Data Analysis on IPL (2008-2022).ipynb

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"
    }
   },
   "cell_type": "markdown",
   "id": "70e53bf0",
   "metadata": {},
   "source": [
    "![917968-ipl-1024x576.jpg](attachment:917968-ipl-1024x576.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "71dbc5f8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e35fa40e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import datetime as dt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "55398de5",
   "metadata": {},
   "source": [
    "# Reading the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "07e6b62d",
   "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>season</th>\n",
       "      <th>start_date</th>\n",
       "      <th>venue</th>\n",
       "      <th>innings</th>\n",
       "      <th>ball</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>striker</th>\n",
       "      <th>non_striker</th>\n",
       "      <th>...</th>\n",
       "      <th>extras</th>\n",
       "      <th>wides</th>\n",
       "      <th>noballs</th>\n",
       "      <th>byes</th>\n",
       "      <th>legbyes</th>\n",
       "      <th>penalty</th>\n",
       "      <th>wicket_type</th>\n",
       "      <th>player_dismissed</th>\n",
       "      <th>other_wicket_type</th>\n",
       "      <th>other_player_dismissed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225949</th>\n",
       "      <td>981019.0</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>2016-05-29</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Sachin Baby</td>\n",
       "      <td>CJ Jordan</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225950</th>\n",
       "      <td>981019.0</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>2016-05-29</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.3</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Sachin Baby</td>\n",
       "      <td>CJ Jordan</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>run out</td>\n",
       "      <td>CJ Jordan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225951</th>\n",
       "      <td>981019.0</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>2016-05-29</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.4</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Iqbal Abdulla</td>\n",
       "      <td>Sachin Baby</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225952</th>\n",
       "      <td>981019.0</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>2016-05-29</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.5</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Sachin Baby</td>\n",
       "      <td>Iqbal Abdulla</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225953</th>\n",
       "      <td>981019.0</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>2016-05-29</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.6</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Iqbal Abdulla</td>\n",
       "      <td>Sachin Baby</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>225954 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         match_id  season  start_date  \\\n",
       "0       1082591.0  2017.0  2017-04-05   \n",
       "1       1082591.0  2017.0  2017-04-05   \n",
       "2       1082591.0  2017.0  2017-04-05   \n",
       "3       1082591.0  2017.0  2017-04-05   \n",
       "4       1082591.0  2017.0  2017-04-05   \n",
       "...           ...     ...         ...   \n",
       "225949   981019.0  2016.0  2016-05-29   \n",
       "225950   981019.0  2016.0  2016-05-29   \n",
       "225951   981019.0  2016.0  2016-05-29   \n",
       "225952   981019.0  2016.0  2016-05-29   \n",
       "225953   981019.0  2016.0  2016-05-29   \n",
       "\n",
       "                                            venue  innings  ball  \\\n",
       "0       Rajiv Gandhi International Stadium, Uppal      1.0   0.1   \n",
       "1       Rajiv Gandhi International Stadium, Uppal      1.0   0.2   \n",
       "2       Rajiv Gandhi International Stadium, Uppal      1.0   0.3   \n",
       "3       Rajiv Gandhi International Stadium, Uppal      1.0   0.4   \n",
       "4       Rajiv Gandhi International Stadium, Uppal      1.0   0.5   \n",
       "...                                           ...      ...   ...   \n",
       "225949                      M Chinnaswamy Stadium      2.0  19.2   \n",
       "225950                      M Chinnaswamy Stadium      2.0  19.3   \n",
       "225951                      M Chinnaswamy Stadium      2.0  19.4   \n",
       "225952                      M Chinnaswamy Stadium      2.0  19.5   \n",
       "225953                      M Chinnaswamy Stadium      2.0  19.6   \n",
       "\n",
       "                       batting_team                 bowling_team  \\\n",
       "0               Sunrisers Hyderabad  Royal Challengers Bangalore   \n",
       "1               Sunrisers Hyderabad  Royal Challengers Bangalore   \n",
       "2               Sunrisers Hyderabad  Royal Challengers Bangalore   \n",
       "3               Sunrisers Hyderabad  Royal Challengers Bangalore   \n",
       "4               Sunrisers Hyderabad  Royal Challengers Bangalore   \n",
       "...                             ...                          ...   \n",
       "225949  Royal Challengers Bangalore          Sunrisers Hyderabad   \n",
       "225950  Royal Challengers Bangalore          Sunrisers Hyderabad   \n",
       "225951  Royal Challengers Bangalore          Sunrisers Hyderabad   \n",
       "225952  Royal Challengers Bangalore          Sunrisers Hyderabad   \n",
       "225953  Royal Challengers Bangalore          Sunrisers Hyderabad   \n",
       "\n",
       "              striker    non_striker  ... extras  wides  noballs  byes  \\\n",
       "0           DA Warner       S Dhawan  ...    0.0    NaN      NaN   NaN   \n",
       "1           DA Warner       S Dhawan  ...    0.0    NaN      NaN   NaN   \n",
       "2           DA Warner       S Dhawan  ...    0.0    NaN      NaN   NaN   \n",
       "3           DA Warner       S Dhawan  ...    0.0    NaN      NaN   NaN   \n",
       "4           DA Warner       S Dhawan  ...    2.0    2.0      NaN   NaN   \n",
       "...               ...            ...  ...    ...    ...      ...   ...   \n",
       "225949    Sachin Baby      CJ Jordan  ...    0.0    NaN      NaN   NaN   \n",
       "225950    Sachin Baby      CJ Jordan  ...    0.0    NaN      NaN   NaN   \n",
       "225951  Iqbal Abdulla    Sachin Baby  ...    1.0    NaN      NaN   NaN   \n",
       "225952    Sachin Baby  Iqbal Abdulla  ...    0.0    NaN      NaN   NaN   \n",
       "225953  Iqbal Abdulla    Sachin Baby  ...    0.0    NaN      NaN   NaN   \n",
       "\n",
       "        legbyes  penalty  wicket_type  player_dismissed other_wicket_type  \\\n",
       "0           NaN      NaN          NaN               NaN               NaN   \n",
       "1           NaN      NaN          NaN               NaN               NaN   \n",
       "2           NaN      NaN          NaN               NaN               NaN   \n",
       "3           NaN      NaN          NaN               NaN               NaN   \n",
       "4           NaN      NaN          NaN               NaN               NaN   \n",
       "...         ...      ...          ...               ...               ...   \n",
       "225949      NaN      NaN          NaN               NaN               NaN   \n",
       "225950      NaN      NaN      run out         CJ Jordan               NaN   \n",
       "225951      1.0      NaN          NaN               NaN               NaN   \n",
       "225952      NaN      NaN          NaN               NaN               NaN   \n",
       "225953      NaN      NaN          NaN               NaN               NaN   \n",
       "\n",
       "       other_player_dismissed  \n",
       "0                         NaN  \n",
       "1                         NaN  \n",
       "2                         NaN  \n",
       "3                         NaN  \n",
       "4                         NaN  \n",
       "...                       ...  \n",
       "225949                    NaN  \n",
       "225950                    NaN  \n",
       "225951                    NaN  \n",
       "225952                    NaN  \n",
       "225953                    NaN  \n",
       "\n",
       "[225954 rows x 22 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.read_excel('D:\\\\PGP IN DATA SCIENCE with Careerera\\\\Files\\\\Ball by Ball Data (2007 - 2022).xlsx')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2e26d54b",
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.options.display.max_columns=50"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a9ee200e",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
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       "</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>season</th>\n",
       "      <th>start_date</th>\n",
       "      <th>venue</th>\n",
       "      <th>innings</th>\n",
       "      <th>ball</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>striker</th>\n",
       "      <th>non_striker</th>\n",
       "      <th>bowler</th>\n",
       "      <th>runs_off_bat</th>\n",
       "      <th>extras</th>\n",
       "      <th>wides</th>\n",
       "      <th>noballs</th>\n",
       "      <th>byes</th>\n",
       "      <th>legbyes</th>\n",
       "      <th>penalty</th>\n",
       "      <th>wicket_type</th>\n",
       "      <th>player_dismissed</th>\n",
       "      <th>other_wicket_type</th>\n",
       "      <th>other_player_dismissed</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>225949</th>\n",
       "      <td>981019.0</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>2016-05-29</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Sachin Baby</td>\n",
       "      <td>CJ Jordan</td>\n",
       "      <td>B Kumar</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>225950</th>\n",
       "      <td>981019.0</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>2016-05-29</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.3</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Sachin Baby</td>\n",
       "      <td>CJ Jordan</td>\n",
       "      <td>B Kumar</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>run out</td>\n",
       "      <td>CJ Jordan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225951</th>\n",
       "      <td>981019.0</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>2016-05-29</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.4</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Iqbal Abdulla</td>\n",
       "      <td>Sachin Baby</td>\n",
       "      <td>B Kumar</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>225952</th>\n",
       "      <td>981019.0</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>2016-05-29</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.5</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Sachin Baby</td>\n",
       "      <td>Iqbal Abdulla</td>\n",
       "      <td>B Kumar</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225953</th>\n",
       "      <td>981019.0</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>2016-05-29</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.6</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Iqbal Abdulla</td>\n",
       "      <td>Sachin Baby</td>\n",
       "      <td>B Kumar</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>225954 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         match_id  season  start_date  \\\n",
       "0       1082591.0  2017.0  2017-04-05   \n",
       "1       1082591.0  2017.0  2017-04-05   \n",
       "2       1082591.0  2017.0  2017-04-05   \n",
       "3       1082591.0  2017.0  2017-04-05   \n",
       "4       1082591.0  2017.0  2017-04-05   \n",
       "...           ...     ...         ...   \n",
       "225949   981019.0  2016.0  2016-05-29   \n",
       "225950   981019.0  2016.0  2016-05-29   \n",
       "225951   981019.0  2016.0  2016-05-29   \n",
       "225952   981019.0  2016.0  2016-05-29   \n",
       "225953   981019.0  2016.0  2016-05-29   \n",
       "\n",
       "                                            venue  innings  ball  \\\n",
       "0       Rajiv Gandhi International Stadium, Uppal      1.0   0.1   \n",
       "1       Rajiv Gandhi International Stadium, Uppal      1.0   0.2   \n",
       "2       Rajiv Gandhi International Stadium, Uppal      1.0   0.3   \n",
       "3       Rajiv Gandhi International Stadium, Uppal      1.0   0.4   \n",
       "4       Rajiv Gandhi International Stadium, Uppal      1.0   0.5   \n",
       "...                                           ...      ...   ...   \n",
       "225949                      M Chinnaswamy Stadium      2.0  19.2   \n",
       "225950                      M Chinnaswamy Stadium      2.0  19.3   \n",
       "225951                      M Chinnaswamy Stadium      2.0  19.4   \n",
       "225952                      M Chinnaswamy Stadium      2.0  19.5   \n",
       "225953                      M Chinnaswamy Stadium      2.0  19.6   \n",
       "\n",
       "                       batting_team                 bowling_team  \\\n",
       "0               Sunrisers Hyderabad  Royal Challengers Bangalore   \n",
       "1               Sunrisers Hyderabad  Royal Challengers Bangalore   \n",
       "2               Sunrisers Hyderabad  Royal Challengers Bangalore   \n",
       "3               Sunrisers Hyderabad  Royal Challengers Bangalore   \n",
       "4               Sunrisers Hyderabad  Royal Challengers Bangalore   \n",
       "...                             ...                          ...   \n",
       "225949  Royal Challengers Bangalore          Sunrisers Hyderabad   \n",
       "225950  Royal Challengers Bangalore          Sunrisers Hyderabad   \n",
       "225951  Royal Challengers Bangalore          Sunrisers Hyderabad   \n",
       "225952  Royal Challengers Bangalore          Sunrisers Hyderabad   \n",
       "225953  Royal Challengers Bangalore          Sunrisers Hyderabad   \n",
       "\n",
       "              striker    non_striker    bowler  runs_off_bat  extras  wides  \\\n",
       "0           DA Warner       S Dhawan  TS Mills           0.0     0.0    NaN   \n",
       "1           DA Warner       S Dhawan  TS Mills           0.0     0.0    NaN   \n",
       "2           DA Warner       S Dhawan  TS Mills           4.0     0.0    NaN   \n",
       "3           DA Warner       S Dhawan  TS Mills           0.0     0.0    NaN   \n",
       "4           DA Warner       S Dhawan  TS Mills           0.0     2.0    2.0   \n",
       "...               ...            ...       ...           ...     ...    ...   \n",
       "225949    Sachin Baby      CJ Jordan   B Kumar           2.0     0.0    NaN   \n",
       "225950    Sachin Baby      CJ Jordan   B Kumar           0.0     0.0    NaN   \n",
       "225951  Iqbal Abdulla    Sachin Baby   B Kumar           0.0     1.0    NaN   \n",
       "225952    Sachin Baby  Iqbal Abdulla   B Kumar           1.0     0.0    NaN   \n",
       "225953  Iqbal Abdulla    Sachin Baby   B Kumar           4.0     0.0    NaN   \n",
       "\n",
       "        noballs  byes  legbyes  penalty wicket_type player_dismissed  \\\n",
       "0           NaN   NaN      NaN      NaN         NaN              NaN   \n",
       "1           NaN   NaN      NaN      NaN         NaN              NaN   \n",
       "2           NaN   NaN      NaN      NaN         NaN              NaN   \n",
       "3           NaN   NaN      NaN      NaN         NaN              NaN   \n",
       "4           NaN   NaN      NaN      NaN         NaN              NaN   \n",
       "...         ...   ...      ...      ...         ...              ...   \n",
       "225949      NaN   NaN      NaN      NaN         NaN              NaN   \n",
       "225950      NaN   NaN      NaN      NaN     run out        CJ Jordan   \n",
       "225951      NaN   NaN      1.0      NaN         NaN              NaN   \n",
       "225952      NaN   NaN      NaN      NaN         NaN              NaN   \n",
       "225953      NaN   NaN      NaN      NaN         NaN              NaN   \n",
       "\n",
       "        other_wicket_type  other_player_dismissed  \n",
       "0                     NaN                     NaN  \n",
       "1                     NaN                     NaN  \n",
       "2                     NaN                     NaN  \n",
       "3                     NaN                     NaN  \n",
       "4                     NaN                     NaN  \n",
       "...                   ...                     ...  \n",
       "225949                NaN                     NaN  \n",
       "225950                NaN                     NaN  \n",
       "225951                NaN                     NaN  \n",
       "225952                NaN                     NaN  \n",
       "225953                NaN                     NaN  \n",
       "\n",
       "[225954 rows x 22 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a78b24e9",
   "metadata": {},
   "source": [
    "# Check how many non_null values present in data set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "142f44c0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 225954 entries, 0 to 225953\n",
      "Data columns (total 22 columns):\n",
      " #   Column                  Non-Null Count   Dtype  \n",
      "---  ------                  --------------   -----  \n",
      " 0   match_id                225954 non-null  float64\n",
      " 1   season                  225954 non-null  object \n",
      " 2   start_date              225954 non-null  object \n",
      " 3   venue                   225954 non-null  object \n",
      " 4   innings                 225954 non-null  float64\n",
      " 5   ball                    225954 non-null  float64\n",
      " 6   batting_team            225954 non-null  object \n",
      " 7   bowling_team            225954 non-null  object \n",
      " 8   striker                 225954 non-null  object \n",
      " 9   non_striker             225954 non-null  object \n",
      " 10  bowler                  225954 non-null  object \n",
      " 11  runs_off_bat            225954 non-null  float64\n",
      " 12  extras                  225954 non-null  float64\n",
      " 13  wides                   7026 non-null    float64\n",
      " 14  noballs                 918 non-null     float64\n",
      " 15  byes                    583 non-null     float64\n",
      " 16  legbyes                 3531 non-null    float64\n",
      " 17  penalty                 2 non-null       float64\n",
      " 18  wicket_type             11151 non-null   object \n",
      " 19  player_dismissed        11151 non-null   object \n",
      " 20  other_wicket_type       0 non-null       float64\n",
      " 21  other_player_dismissed  0 non-null       float64\n",
      "dtypes: float64(12), object(10)\n",
      "memory usage: 37.9+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fceb80f9",
   "metadata": {},
   "source": [
    "# Check how many null values present in data set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "4af524a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "match_id                       0\n",
       "season                         0\n",
       "start_date                     0\n",
       "venue                          0\n",
       "innings                        0\n",
       "ball                           0\n",
       "batting_team                   0\n",
       "bowling_team                   0\n",
       "striker                        0\n",
       "non_striker                    0\n",
       "bowler                         0\n",
       "runs_off_bat                   0\n",
       "extras                         0\n",
       "wides                     218928\n",
       "noballs                   225036\n",
       "byes                      225371\n",
       "legbyes                   222423\n",
       "penalty                   225952\n",
       "wicket_type               214803\n",
       "player_dismissed          214803\n",
       "other_wicket_type         225954\n",
       "other_player_dismissed    225954\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4ad5ff6",
   "metadata": {},
   "source": [
    "# Handling null values"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4027c4e6",
   "metadata": {},
   "source": [
    "# Fill the NAN values in wides columns with appropriate value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f28d4242",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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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>season</th>\n",
       "      <th>start_date</th>\n",
       "      <th>venue</th>\n",
       "      <th>innings</th>\n",
       "      <th>ball</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>striker</th>\n",
       "      <th>non_striker</th>\n",
       "      <th>bowler</th>\n",
       "      <th>runs_off_bat</th>\n",
       "      <th>extras</th>\n",
       "      <th>wides</th>\n",
       "      <th>noballs</th>\n",
       "      <th>byes</th>\n",
       "      <th>legbyes</th>\n",
       "      <th>penalty</th>\n",
       "      <th>wicket_type</th>\n",
       "      <th>player_dismissed</th>\n",
       "      <th>other_wicket_type</th>\n",
       "      <th>other_player_dismissed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    match_id  season  start_date                                      venue  \\\n",
       "0  1082591.0  2017.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "1  1082591.0  2017.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "2  1082591.0  2017.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "3  1082591.0  2017.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "4  1082591.0  2017.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "\n",
       "   innings  ball         batting_team                 bowling_team    striker  \\\n",
       "0      1.0   0.1  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "1      1.0   0.2  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "2      1.0   0.3  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "3      1.0   0.4  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "4      1.0   0.5  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "\n",
       "  non_striker    bowler  runs_off_bat  extras  wides  noballs  byes  legbyes  \\\n",
       "0    S Dhawan  TS Mills           0.0     0.0    0.0      NaN   NaN      NaN   \n",
       "1    S Dhawan  TS Mills           0.0     0.0    0.0      NaN   NaN      NaN   \n",
       "2    S Dhawan  TS Mills           4.0     0.0    0.0      NaN   NaN      NaN   \n",
       "3    S Dhawan  TS Mills           0.0     0.0    0.0      NaN   NaN      NaN   \n",
       "4    S Dhawan  TS Mills           0.0     2.0    2.0      NaN   NaN      NaN   \n",
       "\n",
       "   penalty wicket_type player_dismissed  other_wicket_type  \\\n",
       "0      NaN         NaN              NaN                NaN   \n",
       "1      NaN         NaN              NaN                NaN   \n",
       "2      NaN         NaN              NaN                NaN   \n",
       "3      NaN         NaN              NaN                NaN   \n",
       "4      NaN         NaN              NaN                NaN   \n",
       "\n",
       "   other_player_dismissed  \n",
       "0                     NaN  \n",
       "1                     NaN  \n",
       "2                     NaN  \n",
       "3                     NaN  \n",
       "4                     NaN  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.wides.fillna(0.0, inplace=True)\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b11ec71f",
   "metadata": {},
   "source": [
    "# Fill the NAN values in no-balls columns with appropriate value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b77e5cb2",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>extras</th>\n",
       "      <th>wides</th>\n",
       "      <th>noballs</th>\n",
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       "      <th>legbyes</th>\n",
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       "      <th>0</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    match_id  season  start_date                                      venue  \\\n",
       "0  1082591.0  2017.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "1  1082591.0  2017.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "2  1082591.0  2017.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "3  1082591.0  2017.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "4  1082591.0  2017.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "\n",
       "   innings  ball         batting_team                 bowling_team    striker  \\\n",
       "0      1.0   0.1  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "1      1.0   0.2  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "2      1.0   0.3  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "3      1.0   0.4  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "4      1.0   0.5  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "\n",
       "  non_striker    bowler  runs_off_bat  extras  wides  noballs  byes  legbyes  \\\n",
       "0    S Dhawan  TS Mills           0.0     0.0    0.0      0.0   NaN      NaN   \n",
       "1    S Dhawan  TS Mills           0.0     0.0    0.0      0.0   NaN      NaN   \n",
       "2    S Dhawan  TS Mills           4.0     0.0    0.0      0.0   NaN      NaN   \n",
       "3    S Dhawan  TS Mills           0.0     0.0    0.0      0.0   NaN      NaN   \n",
       "4    S Dhawan  TS Mills           0.0     2.0    2.0      0.0   NaN      NaN   \n",
       "\n",
       "   penalty wicket_type player_dismissed  other_wicket_type  \\\n",
       "0      NaN         NaN              NaN                NaN   \n",
       "1      NaN         NaN              NaN                NaN   \n",
       "2      NaN         NaN              NaN                NaN   \n",
       "3      NaN         NaN              NaN                NaN   \n",
       "4      NaN         NaN              NaN                NaN   \n",
       "\n",
       "   other_player_dismissed  \n",
       "0                     NaN  \n",
       "1                     NaN  \n",
       "2                     NaN  \n",
       "3                     NaN  \n",
       "4                     NaN  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.noballs.fillna(0.0, inplace=True)\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a59e6d0",
   "metadata": {},
   "source": [
