       "      <td>Shahbaz Ahmed</td>\n",
       "      <td>SS Iyer</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>260920 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        match_id  inning           batting_team                 bowling_team  \\\n",
       "0         335982       1  Kolkata Knight Riders  Royal Challengers Bangalore   \n",
       "1         335982       1  Kolkata Knight Riders  Royal Challengers Bangalore   \n",
       "2         335982       1  Kolkata Knight Riders  Royal Challengers Bangalore   \n",
       "3         335982       1  Kolkata Knight Riders  Royal Challengers Bangalore   \n",
       "4         335982       1  Kolkata Knight Riders  Royal Challengers Bangalore   \n",
       "...          ...     ...                    ...                          ...   \n",
       "260915   1426312       2  Kolkata Knight Riders          Sunrisers Hyderabad   \n",
       "260916   1426312       2  Kolkata Knight Riders          Sunrisers Hyderabad   \n",
       "260917   1426312       2  Kolkata Knight Riders          Sunrisers Hyderabad   \n",
       "260918   1426312       2  Kolkata Knight Riders          Sunrisers Hyderabad   \n",
       "260919   1426312       2  Kolkata Knight Riders          Sunrisers Hyderabad   \n",
       "\n",
       "        over  ball       batter         bowler  non_striker  batsman_runs  \\\n",
       "0          0     1   SC Ganguly        P Kumar  BB McCullum             0   \n",
       "1          0     2  BB McCullum        P Kumar   SC Ganguly             0   \n",
       "2          0     3  BB McCullum        P Kumar   SC Ganguly             0   \n",
       "3          0     4  BB McCullum        P Kumar   SC Ganguly             0   \n",
       "4          0     5  BB McCullum        P Kumar   SC Ganguly             0   \n",
       "...      ...   ...          ...            ...          ...           ...   \n",
       "260915     9     5      SS Iyer     AK Markram      VR Iyer             1   \n",
       "260916     9     6      VR Iyer     AK Markram      SS Iyer             1   \n",
       "260917    10     1      VR Iyer  Shahbaz Ahmed      SS Iyer             1   \n",
       "260918    10     2      SS Iyer  Shahbaz Ahmed      VR Iyer             1   \n",
       "260919    10     3      VR Iyer  Shahbaz Ahmed      SS Iyer             1   \n",
       "\n",
       "        extra_runs  total_runs extras_type  is_wicket player_dismissed  \\\n",
       "0                1           1     legbyes          0              NaN   \n",
       "1                0           0         NaN          0              NaN   \n",
       "2                1           1       wides          0              NaN   \n",
       "3                0           0         NaN          0              NaN   \n",
       "4                0           0         NaN          0              NaN   \n",
       "...            ...         ...         ...        ...              ...   \n",
       "260915           0           1         NaN          0              NaN   \n",
       "260916           0           1         NaN          0              NaN   \n",
       "260917           0           1         NaN          0              NaN   \n",
       "260918           0           1         NaN          0              NaN   \n",
       "260919           0           1         NaN          0              NaN   \n",
       "\n",
       "       dismissal_kind fielder  \n",
       "0                 NaN     NaN  \n",
       "1                 NaN     NaN  \n",
       "2                 NaN     NaN  \n",
       "3                 NaN     NaN  \n",
       "4                 NaN     NaN  \n",
       "...               ...     ...  \n",
       "260915            NaN     NaN  \n",
       "260916            NaN     NaN  \n",
       "260917            NaN     NaN  \n",
       "260918            NaN     NaN  \n",
       "260919            NaN     NaN  \n",
       "\n",
       "[260920 rows x 17 columns]"
      ]
     },
     "execution_count": 284,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deliveries = pd.read_csv('deliveries.csv')\n",
    "deliveries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 285,
   "id": "87f5845a-9dc8-467c-87ae-d6b8cdaa2584",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 335982,  335983,  335984, ..., 1426310, 1426311, 1426312],\n",
       "      dtype=int64)"
      ]
     },
     "execution_count": 285,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deliveries['match_id'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 286,
   "id": "4fae95e1-4a1c-4a08-8f1e-0dc925cd780a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
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       "        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>match_id</th>\n",
       "      <th>inning</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>batter</th>\n",
       "      <th>bowler</th>\n",
       "      <th>non_striker</th>\n",
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       "      <th>total_runs</th>\n",
       "      <th>extras_type</th>\n",
       "      <th>is_wicket</th>\n",
       "      <th>player_dismissed</th>\n",
       "      <th>dismissal_kind</th>\n",
       "      <th>fielder</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
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       "      <td>SC Ganguly</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>335982</td>\n",
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       "      <td>0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>335982</td>\n",
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       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
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       "      <td>335982</td>\n",
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       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>SC Ganguly</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>335982</td>\n",
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       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>SC Ganguly</td>\n",
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       "      <td>NaN</td>\n",