    "# Fill the NAN values in byes columns with appropriate value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "363e2429",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>match_id</th>\n",
       "      <th>season</th>\n",
       "      <th>start_date</th>\n",
       "      <th>venue</th>\n",
       "      <th>innings</th>\n",
       "      <th>ball</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
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       "      <th>non_striker</th>\n",
       "      <th>bowler</th>\n",
       "      <th>runs_off_bat</th>\n",
       "      <th>extras</th>\n",
       "      <th>wides</th>\n",
       "      <th>noballs</th>\n",
       "      <th>byes</th>\n",
       "      <th>legbyes</th>\n",
       "      <th>penalty</th>\n",
       "      <th>wicket_type</th>\n",
       "      <th>player_dismissed</th>\n",
       "      <th>other_wicket_type</th>\n",
       "      <th>other_player_dismissed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    match_id  season  start_date                                      venue  \\\n",
       "0  1082591.0  2017.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "1  1082591.0  2017.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "2  1082591.0  2017.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "3  1082591.0  2017.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "4  1082591.0  2017.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "\n",
       "   innings  ball         batting_team                 bowling_team    striker  \\\n",
       "0      1.0   0.1  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "1      1.0   0.2  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "2      1.0   0.3  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "3      1.0   0.4  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "4      1.0   0.5  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "\n",
       "  non_striker    bowler  runs_off_bat  extras  wides  noballs  byes  legbyes  \\\n",
       "0    S Dhawan  TS Mills           0.0     0.0    0.0      0.0   0.0      NaN   \n",
       "1    S Dhawan  TS Mills           0.0     0.0    0.0      0.0   0.0      NaN   \n",
       "2    S Dhawan  TS Mills           4.0     0.0    0.0      0.0   0.0      NaN   \n",
       "3    S Dhawan  TS Mills           0.0     0.0    0.0      0.0   0.0      NaN   \n",
       "4    S Dhawan  TS Mills           0.0     2.0    2.0      0.0   0.0      NaN   \n",
       "\n",
       "   penalty wicket_type player_dismissed  other_wicket_type  \\\n",
       "0      NaN         NaN              NaN                NaN   \n",
       "1      NaN         NaN              NaN                NaN   \n",
       "2      NaN         NaN              NaN                NaN   \n",
       "3      NaN         NaN              NaN                NaN   \n",
       "4      NaN         NaN              NaN                NaN   \n",
       "\n",
       "   other_player_dismissed  \n",
       "0                     NaN  \n",
       "1                     NaN  \n",
       "2                     NaN  \n",
       "3                     NaN  \n",
       "4                     NaN  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.byes.fillna(0.0, inplace=True)\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cdb86d25",
   "metadata": {},
   "source": [
    "# Fill the NAN values in legbyes columns with appropriate value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6af99744",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>byes</th>\n",
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       "      <th>other_player_dismissed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    match_id  season  start_date                                      venue  \\\n",
       "0  1082591.0  2017.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "1  1082591.0  2017.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "2  1082591.0  2017.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "3  1082591.0  2017.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "4  1082591.0  2017.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "\n",
       "   innings  ball         batting_team                 bowling_team    striker  \\\n",
       "0      1.0   0.1  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "1      1.0   0.2  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "2      1.0   0.3  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "3      1.0   0.4  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "4      1.0   0.5  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "\n",
       "  non_striker    bowler  runs_off_bat  extras  wides  noballs  byes  legbyes  \\\n",
       "0    S Dhawan  TS Mills           0.0     0.0    0.0      0.0   0.0      0.0   \n",
       "1    S Dhawan  TS Mills           0.0     0.0    0.0      0.0   0.0      0.0   \n",
       "2    S Dhawan  TS Mills           4.0     0.0    0.0      0.0   0.0      0.0   \n",
       "3    S Dhawan  TS Mills           0.0     0.0    0.0      0.0   0.0      0.0   \n",
       "4    S Dhawan  TS Mills           0.0     2.0    2.0      0.0   0.0      0.0   \n",
       "\n",
       "   penalty wicket_type player_dismissed  other_wicket_type  \\\n",
       "0      NaN         NaN              NaN                NaN   \n",
       "1      NaN         NaN              NaN                NaN   \n",
       "2      NaN         NaN              NaN                NaN   \n",
       "3      NaN         NaN              NaN                NaN   \n",
       "4      NaN         NaN              NaN                NaN   \n",
       "\n",
       "   other_player_dismissed  \n",
       "0                     NaN  \n",
       "1                     NaN  \n",
       "2                     NaN  \n",
       "3                     NaN  \n",
       "4                     NaN  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.legbyes.fillna(0.0, inplace=True)\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "587e216b",
   "metadata": {},
   "source": [
    "# Fill the NAN values in penalty columns with appropriate value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "5ae77c78",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>match_id</th>\n",
       "      <th>season</th>\n",
       "      <th>start_date</th>\n",
       "      <th>venue</th>\n",
       "      <th>innings</th>\n",
       "      <th>ball</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
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       "      <th>non_striker</th>\n",
       "      <th>bowler</th>\n",
       "      <th>runs_off_bat</th>\n",
       "      <th>extras</th>\n",
       "      <th>wides</th>\n",
       "      <th>noballs</th>\n",
       "      <th>byes</th>\n",
       "      <th>legbyes</th>\n",
       "      <th>penalty</th>\n",
       "      <th>wicket_type</th>\n",
       "      <th>player_dismissed</th>\n",
       "      <th>other_wicket_type</th>\n",
       "      <th>other_player_dismissed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</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  season  start_date                                      venue  \\\n",
       "0  1082591.0  2017.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "1  1082591.0  2017.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "2  1082591.0  2017.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "3  1082591.0  2017.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "4  1082591.0  2017.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "\n",
       "   innings  ball         batting_team                 bowling_team    striker  \\\n",
       "0      1.0   0.1  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "1      1.0   0.2  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "2      1.0   0.3  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "3      1.0   0.4  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "4      1.0   0.5  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "\n",
       "  non_striker    bowler  runs_off_bat  extras  wides  noballs  byes  legbyes  \\\n",
       "0    S Dhawan  TS Mills           0.0     0.0    0.0      0.0   0.0      0.0   \n",
       "1    S Dhawan  TS Mills           0.0     0.0    0.0      0.0   0.0      0.0   \n",
       "2    S Dhawan  TS Mills           4.0     0.0    0.0      0.0   0.0      0.0   \n",
       "3    S Dhawan  TS Mills           0.0     0.0    0.0      0.0   0.0      0.0   \n",
       "4    S Dhawan  TS Mills           0.0     2.0    2.0      0.0   0.0      0.0   \n",
       "\n",
       "   penalty wicket_type player_dismissed  other_wicket_type  \\\n",
       "0      0.0         NaN              NaN                NaN   \n",
       "1      0.0         NaN              NaN                NaN   \n",
       "2      0.0         NaN              NaN                NaN   \n",
       "3      0.0         NaN              NaN                NaN   \n",
       "4      0.0         NaN              NaN                NaN   \n",
       "\n",
       "   other_player_dismissed  \n",
       "0                     NaN  \n",
       "1                     NaN  \n",
       "2                     NaN  \n",
       "3                     NaN  \n",
       "4                     NaN  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.penalty.fillna(0.0, inplace=True)\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d291c66",
   "metadata": {},
   "source": [
    "# Check how many years of data we have"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f3b89853",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2017.0, 2018.0, 2019.0, '2020/21', 2021.0, 2022.0, '2007/08',\n",
       "       2009.0, '2009/10', 2011.0, 2012.0, 2013.0, 2014.0, 2015.0, 2016.0],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.season.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ecc1a69",
   "metadata": {},
   "source": [
    "# For better understanding remove season column and add year column by extracting it from start_date column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "57bd22b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
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       "      <th>runs_off_bat</th>\n",
       "      <th>extras</th>\n",
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       "      <th>other_player_dismissed</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1082591.0</td>\n",
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       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    match_id  start_date                                      venue  innings  \\\n",
       "0  1082591.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal      1.0   \n",
       "1  1082591.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal      1.0   \n",
       "2  1082591.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal      1.0   \n",
       "3  1082591.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal      1.0   \n",
       "4  1082591.0  2017-04-05  Rajiv Gandhi International Stadium, Uppal      1.0   \n",
       "\n",
       "   ball         batting_team                 bowling_team    striker  \\\n",
       "0   0.1  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "1   0.2  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "2   0.3  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "3   0.4  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "4   0.5  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "\n",
       "  non_striker    bowler  runs_off_bat  extras  wides  noballs  byes  legbyes  \\\n",
       "0    S Dhawan  TS Mills           0.0     0.0    0.0      0.0   0.0      0.0   \n",
       "1    S Dhawan  TS Mills           0.0     0.0    0.0      0.0   0.0      0.0   \n",
       "2    S Dhawan  TS Mills           4.0     0.0    0.0      0.0   0.0      0.0   \n",
       "3    S Dhawan  TS Mills           0.0     0.0    0.0      0.0   0.0      0.0   \n",
       "4    S Dhawan  TS Mills           0.0     2.0    2.0      0.0   0.0      0.0   \n",
       "\n",
       "   penalty wicket_type player_dismissed  other_wicket_type  \\\n",
       "0      0.0         NaN              NaN                NaN   \n",
       "1      0.0         NaN              NaN                NaN   \n",
       "2      0.0         NaN              NaN                NaN   \n",
       "3      0.0         NaN              NaN                NaN   \n",
       "4      0.0         NaN              NaN                NaN   \n",
       "\n",
       "   other_player_dismissed  \n",
       "0                     NaN  \n",
       "1                     NaN  \n",
       "2                     NaN  \n",
       "3                     NaN  \n",
       "4                     NaN  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.drop('season', axis=1, inplace=True)\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "1ff7a725",
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"start_date\"] = pd.to_datetime(df[\"start_date\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "80607ccc",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>match_id</th>\n",
       "      <th>year</th>\n",
       "      <th>start_date</th>\n",
       "      <th>venue</th>\n",
       "      <th>innings</th>\n",
       "      <th>ball</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>striker</th>\n",
       "      <th>non_striker</th>\n",
       "      <th>bowler</th>\n",
       "      <th>runs_off_bat</th>\n",
       "      <th>extras</th>\n",
       "      <th>wides</th>\n",
       "      <th>noballs</th>\n",
       "      <th>byes</th>\n",
       "      <th>legbyes</th>\n",
       "      <th>penalty</th>\n",
       "      <th>wicket_type</th>\n",
       "      <th>player_dismissed</th>\n",
       "      <th>other_wicket_type</th>\n",
       "      <th>other_player_dismissed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225949</th>\n",
       "      <td>981019.0</td>\n",
       "      <td>2016</td>\n",
       "      <td>2016-05-29</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Sachin Baby</td>\n",
       "      <td>CJ Jordan</td>\n",
       "      <td>B Kumar</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225950</th>\n",
       "      <td>981019.0</td>\n",
       "      <td>2016</td>\n",
       "      <td>2016-05-29</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.3</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Sachin Baby</td>\n",
       "      <td>CJ Jordan</td>\n",
       "      <td>B Kumar</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>run out</td>\n",
       "      <td>CJ Jordan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225951</th>\n",
       "      <td>981019.0</td>\n",
       "      <td>2016</td>\n",
       "      <td>2016-05-29</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.4</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Iqbal Abdulla</td>\n",
       "      <td>Sachin Baby</td>\n",
       "      <td>B Kumar</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225952</th>\n",
       "      <td>981019.0</td>\n",
       "      <td>2016</td>\n",
       "      <td>2016-05-29</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.5</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Sachin Baby</td>\n",
       "      <td>Iqbal Abdulla</td>\n",
       "      <td>B Kumar</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225953</th>\n",
       "      <td>981019.0</td>\n",
       "      <td>2016</td>\n",
       "      <td>2016-05-29</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.6</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Iqbal Abdulla</td>\n",
       "      <td>Sachin Baby</td>\n",
       "      <td>B Kumar</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>225954 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         match_id  year start_date                                      venue  \\\n",
       "0       1082591.0  2017 2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "1       1082591.0  2017 2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "2       1082591.0  2017 2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "3       1082591.0  2017 2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "4       1082591.0  2017 2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "...           ...   ...        ...                                        ...   \n",
       "225949   981019.0  2016 2016-05-29                      M Chinnaswamy Stadium   \n",
       "225950   981019.0  2016 2016-05-29                      M Chinnaswamy Stadium   \n",
       "225951   981019.0  2016 2016-05-29                      M Chinnaswamy Stadium   \n",
       "225952   981019.0  2016 2016-05-29                      M Chinnaswamy Stadium   \n",
       "225953   981019.0  2016 2016-05-29                      M Chinnaswamy Stadium   \n",
       "\n",
       "        innings  ball                 batting_team  \\\n",
       "0           1.0   0.1          Sunrisers Hyderabad   \n",
       "1           1.0   0.2          Sunrisers Hyderabad   \n",
       "2           1.0   0.3          Sunrisers Hyderabad   \n",
       "3           1.0   0.4          Sunrisers Hyderabad   \n",
       "4           1.0   0.5          Sunrisers Hyderabad   \n",
       "...         ...   ...                          ...   \n",
       "225949      2.0  19.2  Royal Challengers Bangalore   \n",
       "225950      2.0  19.3  Royal Challengers Bangalore   \n",
       "225951      2.0  19.4  Royal Challengers Bangalore   \n",
       "225952      2.0  19.5  Royal Challengers Bangalore   \n",
       "225953      2.0  19.6  Royal Challengers Bangalore   \n",
       "\n",
       "                       bowling_team        striker    non_striker    bowler  \\\n",
       "0       Royal Challengers Bangalore      DA Warner       S Dhawan  TS Mills   \n",
       "1       Royal Challengers Bangalore      DA Warner       S Dhawan  TS Mills   \n",
       "2       Royal Challengers Bangalore      DA Warner       S Dhawan  TS Mills   \n",
       "3       Royal Challengers Bangalore      DA Warner       S Dhawan  TS Mills   \n",
       "4       Royal Challengers Bangalore      DA Warner       S Dhawan  TS Mills   \n",
       "...                             ...            ...            ...       ...   \n",
       "225949          Sunrisers Hyderabad    Sachin Baby      CJ Jordan   B Kumar   \n",
       "225950          Sunrisers Hyderabad    Sachin Baby      CJ Jordan   B Kumar   \n",
       "225951          Sunrisers Hyderabad  Iqbal Abdulla    Sachin Baby   B Kumar   \n",
       "225952          Sunrisers Hyderabad    Sachin Baby  Iqbal Abdulla   B Kumar   \n",
       "225953          Sunrisers Hyderabad  Iqbal Abdulla    Sachin Baby   B Kumar   \n",
       "\n",
       "        runs_off_bat  extras  wides  noballs  byes  legbyes  penalty  \\\n",
       "0                0.0     0.0    0.0      0.0   0.0      0.0      0.0   \n",
       "1                0.0     0.0    0.0      0.0   0.0      0.0      0.0   \n",
       "2                4.0     0.0    0.0      0.0   0.0      0.0      0.0   \n",
       "3                0.0     0.0    0.0      0.0   0.0      0.0      0.0   \n",
       "4                0.0     2.0    2.0      0.0   0.0      0.0      0.0   \n",
       "...              ...     ...    ...      ...   ...      ...      ...   \n",
       "225949           2.0     0.0    0.0      0.0   0.0      0.0      0.0   \n",
       "225950           0.0     0.0    0.0      0.0   0.0      0.0      0.0   \n",
       "225951           0.0     1.0    0.0      0.0   0.0      1.0      0.0   \n",
       "225952           1.0     0.0    0.0      0.0   0.0      0.0      0.0   \n",
       "225953           4.0     0.0    0.0      0.0   0.0      0.0      0.0   \n",
       "\n",
       "       wicket_type player_dismissed  other_wicket_type  other_player_dismissed  \n",
       "0              NaN              NaN                NaN                     NaN  \n",
       "1              NaN              NaN                NaN                     NaN  \n",
       "2              NaN              NaN                NaN                     NaN  \n",
       "3              NaN              NaN                NaN                     NaN  \n",
       "4              NaN              NaN                NaN                     NaN  \n",
       "...            ...              ...                ...                     ...  \n",
       "225949         NaN              NaN                NaN                     NaN  \n",
       "225950     run out        CJ Jordan                NaN                     NaN  \n",
       "225951         NaN              NaN                NaN                     NaN  \n",
       "225952         NaN              NaN                NaN                     NaN  \n",
       "225953         NaN              NaN                NaN                     NaN  \n",
       "\n",
       "[225954 rows x 22 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.insert(1, 'year', df['start_date'].dt.year)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d56eafb",
   "metadata": {},
   "source": [
    "# Now check how many years of data we have"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "2d69ea8e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2017, 2018, 2019, 2020, 2021, 2022, 2008, 2009, 2010, 2011, 2012,\n",
       "       2013, 2014, 2015, 2016], dtype=int64)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.year.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "68c3ce09",
   "metadata": {},
   "source": [
    "# Analyzation of data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "86bd4dee",
   "metadata": {},
   "source": [
    "## Check who is the highest run scorer in all IPL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "78c74294",
   "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>runs_off_bat</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>striker</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>V Kohli</th>\n",
       "      <td>6634.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S Dhawan</th>\n",
       "      <td>6244.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DA Warner</th>\n",
       "      <td>5883.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RG Sharma</th>\n",
       "      <td>5881.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SK Raina</th>\n",
       "      <td>5536.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AB de Villiers</th>\n",
       "      <td>5181.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CH Gayle</th>\n",
       "      <td>4997.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MS Dhoni</th>\n",
       "      <td>4978.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RV Uthappa</th>\n",
       "      <td>4954.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KD Karthik</th>\n",
       "      <td>4377.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                runs_off_bat\n",
       "striker                     \n",
       "V Kohli               6634.0\n",
       "S Dhawan              6244.0\n",
       "DA Warner             5883.0\n",
       "RG Sharma             5881.0\n",
       "SK Raina              5536.0\n",
       "AB de Villiers        5181.0\n",
       "CH Gayle              4997.0\n",
       "MS Dhoni              4978.0\n",
       "RV Uthappa            4954.0\n",
       "KD Karthik            4377.0"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.pivot_table(df, index='striker', values='runs_off_bat', aggfunc=sum).sort_values(by='runs_off_bat', ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "7f904780",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "sns.barplot(x='striker', y='runs_off_bat', data=df, estimator=sum, ci=None,\n",
    "           order=df.groupby('striker').runs_off_bat.sum().sort_values(ascending=False)[:10].index)\n",
    "plt.xlabel('Player', fontsize=15)\n",
    "plt.ylabel('Total runs', fontsize=15)\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad64af49",
   "metadata": {},
   "source": [
    "# Check which player's score is highest in single year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "36871ba1",
   "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></th>\n",
       "      <th>runs_off_bat</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th>striker</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <th>V Kohli</th>\n",
       "      <td>973.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022</th>\n",
       "      <th>JC Buttler</th>\n",
       "      <td>863.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <th>DA Warner</th>\n",
       "      <td>848.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <th>KS Williamson</th>\n",
       "      <td>735.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <th>MEK Hussey</th>\n",
       "      <td>733.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <th>CH Gayle</th>\n",
       "      <td>733.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <th>CH Gayle</th>\n",
       "      <td>720.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <th>DA Warner</th>\n",
       "      <td>692.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <th>AB de Villiers</th>\n",
       "      <td>687.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <th>RR Pant</th>\n",
       "      <td>684.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     runs_off_bat\n",
       "year striker                     \n",
       "2016 V Kohli                973.0\n",
       "2022 JC Buttler             863.0\n",
       "2016 DA Warner              848.0\n",
       "2018 KS Williamson          735.0\n",
       "2013 MEK Hussey             733.0\n",
       "2012 CH Gayle               733.0\n",
       "2013 CH Gayle               720.0\n",
       "2019 DA Warner              692.0\n",
       "2016 AB de Villiers         687.0\n",
       "2018 RR Pant                684.0"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.pivot_table(df, index=['year', 'striker'], values='runs_off_bat', aggfunc=sum).sort_values(by='runs_off_bat', ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57e65ee1",
   "metadata": {},
   "source": [
    "## which bowler bowled more wides in entire IPL seasons"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "f2a67703",
   "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>wides</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bowler</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>DJ Bravo</th>\n",
       "      <td>173.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SL Malinga</th>\n",
       "      <td>152.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>P Kumar</th>\n",
       "      <td>144.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R Ashwin</th>\n",
       "      <td>143.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B Kumar</th>\n",
       "      <td>142.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UT Yadav</th>\n",
       "      <td>117.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DW Steyn</th>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mohammed Shami</th>\n",
       "      <td>109.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SN Thakur</th>\n",
       "      <td>104.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DS Kulkarni</th>\n",
       "      <td>103.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                wides\n",
       "bowler               \n",
       "DJ Bravo        173.0\n",
       "SL Malinga      152.0\n",
       "P Kumar         144.0\n",
       "R Ashwin        143.0\n",
       "B Kumar         142.0\n",
       "UT Yadav        117.0\n",
       "DW Steyn        110.0\n",
       "Mohammed Shami  109.0\n",
       "SN Thakur       104.0\n",
       "DS Kulkarni     103.0"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.pivot_table(df, index='bowler', values='wides', aggfunc=sum).sort_values(by='wides', ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "376c0d45",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "sns.barplot(x='bowler', y='wides', data=df, estimator=sum, ci=None,\n",
    "           order=df.groupby('bowler').wides.sum().sort_values(ascending=False)[:10].index)\n",
    "plt.xlabel('Bowler Name', fontsize=15)\n",
    "plt.ylabel('Total Wides bowled', fontsize=15)\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b5c6680",
   "metadata": {},
   "source": [
    "## which bowler bowled more no-balls in entire IPL seasons"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "2a8feaae",
   "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>noballs</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bowler</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>JJ Bumrah</th>\n",
       "      <td>30.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S Sreesanth</th>\n",
       "      <td>27.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UT Yadav</th>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>I Sharma</th>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A Mishra</th>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SL Malinga</th>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JA Morkel</th>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M Prasidh Krishna</th>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AB Dinda</th>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SW Tait</th>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   noballs\n",
       "bowler                    \n",
       "JJ Bumrah             30.0\n",
       "S Sreesanth           27.0\n",
       "UT Yadav              25.0\n",
       "I Sharma              21.0\n",
       "A Mishra              21.0\n",
       "SL Malinga            20.0\n",
       "JA Morkel             18.0\n",
       "M Prasidh Krishna     17.0\n",
       "AB Dinda              14.0\n",
       "SW Tait               14.0"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.pivot_table(df, index='bowler', values='noballs', aggfunc=sum).sort_values(by='noballs', ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "77fb899e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "sns.barplot(x='bowler', y='noballs', data=df, estimator=sum, ci=None,\n",
    "           order=df.groupby('bowler').noballs.sum().sort_values(ascending=False)[:10].index)\n",
    "plt.xlabel('Bowler Name', fontsize=15)\n",
    "plt.ylabel('Total no-balls bowled', fontsize=15)\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3329b6dc",
   "metadata": {},
   "source": [
    "## What are the wicket types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "a9fb6356",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan, 'caught', 'bowled', 'run out', 'lbw', 'caught and bowled',\n",
       "       'stumped', 'retired hurt', 'hit wicket', 'obstructing the field',\n",
       "       'retired out'], dtype=object)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.wicket_type.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "28e01b59",
   "metadata": {},
   "source": [
    "## Which is most common wicket type in entire IPL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "22ee4304",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "caught                   6837\n",
       "bowled                   1944\n",
       "run out                  1007\n",
       "lbw                       685\n",
       "stumped                   325\n",
       "caught and bowled         323\n",
       "hit wicket                 14\n",
       "retired hurt               13\n",
       "obstructing the field       2\n",
       "retired out                 1\n",
       "Name: wicket_type, dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.wicket_type.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "942eed45",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fb0e1dfe",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "fa820883",
   "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>balls_per_over</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>gender</th>\n",
       "      <th>season</th>\n",
       "      <th>date</th>\n",
       "      <th>event</th>\n",
       "      <th>match_number</th>\n",
       "      <th>venue</th>\n",
       "      <th>city</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "      <th>reserve_umpire</th>\n",
       "      <th>tv_umpire</th>\n",
       "      <th>match_referee</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by</th>\n",
       "      <th>match_id</th>\n",
       "      <th>winner_type</th>\n",
       "      <th>date1</th>\n",
       "      <th>date2</th>\n",
       "      <th>method</th>\n",
       "      <th>outcome</th>\n",
       "      <th>eliminator</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>male</td>\n",
       "      <td>2014</td>\n",
       "      <td>2014/05/23</td>\n",
       "      <td>Indian Premier League</td>\n",
       "      <td>52.0</td>\n",
       "      <td>Punjab Cricket Association Stadium, Mohali</td>\n",
       "      <td>Chandigarh</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>SE Marsh</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>PG Pathak</td>\n",
       "      <td>UV Gandhe</td>\n",
       "      <td>VA Kulkarni</td>\n",
       "      <td>RS Mahanama</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>16.0</td>\n",
       "      <td>734033</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>male</td>\n",
       "      <td>2015</td>\n",
       "      <td>2015/04/19</td>\n",
       "      <td>Indian Premier League</td>\n",
       "      <td>15.0</td>\n",
       "      <td>Sardar Patel Stadium, Motera</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>AM Rahane</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>K Srinivasan</td>\n",
       "      <td>K Srinath</td>\n",
       "      <td>Chinmay Sharma</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>8.0</td>\n",
       "      <td>829735</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>male</td>\n",
       "      <td>2015</td>\n",
       "      <td>2015/04/24</td>\n",
       "      <td>Indian Premier League</td>\n",
       "      <td>22.0</td>\n",
       "      <td>Sardar Patel Stadium, Motera</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>MA Starc</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>K Srinath</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>Chinmay Sharma</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>9.0</td>\n",
       "      <td>829749</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>male</td>\n",
       "      <td>2015</td>\n",
       "      <td>2015/04/11</td>\n",
       "      <td>Indian Premier League</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>CH Gayle</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>VK Sharma</td>\n",
       "      <td>PG Pathak</td>\n",
       "      <td>J Srinath</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>3.0</td>\n",
       "      <td>829713</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>male</td>\n",
       "      <td>2015</td>\n",
       "      <td>2015/04/08</td>\n",
       "      <td>Indian Premier League</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>M Morkel</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>VK Sharma</td>\n",
       "      <td>PG Pathak</td>\n",
       "      <td>J Srinath</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>7.0</td>\n",
       "      <td>829705</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   balls_per_over                  team1                        team2 gender  \\\n",
       "0               6        Kings XI Punjab             Rajasthan Royals   male   \n",
       "1               6       Rajasthan Royals          Chennai Super Kings   male   \n",
       "2               6       Rajasthan Royals  Royal Challengers Bangalore   male   \n",
       "3               6  Kolkata Knight Riders  Royal Challengers Bangalore   male   \n",
       "4               6  Kolkata Knight Riders               Mumbai Indians   male   \n",
       "\n",
       "  season        date                  event  match_number  \\\n",
       "0   2014  2014/05/23  Indian Premier League          52.0   \n",
       "1   2015  2015/04/19  Indian Premier League          15.0   \n",
       "2   2015  2015/04/24  Indian Premier League          22.0   \n",
       "3   2015  2015/04/11  Indian Premier League           5.0   \n",
       "4   2015  2015/04/08  Indian Premier League           1.0   \n",
       "\n",
       "                                        venue        city  \\\n",
       "0  Punjab Cricket Association Stadium, Mohali  Chandigarh   \n",
       "1                Sardar Patel Stadium, Motera   Ahmedabad   \n",
       "2                Sardar Patel Stadium, Motera   Ahmedabad   \n",
       "3                                Eden Gardens     Kolkata   \n",
       "4                                Eden Gardens     Kolkata   \n",
       "\n",
       "                   toss_winner toss_decision player_of_match          umpire1  \\\n",
       "0             Rajasthan Royals         field        SE Marsh  HDPK Dharmasena   \n",
       "1          Chennai Super Kings           bat       AM Rahane     AK Chaudhary   \n",
       "2  Royal Challengers Bangalore         field        MA Starc        M Erasmus   \n",
       "3  Royal Challengers Bangalore         field        CH Gayle           S Ravi   \n",
       "4        Kolkata Knight Riders         field        M Morkel           S Ravi   \n",
       "\n",
       "         umpire2 reserve_umpire     tv_umpire   match_referee  \\\n",
       "0      PG Pathak      UV Gandhe   VA Kulkarni     RS Mahanama   \n",
       "1      M Erasmus   K Srinivasan     K Srinath  Chinmay Sharma   \n",
       "2         S Ravi      K Srinath  AK Chaudhary  Chinmay Sharma   \n",
       "3  C Shamshuddin      VK Sharma     PG Pathak       J Srinath   \n",
       "4  C Shamshuddin      VK Sharma     PG Pathak       J Srinath   \n",
       "\n",
       "                        winner  win_by  match_id winner_type date1 date2  \\\n",
       "0              Kings XI Punjab    16.0    734033        runs   NaN   NaN   \n",
       "1             Rajasthan Royals     8.0    829735     wickets   NaN   NaN   \n",
       "2  Royal Challengers Bangalore     9.0    829749     wickets   NaN   NaN   \n",
       "3  Royal Challengers Bangalore     3.0    829713     wickets   NaN   NaN   \n",
       "4        Kolkata Knight Riders     7.0    829705     wickets   NaN   NaN   \n",
       "\n",
       "  method outcome eliminator  \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  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1=pd.read_csv('D:\\\\PGP IN DATA SCIENCE with Careerera\\\\Files\\\\Match Details (2007 - 2022).csv')\n",
    "df1.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "4af8f7c5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 950 entries, 0 to 949\n",
      "Data columns (total 27 columns):\n",
      " #   Column           Non-Null Count  Dtype  \n",
      "---  ------           --------------  -----  \n",
      " 0   balls_per_over   950 non-null    int64  \n",
      " 1   team1            950 non-null    object \n",
      " 2   team2            950 non-null    object \n",
      " 3   gender           950 non-null    object \n",
      " 4   season           950 non-null    object \n",
      " 5   date             948 non-null    object \n",
      " 6   event            950 non-null    object \n",
      " 7   match_number     892 non-null    float64\n",
      " 8   venue            950 non-null    object \n",
      " 9   city             899 non-null    object \n",
      " 10  toss_winner      950 non-null    object \n",
      " 11  toss_decision    950 non-null    object \n",
      " 12  player_of_match  946 non-null    object \n",
      " 13  umpire1          950 non-null    object \n",
      " 14  umpire2          950 non-null    object \n",
      " 15  reserve_umpire   926 non-null    object \n",
      " 16  tv_umpire        947 non-null    object \n",
      " 17  match_referee    950 non-null    object \n",
      " 18  winner           932 non-null    object \n",
      " 19  win_by           932 non-null    float64\n",
      " 20  match_id         950 non-null    int64  \n",
      " 21  winner_type      932 non-null    object \n",
      " 22  date1            2 non-null      object \n",
      " 23  date2            2 non-null      object \n",
      " 24  method           19 non-null     object \n",
      " 25  outcome          18 non-null     object \n",
      " 26  eliminator       14 non-null     object \n",
      "dtypes: float64(2), int64(2), object(23)\n",
      "memory usage: 200.5+ KB\n"
     ]
    }
   ],
   "source": [
    "df1.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "b817cffe",
   "metadata": {},
   "outputs": [],
   "source": [
    "df1[\"date\"] = pd.to_datetime(df1[\"date\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "7d4987a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "df1.drop('season', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "af7374cf",
   "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",
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       "    .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>balls_per_over</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>gender</th>\n",
       "      <th>year</th>\n",
       "      <th>date</th>\n",
       "      <th>event</th>\n",
       "      <th>match_number</th>\n",
       "      <th>venue</th>\n",
       "      <th>city</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "      <th>reserve_umpire</th>\n",
       "      <th>tv_umpire</th>\n",
       "      <th>match_referee</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by</th>\n",
       "      <th>match_id</th>\n",
       "      <th>winner_type</th>\n",
       "      <th>date1</th>\n",
       "      <th>date2</th>\n",
       "      <th>method</th>\n",
       "      <th>outcome</th>\n",
       "      <th>eliminator</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>male</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>2014-05-23</td>\n",
       "      <td>Indian Premier League</td>\n",
       "      <td>52.0</td>\n",
       "      <td>Punjab Cricket Association Stadium, Mohali</td>\n",
       "      <td>Chandigarh</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>SE Marsh</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>PG Pathak</td>\n",
       "      <td>UV Gandhe</td>\n",
       "      <td>VA Kulkarni</td>\n",
       "      <td>RS Mahanama</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>16.0</td>\n",
       "      <td>734033</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>male</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>2015-04-19</td>\n",
       "      <td>Indian Premier League</td>\n",
       "      <td>15.0</td>\n",
       "      <td>Sardar Patel Stadium, Motera</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>AM Rahane</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>K Srinivasan</td>\n",
       "      <td>K Srinath</td>\n",
       "      <td>Chinmay Sharma</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>8.0</td>\n",
       "      <td>829735</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>male</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>2015-04-24</td>\n",
       "      <td>Indian Premier League</td>\n",
       "      <td>22.0</td>\n",
       "      <td>Sardar Patel Stadium, Motera</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>MA Starc</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>K Srinath</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>Chinmay Sharma</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>9.0</td>\n",
       "      <td>829749</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>male</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>2015-04-11</td>\n",
       "      <td>Indian Premier League</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>CH Gayle</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>VK Sharma</td>\n",
       "      <td>PG Pathak</td>\n",
       "      <td>J Srinath</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>3.0</td>\n",
       "      <td>829713</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>male</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>2015-04-08</td>\n",
       "      <td>Indian Premier League</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>M Morkel</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>VK Sharma</td>\n",
       "      <td>PG Pathak</td>\n",
       "      <td>J Srinath</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>7.0</td>\n",
       "      <td>829705</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   balls_per_over                  team1                        team2 gender  \\\n",
       "0               6        Kings XI Punjab             Rajasthan Royals   male   \n",
       "1               6       Rajasthan Royals          Chennai Super Kings   male   \n",
       "2               6       Rajasthan Royals  Royal Challengers Bangalore   male   \n",
       "3               6  Kolkata Knight Riders  Royal Challengers Bangalore   male   \n",
       "4               6  Kolkata Knight Riders               Mumbai Indians   male   \n",
       "\n",
       "     year       date                  event  match_number  \\\n",
       "0  2014.0 2014-05-23  Indian Premier League          52.0   \n",
       "1  2015.0 2015-04-19  Indian Premier League          15.0   \n",
       "2  2015.0 2015-04-24  Indian Premier League          22.0   \n",
       "3  2015.0 2015-04-11  Indian Premier League           5.0   \n",
       "4  2015.0 2015-04-08  Indian Premier League           1.0   \n",
       "\n",
       "                                        venue        city  \\\n",
       "0  Punjab Cricket Association Stadium, Mohali  Chandigarh   \n",
       "1                Sardar Patel Stadium, Motera   Ahmedabad   \n",
       "2                Sardar Patel Stadium, Motera   Ahmedabad   \n",
       "3                                Eden Gardens     Kolkata   \n",
       "4                                Eden Gardens     Kolkata   \n",
       "\n",
       "                   toss_winner toss_decision player_of_match          umpire1  \\\n",
       "0             Rajasthan Royals         field        SE Marsh  HDPK Dharmasena   \n",
       "1          Chennai Super Kings           bat       AM Rahane     AK Chaudhary   \n",
       "2  Royal Challengers Bangalore         field        MA Starc        M Erasmus   \n",
       "3  Royal Challengers Bangalore         field        CH Gayle           S Ravi   \n",
       "4        Kolkata Knight Riders         field        M Morkel           S Ravi   \n",
       "\n",
       "         umpire2 reserve_umpire     tv_umpire   match_referee  \\\n",
       "0      PG Pathak      UV Gandhe   VA Kulkarni     RS Mahanama   \n",
       "1      M Erasmus   K Srinivasan     K Srinath  Chinmay Sharma   \n",
       "2         S Ravi      K Srinath  AK Chaudhary  Chinmay Sharma   \n",
       "3  C Shamshuddin      VK Sharma     PG Pathak       J Srinath   \n",
       "4  C Shamshuddin      VK Sharma     PG Pathak       J Srinath   \n",
       "\n",
       "                        winner  win_by  match_id winner_type date1 date2  \\\n",
       "0              Kings XI Punjab    16.0    734033        runs   NaN   NaN   \n",
       "1             Rajasthan Royals     8.0    829735     wickets   NaN   NaN   \n",
       "2  Royal Challengers Bangalore     9.0    829749     wickets   NaN   NaN   \n",
       "3  Royal Challengers Bangalore     3.0    829713     wickets   NaN   NaN   \n",
       "4        Kolkata Knight Riders     7.0    829705     wickets   NaN   NaN   \n",
       "\n",
       "  method outcome eliminator  \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  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.insert(4, 'year', df1['date'].dt.year)\n",
    "df1.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9d2b2a8",
   "metadata": {},
   "source": [
    "### Lets check what is date1, date2, method, outcome, elimanator column means"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "4f7a8347",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan, '2014/05/27', '2017/05/17'], dtype=object)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1['date1'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "db7d57ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan, '2014/05/28', '2017/05/18'], dtype=object)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1['date2'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "5f0315fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "### date1 and date2 columns are actually the dates where the match has been postponed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "7f9789b1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan, 'D/L'], dtype=object)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1['method'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "fe78bed7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan, 'tie', 'no result'], dtype=object)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1['outcome'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "e59dbeec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan, 'Kings XI Punjab', 'Mumbai Indians', 'Delhi Capitals',\n",
       "       'Royal Challengers Bangalore', 'Kolkata Knight Riders',\n",
       "       'Rajasthan Royals', 'Sunrisers Hyderabad'], dtype=object)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1['eliminator'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "afcbb10c",
   "metadata": {},
   "outputs": [],
   "source": [
    "## elimanator is the match between 3rd and 4th position on points table, and this column return the name of that team which has been eliminated in elimantor"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1e54ea0e",
   "metadata": {},
   "source": [
    "# Filter the data as per our need"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "455b5f93",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>year</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by</th>\n",
       "      <th>winner_type</th>\n",
       "      <th>eliminator</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>SE Marsh</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>16.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>AM Rahane</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>8.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>MA Starc</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>9.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>CH Gayle</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>3.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>M Morkel</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>7.0</td>\n",
       "      <td>wickets</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945</th>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>UT Yadav</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>6.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>946</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>field</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>6.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>947</th>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>SS Iyer</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>37.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>948</th>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>AD Russell</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>4.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>949</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>V Sehwag</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>24.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>950 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     team1                        team2    year  \\\n",
       "0          Kings XI Punjab             Rajasthan Royals  2014.0   \n",
       "1         Rajasthan Royals          Chennai Super Kings  2015.0   \n",
       "2         Rajasthan Royals  Royal Challengers Bangalore  2015.0   \n",
       "3    Kolkata Knight Riders  Royal Challengers Bangalore  2015.0   \n",
       "4    Kolkata Knight Riders               Mumbai Indians  2015.0   \n",
       "..                     ...                          ...     ...   \n",
       "945       Delhi Daredevils        Kolkata Knight Riders  2015.0   \n",
       "946    Chennai Super Kings          Sunrisers Hyderabad  2014.0   \n",
       "947       Delhi Daredevils               Mumbai Indians  2015.0   \n",
       "948        Kings XI Punjab        Kolkata Knight Riders  2015.0   \n",
       "949    Chennai Super Kings              Kings XI Punjab  2014.0   \n",
       "\n",
       "                     toss_winner toss_decision player_of_match  \\\n",
       "0               Rajasthan Royals         field        SE Marsh   \n",
       "1            Chennai Super Kings           bat       AM Rahane   \n",
       "2    Royal Challengers Bangalore         field        MA Starc   \n",
       "3    Royal Challengers Bangalore         field        CH Gayle   \n",
       "4          Kolkata Knight Riders         field        M Morkel   \n",
       "..                           ...           ...             ...   \n",
       "945        Kolkata Knight Riders         field        UT Yadav   \n",
       "946          Sunrisers Hyderabad         field       DA Warner   \n",
       "947               Mumbai Indians         field         SS Iyer   \n",