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       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>335982</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>14</td>\n",
       "      <td>5</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>I Sharma</td>\n",
       "      <td>SB Joshi</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>legbyes</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>335982</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>14</td>\n",
       "      <td>6</td>\n",
       "      <td>SB Joshi</td>\n",
       "      <td>I Sharma</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>222</th>\n",
       "      <td>335982</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>14</td>\n",
       "      <td>7</td>\n",
       "      <td>P Kumar</td>\n",
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       "      <td>SB Joshi</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>223</th>\n",
       "      <td>335982</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>SB Joshi</td>\n",
       "      <td>LR Shukla</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>wides</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>335982</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>SB Joshi</td>\n",
       "      <td>LR Shukla</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>SB Joshi</td>\n",
       "      <td>caught</td>\n",
       "      <td>BB McCullum</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>225 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     match_id  inning                 batting_team  \\\n",
       "0      335982       1        Kolkata Knight Riders   \n",
       "1      335982       1        Kolkata Knight Riders   \n",
       "2      335982       1        Kolkata Knight Riders   \n",
       "3      335982       1        Kolkata Knight Riders   \n",
       "4      335982       1        Kolkata Knight Riders   \n",
       "..        ...     ...                          ...   \n",
       "220    335982       2  Royal Challengers Bangalore   \n",
       "221    335982       2  Royal Challengers Bangalore   \n",
       "222    335982       2  Royal Challengers Bangalore   \n",
       "223    335982       2  Royal Challengers Bangalore   \n",
       "224    335982       2  Royal Challengers Bangalore   \n",
       "\n",
       "                    bowling_team  over  ball       batter     bowler  \\\n",
       "0    Royal Challengers Bangalore     0     1   SC Ganguly    P Kumar   \n",
       "1    Royal Challengers Bangalore     0     2  BB McCullum    P Kumar   \n",
       "2    Royal Challengers Bangalore     0     3  BB McCullum    P Kumar   \n",
       "3    Royal Challengers Bangalore     0     4  BB McCullum    P Kumar   \n",
       "4    Royal Challengers Bangalore     0     5  BB McCullum    P Kumar   \n",
       "..                           ...   ...   ...          ...        ...   \n",
       "220        Kolkata Knight Riders    14     5      P Kumar   I Sharma   \n",
       "221        Kolkata Knight Riders    14     6     SB Joshi   I Sharma   \n",
       "222        Kolkata Knight Riders    14     7      P Kumar   I Sharma   \n",
       "223        Kolkata Knight Riders    15     1     SB Joshi  LR Shukla   \n",
       "224        Kolkata Knight Riders    15     2     SB Joshi  LR Shukla   \n",
       "\n",
       "     non_striker  batsman_runs  extra_runs  total_runs extras_type  is_wicket  \\\n",
       "0    BB McCullum             0           1           1     legbyes          0   \n",
       "1     SC Ganguly             0           0           0         NaN          0   \n",
       "2     SC Ganguly             0           1           1       wides          0   \n",
       "3     SC Ganguly             0           0           0         NaN          0   \n",
       "4     SC Ganguly             0           0           0         NaN          0   \n",
       "..           ...           ...         ...         ...         ...        ...   \n",
       "220     SB Joshi             0           1           1     legbyes          0   \n",
       "221      P Kumar             1           0           1         NaN          0   \n",
       "222     SB Joshi             0           0           0         NaN          0   \n",
       "223      P Kumar             0           1           1       wides          0   \n",
       "224      P Kumar             0           0           0         NaN          1   \n",
       "\n",
       "    player_dismissed dismissal_kind      fielder  \n",
       "0                NaN            NaN          NaN  \n",
       "1                NaN            NaN          NaN  \n",
       "2                NaN            NaN          NaN  \n",
       "3                NaN            NaN          NaN  \n",
       "4                NaN            NaN          NaN  \n",
       "..               ...            ...          ...  \n",
       "220              NaN            NaN          NaN  \n",
       "221              NaN            NaN          NaN  \n",
       "222              NaN            NaN          NaN  \n",
       "223              NaN            NaN          NaN  \n",
       "224         SB Joshi         caught  BB McCullum  \n",
       "\n",
       "[225 rows x 17 columns]"
      ]
     },
     "execution_count": 286,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "match_1 = deliveries[deliveries['match_id']==335982]\n",
    "match_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 287,
   "id": "82d1a182-079c-4bb0-831c-19e70ca8081b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>BB McCullum</td>\n",
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       "      <td>SC Ganguly</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>335982</td>\n",
       "      <td>1</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>SC Ganguly</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   match_id  inning           batting_team                 bowling_team  over  \\\n",
       "0    335982       1  Kolkata Knight Riders  Royal Challengers Bangalore     0   \n",
       "1    335982       1  Kolkata Knight Riders  Royal Challengers Bangalore     0   \n",
       "2    335982       1  Kolkata Knight Riders  Royal Challengers Bangalore     0   \n",