       "948        Kolkata Knight Riders         field      AD Russell   \n",
       "949          Chennai Super Kings         field        V Sehwag   \n",
       "\n",
       "                          winner  win_by winner_type eliminator  \n",
       "0                Kings XI Punjab    16.0        runs        NaN  \n",
       "1               Rajasthan Royals     8.0     wickets        NaN  \n",
       "2    Royal Challengers Bangalore     9.0     wickets        NaN  \n",
       "3    Royal Challengers Bangalore     3.0     wickets        NaN  \n",
       "4          Kolkata Knight Riders     7.0     wickets        NaN  \n",
       "..                           ...     ...         ...        ...  \n",
       "945        Kolkata Knight Riders     6.0     wickets        NaN  \n",
       "946          Sunrisers Hyderabad     6.0     wickets        NaN  \n",
       "947             Delhi Daredevils    37.0        runs        NaN  \n",
       "948        Kolkata Knight Riders     4.0     wickets        NaN  \n",
       "949              Kings XI Punjab    24.0        runs        NaN  \n",
       "\n",
       "[950 rows x 10 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2=df1[['team1','team2','year','toss_winner','toss_decision','player_of_match','winner','win_by','winner_type','eliminator']]\n",
    "df2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ed7137f",
   "metadata": {},
   "source": [
    "## How many matches played every year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "3c68b943",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2013.0    76\n",
       "2022.0    74\n",
       "2012.0    74\n",
       "2011.0    73\n",
       "2016.0    60\n",
       "2019.0    60\n",
       "2018.0    60\n",
       "2020.0    60\n",
       "2021.0    60\n",
       "2010.0    60\n",
       "2014.0    59\n",
       "2015.0    59\n",
       "2017.0    58\n",
       "2008.0    58\n",
       "2009.0    57\n",
       "Name: year, dtype: int64"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.year.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "1708d42d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "ax=sns.countplot(x='year', data=df2,\n",
    "            order=df2.year.value_counts(ascending=False).index)\n",
    "\n",
    "abs_values = df2['year'].value_counts(ascending=False).values\n",
    "\n",
    "ax.bar_label(container=ax.containers[0], labels=abs_values);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8544ed6",
   "metadata": {},
   "source": [
    "## Which team has won the toss most of the times"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "334c7e9f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Mumbai Indians                 123\n",
       "Kolkata Knight Riders          114\n",
       "Chennai Super Kings            109\n",
       "Royal Challengers Bangalore    105\n",
       "Rajasthan Royals                99\n",
       "Kings XI Punjab                 85\n",
       "Delhi Daredevils                80\n",
       "Sunrisers Hyderabad             74\n",
       "Deccan Chargers                 43\n",
       "Delhi Capitals                  36\n",
       "Pune Warriors                   20\n",
       "Gujarat Lions                   15\n",
       "Gujarat Titans                  10\n",
       "Punjab Kings                     9\n",
       "Kochi Tuskers Kerala             8\n",
       "Lucknow Super Giants             7\n",
       "Rising Pune Supergiants          7\n",
       "Rising Pune Supergiant           6\n",
       "Name: toss_winner, dtype: int64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.toss_winner.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "647d0d7d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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O0XzhhRcYPnw4AwYMYPjw4W5Ka2bWCTkhM1tK1M7RnDRpElOnTmXevHlceumljB49mmHDhjF9+nSGDRvG6NGjqx6qmZm14oTMbCnS1jmaY8eOZeTIkQCMHDmSa665ptpBmpnZQpyQmS0l2jtH85lnnqF3794A9O7dm1mzZlU8UjMza80JmdlSor1zNM3MrPNzQma2lOjoHM3a0U0zZ86kV69eFY/UzMxaqyQhk3S0pIclTZV0iaTlJa0uabyk6cXb1aoYm9mSqr1zNPfaay/GjBkDwJgxY9h7770rHqmZmbWWvVO/pD7AV4FNI+I1SZcBnwQ2BSZExGhJxwLHAt/OPT6zJVV752j+73//48ADD+S8886jX79+XH755VUP1czMWqnq6KRuwAqS3gK6A/8BvgPsVNw/BrgFJ2Rm70hb52gut9xyTJgwoaIRmZnZ4si+ZBkRTwM/A54EZgIvRcSNwFoRMbP4mJmAC13MzMysKVSxZLkasDewHvAicLmkQ97B5x8JHAmpZsasmRx29a6lx7hg3xtKj2FmZi1VUdT/MeDxiHg2It4CrgI+CDwjqTdA8bbNZkkRcU5EDI2IoT179sw2aDMzM7OyVJGQPQlsK6m7JAHDgEeBccDI4mNGAmMrGJuZmZlZdtmXLCPibklXAPcBc4H7gXOAlYDLJB1OSto+kXtsZmZmZlWoZJdlRBwPHN/q8huk2TIzMzOzpuJO/Wb2nk2bNo3BgwfP/9ejRw9OPfXU+ff/7Gc/QxLPPfdcdYM0M+vEqupDZmZLkY022ogpU6YAMG/ePPr06cO+++4LwIwZMxg/frx3RZuZdcAzZGbWUBMmTGCDDTZg3XXXBeDoo4/mJz/5CWkPj5mZtcUJmZk11KWXXsqIESMAGDduHH369GHQoEEVj8rMrHPzkqWZNcybb77JuHHjOOWUU5gzZw4nn3wyN954Y9XDMjPr9DxDZmYNc/311zNkyBDWWmst/vWvf/H4448zaNAg+vfvz1NPPcWQIUP473//W/Uwzcw6Hc+QmVnDXHLJJfOXKzfffHNmzVpw4Eb//v2ZNGkSa665ZlXDMzPrtDxDZmYNMWfOHMaPH89+++1X9VDMzJY4niEzs4bo3r07zz//fLv3P/HEE/kGY2a2hPEMmZmZmVnFPENmZotl92u+V3qM6/b5QekxzMw6I8+QmZmZmVXMCZmZmZlZxZyQmZmZmVXMCZmZmZlZxZyQmZmZmVXMCZmZmZlZxZyQmZmZmVXMCZmZmZlZxZyQmZmZmVXMCZmZmZlZxZyQmZmZmVVssRIySRMW55qZmZmZvXMdHi4uaXmgO7CmpNUAFXf1ANYueWxmZmZmTaHDhAz4HPA1UvI1mQUJ2cvAGeUNy8zMzKx5dJiQRcRpwGmSvhIRp2cak5mZmVlTWdQMGQARcbqkDwL96z8nIn5f0rjMzMzMmsZiJWSSLgQ2AKYA84rLATghMzMzM3uPFishA4YCm0ZElDkYMzMzs2a0uH3IpgLvK3MgZmZmZs1qcWfI1gQekXQP8EbtYkTsVcqozMzMzJrI4iZkJ5Q5CDMzM7Nmtri7LP9W9kDMzMzMmtXi7rJ8hbSrEmBZYBng1YjoUdbAzMzMzJrF4s6QrVx/W9I+wNZlDMjMzMys2SzuLssWIuIa4KONHYqZmZlZc1rcJcv96m52IfUlc08yMzMzswZY3F2We9a9Pxd4Ati74aMxMzMza0KLW0N2WNkDMTMzM2tWi1VDJqmvpKslzZL0jKQrJfUte3BmZmZmzWBxi/ovAMYBawN9gD8V18zMzMzsPVrchKxnRFwQEXOLf78DepY4LjMzM7OmsbgJ2XOSDpHUtfh3CPD8uw0qaVVJV0j6u6RHJW0naXVJ4yVNL96u9m6/vpmZmdmSZHETslHAgcB/gZnAAcB7KfQ/DbghIjYGBgGPAscCEyJiADChuG1mZma21FvchOwHwMiI6BkRvUgJ2gnvJqCkHsAOwHkAEfFmRLxIaqMxpviwMcA+7+brm5mZmS1pFjch2yIiZtduRMQLwJbvMub6wLPABZLul/RbSSsCa0XEzOLrzwR6vcuvb2ZmZrZEWdyErEt9TZek1Vn8prKtdQOGAGdGxJbAq7yD5UlJR0qaJGnSs88++y6HYGZmZtZ5LG5C9nPgDkk/kHQScAfwk3cZ8yngqYi4u7h9BSlBe0ZSb4Di7ay2PjkizomIoRExtGdPb/Q0MzOzJd9iJWQR8Xtgf+AZ0nLjfhFx4bsJGBH/BWZI2qi4NAx4hNTnbGRxbSQw9t18fTMzM7MlzWIvO0bEI6TEqRG+AlwsaVngMdKOzS7AZZIOB54EPtGgWGZmZmad2rutA3tPImIKMLSNu4ZlHoqZmZlZ5Ra3hszMzMzMSuKEzMzMzKxiTsjMzMzMKuaEzMzMzKxiTsjMzMzMKuaEzMzMzKxiTsjMzMzMKuaEzMzMzKxiTsjMzMzMKuaEzMzMzKxiTsjMzMzMKuaEzMzMzKxiTsjMzMzMKuaEzMzMzKxiTsjMzMzMKuaEzMzMzKxiTsjMzMzMKuaEzMzMzKxiTsjMzMzMKuaEzMzMzKxiTsjMzMzMKuaEzMzMzKxiTsjMzMzMKuaEzMzMzKxiTsjMzMzMKuaEzMzMzKxiTsjMzMzMKuaEzMzMzKxiTsjMbKkwb948ttxyS/bYYw8Avve977HFFlswePBgdt55Z/7zn/9UPEIzs/Y5ITOzpcJpp53GJptsMv/2N7/5TR588EGmTJnCHnvswUknnVTh6MzMOuaEzMyWeE899RR//vOfOeKII+Zf69Gjx/z3X331VSRVMTQzs8XSreoBmJm9V1/72tf4yU9+wiuvvNLi+nHHHcfvf/97VlllFW6++eaKRmdmtmieITOzJdq1115Lr1692GqrrRa67+STT2bGjBkcfPDB/PrXv65gdGZmi8cJmZkt0W6//XbGjRtH//79+eQnP8lNN93EIYcc0uJjPvWpT3HllVdWNEIzs0VzQmZmS7RTTjmFp556iieeeIJLL72Uj370o1x00UVMnz59/seMGzeOjTfeuMJRmpl1zDVkZrZUOvbYY5k2bRpdunRh3XXX5ayzzqp6SGZm7XJCZmZLjZ122omddtoJwEuUZrZE8ZKlmZmZWcU8Q2Zmnd7Hr/pN6TH+vN8XS49hZtYez5CZmZmZVcwJmZmZmVnFKkvIJHWVdL+ka4vbq0saL2l68Xa1qsZmZmZmllOVM2RHAY/W3T4WmBARA4AJxW0zMzOzpV4lCZmkvsDHgd/WXd4bGFO8PwbYJ/OwzMzMzCpR1QzZqcC3gLfrrq0VETMBire9KhiXmZmZWXbZEzJJewCzImLyu/z8IyVNkjTp2WefbfDozMwW3+uvv87WW2/NoEGD2GyzzTj++OPn33f66aez0UYbsdlmm/Gtb32rwlGa2ZKgij5kHwL2krQ7sDzQQ9JFwDOSekfETEm9gVltfXJEnAOcAzB06NDINWgzs9aWW245brrpJlZaaSXeeusttt9+e3bbbTdee+01xo4dy4MPPshyyy3HrFltPpyZmc2XfYYsIr4TEX0joj/wSeCmiDgEGAeMLD5sJDA299jMzN4JSay00koAvPXWW7z11ltI4swzz+TYY49lueWWA6BXL1dgmFnHOlMfstHAcEnTgeHFbTOzTm3evHkMHjyYXr16MXz4cLbZZhv+8Y9/cOutt7LNNtuw4447cu+991Y9TDPr5Co9OikibgFuKd5/HhhW5XjMzN6prl27MmXKFF588UX23Xdfpk6dyty5c5k9ezZ33XUX9957LwceeCCPPfYYkqoerpl1Up1phszMbIm16qqrstNOO3HDDTfQt29f9ttvPySx9dZb06VLF5577rmqh2hmnZgTMjOzd+nZZ5/lxRdfBOC1117jr3/9KxtvvDH77LMPN910EwD/+Mc/ePPNN1lzzTUrHKmZdXaVLlmamS3JZs6cyciRI5k3bx5vv/02Bx54IHvssQdvvvkmo0aNYuDAgSy77LKMGTPGy5Vm1iEnZGZm79IWW2zB/fffv9D1ZZddlosuuqiCEZnZkspLlmZmZmYV8wyZmVkH9rji4tJjXHvAwaXHMLPOzTNkZmZmZhVzQmZmZmZWMSdkZmZmZhVzQmZmZmZWMSdkZmZmZhVzQmZmZmZWMSdkZmZmZhVzQmZmZmZWMSdkZmZmZhVzQmZmZmZWMSdkZmZmZhVzQmZmZmZWMSdkZmZmZhVzQmZmZmZWMSdkZmZmZhVzQmZmZmZWMSdkZmZmZhVzQmZmZmZWMSdkZmZmZhVzQmZmZmZWMSdkZmZmZhVzQmZmZmZWMSdkZmZmZhVzQmZmZmZWMSdkZmZmZhVzQmZmZmZWMSdkZmZmZhVzQmZmZmZWMSdkZmZmZhVzQmZmZmZWMSdkZmZLoBkzZvCRj3yETTbZhM0224zTTjsNgBdeeIHhw4czYMAAhg8fzuzZsyseqZktDidkZmZLoG7duvHzn/+cRx99lLvuuoszzjiDRx55hNGjRzNs2DCmT5/OsGHDGD16dNVDNbPF4ITMzGwJ1Lt3b4YMGQLAyiuvzCabbMLTTz/N2LFjGTlyJAAjR47kmmuuqXCUZra4nJCZmS3hnnjiCe6//3622WYbnnnmGXr37g2kpG3WrFkVj87MFocTMjOzJdj//vc/9t9/f0499VR69OhR9XDM7F1yQmZmtoR666232H///Tn44IPZb7/9AFhrrbWYOXMmADNnzqRXr15VDtHMFlP2hEzSOpJulvSopIclHVVcX13SeEnTi7er5R6bmdmSIiI4/PDD2WSTTfj6178+//pee+3FmDFjABgzZgx77713VUM0s3egihmyucAxEbEJsC3wJUmbAscCEyJiADChuG1mZm24/fbbufDCC7npppsYPHgwgwcP5rrrruPYY49l/PjxDBgwgPHjx3PssX4oNVsSdMsdMCJmAjOL91+R9CjQB9gb2Kn4sDHALcC3c4/PzGxJsP322xMRbd43YcKEzKMxs/eq0hoySf2BLYG7gbWKZK2WtLnwwczMzJpC9hmyGkkrAVcCX4uIlyUt7ucdCRwJ0K9fv/IGaGZWsb2uuLb0GOMO2KP0GGa2aJXMkElahpSMXRwRVxWXn5HUu7i/N9Bm85yIOCcihkbE0J49e+YZsJmZmVmJqthlKeA84NGI+EXdXeOAkcX7I4GxucdmZmaLZ9SoUfTq1YuBAwfOv3bCCSfQp0+fFpsMzGzxVDFD9iHg08BHJU0p/u0OjAaGS5oODC9um5lZJ3TooYdyww03LHT96KOPZsqUKUyZMoXdd9+9gpGZLZmq2GV5G9BewdiwnGMxM7N3Z4cdduCJJ56oehhmSw136jczs4b59a9/zRZbbMGoUaOYPXt21cMxW2I4ITMzs4b4whe+wL/+9S+mTJlC7969OeaYY6oektkSwwmZmZk1xFprrUXXrl3p0qULn/3sZ7nnnnuqHpLZEsMJmZmZNUTtUHOAq6++usUOTDPrWGWNYc3MbMk1YsQIbrnlFp577jn69u3LiSeeyC233MKUKVOQRP/+/Tn77LOrHqbZEsMJmZmZvWOXXHLJQtcOP/zwCkZitnTwkqWZmZlZxTxDZmZmC9nvyrtKj3HV/tuWHsNsSeEZMjMzM7OKOSEzMzMzq5gTMjMzW6K0dbD5Cy+8wPDhwxkwYADDhw/3KQG2xHFCZmZmS5S2DjYfPXo0w4YNY/r06QwbNozRo0dXNDqzd8cJmZmZLVF22GEHVl999RbXxo4dy8iRIwEYOXIk11xzTQUjM3v3nJCZmdkS75lnnqF3794A9O7dm1mzZpUe87TTTmPgwIFsttlmnHrqqaXHs6WbEzIzM7N3aOrUqZx77rncc889PPDAA1x77bVMnz696mHZEswJmZmZLfHWWmut+Wdpzpw5k169epUa79FHH2Xbbbele/fudOvWjR133JGrr7661Jj1fvnLX7LZZpsxcOBARowYweuvv54ttpXDCZmZmS3x9tprL8aMGQPAmDFj2HvvvUuNN3DgQCZOnMjzzz/PnDlzuO6665gxY0apMWuefvppfvWrXzFp0iSmTp3KvHnzuPTSS7PEtvK4U7+ZmS1R2jrY/Nhjj+XAAw/kvPPOo1+/flx++eWljmGTTTbh29/+NsOHD2ellVZi0KBBdOuW7yl17ty5vPbaayyzzDLMmTOHtddeO1tsK4dnyMzMbIlyySWXMHPmTN566y2eeuopDj/8cNZYYw0mTJjA9OnTmTBhwkK7MMtw+OGHc9999zFx4kRWX311BgwYUHpMgD59+vCNb3yDfv360bt3b1ZZZRV23nnnLLGnTZvG4MGD5//r0aNHtg0NVcbOwTNkZmZm78KsWbPo1asXTz75JFdddRV33nlnlrizZ89m7NixPP7446y66qp84hOf4KKLLuKQQw4pPfZGG23ElClTAJg3bx59+vRh3333LT1u1bFzcEJmZmadylevLr8W61f7rvOev8b+++/P888/zzLLLMMZZ5zBaqut1oCRLdpf//pX1ltvPXr27AnAfvvtxx133JElIas3YcIENthgA9Zdd92scauK/eKLL3LEEUcwdepUJHH++eez3XbbNezrOyEzMzN7F2699dZK4vbr14+77rqLOXPmsMIKKzBhwgSGDh2afRyXXnopI0aMyB63qthHHXUUu+66K1dccQVvvvkmc+bMaejXd0JmZmZWuOTKZ0uPMWL/nu/p87fZZhsOOOAAhgwZQrdu3dhyyy058sgjGzS6xfPmm28ybtw4TjnllKxxq4r98ssvM3HiRH73u98BsOyyy7Lssss2NIaL+s3MzJYwJ554In//+9+ZOnUqF154Icstt1zW+Ndffz1DhgxhrbXWyhq3qtiPPfYYPXv25LDDDmPLLbfkiCOO4NVXX21oDCdkZmZm9o5ccskllS1XVhF77ty53HfffXzhC1/g/vvvZ8UVV2z4AfZesjQzM+sEbv99+culH/rMe1suBZgzZw7jx4/n7LPPbsCIlozYffv2pW/fvmyzzTYAHHDAAQ1PyDxDZmZmZoute/fuPP/886yyyipNE/t973sf66yzDtOmTQPSLs9NN920oTE8Q2ZmZtbknjj1v6XH6P+197V5/ZlfPlh67LWO3uI9f43TTz+dgw8+mDfffJP111+fCy64oAEjW8AJmZmZmdkiDB48mEmTJpX29b1kaWZmZlYxz5CZmZlZU5p1+l9Lj9HrKx9brI/zDJmZmZlZxZyQmZmZmVXMCZmZmZlZxZyQmZmZmVXMCZmZmZlZxZyQmZmZmVXMCZmZmZlZxZyQmZmZmVXMCZmZmZlZxZyQmZmZmVWs0yVkknaVNE3SPyUdW/V4zMzMzMrWqRIySV2BM4DdgE2BEZI2rXZUZmZmZuXqVAkZsDXwz4h4LCLeBC4F9q54TGZmZmal6mwJWR9gRt3tp4prZmZmZkstRUTVY5hP0ieAXSLiiOL2p4GtI+IrdR9zJHBkcXMjYNp7CLkm8Nx7+Pz3wrEd27Ed27Ed27GbK/a6EdGzrTu6vfvxlOIpYJ26232B/9R/QEScA5zTiGCSJkXE0EZ8Lcd2bMd2bMd2bMd27Hersy1Z3gsMkLSepGWBTwLjKh6TmZmZWak61QxZRMyV9GXgL0BX4PyIeLjiYZmZmZmVqlMlZAARcR1wXaZwDVn6dGzHdmzHdmzHdmzHfi86VVG/mZmZWTPqbDVkZmZmZk3HCZmZmZlZxZyQZSJpRUldivc3lLSXpGWW9thFzBUkbZQrnpmk1SRtUfU4cpPURVKPqseRW7N+37lJ+pCkFYv3D5H0C0nrVj2usklabnGuvVdNlZBJ+oSklYv3vyvpKklDMoWfCCwvqQ8wATgM+N3SHlvSnsAU4Ibi9mBJWVqZSDpKUg8l50m6T9LOmWIvL+nrxe/YlZKOlrR8ptjZv29JD0l6sL1/ZcauG8Mtxfe9OvAAcIGkX2SKXeXv2h+K2CsCjwDTJH0zU2x/35m/7yL+xyV9S9L3a/8yhT4TmCNpEPAt4N/A73MElvST4me+jKQJkp6TdEiO2MCdi3ntPWmqhAz4XkS8Iml7YBdgDOkXLAdFxBxgP+D0iNiXdID60h77BNIZpS8CRMQUoH+m2KMi4mVgZ6AnKREdnSn274HNgNOBXwObABdmil3F970HsCcp8b4BOLj4dx1wRcmxa1Ypvu/9gAsiYivgY5liV/m7tmkRex/Sz7sf8OlMsf19Z/6+JZ0FHAR8BRDwCSDXLNXcSDsB9wZOi4jTgJUzxd65+JnvQWoivyFQagIu6X2StgJWkLSlpCHFv52A7o2O1+naXpRsXvH248CZETFW0gmZYkvSdqQnqcOLa7l+/lXGnhsRL0nKFK6FWtDdSU/QDyjfQDaKiEF1t2+W9ECm2Nm/74j4N6QljYj4UN1dx0q6HTipzPiFbpJ6AwcCx2WIV6/K37VllEoQ9gF+HRFvScq1fd7fd/7v+4MRsYWkByPiREk/B67KFPsVSd8BDgF2kNQVyFX+UouzO3BJRLyQ4Ue+C3Ao6dSg+tn2V4D/a3SwZpshe1rS2aQH7OuU1oBz/QyOAr4DXB0RD0taH7g5U+yvVRh7qqRPAV0lDZB0OnBHptiTJd1I+gP+i9Jy9duZYt8vadvaDUnbALdnil3l971iMQMNgKQPAitmin0iqan0PyPi3uL3fHqm2FX+zM8CniD9nCcq1fS8nCl2ld/32TTn9/1a8XaOpLWBt4D1MsU+CHgDODwi/gv0AX6aKfafJP0dGApMkNQTeL3MgBExJiI+AhwaER+p+7dXRDQ8CW6qPmSSugO7Ag9FxPTi1fTmEXFjyXG7AqMjIkt9Q2dS/MyPI03tQ3rC/GFElPqHVMTuAgwGHouIFyWtAfSJiNJqmiQ9BATp1dxGwJPF7XWBRyJiYFmx68aQ/fuui70VcD6wSnHpRdLyzn0lx+0KfDUifllmnA7iV/IzL+IeEBGX1V0T0DUi5pYZuy7+YCr4XWtnPN2W9u9b0vdIpRDDgDNIjy+/jYjvZYj944j49qKulRR7OdIy4csRMa+oHVwpIp7JFHt/UrnN/NWliGjozH9TJWQw/4F7LVr+UJ/MEPemiPho2XHaif0n0h9tvZeAScDZZSVHxc/6LxGRq46nFrfDjRplJgdaxI6j2tJeSbEr+77bGEsP0uPLSxlj3ly8ms2mM/zMJU2MiB3KjtNB/D6kFxz1j6kTM8TN8iTZTuy2/t9fAv6dIyGsG8dywPK5/s4k3RcRQ1pdezAiSt/R3E7sha6VFPsG0v/vZBaUPhERP29knKaqIZP0FeB44BkWTC8HkGN7/P1KuwsvB16tXSxj2rMNj5EKTy8pbh9E+hlsCJxLSYWwxauYOZJWyfnEDHT0RxJAaYlx64RLUi8gy+5KKvy+60n6OGlDw/K1Go8cT5LAHZJ+DfyRln9jZSZFneFnPl7SN1j4+36h7MCSfkx6PHmEBU9UQdrZXbaxLHiSfCNDvHq/AYYAD5LqyQYW768h6fNlrLpI2q+D+0p9LpH0BeCLwPpquWt6ZUouQZH0PtLS6AqStmRB/V4PSiisb0ffiNi17CBNNUMm6Z/ANhHxfAWxL2jjckTEqAyxF3oFXbsm6eGI2KzE2JcB2wLjaflk8dWyYnYGkvYiPVmvDcwizSA8WubPujNQ2gHWHfgI8FvgAOCeiDi8w09sTOy26iKjqpnpXCQ93sbliIj1M8SeBmwREbkTIiRNzVEC0E7sS4EfRMTDxe1NSTv+fgBcFRGDS4jZ1nNITanPJZJWAVYDTgGOrbvrlbITf0kjSYX1Q0mrOvNjA7/LMakh6RxSh4KHSo3TZAnZzcDwnFPKnYGkR4FdakuzkvoBN0TEppLuj4gtS4w9sq3rETGmrJit4g8ktfiYP0sVEaX3zVHaUflR4K8RsaWkjwAjIuLIEmN+NCJuau+VdKYHrgfrdoBtIWkl0hNUth5NVanqd61Kkq4HPhER/6sgdpYnyXZiT2mddNWutXXf0qTCsp/9I+LKsuO0E/sR4P3A46TZWJGS4IaurjXVkiVp6e4WSX+mboo7IkpvHilpQ1LPs7UiYqBSF/G9IuKHZccGjgFuk/Qv0i/SesAXi6LIUhOjiBgjaVnS8ijAtIh4q8yYNZKOB3YiPUleB+wG3EaeRoZvRcTzSh3Eu0TEzcXyTpl2BG4i9QNrLcizNb71DrDnybQDTNJawI+AtSNit2LWYruIOC9D7Mp+15RaP3wBqM2C30KqDc3xdzYHmCJpAi0fU3PMgG8PHFrMEJb2JNmOaZLOBC4tbh8E/KOo6Sr9515fFlC7lql27suk3pJVlP1cq7Rjvz+ZawZJf8+la7YZsuPbuh4RJ2aI/TfSlPbZtRmpnFPuxQPFxqQHrb/n2OVYxN2JlPQ9UcReBxiZqej3IWAQcH9EDCqesH8bEW0lLI2O/VdSf6RTgDVJy5YfiIgPZojdNSLmLfojS4nd1g6wcyOi9E7ixWzNBcBxxf93N9L//eYZYlf5u/Zb0q7e2ourTwPzIuKIDLErmwFvbwNNmRtn6mKvQKqp2p70uHYbqa7sdaB7mTOGFZcFVFn2k6WwfhFjaFET3OiZwaZKyKok6d6I+ED9EmHOqW2lflD9afnKIser98nApyJiWnF7Q1JTv60yxL4nIrYuxvARUs3B1Bx1XMXs4+ukB+uDSW0gLs7xQCbpSVK3/D8CN0VFf+QV7ACr7G+s4t+1B6JlE+I2r5UYv5IZ8Lr4pT5JdjZVlgVUWfZTcc1glprgplqyVGok9y0WnurNUfT7nKQNKNpPSDoAmJkhLpIuBDYgnSlZvxMqx9LdMrVkDCAi/qF8B5tPkrQqaSfpZOB/wD05AkfEq3U3s9TL1dmItGz5JeA8SdcCl0bEbWUHVjqvszZzEKSl8jMzzci+qtQPqvY3ti3pFXUOlf2uAfMkbRAR/wJQaoibZYa0rRlwSblmwNt8kiQ9vpcd+0OkpbvW7T5K30jBgmao2csCqLDsh7SLevMqagZJmzW2pVVNcKODNNUMmVJn5T8C3wA+D4wEno08Te3WB84BPgjMJhUHHhIRT2SI/Sjp3Lfs/9mSzic9QdbOcTwY6BYRh2UeR3+gR5TfqPO2iNhe0iss3PsN0oPnTyPiN2WOo248qwGnAQdHRNcM8S4jzQ5dVFwaAawWEZ/IEHsIabl0IDCV1OrlgLL/z9sYR38y/K7VxRtGWqp9jJQUrQscFhGln8ZR8Qx49o0zdbH/DhzNwstnOWbAqywLqLLsJ0thfTuxJ0XE0OJ3bsuIeLs2K97QOE2WkE2OiK1U18hO0t8iYseMY1gR6BIRr2SMeTmpi3mWGblWsZcjzdTUai0mAr+JDNvkJV1BeqK6PiJyHWvSoWIG546I2KjkODuSCo13A+4F/phjh1InWD7rRpohFHk3kEyIiGGLulZi/OVY8H3/PcffVxF3oaagbV0rKXaWJ8l2Yt8dEduUHaeNuF2AbSPijuJ21rKAKlVcM5ilJriplixZsPtlZrFL5T+kQ0NLI+nr7VwHsk31rgk8IukeWk4z71V24OKJ4Re0PJg1l7OAw4BfFUnp7yLi77mCq53t4cUyT5lxHyctT18GfLPV8mnZ7pe0bUTcVYwl2xmeWrjdx4aSXiIdlTarpJjLkwqs1yxmI+ubVq5dRsy62O21OdlAJTcKrTNJ0nm0nAGfnCEuwItF/dRE4GJJs4BctU03S/opaedy/WNqqSczFEnnz4HtittvkLEpbpVlP7XEq3XNYCZ7k5aKj2ZBTXDDd3c2W0L2Q6UGd8eQpnx7kH7AZVq5eLsR8AFgXHF7T/J0s4ZU65CVFpzp2KYcr6Aj4q/AX4v/8xGkjuYzSHU+F5U5e6IOToXIMFM5KCJyHbIMtPj/Xgb4TLGxYP4ZnpmGcTjpiaq2VLcTcBcpMTspIi5s7xPfg88BXyMlX/VPxi+TlpPK1BnanHyBNAP+VepmwDPEhfQk+RotnyRLXzor1GbHhtZdy3Uyw42S9icV8ude4rqYVPazB3VlPzkCV1kzmKsmuKmWLKtU1K/tX1uqlLQycHlkOI6hCu1NL9fkmGYuxrEGcAipFcB/SA8o25MOld+pxLhVbg/P3vOuM/x/K53ZekQUhw0rtZ44EzgCmFjmDi1JX4mI08v6+h3EXehw8WahCg+6rlJRn7oiqXbtNRbUUvXIELuysp8qagY7qAku5WfeFDNkkr4VET+RdDptzNpEniaG/YA3626/SWpDUZrcv0z1ciVcHZF0Fan32oXAnnUzU3+UNKn9z2yIGeTb4dfauRQ97wAi4kFJfwBKS8ha/39XtKzQv5aMFWYBG0bEC5JKmQ2tLRsCT7exdFj6smGxhPVl0vJ0NpIui4gD25sJzzEDDgwHWidfu7VxrWEkHRIRF7VXipKjBCUiVl70R5Ume9lPfezI3Gw7IrYv3mb5mTdFQkaa1oSW52DldiFwj6SrSQ9g+1Jy24mOfpmKYtDSKbUeOB3YBFgW6Aq8muPVHPDr4slyIRExtK3rDVTl9vDuEXFPrU6xkKW2psplBeBWpRYflxe39wcmFhtpXiwpZmdYNqzicPGjird7lBijTer4oOuy6xVXrIvVWpblJqU/7IOB9SLiB5LWAXpHRI42K1WU/dRUVjMoafU2Lr/S6LIXL1lmpLQt/8PFzYkRcX/J8b4XET9o43oPYFyZS3Z1sSYBnyQ9SQ4FPgO8PyKOyxC79ZEyfwPOyrHzTtVuD78e+DJpSXyIUs+7wyOi9OM/qlhWaBV/f1p2T7+ygjqbrFTh4eJtkXR7RHyoxK9f5UHXfSPiqXbu2zMi/lRm/CLOmaS61I9GxCbFZpIbI+IDZceukqpttv0E6ZSZ2UX8VUl9RGcBn42IhmxkaYqErKgt6ajAvLTdhpJ6RMTL7WTYpb6KLerW7q1PfiS9D/gLqSA0R3JQ25peX3NwR6O3C7cTu7IjZaqkanveVdKKoKilerDMOrFFxF+DtIljfkNc4KSynyyK7/sTEfHHMuO8E5JmRMQ6JX79Kh9TpwG7tP5bknQY8N2I2KCs2HWx7iteaN0fC06kKLW1TCcp+6mM0nFVV0fEX4rbOwO7kkoFTosGtUBpliXLnxVv9wPeR8umlU+UHPsPpGn9ybRRxwWU+Sp2L+AKSb+IiK9LGgBcT2pMenaJcevNUTpaZYqkn5BeVay4iM9plA+0epC6qUgUSqd0xEhbD1w5toc/BnxMFfS8o6JlhSLxe0BSv6jm6JxLSd/z/sXtg0lLiB8rM2jxfX+piNVZlP0qv/Vjav3afNmPqUeTloh3j4jpAJK+A3yKtHydw1tKLXVqJ1L0ZMFO7rJUVvZTZS10naER8fnajYi4UdKPiufVhpX/NMUMWY2kiRGxw6KuLU2KZbtLScWY2wFfi4irM8ZflzStuwzpwWwVUmPYf2aIfR9p9qD+SJkrImJIhtj1ncqXJz1Rz42Ib5UYs81C45oc9WtFEvga0IX8ywo3kVrL3EPLWqrS++3Vdp+1ujYpQ60iSp3bXyNjDVlbGxhqd5HKAnqWGHv/yNDkuIP4w0gbZvYh7eD9ALBHRMzOFP9gUtPnIaTZ/wNIs3OXd/iJ9q4Vq00TSM+lkH7+w0mzZPc26jml2RKyR4GPFzMISFoPuC4iNqlgLBsB34iIz5YYo/YEvQypmd+t1PU+y1RgXhlVeKRMO+MpdXt4Xd1amz3vyl6qLV61/yUiSp0V6iB+mz/biPhbhtg/I80e1HY7HgBsFhFt1hI2OHb2GjJJF3R0f5R4NFptya6sr7+YY9geuAa4AzgwMpzVWl+/Jmlj0tFJIiUK7y+zfq34ftePiN8Xt68AakvGP2xv81SDx5ClsL6d2GuyoCQBipIE0k76fo2aYGi2hGxXUm3NY8Wl/sDnauvCJcXcgrRkujbpD/h0UuPEbYCfR8QvS4zd4ZNBphqytrbFv0R68vphhhqbFkfKkKaeS+8c3+rBowuwFfCrKPnIpCJ2ZT3vJI0DPh1NcJRLPS3oDVVbOurCgtmqXMsqTaHKhKxu2UzAcqSVh3lkWD7roH5tFHBcmfVrkiYAX4mIR4rbDwGHkn7n/y/TY8sTZCisbyNuV2BMRBxSxtev1yw1ZABExA1FHdXGxaUcZ76dS2pOeSdpevM+Ug3EwWW/qsqRcC2G60kPWH8obn+S9Mf0EvA72m4X8J4Uf0AHAn1I51g+KGkP0v/DCsCWjY7ZhvoHh7mkwvrDM8SFCnre1XkdeEjSeFoun5Ve9KsKW6xEtb2hkDQQ2JSWx9mU2lanQhurZbuLmtIPm674/7mt+rVjSaUBZdev9aglY4XptQRI0iklx665gfYL62uTHA0XEfMk9ZS0bES8uejPePeaaoYMQNIHSU9O9ecLlvbAJWlKRAyuuz2D1MByXlkxOxO1sQW+dk3SQxGxeQkxf0d6JXUP6Y/038C2wHci4ppGx+tsJB1HSkjre95dFhE/yhB7ZFvXI6K040bqYrfVYmVARPxf2bGL+KsBA2iZFJV+PFoxE74TKSG7jtQc9baIOKDs2FWQ9DCwe3v3RydoSl2WqurXJE2PiAHt3PfPiHh/mfGLOAvVZNbt6m7xPFtC7LNJNXvjaPlCs6FlP001QybpQmAD0sHLtYQoKLdB6/KStmTBTqD/AVtIqWtnlHwYbSewkqRtIuJuAElbAysV95W1+24o6czIt5UOf36OVGPx35Lizad0mPY5pN+zh4BREfFox5/VWBFxslIvslrPu8Oi5J53dbHHSFqBVFcxLUfMVvH/Kalr8YLnAkl35Igr6QhSs9S+pMeXbUmz4jnONjwAGATcHxGHKR0Z9dsMcZG0XOtVhrauNdibS3PS1ZGImCDpUOAWUv3asBz1a8DfJX08Iv5cf7FYecj1d/6CpG/TsrB+drEiUvYu0/8U/7rQdlPghmiqhIz0RL1p5J0WnAnUZ9H/rbtd+mG0qv6suyOA84tWCCIdunxEsRuvrKnuNyPibYCIeF3SP3IkY4UzgG+QNk/sBZwK7JIpdr3uwMsRcUEx3b5eRLRV/N1QkvYk1UwuC6wnaTCpH1fpOx2ptsXKUaTZirsi4iNF0XWukoHXihcfc5WaPs+i3NYP9e4kzRws6lojlV4D2hm1Ub82DJhVvLgvu07xaODPSk2ma5MIW5F6HeY6reFTpML6a4rbtxXXaiUqpamV/0haMVoeNN5QzZaQTSX1IZu5qA9slIj4SK5Y7cSv5Ky7uvj3ApsrdddWRLxYd3dZY6qvMRGwQXG79BoTUt+v8cX7lyv1KMqqWMIaStrMcAFpl+1FQGnd0+ucAGxNegVPREwpdjPn8GnSK9gvk55A1mFBX7CyvV4k/7UZor8XO6lzmCRpVVK96mTSLHypx+goNZjuA6zQagWgB+nFQGki4stlfv3FVfwMtiYlSfeW/aKvyvq1YuZ5C1K9Wu0YtInA5zPtMO0KnNpBYX2pbZQkbQecR1rd6SdpEGlD4BcbGafZErI1gUck3UPL8wVzvHqvUhVn3QHzdznuT1G3V6zUEhEnlRg2exuTOquqZY+mFrej5MOmC/uSNi7cV8T8T7HTMoe5EfGSWp6jmWVGum4Z63XyzU7VPFUkRdeQ/t5mk5Y4SiNpH+COuieFsyTdQCrAbqvovZF2Ie2y60vLFYBXgCw1e1Uqlqi/TzrHVMDpkk6KiPOrHVl5imXoSr6/nIX17TiV9Ds/rhjPA5Ia3r+02RKyE6oeQEVGFW+/VHet7I7WNWNJOyonU5cEl6ni+pK/0XLnaP3tXIdNvxkRIanWyTvXsh3AVEmfAroWO5q/Sqp1KZ2kD5H+xtel5aad0n/PI2Lf4t0TlE5pWIW0K6xMhwBnSJpDWsa7A7g9QzJW26QxRhU2aa2ofq3mm6SjwZ4v4q5B+vkvtQlZJ/AEcLtSa53SCuvbExEzWr3QbPjGvKZKyCJDg8jOKCJyLRm1pW+OHjWdRZTYEPMduKzYFbSqpM+SEvJzM8X+CnAcKfm+hHRu6kIH3JfkPNJS5WRKeLBsi6QPAGtGxPW1axHxN0l7AZvTsv1JQ9V2URZLwtuR6nk+J6kfaQmt3Z2IDRzDlZI+TlrGqt9dWuYMeE0V9Ws1T5FmA2teAWZkiNvMshTWt2NG0aEhijrVr7LgOKmGaYqETAufgTX/LjI1bZQ0ISKGLepaSbG7A18n7Xw7spi52Cgiri07NnCHpM0j4qEMsZpeUeD7R1KvvZdJdWTfr6trK1VEzCElZMct6mNL8FJ9YpTJT0lLd609Qtptm+Ps0seL0oAVin/LF29Lp3TocnfgI6SdnQewFNevacHpJ08Dd0saS3pu2ZuSv++6MazIgo0cG5L+1q+PkjvWK2OD1LbkKqxvx+eB00i/d0+TXmh+qcPPeBearg9ZbkXbhe7AzaReQfUPHtdHhmObJP2R9Er9MxExsGhLcGeZfVvqYj8CvJ/UGPUN8hTWNzW1ca5ihph/ooNasTLrNCXVZkQOJO24uoqWNaKltZZRB730JD0QLQ+3b3Ts/yPNjPUktR64q/j3YGTqcyjpwYjYou7tSsBVEbFziTFHkpLgobQ87PoV4Hdl1mmqc5x+MpnU0mY10v/3JGBORBycIfZfgD2rqOOqL6yPiNIK66vUFDNkFfsc8DXS0UmTWZCQvUxqkZDDBhFxkKQRABHxmlothpdot0xxFtJGTVEtGczVEqAqd0n6QLHDNZefFW/3I+1kvqi4PYJU+1Gmn7e6Xd88suzWMh3NRJVdu/cZ0o7Ka0n1S3dH/iOrajvs5khaG3geKLVEosr6tRwJ12JQRMyRdDhwekT8RFKWPoNUW8d1KhkK69siaX3SDNm2pMeUO4GjozgXu1GckJUsIk4DTpP0lYg4vaJhvFnMitWKvDcgc4G9pF7U1ZhkUkVN0X4d3Z9pl+VHSLVE/yY9aOY4UuZvAJJ+EBH1D5J/klRqt/qKW8v8VdLJwHejbrlB0omkHXiliYiNlc5M/SBp9v3YYobqAdLuyw4PAG+QPxW7S39K2tUbZKpXrLJ+TVJP4FttxM7RCFjFbNHBLDiOLddzeZV1XFkK69vxB9IESm3zzidJNbINPa7JCVkmEXG6Mh/bVOd40o6vdSRdTOpHdWiGuBTFzT8nzRDOIs1WPcqCXjZlqqKmqKOzOXPtsqxsVhLoKWn92ivHouC8Z5kBi7qelyLivFbXvwJ0jYhTSwx/DKl26p+SphTXBpGWkY4oMS4wv3XNtUW7i62AHUiz8qNIPehKo9R0ekLRW/BKSdcCy+eapauifq3OxaRazT1I9UUjgWczxT4K+A7pXMeHi9mbm3MErriOK0thfTsUERfW3b5Iqb9nw4M0+mtaG9TOsU2R4dDlIv4apOlWkbqJP5cp7gOkJaO/RsSWkj4CjIiIIzPEHk3mmqLOpPWsZEQ8mSHmrqRi9tpUfn/gyIi4scSYU4EhretaikL3e3PUKxZPirUXGQ83eimjnZh7kWbHPlTEfpi0dHkHaYas9ARB0p0RsV3ZcdqJnb1+rS725IjYqha7uPa3iCj1kO+isH50RHyzzDgdxK+sjkvSmqRlw4+RZuj+AhxVaz1ScuzRwIukY5uCdGzTchRlR9Ggnp5NMUMm6baI2L6N3ZbZdllSzbFN9XYEtid9/8uQDp7O4a2IeF5SF0ldIuJmST/OFLs2nZytpkjS6cD/RcQrra5vDPw6Ij5WVuy6WJXNSkbEDcUu3o2LS3+P8vtCRVtFxhHxRq5aySIBKz0Ja+VQUvL1LWByFYXWwI2S9iclQrkf27LXr9Wp7WicWSyb/ofUJLdUkRqkZt2w08qpVFTHVUwilL5xoR0HFW8/1+r6KBrY07MpErKI2L54W9nRE1RwbFONpN+QdjpeUlz6nKSPRUTDt+224cXiletE4GJJsyjvUPEWKqot+i/pLMXvRcQflFqOnADsA3w70xh+QJoNbTErmSOwpEmk5piXRMTsHDGLuGtFxDOtr+WKX4WI6LBeMZOvkzYvzJX0Onlf5FZWvwb8UOk4uGOA00m75o/OFPv+oqj+cloW1ucoh6isjitXYX1bIlMvz6Zcssy5lFPXDmBlYDCpxiHrsU2SHgYG1l7BFrUfD0VE6TMmKnrmkKaYDyZ1ML84xzRzET970W9RN/Vr0v/52qQzO38YqUdX6SRNioihxXLxlpH6Fd0TEVtniP1+4DDSK8pJpDqmG8ucPZH0GVI9yTG0PPj4J8AZxa48W4oUj2HbRsQdxe3lyFi/ViVJbdUGRkSMauN6o2NfQToq69ekxOirwNCI+GSG2HeRlghrEwufBL4SEQ0trG8n9mfaut7oGvCmmCGrqWgp52eL/pDSTQP6AbUjhdYBSj9eBaCu8PNtSX8Gns+1tFFh0W/t++tGSkQfzZWMFWqzkreSf1byn8Bxkr5HKng+n/R/fz5wWqNqLVrF/L2kZ4GTgIGkn//DwPFlb+qQ1CMiXi52O7Y1ttLPi62apNWAAbR80VP2ztq3Jf2c1Ietds5i6TvHJX0rUpuJ01m4714ALwAXRcS/yhpDVHsaSJYGqe3IUljfjg/Uvb88MIz04q+hCVlTzZBVWWBeJUl/I/1C1ZKRD5Cme+dAObN0krYFRpMeoH4AXEg63L0LqUFt2ef8VdW08ruk2p7jIuKPkvqQHsB6Al+IiEfKil03hqpnJbcgzZLtTnrAvphUv/jpyNCMOCdJ10bEHpIeJz0h16/lRGTqeafU1qZfREzLEa8u7hGkXX99SRuWtiU1nS69/YNSa5EHyVi/JmnPiPiTUnPatqwBjIxyGwJvCJwJrBWp0fcWwF4R8cOyYnYGuQrrF3MsqwAXNvq5s9kSsiqXcto6vukl0rLOMWWug0vqcOdPlHDGZ1FL9H+kZOAcYLeIuKsobr8kIrZsdMw2xnB3RGxTTHXvRyr6nRoRA0qMeRqpJ1Xrov7dgF9EnpMZViXNWAD8I+cyjlIX8RdJO7GurC/ol3RVJ6l7WqpI2pM0E79sRKwnaTBwUqZyiIdIL/DuiojBxd/3iRFx0CI+tRGxX6GoXyMV+OesX+toXJ+LiLNL/Pp/Ix1ufnbtcVTS1IgYWFbMutiV1XEVL3rak+3FTzGWZUgnYjT08bypliypcCmHtO7+H1KDOZHWv99HWk48n9TYsRRlJFyLoVsUrQ4knRQRdxVj+XumjW+Q+jOtSsui39+WGTAijmrn+vWSSm0UqtSb5xzSBoLHSb9n60q6Gvh8pl14n2jvwXlpT8aK2dDaqRBA+Ut3hROArYFbiphTJPXPEBfg9Yh4XRKSliv+vjfKEbjKTVrFLNU3WLiv5EfLTMYK3SPinlaPo7mex7I0SG1LrsL6tqjl0XBdgU1ItcEN1WwJ2d6kV1JfY8FSTuldnQu7tio+PEfSXRFxktKZdKVpNTu3LKntxaslv5J8u+7911rdl2VaNiJ+ULybvWllO+Mpu8blu6T/23VqM3SSViY9gH6v+FcKLTh0mbYS7shztEpllFq5HEQ6VHx+n0HS7uKyzY2IlzK+0Kn3VPGi5xpgvKTZpBeeWVRRv1a4HDiL9AIvV7f4mueUTlupbdI6gHy79yur48pVWN+O+lrwucC/I+KpRgdpqoQsIl6V9D7Sq8kXgL/kqqshFTYfCFxR3D6gfmhlBm79SlLSPqSfQZkGSXqZNEuzQvE+xe1sRyip1ekIknL9AVdhP2Dr+g0EEfGKpC+SDiEuLSGj5TEqnwPKniVYSLHTbn8WnrXI8aJrH2CjDEl3W6ZK+hTQVakH3FdJ/clKFxG1mZITJN1MepFben0otF+/Rrlnl9bMjYgzM8Rpy5dIM+EbS3qaNBueqz/XzZKOpWUd159rm1pKruPKUljfllhwNNwapNMwXgcanpA1Ww3ZEcD3SWfMidQs9aSIOD9D7Nra+3akX+S7SH1rnga2iojbyh5Dq/HcFRHb5oyZmyo+HSE31XUNb+O+hyJi80zjuD9HjWAbcW8g1WW2OLs0IlofPl5G7OtJy7X/KztWG7G7A8cBO5Me1/4C/CAiXu/wE99bzI52lwbwckSUOnNUcf3aCaSd+lfTso1R6YXlkraKiMnF5p0uxYuuPSPiTxlid6Y6rlIK61vFuBY4NiKmSupNSgAnkZ5XzokGH8vWbAnZNOCDtVmxItu9IyKy1DxURS0PvO5C6ly/Y1R05Ekukh6lotMRJB1F6sH1CmlZY0vSH3aZRwg9QKpFbGvt6uYyd361Gsd9ETEkR6xWcbMUNreKWWt/0Id0huUEWj5BL63Jf0e7SwFWAs6NiNLKMSTdGxEfUDpDdJtIJzNMiQw7edtJTLIkJJLuI+3kfKi4/UlSYX3pdVydSVmF9a1iPBxFv86itGjjiPhMUQpye3svgN+tplqyJE0x1u9+ewWYUWZAddy3JtcDdv2B13OBJ0j1dEu7yk5HAEZFxGmSdiG1vDiMoklqiTFXIc0OtZWQNcMrrzskbV57ospkUvF2MsVxMrl1VGBeVsyI2KN422ahtdKZi1NJO63LUln9WpUF5qRylyskHUxqJ/MZ0uxo6aqs48pVWN/KW3XvD6M4CaKYlXy77U9595oiIasrOH4auFvSWNJ/7N6U3yi0dhr9pA4/qkRRbSPB7NTydIRHJGU/HYEFSdHuwAWRznwrteo6IvqX+fU7Uiwf1R4s3y+p1ni41oqg9AO+SU9OhxazF2/kiB2d4xSAygrM1c45hkVhfaktXiquX6ssMYmIx4pZsWtIEwo7R0TrjVNlqayOi0yF9a3MkPQV0mTOEIrfL6W+f8s0OlhTLFlKOr6j+yPixFxjyUnSZ4FbImJ6kQycRyp6/jdwaETc1+EXaMwYVgRei9TzbUPSodPXR8Rbi/jU9xIze9+1NsZwAWkZaz3SUlZX0v9FlQcDl0bSuh3dHxH/7uj+MsdQZuxWiWhbsUtPRCVNrur3qnjxU7M8abPQ5DJn5zpJ/drpdTfnJyYRcUA7n9KImK1/13qRaibfgDy/a22MqfQ6rjZi1grrn4yIySXH6kXqxNCbdAxbrZXTR0i13w09iacpErLOoIplBUlTSQ1w3yp2YR1DmtreknSszIfLil03hsnAh4HVSBsZJgFzIqL0XUGSfhwR317UtZJidyGdXfpYRLxYPIj0iYgsR1Y1M+U9q7YzJKInUFGBeRtjWQf4SUSUdph9Z6hfa2NMOQrMK/9day1THVfWwvoqNVVCJmkoaTdS6+aNOV7FPkBaVmi9A6y0DL++wFXSH4C7I+K04naWwutanGLad4Wini7LLry2vseOdiI2OHZbP9uXSNPsuZo4NhW1c1ZtrSg3Q/x1gQER8ddiSaNbtDqxoaS4lRWYtzEWkZ6gs+zobWcMXUkncpR+KkZdzNITk7pYGwBPFZsYdgK2AH4fES9miN1mHVdEHFtizKyF9VVqihqyOheTjpx4iJaNS3Ooom/N28UritmkKfWT6+5bIdMYJGk7Up+cw4trpf7eSfoC8EVgg7paJkg1ZbeXGbvOb0g1Bw+SXsEPLN5fQ9Lny9htuYilnGY46PoHpF5ULc6qzRG4KA84Elid9Mq9L+kF2LCyY1dZYN5qs1JtVviBTLErq19rlZh0ATal/ALzmiuBoZLeTypDGUfqoL97hthV1HFlLayvUrMlZM9GRCU7oYA/KTXozLms8H3S1G5XYFxEPAzza6xKP3uscBTwHeDqiHhYqR/bzSXH/ANwPXAKUP/K7ZWMSckTwOF1P/NNSS8GfgBcRTm7Lf8A7EGahV3ooGsg64yJUhf1dTIu074VEc9L6iKpS0TcrNRBP4cvkeqn7gYo6jZ75QhcZYE5LTcrzSWdU5vrRc83696fX79GnsawVSQmNW9HxFyldkanRsTpku7PETgyNUhtJWthfZWaLSE7XtJvWbhX0FUZYo8s3tY/iJT6JBkR1xbLKCtHxOy6uyaROiyXqlg62LO+riLSOYeltvqIdDzSS5K+C/y3fmpfUpapfdK0+sN1Y3pE0pbFDqlSAi6qFUEOkm4B9iI9tkwBnpX0t4j4ekef1yAvKp1VO5H8Z9W+ERFv1v5vJXUjX6uRKjuYV7bLNCLq2/nMr18rM6ak5YHPA+8nrbScV0EJwluSRpDaXdR+BqUmJh3VcUkqu47rcFJh/ceAg+oev7cltRIqXVEDfiawVkQMlLQFsFdE/LChcZqshuwi0i6/h1mwZBkRMarEmMu0t6NQ0vrRzkHMSwtJN5W5cWERsaeQmuD2J3UvH0c63qb0qX1JfyQdz3VpcekgYE3g08BtEfGB9j63QfErOei6Vh+odCrGOhFxfMa6vRVJ56Z2YcFZtRdHhuPRJP0EeJH0JPkV0pL5IxFxXNmx2xhLjgLzvYG+EXFGcftuUr89gG9HxOVlxe5gTKXXrxV/128BtwK7kWbGjiorXjtj2JSUFN4ZEZdIWo+UqIwuMWbT1HG1RdLfSJMpZ9fqn1VCI+pmmyEbVEGx6ThJe0fEm/UXiwx7HClZWJrdL2kcqVfSq7WLmWYlK5vaBw4lPSl/jbR0eBtpl+1bwEfKDKxqD7ruVryCPpC0gSanXsDMSEcGjSmWNNYCcpxXeyzplfxDpLM8ryP1BavCHNKB22X6FvDJutvLkWbqViTNWpSekFVUv7Zp7TlE0nmU38dyIRHxCHWrDBHxOFBaMlZomjqudnSPiHtarW40fGa02RKyuyRtWvxC5zIZuF7prLE5AMXy2UWk7u1Lu9VJT4j1s2RBqqMqW/ap/ZpIjRp/XvxrrezzDvehuoOuTyTNRt4WEfcWNYPTM8W+HPhg3e15xbVSZyMBIvXZuwa4JiKeLTtevYoKzJeNiPpTTm4rZiKfL2Yqc6iifm1+YlK82Cs53MK0oN1HCyXvqm2aOq52PFfsbg0ASQdQwgkwzbZk+ShpB1S2Tt5F3OOAXUlT3LsAvwT2i4hSu/dL2jgi/t5OCwYiQ2PYKlUxtV8X+0PACSy8bJjjrLtKDrouaga/GhG/zBm3Lv5C5xhKeiBKPMOzWCY7Hvgy6fFEpETw9Ig4qay4rcZQ3wg5S4G5pH9GxPvbue9fEbFBmfGrImkeC2b6RdqtPocFzyU9MoxhjbqbywOfAFaPiO+XGDNrg9TOpnhheQ7pBd9sUg5xSEQ80dA4TZaQZe/kXRf766SlDAG7R8Q/M8Q8JyKOVDpWpLXIUduVqxiys5H0d+BoFu47V9rymTrBQdeSbo6IUpdkO4g9npQIjStu701KEEtrPSHpaFK7gSOLpaPag/eZwA1lJqdVFphLuph08sS5ra5/Dtgpym0M2+nq16om6baI2L7qcZSpMzyXFLO/XaKk/oLNlpD1a+t6lNvJu7acIOBDwD+B/9bFznbkRBVyFUO2E3sAqfXFprTs3J5jluruiNim7DitYo7s6P4cO+IknUwqpv8jLWsGcxzTtQGp1+DaxaWngM+U+eKnqEkcHhHPtbreE7gxSmyAXGWBeTFjcg0p4a/9325FqiXbJyKeKTH27cAna0umxeadYRT1a2Um4J1BqxWPLqSNS18ocya4M6j4uWQ50rGD/Wm54tHQWfBmqyH7MwuSo+VJ5wxOA8rs5P2zdt7PStJAFk5McvQpylIM2Y4LSMtJvyQV0h8GCx2zUpabJf2UVCtXP0tVWmKSI+FaDLUarvoHqiBDb6iI+BewrVLrC5X1KraVZVonY8VYnlXq3l6mygrMI2IW8EFJH2XB4+efI+KmDOE7Q/1adpJujIidaVmXOpfU8/DASgaVV5XPJWNJJ61Mpu7xvNGaKiFrvcOyeKXxuZJjln6Q9aIoHa6+Eykhu470avo2MvQpIlMxZDtWiIgJklQsS58g6VZSkla22uzY0LprpSYm6gQHXVe1XAkg6UekcxRfLG6vBhwTEd8tMeyb7/K+Rqi8wLxIwHIkYfVWazWGL9fd7MnSqydU/je2fLGLuQpVPpf0jYhdyw7SVAlZaxFxn6TSd2B1AgeQaoruj4jDJK1Fvi35XyIVQ24s6WmKYshMsV9XOuR7uqQvA0+TWiOUrqIHzT0qiNlC8bv1I2DtiNit2FixXUSclyH8blF3oHREzJa0O1BmQjZI0sttXK/NwpepPraAFYrb2QrMK3K3pM+2U7+WvQ1FRqsULXzaFHlaCU2V9AxpmXwiqQfZSxniQrXPJXdI2jwiHiozSLPVkNV3C+9C2r67RkTsUtGQspB0T0RsLWkyaenuFdLhu1kOXS7GUGoxZDsxPwA8CqxKOrJoFdIMyl0lxjwkIi5q9bs2X0T8oqzYrcZR1UHX15OWio+LiEFKHevvbz07XVLsB4EPRNHuo/i+J+X8PbfyVVm/ViVJz5OWztqaCo0oscF5q3H0Az5MqoneHXix9e7mkuNX8VzyCGnzTKkdGppthmzluvfnkmrKrqxoLDlNkrQqqZnfZFIfrCyvJFsnJsWyykvA5IiYUmbsiLi3ePd/5Ov5VqthWbmN+7K8+lGFB10Da0bEZZK+A/OX0uYt6pMa5CJggqQLSD/rUUBnqKuzBqq4fq1K/86VdLVHUl9SIvZh0qrLw6TylxyxWxTW15boM7WX2S1DjOaaIatSsevq2yxcWJ/1WCFJ/YEekenAZ0l/INVR/am49HHgXtIRVpdHRMPPnpN0akR8TS0bZtYE6Uijs8uYKZPUN9rpAaXUHPhPbd3X4DFMoTjoum430kOZZqluIT1ojo+IIZK2BX4cETt2/JkNi78r6cw7kXY5/iVHXLOyqTiWrOIxvE16/P5RRIzNHPsGFhTW17cSaqv5dqNjZ+nQ0BQzZEpH97QrU+uJi0mtAD5O6h00EsjW0VutzjaUtENkONsQWAMYEkWT0mKDwRXADqQ/rDIOA76weNvertY1gfNJyXGjTZC0S7RqGCjpMFItU+kJGdUedP110pFgGxTtCXqSahhzeRSYWyzVdpe0cs6lDbMSfbrqAQBbAtsDn5J0LOkUjr9lqhHNUljfjiwdGpoiIQO2A2YAlwB3k6/1Qb01IuI8SUcVOy//VvRVKZ2qPduwHy13m70FrBsRr0kqZftwREwu3rb785VU1g64o4HxknaPiOlFrO8AnwKyzBKRfrf+j1TkPZx0pmaORLC2UWZHYCPS39m0iHhrEZ/WEG0s1fYh31KtWakiYmonGMMDkv4F/Iu0bHkI6cV1joQsS2F9W3J1aGiWhOx9wHBgBOmJ8c+kc88ezjiG2pPSTEkfB/5Dqu3JYR+qO9vwD6QzRGvT23sClxSFmaWeKaoOGsOWtXQYEdcVieb1kvYBjiCdpbhDRMwuI2YbKjvoWtInSB3qH5b0XWCIpB+W2X+tzpcolmoBImJ6UQBuZg0gaRJp88QdpNqxHSLDSTeF7YFDlc7yzHb0YVvK6tDQdDVkRWHgCOCnwEkRcXqmuHuQtgqvA5wO9ABOyFRTVMnZhnXxh5IKQUVq4ljqGZ51cW9jQWPYPSkaw0ZE6X3IJG1P2gl2B3Bg7t49Rc0ikf+g6wcjYovi+z+FtGz8f5Hh1AIVpyPUam2Kpdr7qnjANlsaSeqZ+zGlLnbVRx/WlNahoVlmyGqJ2MdJyVh/4FekLuq5zC76tbxEaj2B0gHUOcwBpkjKfrZh4X7SjGCtfq1fo4sh25G9MaykV1hQa7AcablsllJBV6m9oYoYLQ66LnY4ZjvomgVL4h8HzoyIsZJOyBS7sqVas7JJuiwiDtTCDaBzzhS9KekXpGVKgL+RJjZy9CKrcvYoS4eGppghkzQGGAhcD1xaxVq8pPsiYsiirpUUu80zDiPP2YZfISUJz5CerLM9eBRF5R8mbSK4idQYdnREbFR27CqowoOu68ZwLenn/DFSb6jXgHsiwzl7Sk2ADwd2Jv2e/QX4bTTDg5wt9ST1joiZFc8UXQlMZUE7mU8DgyKi3Ya1DYxdS0RbFNaX3WdQ0pakmtSHI+LRUmM1w2NVsVW3dtBxW68sypy12I50vt/XSEtnNT2AfXM8UVVJ0j+BbSKdNZc7dluNYX8cEXfnHksOqvCg67pY3YFdgYeKGq7ewOYRcWPZsYv4lSzVmjUDSVNaN4Ft61qmsQwBPhcRpR1/KOn7pI0Lk0nH4Z0SrU6IaKQuZX3hziQiukTEysW/HnX/Vi4zGSssC6xEWq5bue7fy2RqByDpQ5LGS/qHpMckPS7psRyxSbtbcx2t0UJE3BsR/4uIpyLiMNIBvO+vYiyZtHvQNVDqQdeSan9HywO3kA56Xp20RF5qzaCSEyQ9B/wdmCbp2eLB1GypImk/SdMlvSTpZUmvqO3ju8rwWlEfWhvLh0iz4NkVG4XKPvrwIGBwRIwoYh1ZZrCmqSGrSl2Li99l3I3S2nmkdgwtGupl8hhwi6Q/07J+rbQjhIrk4EuktgfjgPHF7W8AD5B6wi2Nqjzo+g+kszQns2BZoSaA9UuM/TXSppEPtF6qlXR0jqVas4x+AuxZ9vJZOz4P/F7SKqS/8ReAQ3MEbqewvuyZ8NcjYg5ARDxflEWUpimWLDuDYinlW6RGclk79dd2n5Udp53YbRbQR8SJJcYcC8wG7iQV1a9Gmqk8Kko+rqlKRQH/q23dBSwfEWXPkglYJ9OGjfq4lS/VmuUi6faIyLUhrL0x9ACIiFwzc62fS+YCTwBXlrmDXdKLLOjXKVJN8vz+ndHgpvJOyDKRdCOpU/83qOvUHxHfzhB7NNCVtKu0fpYqR2+o2hhWjIi2koUyYs0/JkhSV+A5oF+4Y3vpJE2OiK0yx5waEQPf6X1mSxJJtcL5HUm9Na+h5eN56V0D1Oo8ybrYpe7izllY3ypuh828o4Pm4++GlyzzqaxTP6kYEdKZkjUB5Jid2460ZLoS0E/SIFIh5hdLDDu/M3xEzJP0uJOxbO6S9IFYcLB7DlUu1Zrlsmfd+3NIu4lrgjxtnMay4DzJLI3GWxXW/0RSqYX19RqdcC2KZ8gykXRXRGwr6S+kHmj/Aa6IiA0qHlqpJN1N2rwwLhYcdF3qrEWrpTsBK5AewErfVdvsJD0CbAj8m/R/UHqbk6qXas2aRRUzzpIeJtWHzpG0BqmFT9nF/JXwDFk+PywKIY9hQaf+r+UILGkt4EfA2hGxm6RNge0iz4GwRMQMqcXxoaVuLIiIrmV+fevQbrkD+v/bmknRV/OoiHixuL0a8POIGJUhfBXnSWYtrK+SE7J8psbCnfpzZfm/Ay4Ajitu/4NUz5YjIZsh6YNASFoW+CqpN5gthSLi30Xd3lr48cWsDFvUkjGAiJhd1FjlUMV5khtIGle8r1a3G15YXyU/YOZzpaS9IuJpAEk7AGcAm3f8aQ2xZkRcJuk7ABExt1jmyeHzwGmkFhRPATeSWlDYUqjVyQxvF5cD8HmSZo3RRdJqETEboOj3l+u5PPsMOLB3q9s/yz0ASX9i4aObXiL1WDy7UTs9nZDl83ngGkl7kvqn/Ih0zE0OrxZr7wEgaVsyNWstWhEcnCOWdQpHARtVcTKDWZP4OWnp8Iri9ieAkzPF/ljrUpdiF/+xZQXMXVjfjseAnsAlxe2DSC86NwTOJR0h9Z45IcskIu6V9FXSDNHrpL5JuY53+TqpQeoGSuc79qTkUwIknU4Hh8FGvoPNLa/KTmYwawYR8XtJk1iwS36/iHgkU/gDJL0eERcDSPoNsFym2FXaMiJ2qLv9J0kTI2KHYtNBQzghK1kbU53dSU9Y50nKsv4dEfcV/VQ2Iq3BT4uItxbxae9VqcflWKeV/WQGsya0DEX9FiUfi9bKfsA4pfOhdwNeKLmFUWfRU1K/WtNrSf2ANYv7GtZaxwlZ+bKvd7djaxY08xtSJIO/LytYRIwp62tbp/Zk8W/Z4p+ZNZCko4DPAleSkrKLJJ0TEaeXGHP1uptHkJrS3g6cJGn1iHihrNidxDHAbZL+RfqZrwd8UdKKQMOe69yHrAlIupDU5XgKC1pORJnLhu0UQc63NO2MMTPLRdKDpLZFrxa3VwTuLLnX3+MsOKN2obNqI6LMs2prY8hSWN9B/OWAjUnf+9/LiOcZspJJeoWWv0T1v9C5mpQOBTaNvNl3Z5kZtIwk3UwbiXiOM1vNmoRo2ctxHi0TpIaLiPXK/PqLKUthfQe2YsEq0xZlrDI5IStZRKxc9RiAqaSzz2bmCthJdsZYft+oe3950rl3cysai9nS6ALgbklXF7f3IU9PSSR9Cbi4VVPaERHxmwzhsxTWt6W9VSagoQmZlywzKs5x/HBxc2JEPFhyvNoU78rAYOAeWhZal75sKGkAcAqwKekJuha79Clu6xwk/S0iOjyk18w6JqlvRDxVvD+E1KRVwESgb0T8KcMYpkTE4FbX7q8di1dy7EeBXVoV1t8QEZuWPYYidumrTJ4hy6SuELN2AOzFZRdi0jmWDS8gNQr9JemEgsMoeXrdqtOq+LcLaZr/fRUNx2xpMkHSLhHxRETcB9wHIGkU6RSW0hMyUlNa1RKT4lSOXJt3shTWtyPLKpNnyDKpqBDz/cBaEXF7q+s7AE9HxL/Kil0Xa3JEbCXpoYjYvLh2a0R8eFGfa0ueVsW/c4HHgZMi4rZKB2a2hJO0O+nUk90jYnpx7VhS4+3darNnJY/hp6Q6qrNIf+efB2ZExDFlxy7il15Y307cm8mwyuQZsnyyF2ICpwL/18b1OcV9e5YcH+D14jDY6ZK+DDwN9MoQ1yrQSYp/zZY6EXGdpDeA6yXtQ2o/8QFgh9oxShl8G/gc8AXS89eNwG8zxYYMhfXtOCFDDM+Q5SLp68BIoL4Q83cRcWqJMadGxMB27ps/Y1Wm4gD1R4FVgR8AqwA/iYi7yo5t+RT/zzMi4r/F7c+QCvr/DZzQBH2KzLKQtD2pD9gdwIG5ZomqVkX7ptyckJWsykJMSf+MiPe/0/vM3ilJ95HOuXuhWBK/FPgKaZp/k4go9agus6VdXQslkY4reosFKy1ZWijVlSS0kKkPWZbC+lYxb4uI7dtrX9Xon7mXLMtXZSHmvZI+GxHn1l+UdDgwucS49bE2BL4JrEvd75v7Ui11utbNgh0EnBMRVwJXSppS3bDMlg6dpIXS0Lr3lycdbL56Ox/baFW0b9q+eJvlZ+8ZspJVWYgpaS3SEumbLEjAhpJ2xexbW14qk6QHSAWgk6mroYuILAmh5SFpKjA4IuZK+jtwZERMrN3X3tK5mS3ZarNIGeJkKaxvJ/YGwFMR8YaknYAtgN/X+rE1imfISlZlIWZEPAN8UNJHgNoT4p8j4qYy47YyNyLOzBjPqnEJ8DdJzwGvAbfC/J2+L1U5MDNrjKLspqYL6QV+rpm7EzLFacuVwNDi8ew8YBzwB2D3RgbxDFkmzVaIWdeP6qvALNJMXf2rGhd5L2UkbQv0Bm6sa++yIbBSsVxvZkuwYpaqptbW5mcR8Y+KhpSFpPsiYoikbwKvR8TpZTSjdUJWss5QiFmFVv2oWstyGK2ZmZVL0tdK7haQtbC+nTHcTWoVdRywZ0Q8XkYphhMyMzMze1ckPRkR/aoeR5kkbUpqgntnRFwiaT3goIgY3dA4TsisDJIOIf1+Xdjq+meBVyPiD9WMzMzMGkXSjIhYJ0OcLIX1VXJCZqWQdD9p48Irra73AG6OiK2qGZmZmTVKrhmyon3OUFKn/r+QCus3ioiGFta3inlZRBwo6SHaXi5t6NGH3mVpZenaOhkDiIiXJS1TxYDMzOyda6N+a/5dwAqZhvF20VZnX+DUWmF9yTGPKt7uUXIcwAmZlWcZSSvWdtvVSFqZ1AfNzMyWAJ2kKe1bkkaQjiCsncNc6ov7iJhZvP13/XVJXYFPko6Ga5gujfxiZnXOA66Q1L92oXj/0uI+MzOzxXUYsB1wcrHLcT3gojIDSuoh6TuSfi1pZyVfAR4DDmx4PNeQWVkkfR74DrASabr7VWC0G8WamVlnJ2ksMBu4ExgGrEZa4TkqIqY0PJ4TMiubpJVIv2sL1ZSZmZm1J3dhfavYD0XE5sX7XYHngH5lPZe5hsxKFxH/q3oMZma2RMpaWN/KW7V3ImKepMfLnFjwDJmZmZktUWqF9RFxcYkx5pFKbWDBjtI5lHRKgBMyMzMz65SK3pVfAvqQeo+NB74MfAOYEhF7Vzi8hnJCZqWQtF9H90fEVbnGYmZmS6bchfVVckJmpZB0QQd3R0SMyjYYMzNbIuUurK+Si/qtFBFxWNVjMDOzJV7WwvoqeYbMSifp48BmwPK1axFxUnUjMjOzJUHuwvoqeYbMSiXpLKA78BHgt8ABwD2VDsrMzJYIEdG16jHk4hkyK5WkByNii7q3KwFXRcTOVY/NzMyss/BZlla214q3cyStTaoHWK/C8ZiZmXU6XrK0sl0raVXgp8B9pKMvzq10RGZmZp2MlywtG0nLActHxEtVj8XMzKwz8ZKllUrSJElfkrRaRLzhZMzMzGxhTsisbJ8E1gbulXSppF0kqepBmZmZdSZesrQsJHUB9gDOBN4GzgdOi4gXKh2YmZlZJ+AZMiudpC2An5MK+68k9SJ7GbipynGZmZl1Ft5laaWSNBl4ETgPODYi3ijuulvShyobmJmZWSfiJUsrlaT1I+KxqsdhZmbWmXnJ0sr2vKRfFLstJ0n6uaRVqh6UmZlZZ+KEzMp2PvAKcGDx72XggkpHZGZm1sl4ydJKJWlKRAxe1DUzM7Nm5hkyK9trkrav3SgK+V/r4OPNzMyajmfIrFSSBgNjgFUAAS8AIyPiwSrHZWZm1pk4IbMsJPUo3p0DHBQRF1c5HjMzs87ES5ZWCkk9JH1H0q8lDScV9n8G+CepuN/MzMwKniGzUkgaC8wG7gSGAasBywJHRcSUCodmZmbW6Tghs1JIeigiNi/e7wo8B/SLiFeqHZmZmVnn4yVLK8tbtXciYh7wuJMxMzOztnmGzEohaR7wau0msAKpoF9ARESP9j7XzMys2TghMzMzM6uYlyzNzMzMKuaEzMzMzKxiTsjMzMzMKuaEzMzMzKxiTsjMrFOTtKqkL1Y8hs9L+kyVYzCzpZt3WZpZpyapP3BtRAyseixlktS16NlnZk3IM2Rm1tmNBjaQNEXST4t/UyU9JOkgAEm9JU0sPmaqpA9L6irpd3Ufe3RbX1xSL0mTi/cHSQpJ/Yrb/5LUXdIJkr5RXLtF0o8l3SPpH5I+XFw/VNJVkm6QNF3ST+pi7CzpTkn3Sbpc0krF9SckfV/SbcAnyvwhmlnn1q3qAZiZLcKxwMCIGCxpf+DzwCBgTeBeSROBTwF/iYiTi6O6ugODgT61mTVJq7b1xSNilqTlJfUAPgxMAj5cJEmzImKOpNaf1i0itpa0O3A88LHi+mBgS+ANYJqk04HXgO8CH4uIVyV9G/g6cFLxOa9HxPbv4edjZksBJ2RmtiTZHrikWNp7RtLfgA8A9wLnS1oGuCYipkh6DFi/SIr+DNzYwde9A/gQsAPwI2BX0qkSt7bz8VcVbycD/euuT4iIlwAkPQKsC6wKbArcXiR2ywJ31n3OHxf9bZvZ0s5Llma2JFloqgogIiaSkqmngQslfSYiZpNm0m4BvgT8toOveytpdmxdYGzxedsDE9v5+DeKt/No+cL2jbr3a/cJGB8Rg4t/m0bE4XUf9ypm1vSckJlZZ/cKsHLx/kTgoKI+rCcpCbtH0rqk5cVzgfOAIZLWBLpExJXA94AhHcSYCBwCTI+It4EXgN2B2xsw/ruAD0l6P0BRk7ZhA76umS1FvGRpZp1aRDwv6XZJU4HrgQeBB4AAvhUR/5U0EvimpLeA/wGfAfoAF0iqvfD8TgcxniiWE2szYrcBfYtZtvc6/mclHQpcImm54vJ3gX+8169tZksPt70wMzMzq5iXLM3MzMwq5iVLM2saks4g7aasd1pEXFDFeMzMarxkaWZmZlYxL1mamZmZVcwJmZmZmVnFnJCZmZmZVcwJmZmZmVnFnJCZmZmZVez/AUpa1bfNidhXAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "ax=sns.countplot(x='toss_winner', data=df2,\n",
    "            order=df2.toss_winner.value_counts(ascending=False).index)\n",
    "plt.xticks(rotation=90)\n",
    "\n",
    "abs_values = df2['toss_winner'].value_counts(ascending=False).values\n",
    "\n",
    "ax.bar_label(container=ax.containers[0], labels=abs_values);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0aa1ed52",
   "metadata": {},
   "source": [
    "## What is the probable decision of toss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "1aac5cbf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['field', 'bat'], dtype=object)"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.toss_decision.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "c136d820",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "field    599\n",
       "bat      351\n",
       "Name: toss_decision, dtype: int64"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.toss_decision.value_counts(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "f0c6a914",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAEHCAYAAABBW1qbAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAAsTAAALEwEAmpwYAAAWdElEQVR4nO3df7RdZX3n8fcniYAaNTAkTEjA0E5aJgSSyjWOQF0oIjij8qPFRluNgFIsirqgCl1rCgNmLbqw47AEWqOCER2ZKEVSf2BiFF1SNSQ1SAhFoyCkRBIRBUGBhO/8cXZ2Dzc34Qqce8K979dad+29n/08e39v1s39nP3sc/ZNVSFJEsC4fhcgSdp1GAqSpJahIElqGQqSpJahIElqTeh3AU/H3nvvXTNmzOh3GZL0rLJ69eqfV9XkofY9q0NhxowZrFq1qt9lSNKzSpKf7mif00djyIwZMzj44IOZO3cuAwMDANx88828/OUv5+CDD+b1r389DzzwAACPPvooJ598MgcffDBz5szhhhtu6GPlkkaKoTDGfOMb32DNmjXtFdbb3/52LrroIm655RZOOOEELr74YgA+9rGPAXDLLbewfPlyzjrrLB5//PG+1S1pZBgKY9ztt9/OK17xCgCOPvporrnmGgDWrVvHUUcdBcCUKVOYNGmSU3XSGGAojCFJeM1rXsOhhx7KokWLAJg9ezZLly4F4HOf+xx33303AHPmzOG6665jy5Yt3HHHHaxevbrdJ2n0elbfaNbv5sYbb2Tfffdl06ZNHH300Rx44IFcccUVnHnmmVxwwQW84Q1vYLfddgPglFNO4bbbbmNgYIAXv/jFHHbYYUyY4I+LNNr19H95kknAx4HZQAGnALcD/w+YAdwJvLGq7m/6nwucCmwFzqyqr/ayvrFm3333BTrTQSeccAIrV67k7LPPZtmyZQD88Ic/5Etf+hIAEyZM4MMf/nA79rDDDmPmzJkjX7SkEdXr6aNLgOur6kBgDnAbcA6woqpmAiuabZLMAuYDBwHHApcnGd/j+saMhx56iAcffLBdX7ZsGbNnz2bTpk0APP7443zwgx/k9NNPB+Dhhx/moYceAmD58uVMmDCBWbNm9ad4SSOmZ1cKSV4IvAJ4G0BVPQo8muQ44Mim22LgBuADwHHA1VX1CHBHkvXAPOA7vapxLLn33ns54YQTANiyZQtvfvObOfbYY7nkkku47LLLADjxxBM5+eSTAdi0aRPHHHMM48aNY9q0aVx11VV9q13SyEmv/p5CkrnAImAdnauE1cB7gH+vqkld/e6vqj2TXAp8t6o+3bR/AvhKVX1+0HFPA04D2H///Q/96U93+BkMSdIQkqyuqoGh9vXynsIE4CXAu6vqe0kuoZkq2oEM0bZdYlXVIjphw8DAwNNOtEP/+lNP9xAahVZf/NZ+lyD1RS/vKWwANlTV95rtz9MJiXuTTAVolpu6+u/XNX46cE8P65MkDdKzUKiqnwF3J/nDpukoOlNJS4EFTdsC4LpmfSkwP8nuSQ4AZgIre1WfJGl7vX7j+buBzyTZDfgJcDKdIFqS5FTgLuAkgKq6NckSOsGxBTijqrb2uD5JUpeehkJVrQGGuplx1A76LwQW9rImSdKO+ZgLSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktXoaCknuTHJLkjVJVjVteyVZnuRHzXLPrv7nJlmf5PYkx/SyNknS9kbiSuGVVTW3qgaa7XOAFVU1E1jRbJNkFjAfOAg4Frg8yfgRqE+S1OjH9NFxwOJmfTFwfFf71VX1SFXdAawH5o18eZI0dvU6FApYlmR1ktOatn2qaiNAs5zStE8D7u4au6Fpe4IkpyVZlWTV5s2be1i6JI09E3p8/MOr6p4kU4DlSf5tJ30zRFtt11C1CFgEMDAwsN1+SdJT19Mrhaq6p1luAq6lMx10b5KpAM1yU9N9A7Bf1/DpwD29rE+S9EQ9C4Ukz0/ygm3rwGuAtcBSYEHTbQFwXbO+FJifZPckBwAzgZW9qk+StL1eTh/tA1ybZNt5/m9VXZ/kJmBJklOBu4CTAKrq1iRLgHXAFuCMqtraw/okSYP0LBSq6ifAnCHa7wOO2sGYhcDCXtUkSdo5P9EsSWoZCpKklqEgSWoZCpKklqEgSWoZCpKklqEgSWoZCpKklqEgSWoZCpKklqEgSWoZCpKklqEgSWoZCpKklqEgSWoZCpKklqEgSWoZCpKklqEgSWoZCpKklqEgSWoZCpKklqEgSWoZCpKklqEgSWr1PBSSjE/y/SRfbLb3SrI8yY+a5Z5dfc9Nsj7J7UmO6XVtkqQnGokrhfcAt3VtnwOsqKqZwIpmmySzgPnAQcCxwOVJxo9AfZKkRk9DIcl04H8AH+9qPg5Y3KwvBo7var+6qh6pqjuA9cC8XtYnSXqiXl8p/B/g/cDjXW37VNVGgGY5pWmfBtzd1W9D0yZJGiE9C4UkrwM2VdXq4Q4Zoq2GOO5pSVYlWbV58+anVaMk6Yl6eaVwOPCGJHcCVwOvSvJp4N4kUwGa5aam/wZgv67x04F7Bh+0qhZV1UBVDUyePLmH5UvS2NOzUKiqc6tqelXNoHMD+etV9RfAUmBB020BcF2zvhSYn2T3JAcAM4GVvapPkrS9CX0450XAkiSnAncBJwFU1a1JlgDrgC3AGVW1tQ/1SdKYNSKhUFU3ADc06/cBR+2g30Jg4UjUJEnanp9oliS1DAVJUstQkNR3v/3tb5k3bx5z5szhoIMO4rzzzgPg/PPPZ9q0acydO5e5c+fy5S9/GYD77ruPV77ylUycOJF3vetd/Sx91OnHjWZJeoLdd9+dr3/960ycOJHHHnuMI444gte+9rUAvO997+Pss89+Qv899tiDCy+8kLVr17J27dp+lDxqeaUgqe+SMHHiRAAee+wxHnvsMZKhPs/a8fznP58jjjiCPfbYY6RKHDMMBUm7hK1btzJ37lymTJnC0Ucfzcte9jIALr30Ug455BBOOeUU7r///j5XOfoZCpJ2CePHj2fNmjVs2LCBlStXsnbtWt75znfy4x//mDVr1jB16lTOOuusfpc56hkKknYpkyZN4sgjj+T6669nn332Yfz48YwbN453vOMdrFzpQw56zVCQ1HebN2/ml7/8JQC/+c1v+NrXvsaBBx7Ixo0b2z7XXnsts2fP7lOFY4fvPpLUdxs3bmTBggVs3bqVxx9/nDe+8Y287nWv4y1veQtr1qwhCTNmzOCjH/1oO2bGjBk88MADPProo3zhC19g2bJlzJo1q4/fxehgKEjqu0MOOYTvf//727VfddVVOxxz55139rCiscvpI0lSyysFaRd11wUH97sE7YL2/9tbenr8YV0pJFkxnDZJ0rPbTq8UkuwBPA/YO8me/MefzHwhsG+Pa5MkjbAnmz76S+C9dAJgNf8RCg8Al/WuLElSP+w0FKrqEuCSJO+uqo+MUE2SpD4Z1o3mqvpIksOAGd1jqupTPapLktQHwwqFJFcBvw+sAbb93eQCDAVJGkWG+5bUAWBWVVUvi5Ek9ddwP7y2FvjPvSxEktR/w71S2BtYl2Ql8Mi2xqp6Q0+qkiT1xXBD4fxeFiFJ2jUM991H3+x1IZKk/hvuu48epPNuI4DdgOcAD1XVC3tVmCRp5A33SuEF3dtJjgfm9aIgSVL/PKVHZ1fVF4BX7axPkj2SrExyc5Jbk/yvpn2vJMuT/KhZ7tk15twk65PcnuSYp1KbJOmpG+700Yldm+PofG7hyT6z8Ajwqqr6dZLnAN9O8hXgRGBFVV2U5BzgHOADSWYB84GD6Dxr6WtJ/qCqtu7oBJKkZ9Zw3330+q71LcCdwHE7G9B80O3XzeZzmq9qxh3ZtC8GbgA+0LRfXVWPAHckWU9niuo7w6xRkvQ0DfeewslP5eBJxtN5uup/AS6rqu8l2aeqNjbH3ZhkStN9GvDdruEbmrbBxzwNOA1g//33fyplSZJ2YLh/ZGd6kmuTbEpyb5Jrkkx/snFVtbWq5gLTgXlJZu/sNEMdYohjLqqqgaoamDx58nDKlyQN03BvNF8JLKUz1z8N+OembViq6pd0pomOBe5NMhWgWW5qum0A9usaNh24Z7jnkCQ9fcMNhclVdWVVbWm+Pgns9GV6kslJJjXrzwVeDfwbnXBZ0HRbAFzXrC8F5ifZPckBwExg5e/yzUiSnp7h3mj+eZK/AD7bbL8JuO9JxkwFFjf3FcYBS6rqi0m+AyxJcipwF3ASQFXdmmQJsI7OzewzfOeRJI2s4YbCKcClwIfpzPP/C7DTm89V9QPgj4Zovw84agdjFgILh1mTJOkZNtxQuBBYUFX3Q+cDaMCH6ISFJGmUGO49hUO2BQJAVf2CIa4CJEnPbsMNhXGDHkexF8O/ypAkPUsM9xf73wP/kuTzdO4pvBHn/iVp1BnuJ5o/lWQVnYfgBTixqtb1tDJJ0ogb9hRQEwIGgSSNYk/p0dmSpNHJUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVKrZ6GQZL8k30hyW5Jbk7ynad8ryfIkP2qWe3aNOTfJ+iS3JzmmV7VJkobWyyuFLcBZVfVfgf8GnJFkFnAOsKKqZgIrmm2affOBg4BjgcuTjO9hfZKkQXoWClW1sar+tVl/ELgNmAYcByxuui0Gjm/WjwOurqpHquoOYD0wr1f1SZK2NyL3FJLMAP4I+B6wT1VthE5wAFOabtOAu7uGbWjaJEkjpOehkGQicA3w3qp6YGddh2irIY53WpJVSVZt3rz5mSpTkkSPQyHJc+gEwmeq6p+a5nuTTG32TwU2Ne0bgP26hk8H7hl8zKpaVFUDVTUwefLk3hUvSWNQL999FOATwG1V9b+7di0FFjTrC4DrutrnJ9k9yQHATGBlr+qTJG1vQg+PfTjwFuCWJGuatr8BLgKWJDkVuAs4CaCqbk2yBFhH551LZ1TV1h7WJ0kapGehUFXfZuj7BABH7WDMQmBhr2qSJO2cn2iWJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlSq2ehkOSKJJuSrO1q2yvJ8iQ/apZ7du07N8n6JLcnOaZXdUmSdqyXVwqfBI4d1HYOsKKqZgIrmm2SzALmAwc1Yy5PMr6HtUmShtCzUKiqbwG/GNR8HLC4WV8MHN/VfnVVPVJVdwDrgXm9qk2SNLSRvqewT1VtBGiWU5r2acDdXf02NG3bSXJaklVJVm3evLmnxUrSWLOr3GjOEG01VMeqWlRVA1U1MHny5B6XJUljy0iHwr1JpgI0y01N+wZgv65+04F7Rrg2SRrzRjoUlgILmvUFwHVd7fOT7J7kAGAmsHKEa5OkMW9Crw6c5LPAkcDeSTYA5wEXAUuSnArcBZwEUFW3JlkCrAO2AGdU1dZe1SZJGlrPQqGq3rSDXUftoP9CYGGv6pEkPbld5UazJGkXYChIklqGgiSpZShIklqGgiSpZShIklqGgiSpZShIklqGgiSpZShIklqGgiSpZShIklqGgiSpZShIklqGgiSpZShIklqGgiSpZShIklqGgiSpZShIklqGgiSpZShIklqGgiSpZShIklqGgiSpZShIklq7XCgkOTbJ7UnWJzmn3/VI0liyS4VCkvHAZcBrgVnAm5LM6m9VkjR27FKhAMwD1lfVT6rqUeBq4Lg+1yRJY8aEfhcwyDTg7q7tDcDLujskOQ04rdn8dZLbR6i2sWBv4Of9LmJXkA8t6HcJeiJ/Nrc5L8/EUV68ox27WigM9d3WEzaqFgGLRqacsSXJqqoa6Hcd0mD+bI6cXW36aAOwX9f2dOCePtUiSWPOrhYKNwEzkxyQZDdgPrC0zzVJ0pixS00fVdWWJO8CvgqMB66oqlv7XNZY4rScdlX+bI6QVNWT95IkjQm72vSRJKmPDAVJUstQGAOSnJnktiT3P9mjQ5K8LcmlO9j3695UKEGSGUnW/g7935Zk317WNBbtUjea1TN/Bby2qu7odyHSM+htwFp82/ozyiuFUS7JPwK/ByxN8r5tVwFJJie5JslNzdfhQ4w9IMl3mv0XjnTtGpMmJFmc5AdJPp/keUn+tvkZXJtkUTr+FBgAPpNkTZLn9rvw0cJQGOWq6nQ6r6ReCdzftesS4MNV9VLgT4CPDzH8EuAfmj4/63WtEvCHwKKqOgR4gM5V7qVV9dKqmg08F3hdVX0eWAX8eVXNrarf9K/k0cXpo7Hr1cCspH2yyAuTvGBQn8PpBAbAVcDfjVBtGrvurqobm/VPA2cCdyR5P/A8YC/gVuCf+1TfqGcojF3jgJcPfoXVFRLb+EEWjaTBP28FXA4MVNXdSc4H9hjxqsYQp4/GrmXAu7ZtJJk7RJ8b6TxqBODPR6Amaf8kL2/W3wR8u1n/eZKJwJ929X0QGHx1q6fJUBi7zgQGmht664DTh+jzHuCMJDcBLxrR6jRW3QYsSPIDOlNF/wB8DLgF+AKd56Nt80ngH73R/MzyMReSpJZXCpKklqEgSWoZCpKklqEgSWoZCpKklqEgSWoZChqVkkxK8lcjeL7f6bHPg8ZekOTVO9l/epK3PvXqpOHzcwoalZLMAL7YPERt1J1P6hWvFDRaXQT8fvNp14ubr7VJbknyZwBJpib5VtNnbZI/TjI+ySe7+r5vRydIcmiSm5N8Bzijq318c76bmk+M/2XXvvc3x705yUVN2yebR0GT5KIk65pxH2razk9ydrM+N8l3m/3XJtmzab8hyd8lWZnkh0n++Jn/J9VY4APxNFqdA8yuqrlJ/oTOYzzmAHsDNyX5FvBm4KtVtTDJeDpP4ZwLTNv2ij/JpJ2c40rg3VX1zSQXd7WfCvyqql6aZHfgxiTLgAOB44GXVdXDSfbqPlizfQJwYFXVDs79qa5zXgCcB7y32TehquYl+e9N+w6npKQd8UpBY8ERwGeramtV3Qt8E3gpnefonNw8efPgqnoQ+Anwe0k+kuRYOs/0306SFwGTquqbTdNVXbtfA7w1yRrge8B/AmbS+SV9ZVU9DFBVvxh02AeA3wIfT3Ii8PCTnHMx8IquLv/ULFcDM3b6LyLtgKGgsWC754EDVNW36PxS/XfgqiRvrar76VxR3EBnSmioPz607Zg7uiEXOq/m5zZfB1TVsicZQ1VtAeYB19C5orj+Sb6vwR5plltxFkBPkaGg0ar7scrfAv6smeufTCcIViZ5MbCpqj4GfAJ4SZK9gXFVdQ3wP4GXDHXwqvol8KskRzRN3Y8W/yrwziTPAUjyB0meT+dx5ackeV7TPnj6aCLwoqr6Mp0pobmDzvkr4P6u+wVvoXPVIz1jfDWhUamq7ktyY/M20a8APwBupvNK/f1V9bMkC4C/TvIY8GvgrcA04Mok214wnbuT05wMXJHkYTpBsM3H6Uzf/Gs6f7VoM3B8VV3f/N2KVUkeBb4M/E3XuBcA1yXZg85VxVA3uRfQeVz08+hMdZ08vH8RaXh8S6okqeX0kSSp5fSR9CSSXAYcPqj5kqq6sh/1SL3k9JEkqeX0kSSpZShIklqGgiSpZShIklr/H9T3/LqlRrbeAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax=sns.countplot(x='toss_decision', data=df2)\n",
    "abs_values = df2['toss_decision'].value_counts(ascending=False).values\n",
    "\n",
    "ax.bar_label(container=ax.containers[0], labels=abs_values);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5bb725f0",
   "metadata": {},
   "source": [
    "## Which team won most matches"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "14f42254",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Mumbai Indians                 129\n",
       "Chennai Super Kings            121\n",
       "Kolkata Knight Riders          113\n",
       "Royal Challengers Bangalore    107\n",
       "Rajasthan Royals                94\n",
       "Kings XI Punjab                 85\n",
       "Sunrisers Hyderabad             74\n",
       "Delhi Daredevils                67\n",
       "Delhi Capitals                  33\n",
       "Deccan Chargers                 29\n",
       "Punjab Kings                    13\n",
       "Gujarat Lions                   13\n",
       "Gujarat Titans                  12\n",
       "Pune Warriors                   12\n",
       "Rising Pune Supergiant          10\n",
       "Lucknow Super Giants             9\n",
       "Kochi Tuskers Kerala             6\n",
       "Rising Pune Supergiants          5\n",
       "Name: winner, dtype: int64"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.winner.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "492dcc5a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,8))\n",
    "ax=sns.countplot(y='winner', data=df2, order=df2.winner.value_counts().index)\n",
    "\n",
    "abs_values = df2.winner.value_counts().values\n",
    "\n",
    "ax.bar_label(container=ax.containers[0], labels=abs_values);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0dc8f396",
   "metadata": {},
   "source": [
    "## Which player won player of the match most of the times"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "c88b981e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AB de Villiers    25\n",
       "CH Gayle          22\n",
       "DA Warner         18\n",
       "RG Sharma         18\n",
       "MS Dhoni          17\n",
       "SR Watson         16\n",
       "YK Pathan         16\n",
       "KA Pollard        14\n",
       "V Kohli           14\n",
       "SK Raina          14\n",
       "Name: player_of_match, dtype: int64"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.player_of_match.value_counts()[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "6cb20a32",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "ax=sns.countplot(x='player_of_match', data=df2, order=df2.player_of_match.value_counts()[:10].index)\n",
    "plt.xticks(rotation=90)\n",
    "\n",
    "abs_values = df2.player_of_match.value_counts()[:10].values\n",
    "\n",
    "ax.bar_label(container=ax.containers[0], labels=abs_values);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b37f298",
   "metadata": {},
   "source": [
    "## Who won the most matches, batting first or batting second?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "b45dd06e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "wickets    509\n",
       "runs       423\n",
       "Name: winner_type, dtype: int64"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.winner_type.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "4132d0e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "## here the winner type= wickets means batting second \n",
    "## here the winner type= runs means batting first\n",
    "## clearly the batting second team has won most of the time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "f6af06a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax=sns.countplot(x='winner_type', data=df2, order=df2.winner_type.value_counts().index)\n",
    "plt.xticks(rotation=90)\n",
    "\n",
    "abs_values = df2.winner_type.value_counts().values\n",
    "\n",
    "ax.bar_label(container=ax.containers[0], labels=abs_values);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2543b9d5",
   "metadata": {},
   "source": [
    "## Add new column into dataframe to see wining toss=wining match?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "a11bc3d4",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\User\\AppData\\Local\\Temp/ipykernel_5432/1474709236.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df2[\"win_toss=win_match\"] = np.where(df2['toss_winner'] == df2['winner'], 'Win', 'Lost')\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>year</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by</th>\n",
       "      <th>winner_type</th>\n",
       "      <th>eliminator</th>\n",
       "      <th>win_toss=win_match</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>SE Marsh</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>16.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>AM Rahane</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>8.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>MA Starc</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>9.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>CH Gayle</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>3.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>M Morkel</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>7.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   team1                        team2    year  \\\n",
       "0        Kings XI Punjab             Rajasthan Royals  2014.0   \n",
       "1       Rajasthan Royals          Chennai Super Kings  2015.0   \n",
       "2       Rajasthan Royals  Royal Challengers Bangalore  2015.0   \n",
       "3  Kolkata Knight Riders  Royal Challengers Bangalore  2015.0   \n",
       "4  Kolkata Knight Riders               Mumbai Indians  2015.0   \n",
       "\n",
       "                   toss_winner toss_decision player_of_match  \\\n",
       "0             Rajasthan Royals         field        SE Marsh   \n",
       "1          Chennai Super Kings           bat       AM Rahane   \n",
       "2  Royal Challengers Bangalore         field        MA Starc   \n",
       "3  Royal Challengers Bangalore         field        CH Gayle   \n",
       "4        Kolkata Knight Riders         field        M Morkel   \n",
       "\n",
       "                        winner  win_by winner_type eliminator  \\\n",
       "0              Kings XI Punjab    16.0        runs        NaN   \n",
       "1             Rajasthan Royals     8.0     wickets        NaN   \n",
       "2  Royal Challengers Bangalore     9.0     wickets        NaN   \n",
       "3  Royal Challengers Bangalore     3.0     wickets        NaN   \n",
       "4        Kolkata Knight Riders     7.0     wickets        NaN   \n",
       "\n",
       "  win_toss=win_match  \n",
       "0               Lost  \n",
       "1               Lost  \n",
       "2                Win  \n",
       "3                Win  \n",
       "4                Win  "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2[\"win_toss=win_match\"] = np.where(df2['toss_winner'] == df2['winner'], 'Win', 'Lost') \n",
    "df2.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb77c254",
   "metadata": {},
   "source": [
    "## How many times the toss winning team won the match and lost the match?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "17b628b2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Win     483\n",
       "Lost    467\n",
       "Name: win_toss=win_match, dtype: int64"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2['win_toss=win_match'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "1346bbfe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax=sns.countplot(x='win_toss=win_match', data=df2, order=df2['win_toss=win_match'].value_counts().index)\n",
    "plt.xticks(rotation=90)\n",
    "\n",
    "abs_values = df2['win_toss=win_match'].value_counts().values\n",
    "\n",
    "ax.bar_label(container=ax.containers[0], labels=abs_values);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "6d5b1607",
   "metadata": {},
   "outputs": [],
   "source": [
    "# clearly the toss winning team won most of the matches"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9398e703",
   "metadata": {},
   "source": [
    "## the graph showing the teams which are won the toss and then won the match(orange) and won the toss but lost the match(blue)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "396575b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,6))\n",
    "sns.countplot(y='toss_winner', hue='win_toss=win_match', data=df2);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "28afc2bb",
   "metadata": {},
   "source": [
    "## total matches played by each team "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "c80d6056",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Royal Challengers Bangalore    126\n",
       "Mumbai Indians                 112\n",
       "Chennai Super Kings            111\n",
       "Kolkata Knight Riders          105\n",
       "Kings XI Punjab                 92\n",
       "Rajasthan Royals                89\n",
       "Delhi Daredevils                85\n",
       "Sunrisers Hyderabad             69\n",
       "Deccan Chargers                 39\n",
       "Delhi Capitals                  29\n",
       "Pune Warriors                   23\n",
       "Punjab Kings                    18\n",
       "Gujarat Lions                   16\n",
       "Lucknow Super Giants             8\n",
       "Rising Pune Supergiants          7\n",