       "3    335982       1  Kolkata Knight Riders  Royal Challengers Bangalore     0   \n",
       "4    335982       1  Kolkata Knight Riders  Royal Challengers Bangalore     0   \n",
       "\n",
       "   ball       batter   bowler  non_striker  batsman_runs  extra_runs  \\\n",
       "0     1   SC Ganguly  P Kumar  BB McCullum             0           1   \n",
       "1     2  BB McCullum  P Kumar   SC Ganguly             0           0   \n",
       "2     3  BB McCullum  P Kumar   SC Ganguly             0           1   \n",
       "3     4  BB McCullum  P Kumar   SC Ganguly             0           0   \n",
       "4     5  BB McCullum  P Kumar   SC Ganguly             0           0   \n",
       "\n",
       "   total_runs extras_type  is_wicket player_dismissed dismissal_kind fielder  \n",
       "0           1     legbyes          0              NaN            NaN     NaN  \n",
       "1           0         NaN          0              NaN            NaN     NaN  \n",
       "2           1       wides          0              NaN            NaN     NaN  \n",
       "3           0         NaN          0              NaN            NaN     NaN  \n",
       "4           0         NaN          0              NaN            NaN     NaN  "
      ]
     },
     "execution_count": 287,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "match_1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 288,
   "id": "c579cff1-16fd-45a4-be2d-98a036f6715e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(225, 17)"
      ]
     },
     "execution_count": 288,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "match_1.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 343,
   "id": "d257831b-12ed-4e7c-b6fb-857277bad5a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "kkr= match_1[match_1['inning']==1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 345,
   "id": "3b878633-44ab-47ca-b725-cf032907e612",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "batsman_runs\n",
       "0    45\n",
       "1    39\n",
       "4    15\n",
       "6    14\n",
       "2    11\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 345,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kkr['batsman_runs'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 373,
   "id": "09fe6a6e-c91d-4078-a75c-52a1208819ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "124"
      ]
     },
     "execution_count": 373,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sum(kkr['batsman_runs'].value_counts())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 347,
   "id": "aceac9f7-986a-4643-adba-4fd01663b728",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "player_dismissed\n",
       "SC Ganguly    1\n",
       "RT Ponting    1\n",
       "DJ Hussey     1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 347,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kkr['player_dismissed'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 349,
   "id": "7990a4ba-e70c-4bbc-968e-2e277d93118c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dismissal_kind\n",
       "caught    3\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 349,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kkr['dismissal_kind'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 351,
   "id": "6772d885-3c1d-491f-9332-7651c073e1d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "extras_type\n",
       "legbyes    4\n",
       "wides      4\n",
       "byes       1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 351,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kkr['extras_type'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 363,
   "id": "e3d6129d-c6a4-43f4-a5a2-994d807cb030",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "124"
      ]
     },
     "execution_count": 363,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sum(kkr['total_runs'].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 357,
   "id": "3f076bbd-a46a-435b-a7a0-531f1952e3a2",
   "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>match_id</th>\n",
       "      <th>inning</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>batter</th>\n",
       "      <th>bowler</th>\n",
       "      <th>non_striker</th>\n",
       "      <th>batsman_runs</th>\n",
       "      <th>extra_runs</th>\n",
       "      <th>total_runs</th>\n",
       "      <th>extras_type</th>\n",
       "      <th>is_wicket</th>\n",
       "      <th>player_dismissed</th>\n",
       "      <th>dismissal_kind</th>\n",
       "      <th>fielder</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>335982</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>R Dravid</td>\n",
       "      <td>AB Dinda</td>\n",
       "      <td>W Jaffer</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>335982</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>W Jaffer</td>\n",
       "      <td>AB Dinda</td>\n",
       "      <td>R Dravid</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>wides</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>335982</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>W Jaffer</td>\n",
       "      <td>AB Dinda</td>\n",
       "      <td>R Dravid</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>335982</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>W Jaffer</td>\n",
       "      <td>AB Dinda</td>\n",
       "      <td>R Dravid</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>335982</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>R Dravid</td>\n",
       "      <td>AB Dinda</td>\n",
       "      <td>W Jaffer</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>335982</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>14</td>\n",
       "      <td>5</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>I Sharma</td>\n",
       "      <td>SB Joshi</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>legbyes</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>335982</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>14</td>\n",
       "      <td>6</td>\n",
       "      <td>SB Joshi</td>\n",
       "      <td>I Sharma</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>222</th>\n",