       "Gujarat Titans                   7\n",
       "Rising Pune Supergiant           7\n",
       "Kochi Tuskers Kerala             7\n",
       "Name: team1, dtype: int64"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "match1=df2.team1.value_counts()\n",
    "match1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "d1376b86",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Mumbai Indians                 119\n",
       "Kolkata Knight Riders          118\n",
       "Rajasthan Royals               103\n",
       "Royal Challengers Bangalore    100\n",
       "Kings XI Punjab                 98\n",
       "Chennai Super Kings             97\n",
       "Sunrisers Hyderabad             83\n",
       "Delhi Daredevils                76\n",
       "Deccan Chargers                 36\n",
       "Delhi Capitals                  34\n",
       "Pune Warriors                   23\n",
       "Gujarat Lions                   14\n",
       "Punjab Kings                    10\n",
       "Rising Pune Supergiant           9\n",
       "Gujarat Titans                   9\n",
       "Lucknow Super Giants             7\n",
       "Rising Pune Supergiants          7\n",
       "Kochi Tuskers Kerala             7\n",
       "Name: team2, dtype: int64"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "match2=df2.team2.value_counts()\n",
    "match2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "e66728cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Chennai Super Kings            208\n",
       "Deccan Chargers                 75\n",
       "Delhi Capitals                  63\n",
       "Delhi Daredevils               161\n",
       "Gujarat Lions                   30\n",
       "Gujarat Titans                  16\n",
       "Kings XI Punjab                190\n",
       "Kochi Tuskers Kerala            14\n",
       "Kolkata Knight Riders          223\n",
       "Lucknow Super Giants            15\n",
       "Mumbai Indians                 231\n",
       "Pune Warriors                   46\n",
       "Punjab Kings                    28\n",
       "Rajasthan Royals               192\n",
       "Rising Pune Supergiant          16\n",
       "Rising Pune Supergiants         14\n",
       "Royal Challengers Bangalore    226\n",
       "Sunrisers Hyderabad            152\n",
       "dtype: int64"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total=match1+match2\n",
    "total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b5241fdf",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1fb4731d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "3054c974",
   "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>year</th>\n",
       "      <th>start_date</th>\n",
       "      <th>venue</th>\n",
       "      <th>innings</th>\n",
       "      <th>ball</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>striker</th>\n",
       "      <th>non_striker</th>\n",
       "      <th>bowler</th>\n",
       "      <th>runs_off_bat</th>\n",
       "      <th>extras</th>\n",
       "      <th>wides</th>\n",
       "      <th>noballs</th>\n",
       "      <th>byes</th>\n",
       "      <th>legbyes</th>\n",
       "      <th>penalty</th>\n",
       "      <th>wicket_type</th>\n",
       "      <th>player_dismissed</th>\n",
       "      <th>other_wicket_type</th>\n",
       "      <th>other_player_dismissed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225949</th>\n",
       "      <td>981019.0</td>\n",
       "      <td>2016</td>\n",
       "      <td>2016-05-29</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Sachin Baby</td>\n",
       "      <td>CJ Jordan</td>\n",
       "      <td>B Kumar</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225950</th>\n",
       "      <td>981019.0</td>\n",
       "      <td>2016</td>\n",
       "      <td>2016-05-29</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.3</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Sachin Baby</td>\n",
       "      <td>CJ Jordan</td>\n",
       "      <td>B Kumar</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>run out</td>\n",
       "      <td>CJ Jordan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225951</th>\n",
       "      <td>981019.0</td>\n",
       "      <td>2016</td>\n",
       "      <td>2016-05-29</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.4</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Iqbal Abdulla</td>\n",
       "      <td>Sachin Baby</td>\n",
       "      <td>B Kumar</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225952</th>\n",
       "      <td>981019.0</td>\n",
       "      <td>2016</td>\n",
       "      <td>2016-05-29</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.5</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Sachin Baby</td>\n",
       "      <td>Iqbal Abdulla</td>\n",
       "      <td>B Kumar</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225953</th>\n",
       "      <td>981019.0</td>\n",
       "      <td>2016</td>\n",
       "      <td>2016-05-29</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.6</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Iqbal Abdulla</td>\n",
       "      <td>Sachin Baby</td>\n",
       "      <td>B Kumar</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>225954 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         match_id  year start_date                                      venue  \\\n",
       "0       1082591.0  2017 2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "1       1082591.0  2017 2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "2       1082591.0  2017 2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "3       1082591.0  2017 2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "4       1082591.0  2017 2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "...           ...   ...        ...                                        ...   \n",
       "225949   981019.0  2016 2016-05-29                      M Chinnaswamy Stadium   \n",
       "225950   981019.0  2016 2016-05-29                      M Chinnaswamy Stadium   \n",
       "225951   981019.0  2016 2016-05-29                      M Chinnaswamy Stadium   \n",
       "225952   981019.0  2016 2016-05-29                      M Chinnaswamy Stadium   \n",
       "225953   981019.0  2016 2016-05-29                      M Chinnaswamy Stadium   \n",
       "\n",
       "        innings  ball                 batting_team  \\\n",
       "0           1.0   0.1          Sunrisers Hyderabad   \n",
       "1           1.0   0.2          Sunrisers Hyderabad   \n",
       "2           1.0   0.3          Sunrisers Hyderabad   \n",
       "3           1.0   0.4          Sunrisers Hyderabad   \n",
       "4           1.0   0.5          Sunrisers Hyderabad   \n",
       "...         ...   ...                          ...   \n",
       "225949      2.0  19.2  Royal Challengers Bangalore   \n",
       "225950      2.0  19.3  Royal Challengers Bangalore   \n",
       "225951      2.0  19.4  Royal Challengers Bangalore   \n",
       "225952      2.0  19.5  Royal Challengers Bangalore   \n",
       "225953      2.0  19.6  Royal Challengers Bangalore   \n",
       "\n",
       "                       bowling_team        striker    non_striker    bowler  \\\n",
       "0       Royal Challengers Bangalore      DA Warner       S Dhawan  TS Mills   \n",
       "1       Royal Challengers Bangalore      DA Warner       S Dhawan  TS Mills   \n",
       "2       Royal Challengers Bangalore      DA Warner       S Dhawan  TS Mills   \n",
       "3       Royal Challengers Bangalore      DA Warner       S Dhawan  TS Mills   \n",
       "4       Royal Challengers Bangalore      DA Warner       S Dhawan  TS Mills   \n",
       "...                             ...            ...            ...       ...   \n",
       "225949          Sunrisers Hyderabad    Sachin Baby      CJ Jordan   B Kumar   \n",
       "225950          Sunrisers Hyderabad    Sachin Baby      CJ Jordan   B Kumar   \n",
       "225951          Sunrisers Hyderabad  Iqbal Abdulla    Sachin Baby   B Kumar   \n",
       "225952          Sunrisers Hyderabad    Sachin Baby  Iqbal Abdulla   B Kumar   \n",
       "225953          Sunrisers Hyderabad  Iqbal Abdulla    Sachin Baby   B Kumar   \n",
       "\n",
       "        runs_off_bat  extras  wides  noballs  byes  legbyes  penalty  \\\n",
       "0                0.0     0.0    0.0      0.0   0.0      0.0      0.0   \n",
       "1                0.0     0.0    0.0      0.0   0.0      0.0      0.0   \n",
       "2                4.0     0.0    0.0      0.0   0.0      0.0      0.0   \n",
       "3                0.0     0.0    0.0      0.0   0.0      0.0      0.0   \n",
       "4                0.0     2.0    2.0      0.0   0.0      0.0      0.0   \n",
       "...              ...     ...    ...      ...   ...      ...      ...   \n",
       "225949           2.0     0.0    0.0      0.0   0.0      0.0      0.0   \n",
       "225950           0.0     0.0    0.0      0.0   0.0      0.0      0.0   \n",
       "225951           0.0     1.0    0.0      0.0   0.0      1.0      0.0   \n",
       "225952           1.0     0.0    0.0      0.0   0.0      0.0      0.0   \n",
       "225953           4.0     0.0    0.0      0.0   0.0      0.0      0.0   \n",
       "\n",
       "       wicket_type player_dismissed  other_wicket_type  other_player_dismissed  \n",
       "0              NaN              NaN                NaN                     NaN  \n",
       "1              NaN              NaN                NaN                     NaN  \n",
       "2              NaN              NaN                NaN                     NaN  \n",
       "3              NaN              NaN                NaN                     NaN  \n",
       "4              NaN              NaN                NaN                     NaN  \n",
       "...            ...              ...                ...                     ...  \n",
       "225949         NaN              NaN                NaN                     NaN  \n",
       "225950     run out        CJ Jordan                NaN                     NaN  \n",
       "225951         NaN              NaN                NaN                     NaN  \n",
       "225952         NaN              NaN                NaN                     NaN  \n",
       "225953         NaN              NaN                NaN                     NaN  \n",
       "\n",
       "[225954 rows x 22 columns]"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3fb1bcfa",
   "metadata": {},
   "source": [
    "# Analysis on IPL 2008 season"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "95869b89",
   "metadata": {
    "scrolled": true
   },
   "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>year</th>\n",
       "      <th>start_date</th>\n",
       "      <th>venue</th>\n",
       "      <th>innings</th>\n",
       "      <th>ball</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>striker</th>\n",
       "      <th>non_striker</th>\n",
       "      <th>bowler</th>\n",
       "      <th>runs_off_bat</th>\n",
       "      <th>extras</th>\n",
       "      <th>wides</th>\n",
       "      <th>noballs</th>\n",
       "      <th>byes</th>\n",
       "      <th>legbyes</th>\n",
       "      <th>penalty</th>\n",
       "      <th>wicket_type</th>\n",
       "      <th>player_dismissed</th>\n",
       "      <th>other_wicket_type</th>\n",
       "      <th>other_player_dismissed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>89356</th>\n",
       "      <td>335982.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>SC Ganguly</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89357</th>\n",
       "      <td>335982.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>SC Ganguly</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89358</th>\n",
       "      <td>335982.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>SC Ganguly</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89359</th>\n",
       "      <td>335982.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>SC Ganguly</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89360</th>\n",
       "      <td>335982.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>SC Ganguly</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102840</th>\n",
       "      <td>336040.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>2008-06-01</td>\n",
       "      <td>Dr DY Patil Sports Academy</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.3</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>SK Warne</td>\n",
       "      <td>Sohail Tanvir</td>\n",
       "      <td>L Balaji</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102841</th>\n",
       "      <td>336040.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>2008-06-01</td>\n",
       "      <td>Dr DY Patil Sports Academy</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.4</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Sohail Tanvir</td>\n",
       "      <td>SK Warne</td>\n",
       "      <td>L Balaji</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102842</th>\n",
       "      <td>336040.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>2008-06-01</td>\n",
       "      <td>Dr DY Patil Sports Academy</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.5</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>SK Warne</td>\n",
       "      <td>Sohail Tanvir</td>\n",
       "      <td>L Balaji</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102843</th>\n",
       "      <td>336040.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>2008-06-01</td>\n",
       "      <td>Dr DY Patil Sports Academy</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.6</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Sohail Tanvir</td>\n",
       "      <td>SK Warne</td>\n",
       "      <td>L Balaji</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102844</th>\n",
       "      <td>336040.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>2008-06-01</td>\n",
       "      <td>Dr DY Patil Sports Academy</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.7</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Sohail Tanvir</td>\n",
       "      <td>SK Warne</td>\n",
       "      <td>L Balaji</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>13489 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        match_id  year start_date                       venue  innings  ball  \\\n",
       "89356   335982.0  2008 2008-04-18       M Chinnaswamy Stadium      1.0   0.1   \n",
       "89357   335982.0  2008 2008-04-18       M Chinnaswamy Stadium      1.0   0.2   \n",
       "89358   335982.0  2008 2008-04-18       M Chinnaswamy Stadium      1.0   0.3   \n",
       "89359   335982.0  2008 2008-04-18       M Chinnaswamy Stadium      1.0   0.4   \n",
       "89360   335982.0  2008 2008-04-18       M Chinnaswamy Stadium      1.0   0.5   \n",
       "...          ...   ...        ...                         ...      ...   ...   \n",
       "102840  336040.0  2008 2008-06-01  Dr DY Patil Sports Academy      2.0  19.3   \n",
       "102841  336040.0  2008 2008-06-01  Dr DY Patil Sports Academy      2.0  19.4   \n",
       "102842  336040.0  2008 2008-06-01  Dr DY Patil Sports Academy      2.0  19.5   \n",
       "102843  336040.0  2008 2008-06-01  Dr DY Patil Sports Academy      2.0  19.6   \n",
       "102844  336040.0  2008 2008-06-01  Dr DY Patil Sports Academy      2.0  19.7   \n",
       "\n",
       "                 batting_team                 bowling_team        striker  \\\n",
       "89356   Kolkata Knight Riders  Royal Challengers Bangalore     SC Ganguly   \n",
       "89357   Kolkata Knight Riders  Royal Challengers Bangalore    BB McCullum   \n",
       "89358   Kolkata Knight Riders  Royal Challengers Bangalore    BB McCullum   \n",
       "89359   Kolkata Knight Riders  Royal Challengers Bangalore    BB McCullum   \n",
       "89360   Kolkata Knight Riders  Royal Challengers Bangalore    BB McCullum   \n",
       "...                       ...                          ...            ...   \n",
       "102840       Rajasthan Royals          Chennai Super Kings       SK Warne   \n",
       "102841       Rajasthan Royals          Chennai Super Kings  Sohail Tanvir   \n",
       "102842       Rajasthan Royals          Chennai Super Kings       SK Warne   \n",
       "102843       Rajasthan Royals          Chennai Super Kings  Sohail Tanvir   \n",
       "102844       Rajasthan Royals          Chennai Super Kings  Sohail Tanvir   \n",
       "\n",
       "          non_striker    bowler  runs_off_bat  extras  wides  noballs  byes  \\\n",
       "89356     BB McCullum   P Kumar           0.0     1.0    0.0      0.0   0.0   \n",
       "89357      SC Ganguly   P Kumar           0.0     0.0    0.0      0.0   0.0   \n",
       "89358      SC Ganguly   P Kumar           0.0     1.0    1.0      0.0   0.0   \n",
       "89359      SC Ganguly   P Kumar           0.0     0.0    0.0      0.0   0.0   \n",
       "89360      SC Ganguly   P Kumar           0.0     0.0    0.0      0.0   0.0   \n",
       "...               ...       ...           ...     ...    ...      ...   ...   \n",
       "102840  Sohail Tanvir  L Balaji           1.0     0.0    0.0      0.0   0.0   \n",
       "102841       SK Warne  L Balaji           0.0     2.0    2.0      0.0   0.0   \n",
       "102842  Sohail Tanvir  L Balaji           1.0     0.0    0.0      0.0   0.0   \n",
       "102843       SK Warne  L Balaji           2.0     0.0    0.0      0.0   0.0   \n",
       "102844       SK Warne  L Balaji           1.0     0.0    0.0      0.0   0.0   \n",
       "\n",
       "        legbyes  penalty wicket_type player_dismissed  other_wicket_type  \\\n",
       "89356       1.0      0.0         NaN              NaN                NaN   \n",
       "89357       0.0      0.0         NaN              NaN                NaN   \n",
       "89358       0.0      0.0         NaN              NaN                NaN   \n",
       "89359       0.0      0.0         NaN              NaN                NaN   \n",
       "89360       0.0      0.0         NaN              NaN                NaN   \n",
       "...         ...      ...         ...              ...                ...   \n",
       "102840      0.0      0.0         NaN              NaN                NaN   \n",
       "102841      0.0      0.0         NaN              NaN                NaN   \n",
       "102842      0.0      0.0         NaN              NaN                NaN   \n",
       "102843      0.0      0.0         NaN              NaN                NaN   \n",
       "102844      0.0      0.0         NaN              NaN                NaN   \n",
       "\n",
       "        other_player_dismissed  \n",
       "89356                      NaN  \n",
       "89357                      NaN  \n",
       "89358                      NaN  \n",
       "89359                      NaN  \n",
       "89360                      NaN  \n",
       "...                        ...  \n",
       "102840                     NaN  \n",
       "102841                     NaN  \n",
       "102842                     NaN  \n",
       "102843                     NaN  \n",
       "102844                     NaN  \n",
       "\n",
       "[13489 rows x 22 columns]"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "IPL_2008=df[df['year']==2008]\n",
    "IPL_2008"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8299f5e6",
   "metadata": {},
   "source": [
    "## Which player scored most runs in IPL 2008"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "12d735ca",
   "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>runs_off_bat</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>striker</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>SE Marsh</th>\n",
       "      <td>616.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>G Gambhir</th>\n",
       "      <td>534.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ST Jayasuriya</th>\n",
       "      <td>514.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SR Watson</th>\n",
       "      <td>472.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GC Smith</th>\n",
       "      <td>441.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AC Gilchrist</th>\n",
       "      <td>436.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YK Pathan</th>\n",
       "      <td>435.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SK Raina</th>\n",
       "      <td>421.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MS Dhoni</th>\n",
       "      <td>414.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>V Sehwag</th>\n",
       "      <td>406.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               runs_off_bat\n",
       "striker                    \n",
       "SE Marsh              616.0\n",
       "G Gambhir             534.0\n",
       "ST Jayasuriya         514.0\n",
       "SR Watson             472.0\n",
       "GC Smith              441.0\n",
       "AC Gilchrist          436.0\n",
       "YK Pathan             435.0\n",
       "SK Raina              421.0\n",
       "MS Dhoni              414.0\n",
       "V Sehwag              406.0"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.pivot_table(IPL_2008, index='striker', values='runs_off_bat', aggfunc=sum).sort_values(by='runs_off_bat', ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "b5de02f1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def add_value_label(x_list, y_list):\n",
    "    for i in range(len(x_list)):\n",
    "        plt.annotate(y_list[i], (i,y_list[i]), ha='center')\n",
    "        \n",
    "plt.figure(figsize=(10,6))\n",
    "sns.barplot(x='striker', y='runs_off_bat', data=IPL_2008, estimator=sum, ci=None,\n",
    "           order=IPL_2008.groupby('striker').runs_off_bat.sum().sort_values(ascending=False)[:10].index)\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel('Player', fontsize=15)\n",
    "plt.ylabel('Total Runs Scored', fontsize=15)\n",
    "\n",
    "index=IPL_2008.groupby('striker').runs_off_bat.sum().sort_values(ascending=False)[:10].index\n",
    "value=IPL_2008.groupby('striker').runs_off_bat.sum().sort_values(ascending=False)[:10].values\n",
    "\n",
    "add_value_label(index, value);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9b3fd99",
   "metadata": {},
   "source": [
    "## What is the most common wicket type in IPL 2008"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "e0994657",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax=sns.countplot(y='wicket_type', data=IPL_2008,\n",
    "                order=IPL_2008.wicket_type.value_counts(ascending=False).index)\n",
    "value=IPL_2008.wicket_type.value_counts(ascending=False).values\n",
    "ax.bar_label(container=ax.containers[0], labels=value);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "dcba4878",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>year</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by</th>\n",
       "      <th>winner_type</th>\n",
       "      <th>eliminator</th>\n",
       "      <th>win_toss=win_match</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>SE Marsh</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>16.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>AM Rahane</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>8.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>MA Starc</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>9.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>CH Gayle</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>3.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>M Morkel</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>7.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945</th>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>UT Yadav</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>6.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>946</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>field</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>6.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>947</th>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>SS Iyer</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>37.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>948</th>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>AD Russell</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>4.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>949</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>V Sehwag</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>24.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>950 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     team1                        team2    year  \\\n",
       "0          Kings XI Punjab             Rajasthan Royals  2014.0   \n",
       "1         Rajasthan Royals          Chennai Super Kings  2015.0   \n",
       "2         Rajasthan Royals  Royal Challengers Bangalore  2015.0   \n",
       "3    Kolkata Knight Riders  Royal Challengers Bangalore  2015.0   \n",
       "4    Kolkata Knight Riders               Mumbai Indians  2015.0   \n",
       "..                     ...                          ...     ...   \n",
       "945       Delhi Daredevils        Kolkata Knight Riders  2015.0   \n",
       "946    Chennai Super Kings          Sunrisers Hyderabad  2014.0   \n",
       "947       Delhi Daredevils               Mumbai Indians  2015.0   \n",
       "948        Kings XI Punjab        Kolkata Knight Riders  2015.0   \n",
       "949    Chennai Super Kings              Kings XI Punjab  2014.0   \n",
       "\n",
       "                     toss_winner toss_decision player_of_match  \\\n",
       "0               Rajasthan Royals         field        SE Marsh   \n",
       "1            Chennai Super Kings           bat       AM Rahane   \n",
       "2    Royal Challengers Bangalore         field        MA Starc   \n",
       "3    Royal Challengers Bangalore         field        CH Gayle   \n",
       "4          Kolkata Knight Riders         field        M Morkel   \n",
       "..                           ...           ...             ...   \n",
       "945        Kolkata Knight Riders         field        UT Yadav   \n",
       "946          Sunrisers Hyderabad         field       DA Warner   \n",
       "947               Mumbai Indians         field         SS Iyer   \n",
       "948        Kolkata Knight Riders         field      AD Russell   \n",
       "949          Chennai Super Kings         field        V Sehwag   \n",
       "\n",
       "                          winner  win_by winner_type eliminator  \\\n",
       "0                Kings XI Punjab    16.0        runs        NaN   \n",
       "1               Rajasthan Royals     8.0     wickets        NaN   \n",
       "2    Royal Challengers Bangalore     9.0     wickets        NaN   \n",
       "3    Royal Challengers Bangalore     3.0     wickets        NaN   \n",
       "4          Kolkata Knight Riders     7.0     wickets        NaN   \n",
       "..                           ...     ...         ...        ...   \n",
       "945        Kolkata Knight Riders     6.0     wickets        NaN   \n",
       "946          Sunrisers Hyderabad     6.0     wickets        NaN   \n",
       "947             Delhi Daredevils    37.0        runs        NaN   \n",
       "948        Kolkata Knight Riders     4.0     wickets        NaN   \n",
       "949              Kings XI Punjab    24.0        runs        NaN   \n",
       "\n",
       "    win_toss=win_match  \n",
       "0                 Lost  \n",
       "1                 Lost  \n",
       "2                  Win  \n",
       "3                  Win  \n",
       "4                  Win  \n",
       "..                 ...  \n",
       "945                Win  \n",
       "946                Win  \n",
       "947               Lost  \n",
       "948                Win  \n",
       "949               Lost  \n",
       "\n",
       "[950 rows x 11 columns]"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "2fe83ade",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>year</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by</th>\n",
       "      <th>winner_type</th>\n",
       "      <th>eliminator</th>\n",
       "      <th>win_toss=win_match</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>500</th>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>140.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>bat</td>\n",
       "      <td>DJ Hussey</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>5.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>bat</td>\n",
       "      <td>SR Watson</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>6.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>bat</td>\n",
       "      <td>MF Maharoof</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>9.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504</th>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>MV Boucher</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>5.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>505</th>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>MEK Hussey</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>33.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>506</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>bat</td>\n",
       "      <td>Shoaib Akhtar</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>23.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>507</th>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>MS Dhoni</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>4.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508</th>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>bat</td>\n",
       "      <td>V Sehwag</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>9.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>509</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>field</td>\n",
       "      <td>AC Gilchrist</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>7.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>510</th>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>A Nehra</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>7.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>511</th>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>field</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>3.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512</th>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>S Sreesanth</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>6.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>513</th>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>GD McGrath</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>10.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>514</th>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>bat</td>\n",
       "      <td>SC Ganguly</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>23.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>515</th>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>bat</td>\n",
       "      <td>SE Marsh</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>9.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>516</th>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>bat</td>\n",
       "      <td>SM Katich</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>4.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>517</th>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>SE Marsh</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>7.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>518</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>bat</td>\n",
       "      <td>SA Asnodkar</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>45.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>519</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>bat</td>\n",
       "      <td>JDP Oram</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>9.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>520</th>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>field</td>\n",
       "      <td>SM Pollock</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>29.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>521</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>bat</td>\n",
       "      <td>ST Jayasuriya</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>7.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>522</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>bat</td>\n",
       "      <td>SC Ganguly</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>5.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>523</th>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>bat</td>\n",
       "      <td>IK Pathan</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>9.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>524</th>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>KC Sangakkara</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>66.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>525</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>YK Pathan</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>8.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>526</th>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>field</td>\n",
       "      <td>AC Gilchrist</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>10.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>L Balaji</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>18.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528</th>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>SR Watson</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>7.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>529</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>SR Watson</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>3.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>530</th>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>YK Pathan</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>3.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>531</th>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>MS Dhoni</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>13.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>532</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>ML Hayden</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>6.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>533</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>Sohail Tanvir</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>8.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>534</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>V Sehwag</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>8.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>535</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>bat</td>\n",
       "      <td>Umar Gul</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>3.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>538</th>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>SE Marsh</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>6.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>540</th>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>SE Marsh</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>41.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>541</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>bat</td>\n",
       "      <td>JA Morkel</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>10.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>542</th>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>field</td>\n",
       "      <td>SP Goswami</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>5.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>543</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>bat</td>\n",
       "      <td>M Ntini</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>3.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>544</th>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>ST Jayasuriya</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>9.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>545</th>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>field</td>\n",
       "      <td>A Mishra</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>12.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>546</th>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>bat</td>\n",
       "      <td>R Vinay Kumar</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>5.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>547</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>YK Pathan</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>3.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>548</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>Sohail Tanvir</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>5.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>549</th>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>SE Marsh</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>1.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>550</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>bat</td>\n",
       "      <td>M Ntini</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>9.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>552</th>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>CRD Fernando</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>9.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>553</th>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>bat</td>\n",
       "      <td>DPMD Jayawardene</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>6.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>554</th>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>field</td>\n",
       "      <td>DJ Bravo</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>25.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>555</th>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>bat</td>\n",
       "      <td>SK Raina</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>7.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>556</th>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>field</td>\n",
       "      <td>KD Karthik</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>5.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>557</th>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>field</td>\n",
       "      <td>SR Watson</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>105.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>558</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>YK Pathan</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>6.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>559</th>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>SM Pollock</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>8.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>560</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>GC Smith</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>65.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>561</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>bat</td>\n",
       "      <td>A Kumble</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>14.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           team1                        team2    year  \\\n",
       "500  Royal Challengers Bangalore        Kolkata Knight Riders  2008.0   \n",
       "501        Kolkata Knight Riders              Deccan Chargers  2008.0   \n",
       "502             Rajasthan Royals              Kings XI Punjab  2008.0   \n",
       "503             Delhi Daredevils             Rajasthan Royals  2008.0   \n",
       "504               Mumbai Indians  Royal Challengers Bangalore  2008.0   \n",
       "505              Kings XI Punjab          Chennai Super Kings  2008.0   \n",
       "506        Kolkata Knight Riders             Delhi Daredevils  2008.0   \n",
       "507             Delhi Daredevils          Chennai Super Kings  2008.0   \n",
       "508              Deccan Chargers             Delhi Daredevils  2008.0   \n",
       "509          Chennai Super Kings              Deccan Chargers  2008.0   \n",
       "510               Mumbai Indians             Rajasthan Royals  2008.0   \n",
       "511  Royal Challengers Bangalore              Deccan Chargers  2008.0   \n",
       "512  Royal Challengers Bangalore              Kings XI Punjab  2008.0   \n",
       "513             Delhi Daredevils  Royal Challengers Bangalore  2008.0   \n",
       "514              Deccan Chargers        Kolkata Knight Riders  2008.0   \n",
       "515              Kings XI Punjab  Royal Challengers Bangalore  2008.0   \n",
       "516              Kings XI Punjab             Delhi Daredevils  2008.0   \n",
       "517              Deccan Chargers              Kings XI Punjab  2008.0   \n",
       "518             Rajasthan Royals        Kolkata Knight Riders  2008.0   \n",
       "519          Chennai Super Kings        Kolkata Knight Riders  2008.0   \n",
       "520               Mumbai Indians             Delhi Daredevils  2008.0   \n",
       "521        Kolkata Knight Riders               Mumbai Indians  2008.0   \n",
       "522        Kolkata Knight Riders  Royal Challengers Bangalore  2008.0   \n",
       "523              Kings XI Punjab        Kolkata Knight Riders  2008.0   \n",
       "524              Kings XI Punjab               Mumbai Indians  2008.0   \n",
       "525             Rajasthan Royals              Deccan Chargers  2008.0   \n",
       "526               Mumbai Indians              Deccan Chargers  2008.0   \n",
       "527          Chennai Super Kings              Kings XI Punjab  2008.0   \n",
       "528  Royal Challengers Bangalore             Rajasthan Royals  2008.0   \n",
       "529             Rajasthan Royals             Delhi Daredevils  2008.0   \n",
       "530              Deccan Chargers             Rajasthan Royals  2008.0   \n",
       "531  Royal Challengers Bangalore          Chennai Super Kings  2008.0   \n",
       "532          Chennai Super Kings               Mumbai Indians  2008.0   \n",
       "533             Rajasthan Royals          Chennai Super Kings  2008.0   \n",
       "534          Chennai Super Kings             Delhi Daredevils  2008.0   \n",
       "535        Kolkata Knight Riders              Kings XI Punjab  2008.0   \n",
       "538              Kings XI Punjab              Deccan Chargers  2008.0   \n",
       "540              Kings XI Punjab             Rajasthan Royals  2008.0   \n",
       "541          Chennai Super Kings             Rajasthan Royals  2008.0   \n",
       "542  Royal Challengers Bangalore             Delhi Daredevils  2008.0   \n",
       "543        Kolkata Knight Riders          Chennai Super Kings  2008.0   \n",
       "544               Mumbai Indians          Chennai Super Kings  2008.0   \n",
       "545             Delhi Daredevils              Deccan Chargers  2008.0   \n",
       "546              Deccan Chargers  Royal Challengers Bangalore  2008.0   \n",
       "547          Chennai Super Kings             Rajasthan Royals  2008.0   \n",
       "548             Rajasthan Royals               Mumbai Indians  2008.0   \n",
       "549               Mumbai Indians              Kings XI Punjab  2008.0   \n",
       "550          Chennai Super Kings              Kings XI Punjab  2008.0   \n",
       "552  Royal Challengers Bangalore               Mumbai Indians  2008.0   \n",
       "553             Delhi Daredevils              Kings XI Punjab  2008.0   \n",
       "554              Deccan Chargers               Mumbai Indians  2008.0   \n",
       "555              Deccan Chargers          Chennai Super Kings  2008.0   \n",
       "556             Delhi Daredevils               Mumbai Indians  2008.0   \n",
       "557             Delhi Daredevils             Rajasthan Royals  2008.0   \n",
       "558        Kolkata Knight Riders             Rajasthan Royals  2008.0   \n",
       "559               Mumbai Indians        Kolkata Knight Riders  2008.0   \n",
       "560             Rajasthan Royals  Royal Challengers Bangalore  2008.0   \n",
       "561          Chennai Super Kings  Royal Challengers Bangalore  2008.0   \n",
       "\n",
       "                     toss_winner toss_decision   player_of_match  \\\n",
       "500  Royal Challengers Bangalore         field       BB McCullum   \n",
       "501              Deccan Chargers           bat         DJ Hussey   \n",
       "502              Kings XI Punjab           bat         SR Watson   \n",
       "503             Rajasthan Royals           bat       MF Maharoof   \n",
       "504               Mumbai Indians           bat        MV Boucher   \n",
       "505          Chennai Super Kings           bat        MEK Hussey   \n",
       "506        Kolkata Knight Riders           bat     Shoaib Akhtar   \n",
       "507          Chennai Super Kings         field          MS Dhoni   \n",
       "508              Deccan Chargers           bat          V Sehwag   \n",
       "509              Deccan Chargers         field      AC Gilchrist   \n",
       "510               Mumbai Indians         field           A Nehra   \n",
       "511              Deccan Chargers         field           P Kumar   \n",
       "512              Kings XI Punjab         field       S Sreesanth   \n",
       "513  Royal Challengers Bangalore         field        GD McGrath   \n",
       "514        Kolkata Knight Riders           bat        SC Ganguly   \n",
       "515  Royal Challengers Bangalore           bat          SE Marsh   \n",
       "516             Delhi Daredevils           bat         SM Katich   \n",
       "517              Kings XI Punjab         field          SE Marsh   \n",
       "518             Rajasthan Royals           bat       SA Asnodkar   \n",
       "519        Kolkata Knight Riders           bat          JDP Oram   \n",
       "520             Delhi Daredevils         field        SM Pollock   \n",
       "521        Kolkata Knight Riders           bat     ST Jayasuriya   \n",
       "522        Kolkata Knight Riders           bat        SC Ganguly   \n",
       "523              Kings XI Punjab           bat         IK Pathan   \n",
       "524               Mumbai Indians         field     KC Sangakkara   \n",
       "525             Rajasthan Royals         field         YK Pathan   \n",
       "526              Deccan Chargers         field      AC Gilchrist   \n",
       "527              Kings XI Punjab         field          L Balaji   \n",
       "528             Rajasthan Royals         field         SR Watson   \n",
       "529             Rajasthan Royals         field         SR Watson   \n",
       "530             Rajasthan Royals         field         YK Pathan   \n",
       "531          Chennai Super Kings           bat          MS Dhoni   \n",
       "532               Mumbai Indians         field         ML Hayden   \n",
       "533          Chennai Super Kings           bat     Sohail Tanvir   \n",
       "534          Chennai Super Kings           bat          V Sehwag   \n",
       "535              Kings XI Punjab           bat          Umar Gul   \n",
       "538              Kings XI Punjab         field          SE Marsh   \n",
       "540             Rajasthan Royals         field          SE Marsh   \n",
       "541             Rajasthan Royals           bat         JA Morkel   \n",
       "542             Delhi Daredevils         field        SP Goswami   \n",
       "543        Kolkata Knight Riders           bat           M Ntini   \n",
       "544               Mumbai Indians         field     ST Jayasuriya   \n",
       "545              Deccan Chargers         field          A Mishra   \n",
       "546              Deccan Chargers           bat     R Vinay Kumar   \n",
       "547             Rajasthan Royals         field         YK Pathan   \n",
       "548             Rajasthan Royals         field     Sohail Tanvir   \n",
       "549               Mumbai Indians         field          SE Marsh   \n",
       "550              Kings XI Punjab           bat           M Ntini   \n",
       "552               Mumbai Indians         field      CRD Fernando   \n",
       "553             Delhi Daredevils           bat  DPMD Jayawardene   \n",
       "554              Deccan Chargers         field          DJ Bravo   \n",
       "555              Deccan Chargers           bat          SK Raina   \n",
       "556             Delhi Daredevils         field        KD Karthik   \n",
       "557             Delhi Daredevils         field         SR Watson   \n",
       "558             Rajasthan Royals         field         YK Pathan   \n",
       "559               Mumbai Indians         field        SM Pollock   \n",
       "560  Royal Challengers Bangalore         field          GC Smith   \n",
       "561  Royal Challengers Bangalore           bat          A Kumble   \n",
       "\n",
       "                          winner  win_by winner_type eliminator  \\\n",
       "500        Kolkata Knight Riders   140.0        runs        NaN   \n",
       "501        Kolkata Knight Riders     5.0     wickets        NaN   \n",
       "502             Rajasthan Royals     6.0     wickets        NaN   \n",
       "503             Delhi Daredevils     9.0     wickets        NaN   \n",
       "504  Royal Challengers Bangalore     5.0     wickets        NaN   \n",
       "505          Chennai Super Kings    33.0        runs        NaN   \n",
       "506        Kolkata Knight Riders    23.0        runs        NaN   \n",
       "507          Chennai Super Kings     4.0     wickets        NaN   \n",
       "508             Delhi Daredevils     9.0     wickets        NaN   \n",
       "509              Deccan Chargers     7.0     wickets        NaN   \n",
       "510               Mumbai Indians     7.0     wickets        NaN   \n",
       "511  Royal Challengers Bangalore     3.0        runs        NaN   \n",
       "512              Kings XI Punjab     6.0     wickets        NaN   \n",
       "513             Delhi Daredevils    10.0        runs        NaN   \n",
       "514        Kolkata Knight Riders    23.0        runs        NaN   \n",
       "515              Kings XI Punjab     9.0     wickets        NaN   \n",
       "516              Kings XI Punjab     4.0     wickets        NaN   \n",
       "517              Kings XI Punjab     7.0     wickets        NaN   \n",
       "518             Rajasthan Royals    45.0        runs        NaN   \n",
       "519          Chennai Super Kings     9.0     wickets        NaN   \n",
       "520               Mumbai Indians    29.0        runs        NaN   \n",
       "521               Mumbai Indians     7.0     wickets        NaN   \n",
       "522        Kolkata Knight Riders     5.0        runs        NaN   \n",
       "523              Kings XI Punjab     9.0        runs        NaN   \n",
       "524              Kings XI Punjab    66.0        runs        NaN   \n",
       "525             Rajasthan Royals     8.0     wickets        NaN   \n",
       "526              Deccan Chargers    10.0     wickets        NaN   \n",
       "527          Chennai Super Kings    18.0        runs        NaN   \n",
       "528             Rajasthan Royals     7.0     wickets        NaN   \n",
       "529             Rajasthan Royals     3.0     wickets        NaN   \n",
       "530             Rajasthan Royals     3.0     wickets        NaN   \n",
       "531          Chennai Super Kings    13.0        runs        NaN   \n",
       "532          Chennai Super Kings     6.0        runs        NaN   \n",
       "533             Rajasthan Royals     8.0     wickets        NaN   \n",
       "534             Delhi Daredevils     8.0     wickets        NaN   \n",
       "535        Kolkata Knight Riders     3.0     wickets        NaN   \n",
       "538              Kings XI Punjab     6.0     wickets        NaN   \n",
       "540              Kings XI Punjab    41.0        runs        NaN   \n",
       "541             Rajasthan Royals    10.0        runs        NaN   \n",
       "542             Delhi Daredevils     5.0     wickets        NaN   \n",
       "543          Chennai Super Kings     3.0        runs        NaN   \n",
       "544               Mumbai Indians     9.0     wickets        NaN   \n",
       "545             Delhi Daredevils    12.0        runs        NaN   \n",
       "546  Royal Challengers Bangalore     5.0     wickets        NaN   \n",
       "547             Rajasthan Royals     3.0     wickets        NaN   \n",
       "548             Rajasthan Royals     5.0     wickets        NaN   \n",
       "549              Kings XI Punjab     1.0        runs        NaN   \n",
       "550          Chennai Super Kings     9.0     wickets        NaN   \n",
       "552               Mumbai Indians     9.0     wickets        NaN   \n",
       "553              Kings XI Punjab     6.0        runs        NaN   \n",
       "554               Mumbai Indians    25.0        runs        NaN   \n",
       "555          Chennai Super Kings     7.0     wickets        NaN   \n",
       "556             Delhi Daredevils     5.0     wickets        NaN   \n",
       "557             Rajasthan Royals   105.0        runs        NaN   \n",
       "558             Rajasthan Royals     6.0     wickets        NaN   \n",