       "      <td>335982</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>14</td>\n",
       "      <td>7</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>I Sharma</td>\n",
       "      <td>SB Joshi</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>223</th>\n",
       "      <td>335982</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>SB Joshi</td>\n",
       "      <td>LR Shukla</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>wides</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>335982</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>SB Joshi</td>\n",
       "      <td>LR Shukla</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>SB Joshi</td>\n",
       "      <td>caught</td>\n",
       "      <td>BB McCullum</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>101 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     match_id  inning                 batting_team           bowling_team  \\\n",
       "124    335982       2  Royal Challengers Bangalore  Kolkata Knight Riders   \n",
       "125    335982       2  Royal Challengers Bangalore  Kolkata Knight Riders   \n",
       "126    335982       2  Royal Challengers Bangalore  Kolkata Knight Riders   \n",
       "127    335982       2  Royal Challengers Bangalore  Kolkata Knight Riders   \n",
       "128    335982       2  Royal Challengers Bangalore  Kolkata Knight Riders   \n",
       "..        ...     ...                          ...                    ...   \n",
       "220    335982       2  Royal Challengers Bangalore  Kolkata Knight Riders   \n",
       "221    335982       2  Royal Challengers Bangalore  Kolkata Knight Riders   \n",
       "222    335982       2  Royal Challengers Bangalore  Kolkata Knight Riders   \n",
       "223    335982       2  Royal Challengers Bangalore  Kolkata Knight Riders   \n",
       "224    335982       2  Royal Challengers Bangalore  Kolkata Knight Riders   \n",
       "\n",
       "     over  ball    batter     bowler non_striker  batsman_runs  extra_runs  \\\n",
       "124     0     1  R Dravid   AB Dinda    W Jaffer             1           0   \n",
       "125     0     2  W Jaffer   AB Dinda    R Dravid             0           1   \n",
       "126     0     3  W Jaffer   AB Dinda    R Dravid             0           0   \n",
       "127     0     4  W Jaffer   AB Dinda    R Dravid             1           0   \n",
       "128     0     5  R Dravid   AB Dinda    W Jaffer             1           0   \n",
       "..    ...   ...       ...        ...         ...           ...         ...   \n",
       "220    14     5   P Kumar   I Sharma    SB Joshi             0           1   \n",
       "221    14     6  SB Joshi   I Sharma     P Kumar             1           0   \n",
       "222    14     7   P Kumar   I Sharma    SB Joshi             0           0   \n",
       "223    15     1  SB Joshi  LR Shukla     P Kumar             0           1   \n",
       "224    15     2  SB Joshi  LR Shukla     P Kumar             0           0   \n",
       "\n",
       "     total_runs extras_type  is_wicket player_dismissed dismissal_kind  \\\n",
       "124           1         NaN          0              NaN            NaN   \n",
       "125           1       wides          0              NaN            NaN   \n",
       "126           0         NaN          0              NaN            NaN   \n",
       "127           1         NaN          0              NaN            NaN   \n",
       "128           1         NaN          0              NaN            NaN   \n",
       "..          ...         ...        ...              ...            ...   \n",
       "220           1     legbyes          0              NaN            NaN   \n",
       "221           1         NaN          0              NaN            NaN   \n",
       "222           0         NaN          0              NaN            NaN   \n",
       "223           1       wides          0              NaN            NaN   \n",
       "224           0         NaN          1         SB Joshi         caught   \n",
       "\n",
       "         fielder  \n",
       "124          NaN  \n",
       "125          NaN  \n",
       "126          NaN  \n",
       "127          NaN  \n",
       "128          NaN  \n",
       "..           ...  \n",
       "220          NaN  \n",
       "221          NaN  \n",
       "222          NaN  \n",
       "223          NaN  \n",
       "224  BB McCullum  \n",
       "\n",
       "[101 rows x 17 columns]"
      ]
     },
     "execution_count": 357,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rcb= match_1[match_1['inning']==2]\n",
    "rcb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 361,
   "id": "840d79ba-f229-40f9-b7f9-4ec8b71adee4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "batsman_runs\n",
       "0    65\n",
       "1    27\n",
       "2     3\n",
       "6     3\n",
       "4     3\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 361,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rcb['batsman_runs'].value_counts()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 365,
   "id": "d726f8ba-9e72-4718-8138-a0f8ab78971c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dismissal_kind\n",
       "caught     6\n",
       "bowled     3\n",
       "run out    1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 365,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rcb['dismissal_kind'].value_counts()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 367,
   "id": "e1096700-ea42-4e46-a21e-693d84843cfe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "extras_type\n",
       "wides      10\n",
       "legbyes     5\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 367,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rcb['extras_type'].value_counts()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 369,
   "id": "566f74fb-9d6f-46bc-bbd5-1797e227fda0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "101"
      ]
     },
     "execution_count": 369,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sum(rcb['total_runs'].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9451f193-d714-4d00-b5ef-c14a578d45f5",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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