       "559               Mumbai Indians     8.0     wickets        NaN   \n",
       "560             Rajasthan Royals    65.0        runs        NaN   \n",
       "561  Royal Challengers Bangalore    14.0        runs        NaN   \n",
       "\n",
       "    win_toss=win_match  \n",
       "500               Lost  \n",
       "501               Lost  \n",
       "502               Lost  \n",
       "503               Lost  \n",
       "504               Lost  \n",
       "505                Win  \n",
       "506                Win  \n",
       "507                Win  \n",
       "508               Lost  \n",
       "509                Win  \n",
       "510                Win  \n",
       "511               Lost  \n",
       "512                Win  \n",
       "513               Lost  \n",
       "514                Win  \n",
       "515               Lost  \n",
       "516               Lost  \n",
       "517                Win  \n",
       "518                Win  \n",
       "519               Lost  \n",
       "520               Lost  \n",
       "521               Lost  \n",
       "522                Win  \n",
       "523                Win  \n",
       "524               Lost  \n",
       "525                Win  \n",
       "526                Win  \n",
       "527               Lost  \n",
       "528                Win  \n",
       "529                Win  \n",
       "530                Win  \n",
       "531                Win  \n",
       "532               Lost  \n",
       "533               Lost  \n",
       "534               Lost  \n",
       "535               Lost  \n",
       "538                Win  \n",
       "540               Lost  \n",
       "541                Win  \n",
       "542                Win  \n",
       "543               Lost  \n",
       "544                Win  \n",
       "545               Lost  \n",
       "546               Lost  \n",
       "547                Win  \n",
       "548                Win  \n",
       "549               Lost  \n",
       "550               Lost  \n",
       "552                Win  \n",
       "553               Lost  \n",
       "554               Lost  \n",
       "555               Lost  \n",
       "556                Win  \n",
       "557               Lost  \n",
       "558                Win  \n",
       "559                Win  \n",
       "560               Lost  \n",
       "561                Win  "
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "IPL2008=df2[df2['year']==2008]\n",
    "IPL2008"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a1138051",
   "metadata": {},
   "source": [
    "## Which team won the toss maximum times in IPL 2008"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "b141fbcb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "ax=sns.countplot(x='toss_winner', data=IPL2008,\n",
    "                order=IPL2008.toss_winner.value_counts(ascending=False).index)\n",
    "plt.xticks(rotation=90)\n",
    "\n",
    "value=IPL2008.toss_winner.value_counts(ascending=False).values\n",
    "ax.bar_label(container=ax.containers[0], labels=value);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59402816",
   "metadata": {},
   "source": [
    "## How many times the batting first and batting second won the match in IPL 2008"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "2377ba4a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax=sns.countplot(x='winner_type', data=IPL2008, order=IPL2008.winner_type.value_counts(ascending=False).index)\n",
    "value=IPL2008.winner_type.value_counts(ascending=False).values\n",
    "ax.bar_label(container=ax.containers[0], labels=value);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be4ba7d7",
   "metadata": {},
   "source": [
    "#### Batting second was won the match most of the times"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65ec54d8",
   "metadata": {},
   "source": [
    "## Who won the player of the match most time in IPL 2008"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "5da963c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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mOeMAxhdvPy2u9yItK/+YpIsi4sRuNdTTPXhJ9wKbRcSzFcdxH6kMw2MVxlDp90LS4cAHSE/cW1ic4J8EzsrZY5T0uw63IyJenyuGtljeCnwPeAbYKyIW5o6hTiRtBHwQOBiYBXw/Iq7J1PY8YGfgvyNiC0k7AQdHxKTlfGq34/gVMDEiniqu1wAuBvYl9eK7VpSxp3vwwP3ASkClCR54kPQSq0qVfi8i4mzgbEkTI+KSKmJoi+V1VbYv6acsWZZjNdLz4wxJRMS7MsayMjARGMWSQ3dfyRVDWyxDgY2Lt0eBecAxkj4aEQdlCOG5iHismKcZEhHXFK98cxsJ/L09LlI9mb9J6urvb08meEmnkX6B/g+YK+kq2hJbRHwyc0j3AzMk/axPHN/MGENdvhcbSFqT1HP/Pmlo4t8i4oqyG67RuPPJmdoZiMsoxnepsCMk6ZvAu4CrgG9ExM3FQycUrz5z+EvRW74WOFfSAmBRprbbnQfcJOmy4nof4HxJq5OGWLumJ4doiuGAZSp6k9lI+vIy4jg+YwwdvycVfC/mRcTmknYHPg58kTS5Vvokq6TjI+LLkqZ2eDgi4kNlx9AnntcBf4yIZ4rrVYFXRcT8jDHcERGb5mqvnzg+BFwQEf/X4bG1cozHFwn0GdLw4SHAWsC5VQytShoPTChiuT4iZpfSTi8m+E4krQ28NiJuqzqWqhQ1f95cXN4bEc9VEMNtEbGZpMnAjIiYJunWiNgiYwxDI+L55X9k6XHMBt5WnIfQ+vnMiohsSyUlTQFOi4jbc7XZp/1+/7BHxG8yxnIkKaE/nqvN/uRYzdOTQzQtkmaQXvYNA+YCCyXNjIhOy5DKjGME8FnSbHz7D2znjDHsCJwNzCf1Cl4r6fAKlozOkXQF8Drgc5KGs3hlUS6/k/RL0iqaq6O6XsywVnIHiIi/F0k+p+2ADxQTz8+SnhsREblWeJ3Sz2NBmvTM5dXALcXy1TOBX1Xx3OiwmmckaZVR91fzRETPvgG3Fv8eARxfvH9bBXFcAXyYtORqB9KT54TMMcwBNmq7fjNpRj7392IIadz95cX1K0mre3LGsCpwAGkp4HzgdGC7Cr4XVwLvart+N3BV5hg27PSW+3tRlzfSH7jdSSfM3UdauvqGzDHMK34vbi2udwKmlNFWT/fggWGS1iP9Mh9bYRyvjIgzJB0VETOBmZJmZo5hpYh4cbIqIv5H0kq5Gpe0cUTcA4wtbr1e6nTmS/ki4m/AhcCFxdDdZGAmqappTh8jTeZ9u7h+EHh/joYlrRkRT5Amuysn6bBO9yPihznjiIiQ9CfgT6QJ1rWBiyVdGRGfzRRGttU8vZ7gjyeVI74+Im6R9HrgtxXE0Rrr/qOkvUgHm2yQOYbZks4AzimuDyX16nM5hnT0YqeX5Llfird2jR5IOvT9FlInIKuI+F9g22LlhiIiZ7I9D9ib9BwIljxhLYDcewLa5x1WAXYBfgNkS/CSPgkcTlqi+QPgMxHxnKQhpLyRK8FnW83Ts5OsxZraT0bEf9Yglr2B60gnWJ1G2r15fERkO+CkWO/8cdKYq0hPnu9Exo1PxS/KWyNiVq42lxHH70hzMhcCl0fE0/1/RmlxrEXa4dwqmzAT+Epk3sFZR8X35pzIuyfgK8AZEfFAh8dGR8TdmeJYHfgbaTiz1NU8PZvgASRdExE7VR1H3Uh6BbBBVLCiSNKNEfHW3O32iaE1PFEpSZcAd5AmvyENz2weER3X6ZcUw1URscvy7uVWDB/eFhGjM7S1ZkQ8UfxeLCUyl7AoloxeFxGljzb0+hDNDZJOZ+maI9mWXsGLq2g+wtK7BbOtu67LiiLgCkkTgUujut7DypI+T4U/j8IbImJi2/XxkubmaFjSKqQdtOsU8xDttYHWzxFDn3jad/cOAcaQXmHlULfhqlHAoUrVRmeTXv1fF10uNAYN6MF3uB2RcXliEccNpB/SHBYX+iIybtlvrTWXdARpP8CXW2vSc8VQxPEksDppTLG1qSQiYs2MMVT+8yjiuJE0znt9cT0BODnHKxxJRwFHk5L5wyxOak+Q6r+cXnYMfeLZoe1yEfBARDyUsX2Rfi+yVo7sT7Hx7SPAp4HXRETXFwH0dIKvC0lzI2JsxTHcDuxGGg44tph0zp7g66AOP48ijrGkn8dapAT7Z+ADETEvYwyfiIjTcrVXZ5LmRMS4GsTxBdIu1jWAW4HrST34P3a7rV4foqFYtdJ3g1HuQkrTJe0ZET/P3G67uqwoqkNd+jr8PChecm+uVJuHnPMCkloTu/Pa3m+PLXdJ7SdZsgAbpBo5s4FPRcT9GcK4SdJWEXFLhrb6sx/pVczPSBPvN0VRzqLberoHL+m/SOOMO5GWPe0P3BwRH87UfutJK9KwxLOkJZNVDEtM6Lt6pdO9DHF0rEufebVEa5iokp+HOh/o8KLIUISuGPNeqmlgc9IEfNY9AZKOJy0fPo/08ziItLP0XuCfImLHDDHcRdoA+ABpzi73rt72WIaTVrxtR1rC+0hEbNf1dno8wbfqnrT+XYM0ubdb1bHlphqcpFS0WYsa/VXSMorPtUTGInQtkrYjbQZcG/h6RHT6A1Bm+7+OiG363LspIrZVUaAuQwwbdrrfadlkyXFsCrydtOt9PGkD3HUR8aVut9XrQzR/K/79P0nrA4+RaqBkVeVSNKUDJd4GjOjTc1yT/Ds3oSY1+ouVI29iyaG7LMMSVSTwZZG0C6miZ5DK9F5ZUSgvKJ2Ve3FxvX/bY7l6mXXpzZ5A2qfyLeCWKLEoYK8n+OmSXg6cRNoVF6ShmiyKpWirU+1StJeRJmuGAcPb7j/Bkr9EpVKNavQXK4mOIu0mngtsC9xIpt20kr7V3+M5vhfF3NSxpHHuY6vefEba0DMZ+A7peXITaangqsCRmWL4GYuHVFchdQbvJfORfRGxV662enqIpl2xk3OVnLsE67QUTdKGuV9q9mm/NjX6ixVFW5Emr8ZK2pi0s/jATO1X/r2Q9ALwEKmw1VK/5DnnROpKqZTxRyPio5nbnQAcx+KFCK25gK6vx+/JBK9lnNjTEvlPjK98KZpqULK4iGN14Jko6rEXJSVWjg4HPZQYwy0RsVWxqWibiHi2yqWTxYRaRHEGZ6Y2d+jv8UhF8bKpw2bATiqap7oH+BeW3qfR9VIFvTpEczHppffc4rrvzrSsCT4iTismTsawZHLNWSnvXNKO3r1JVQwPB6o44Pkq4B1AK5mtSiqn/LayG5b0jYj4PPBQMXT3E+BKSY+TVnBkVTwnzgFekS61EDgsIu4su+3cCXwALiNtPvtv2pJaTn3mqIYA46jmd+SvEfGLHA31ag9+X9JSvDeSnjjnR8R9FcbzZWBHUoL/OamC4fURkXMMfE5EjGvf3FSUKui3J1dCHEv1lHP1npexkmgH0kajX0bb4Rs5FDtqj42Ia4rrHUkTnaX/saubOmw+67O6aRHprIBLylqD3qH91nPzANICiEtZcp6q6yVWerIHHxHTgGnFcMC7gVMkvZL0y1RFz2V/0vriWyPig5JeRcbJ3kIdShYDPC1py9aTVdI4Fq92KtvQPpPdAK2j6tYg7STNafVWcgeIiBnFc3YwqnzzWfvqJqXKp2vkSu6FvqW0x7e9X0pJ7Z5M8G2eIa0SeIJ07NUq/X94af4WES9IWlTsWlxA/gJGX1MqwfopFpcs/pfMMUCadL5IUmtIZD3Sq60cNiaNa/YdshPVFJW6X9IXWbJG/+8yx1AXRwGfl1TlZsDzSMOXz5OeJ2tJ+mZEnJSj/aig8m1PJnhJOwEHA1uTxvQmR0mnkg/Q7GLM9/ukJ85TwM05GpZ0GamWxQ2kPzR3kHb2VqIok7AxsBHpl/ieMtf59nFXZDzcewA+RCoh0ZoTuhb4YI6GJfV7FkHuVTQRMXz5H1W6MZHKBh9CGkr9V9Lva5YE31K8wv8GsH5EvFPSGNI5Cmd0va0eHYN/AbiNlNiCPsvAMq+5HkFa7nRfRPxFqQTompGpFrvSYSNvK942Ix3eO4uU8G+IiEcyxVH5yiYVFTXLbmcAcaxC6im+kTREdGbGP3KtGBaSdkieD/yaJV/VVDIJW+Xms6L9O0lHSp4HnB4RM3Ptou0Txy+AqaQh5c0lDSMN776l2231ZA+eTL2g5Sk21HwD+F/gdZImRcZTnAAiYjowvYhnKLAFacL3JNJGjly7Wffp57FcK5smZ2hjIM4mDUNcR5pwH00ausrp1cCupFe67yNt8jk/xwqeTqrefFb4HmlidR5wbVG6oIqDYdaJiAslfQ4gIhZJKmVlUU/24OtC0h3AThGxUKl647lRwWlGktZhcS9+W1IPaS5wY84NRpZIur3VGyt6ZzfnXmvdJ56VSYn+JNKRgdn3bFS9+ayfuIZFRCnnofbT5gxgInBlRGwpaVvghDJWvPVqD74u/h4RCwEi4v7iFykrSb8lTTRfQioX/LWcG2ra4jg0In6kZVRSjAwVFGvkxeGYondWSRDF83EvUnIfRap9knWPSJtnIuIZSUhaOSLukbRR7iDUobw4kLu8+DHA5cAbJM0CRlBSWREn+BWzQZ+6I0tcZ5oLOJPUa58IvAXYVOkkoVtbu0kzaS3/q8NkWtU2l9R66S9g1eI628oRSWcDmwK/IPWU7yi7zeWofPOZllFePGcMkNa7F/szWgsR7i1rjsZDNCugDjVH2kl6M2mY5q2kcqQLc290qpIWFzzrKOfke9WKhQitc4rbvyfZlyf2VdXmM1VcXlzSVsCDEfGn4vowUsfsAeC4KOHw757swUu6MCIOKN4/ISL+te2xK3L9wOo0vl3MAWwNbEPq0Y8gle7N1f4mpEOmLy+u/5P0SwxpxUKOg9CrXCpbKxExpOoYOlE67au1F+CFzM1XXV78e6QyHiidsvUfwCdIK3umUMIwTU8meNJSq5ZdSetZW0ZkjqVSkqaREvpfSasSZgGnRcRdmUP5D+Df2653J9UhXw34EvCesgOo0x9cS4qVIivF4mM0bwT+QipzfTZLPmfK1qm8+Pcztj+0rZd+IDAl0kHwlygVxuu6Xk3w/Y0rDbYxp6nARyLi0YrjWC8ibmi7fqJ48iIpSzlWSadGxNFKx9W5RG49vJc0XNjyWERsUSzpnUnGBB8RXy3evUTSdDKXFyeV0mit2tkFmNT2WCm5uFcT/GqStiBVhFu1eF/F26q5gpC0QUQ8tIzH9okMx6LlXnffjyUmVyNi27bLdTPF0CoJcHKm9mwAIuLptsvJxb3nlQ77yEbSbFKH6LyIeJz8p46dD8yU9ChpuOi6Iq43kl6Bd11PTrIW60j7m0zLslVf6fzR3SNifp/7HyLtUntDjjjqQNI1wL9FxK/73N8W+I/IcKhyXWjxYewv3qKtJk6VE5y5SfofYJO+q0SKJZx3RMSbOn9mKbG8kbRJ8kDSfM1U4IrImASL34f1inafLu69mVT4rOvzVD2Z4OtC0p6kHsmeEfHb4t7nSDsH37ms3n0TSdqaVI/+LNL4JqR624cDB0ZEtuVokt5Eeunftz5/lmJjkn5C2kl6KXBBRPw+R7t1JOkbpO/FkVEc+qJUUfN04E8R8bkKYhpCOjfhu6SJ3jNJ9axyVxstXS1n2pdH0laSXt12fZikyyR9S9IrcsURqfTpx4BfSNpU0qmkJ872VSd3SRtJyjaBVCTwbUilET5QvA0Bts2Z3AtTSb+8i0hrnn/I4uGb0kXEe0iTzAuB70uaKemfcz43a+SLpOqqv5c0R9IcUrmAR4rHspK0Gals70mkzYH7k8oVXJ07lhx6sgcv6TfAOyLiz8VyowtYvNxodGQ8aKOIZzvSBo4bgAMiY43p4gl7Mulc2J+QSgV/h5RsT4mI/8wVS11o8eEn7SUDrouIty/vc0uIZQhpSOA00mEfg2lH74uK8fY3Fpf3RUSuMwLaY5hDWsFzBumgj2fbHrs0IvotmNeLenWSNftyo07axloFrEyaGV+gtDc911jr90m91RuBPUjDI+cBh+T8Q1MzzxSJ9beSjiQdiJ5rohcASW8jlQh4O6nq6b4RcV3OGOqkSOi3L/cDy/XeiOi4NyRHcpd0OmmC94blfnC32uzRHvwdwNiizsc9wKQoyo5KuiMiNs0Uxy+Af46Iyg5xUJ+j0CQ9CIzKXKagVoodg3cDLwe+StpwdWJE3JSp/fmknuIFpJf+SxSzyrTpyzroVIumbY1+2W0fBRxEmmT9Mam659wy2+zVHnz25UbLcCbwy6Lux0ll1ZNYjlXalolCOmxks+JVRLZkolQDfXir+Frb/XVJa+KzvZqIiFuKd5+imtLS80mv7HYHdmPpE6Zylsi1QtW1aCJiMjBZqUzxQcDU4vfmfNJk/P90u82e7MFD/uVG/cSxOmmn5h6kibwXt1/nGG9dzpLRiIgsyUTSFFJtkUv73D8E2C4i/ilHHEWbbwY+QzqI5cVOTK7vhS0maXfSH/6L+9w/BFgQEVdmjKXSWjTLiGkLUkdxs4jo+tkNvdqDp9PL7TL+Ag7Ac6SiTiuTNvtkra9Ro/Xl20XEpL43I+JcSZ/PHMtFwH+R5ieyD1VVUVSqxo6n82EwVwHTgGwJnupr0QAgaSVSh/Ag0rzdTNL3qet6NsHXgaQ9gG+Sajtv2VrnmzmGuiST/oqe516Ouygivpu5zXbZi0rV2Gp9h+0AIuJPxavfnDrVovlBrsYltU7Y2os0NHQBaf7w6X4/cUXa7NUhmjqQdB3wsajoGLQihlosGZU0E/hM3zXvxR+gUyJi+wwxtNaZf5K09noabdvRc/2xU9s5n5K+TSrbfFxxvcSkeNMVO1nHRJ9Tk4pe7F05d7L2aX9lMteiKXZ7n0daopnluege/AqoYl11B7VYMkoa875Q0lmkk+oBxgOHkV6K5jCHxctWWzG1BJBlJysVFJWqsUtJm72ObJsrW52Mp0upnwPhJT0L3B8Rd5cdR64SKu0G25OtiWqRTCLi5qJcwcdJu1gB7gS2iYgFmWLIPp66DHVZ5VUHXwC+Bjwg6QHSH9/XkjYb5drJ2t+B8MOA0ZJuiAYeCOMhmh4n6VhgT+BRYCRpLiCKZHJ2REyoOL4JwPsi4uMZ21wJ+CegNSw0A/hezmWsdVnlVRd12Mm6LMWmuNsjYpOqY+k2J/gGqFsykTSWNJl0IOn0nksj4rSM7f8AWIl0oATA+4HnI+KIXDFYUqNFAP2StF5E/LHqOLrNCd66oviDchApsT9G2qn36YjYsIJYXpzk7O+ela8uiwAGq56sJmm1dA9pDmCfiNiu6LFXVS7heUkv1uJXOq920JZuqFjHRQAR8UUWD9mUqniFOyh5ktW6ZSKpB3+NpF+Semr9rY0v02eKOO4vYtiQakoWWD0WAXwH2DJTW7XiBG9dERHTgGnFErj3AP8CvErSd4FpEXFFxliuUjr0YyNSgr+nvTSsZeUVRRXyGLyVpth49F7SiU6l14HplQm9wabqRQCS/gJcu6zHo8GHsTvBW2N4Qs86kfRbYJkrqCJiZsZwsvIQjTVJXXb1Wr081eQk3h+vorEmGSqp1WnZhSXP2XRnZvCq7ECeqjnBW5O0JvQuwxN6tti/S3p160LSYZIuk/QtNfwgdI/BW6NUPaFn9TOY52ac4M2s0QZz+WYP0ZhZ0w3auZlG/+fMzBjEm608RGNmjTdY52ac4M3MGspj8GZmDeUEb2bWUE7wZmYN5QRvtSZphqTxVcfRImljSXMl3dp+qEgXv/5YSXsO4OOe6nbb1jxO8DaoSRr6D37Ke4DLImKLiPjfEkIaSzpE3WyFOcFbLUgaJekeSWdLuk3SxZJW6/Mx35U0W9Kdko4v7u0iaVrbx+wq6dLi/d0k3SjpN5IukrRGcX++pC9Jup5Ur75TPGMl3VTEMk3S2kXP+mjgCEnXLOf/8QNJd0g6V9I7JM2S9FtJWxcft7WkG4pXAjdI2kjSy4CvAAcWrxIOlLSGpKmSbi9imdjW1tclzSvifNVL/+5bY0WE3/xW+RswCghgQnF9JvBpYAYwvrj3iuLfocX9zShObAJGFI+dB+wDrEM65GH14v6/Al8q3p8PfHY58dwG7FC8/xXg1OL940iHiff3/1gEvIXUgZpT/F8EvBv4SfFxawLDivffAVxSvP8B4PS2r3dCq+3ieu3i3yCdfwtwIvCFqn+Gfqvfm3eyWp08GBGzivd/BHyyz+MHSJpE2oG9HjAmIm6TdA5wqKSpwFuBw4A9gDHALEkALwNubPtaP15WEJLWAl4ei2uInw1c9A/8P34XEbcXX+tO4KqICEm3k/4AAKwFnF0cLRjASsv4Wu8gnXULQEQ8Xrz7d2B68f4cYNd/ID4bJJzgrU767rp78VrS60g9+q0i4nFJZwGrFA9PBX4KPANcFBGLlLL6lRFx8DLaerqrkS+p/fzXF9quX2Dx79xXgWsiYl9Jo0ivSDoRS39fAJ6LiNb95/HvsnXgMXirk5GS3lq8fzBwfdtja5KS8l+L8eZ3th6IiD8AfwC+AJxV3L4JmFDUG0HSasXW9OWKiL8Cj0t6e3Hr/UC3TwRaC3i4eP8DbfefBIa3XV8BHNm6kLR2l+OwBnOCtzq5Gzhc0m3AK4Dvth6IiHnArcCdpDHtWX0+91zSEM9dxccvJCXO84uvdxOw8T8Qy+HAScXnjiWNw3fTiaSDKGaR5hRargHGtCZZga8BaxcTtvOAnbochzWYa9FYLRTDFNMjYtOX+PmnA7dGxBldDcysh3ncznqepDmk4ZtPVR2LWZ24B2+DWnHCz4Q+tydHxNTlfN4rgas6PLRLRDzWrfjMVoQTvJlZQ3mS1cysoZzgzcwaygnezKyhnODNzBrq/wFzPL9Fyhj7agAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax=sns.countplot(x='player_of_match', data=IPL2008, \n",
    "                 order=IPL2008.player_of_match.value_counts(ascending=False)[:10].index)\n",
    "plt.xticks(rotation=90)\n",
    "value=IPL2008.player_of_match.value_counts(ascending=False)[:10].values\n",
    "ax.bar_label(container=ax.containers[0], labels=value);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "367f5247",
   "metadata": {},
   "source": [
    "## In IPL 2008 which are the top 4 teams that are qualified"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "fdb39ff4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax=sns.countplot(x='winner', data=IPL2008, \n",
    "                 order=IPL2008.winner.value_counts(ascending=False)[:10].index)\n",
    "plt.xticks(rotation=90)\n",
    "value=IPL2008.winner.value_counts(ascending=False)[:10].values\n",
    "ax.bar_label(container=ax.containers[0], labels=value);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "78d2ded1",
   "metadata": {},
   "source": [
    "# Analyse the recent IPL season 2022"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "828ca28e",
   "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>year</th>\n",
       "      <th>start_date</th>\n",
       "      <th>venue</th>\n",
       "      <th>innings</th>\n",
       "      <th>ball</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>striker</th>\n",
       "      <th>non_striker</th>\n",
       "      <th>bowler</th>\n",
       "      <th>runs_off_bat</th>\n",
       "      <th>extras</th>\n",
       "      <th>wides</th>\n",
       "      <th>noballs</th>\n",
       "      <th>byes</th>\n",
       "      <th>legbyes</th>\n",
       "      <th>penalty</th>\n",
       "      <th>wicket_type</th>\n",
       "      <th>player_dismissed</th>\n",
       "      <th>other_wicket_type</th>\n",
       "      <th>other_player_dismissed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1082591.0</td>\n",
       "      <td>2017</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</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  year start_date                                      venue  \\\n",
       "0  1082591.0  2017 2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "1  1082591.0  2017 2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "2  1082591.0  2017 2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "3  1082591.0  2017 2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "4  1082591.0  2017 2017-04-05  Rajiv Gandhi International Stadium, Uppal   \n",
       "\n",
       "   innings  ball         batting_team                 bowling_team    striker  \\\n",
       "0      1.0   0.1  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "1      1.0   0.2  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "2      1.0   0.3  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "3      1.0   0.4  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "4      1.0   0.5  Sunrisers Hyderabad  Royal Challengers Bangalore  DA Warner   \n",
       "\n",
       "  non_striker    bowler  runs_off_bat  extras  wides  noballs  byes  legbyes  \\\n",
       "0    S Dhawan  TS Mills           0.0     0.0    0.0      0.0   0.0      0.0   \n",
       "1    S Dhawan  TS Mills           0.0     0.0    0.0      0.0   0.0      0.0   \n",
       "2    S Dhawan  TS Mills           4.0     0.0    0.0      0.0   0.0      0.0   \n",
       "3    S Dhawan  TS Mills           0.0     0.0    0.0      0.0   0.0      0.0   \n",
       "4    S Dhawan  TS Mills           0.0     2.0    2.0      0.0   0.0      0.0   \n",
       "\n",
       "   penalty wicket_type player_dismissed  other_wicket_type  \\\n",
       "0      0.0         NaN              NaN                NaN   \n",
       "1      0.0         NaN              NaN                NaN   \n",
       "2      0.0         NaN              NaN                NaN   \n",
       "3      0.0         NaN              NaN                NaN   \n",
       "4      0.0         NaN              NaN                NaN   \n",
       "\n",
       "   other_player_dismissed  \n",
       "0                     NaN  \n",
       "1                     NaN  \n",
       "2                     NaN  \n",
       "3                     NaN  \n",
       "4                     NaN  "
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "12ba6461",
   "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>year</th>\n",
       "      <th>start_date</th>\n",
       "      <th>venue</th>\n",
       "      <th>innings</th>\n",
       "      <th>ball</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>striker</th>\n",
       "      <th>non_striker</th>\n",
       "      <th>bowler</th>\n",
       "      <th>runs_off_bat</th>\n",
       "      <th>extras</th>\n",
       "      <th>wides</th>\n",
       "      <th>noballs</th>\n",
       "      <th>byes</th>\n",
       "      <th>legbyes</th>\n",
       "      <th>penalty</th>\n",
       "      <th>wicket_type</th>\n",
       "      <th>player_dismissed</th>\n",
       "      <th>other_wicket_type</th>\n",
       "      <th>other_player_dismissed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>71444</th>\n",
       "      <td>1304047.0</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-03-26</td>\n",
       "      <td>Wankhede Stadium, Mumbai</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>RD Gaikwad</td>\n",
       "      <td>DP Conway</td>\n",
       "      <td>UT Yadav</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71445</th>\n",
       "      <td>1304047.0</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-03-26</td>\n",
       "      <td>Wankhede Stadium, Mumbai</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>RD Gaikwad</td>\n",
       "      <td>DP Conway</td>\n",
       "      <td>UT Yadav</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71446</th>\n",
       "      <td>1304047.0</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-03-26</td>\n",
       "      <td>Wankhede Stadium, Mumbai</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>RD Gaikwad</td>\n",
       "      <td>DP Conway</td>\n",
       "      <td>UT Yadav</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71447</th>\n",
       "      <td>1304047.0</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-03-26</td>\n",
       "      <td>Wankhede Stadium, Mumbai</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>RD Gaikwad</td>\n",
       "      <td>DP Conway</td>\n",
       "      <td>UT Yadav</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71448</th>\n",
       "      <td>1304047.0</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-03-26</td>\n",
       "      <td>Wankhede Stadium, Mumbai</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>RD Gaikwad</td>\n",
       "      <td>DP Conway</td>\n",
       "      <td>UT Yadav</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>caught</td>\n",
       "      <td>RD Gaikwad</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        match_id  year start_date                     venue  innings  ball  \\\n",
       "71444  1304047.0  2022 2022-03-26  Wankhede Stadium, Mumbai      1.0   0.1   \n",
       "71445  1304047.0  2022 2022-03-26  Wankhede Stadium, Mumbai      1.0   0.2   \n",
       "71446  1304047.0  2022 2022-03-26  Wankhede Stadium, Mumbai      1.0   0.3   \n",
       "71447  1304047.0  2022 2022-03-26  Wankhede Stadium, Mumbai      1.0   0.4   \n",
       "71448  1304047.0  2022 2022-03-26  Wankhede Stadium, Mumbai      1.0   0.5   \n",
       "\n",
       "              batting_team           bowling_team     striker non_striker  \\\n",
       "71444  Chennai Super Kings  Kolkata Knight Riders  RD Gaikwad   DP Conway   \n",
       "71445  Chennai Super Kings  Kolkata Knight Riders  RD Gaikwad   DP Conway   \n",
       "71446  Chennai Super Kings  Kolkata Knight Riders  RD Gaikwad   DP Conway   \n",
       "71447  Chennai Super Kings  Kolkata Knight Riders  RD Gaikwad   DP Conway   \n",
       "71448  Chennai Super Kings  Kolkata Knight Riders  RD Gaikwad   DP Conway   \n",
       "\n",
       "         bowler  runs_off_bat  extras  wides  noballs  byes  legbyes  penalty  \\\n",
       "71444  UT Yadav           0.0     1.0    0.0      1.0   0.0      0.0      0.0   \n",
       "71445  UT Yadav           0.0     0.0    0.0      0.0   0.0      0.0      0.0   \n",
       "71446  UT Yadav           0.0     1.0    1.0      0.0   0.0      0.0      0.0   \n",
       "71447  UT Yadav           0.0     0.0    0.0      0.0   0.0      0.0      0.0   \n",
       "71448  UT Yadav           0.0     0.0    0.0      0.0   0.0      0.0      0.0   \n",
       "\n",
       "      wicket_type player_dismissed  other_wicket_type  other_player_dismissed  \n",
       "71444         NaN              NaN                NaN                     NaN  \n",
       "71445         NaN              NaN                NaN                     NaN  \n",
       "71446         NaN              NaN                NaN                     NaN  \n",
       "71447         NaN              NaN                NaN                     NaN  \n",
       "71448      caught       RD Gaikwad                NaN                     NaN  "
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "IPL_2022=df[df['year']==2022]\n",
    "IPL_2022.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9408f3b0",
   "metadata": {},
   "source": [
    "## Which player scored most runs in IPL 2022"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "8222a941",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def add_value_label(x_list, y_list):\n",
    "    for i in range(len(x_list)):\n",
    "        plt.annotate(y_list[i], (i,y_list[i]), ha='center', fontsize=15)\n",
    "        \n",
    "plt.figure(figsize=(10,6))\n",
    "sns.barplot(x='striker', y='runs_off_bat', data=IPL_2022, estimator=sum, ci=None,\n",
    "           order=IPL_2022.groupby('striker').runs_off_bat.sum().sort_values(ascending=False)[:10].index)\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel('Player', fontsize=15)\n",
    "plt.ylabel('Total Runs Scored', fontsize=15)\n",
    "\n",
    "index=IPL_2022.groupby('striker').runs_off_bat.sum().sort_values(ascending=False)[:10].index\n",
    "value=IPL_2022.groupby('striker').runs_off_bat.sum().sort_values(ascending=False)[:10].values\n",
    "\n",
    "add_value_label(index, value);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89213fb0",
   "metadata": {},
   "source": [
    "## What is the most common wicket type in IPL 2022"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "b2e759f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax=sns.countplot(y='wicket_type', data=IPL_2022,\n",
    "                order=IPL_2022.wicket_type.value_counts(ascending=False).index)\n",
    "value=IPL_2022.wicket_type.value_counts(ascending=False).values\n",
    "ax.bar_label(container=ax.containers[0], labels=value);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "93efdce0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>year</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by</th>\n",
       "      <th>winner_type</th>\n",
       "      <th>eliminator</th>\n",
       "      <th>win_toss=win_match</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>SE Marsh</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>16.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>AM Rahane</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>8.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>MA Starc</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>9.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>CH Gayle</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>3.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>M Morkel</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>7.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945</th>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>UT Yadav</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>6.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>946</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>field</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>6.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>947</th>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>SS Iyer</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>37.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>948</th>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>AD Russell</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>4.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>949</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>V Sehwag</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>24.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>950 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     team1                        team2    year  \\\n",
       "0          Kings XI Punjab             Rajasthan Royals  2014.0   \n",
       "1         Rajasthan Royals          Chennai Super Kings  2015.0   \n",
       "2         Rajasthan Royals  Royal Challengers Bangalore  2015.0   \n",
       "3    Kolkata Knight Riders  Royal Challengers Bangalore  2015.0   \n",
       "4    Kolkata Knight Riders               Mumbai Indians  2015.0   \n",
       "..                     ...                          ...     ...   \n",
       "945       Delhi Daredevils        Kolkata Knight Riders  2015.0   \n",
       "946    Chennai Super Kings          Sunrisers Hyderabad  2014.0   \n",
       "947       Delhi Daredevils               Mumbai Indians  2015.0   \n",
       "948        Kings XI Punjab        Kolkata Knight Riders  2015.0   \n",
       "949    Chennai Super Kings              Kings XI Punjab  2014.0   \n",
       "\n",
       "                     toss_winner toss_decision player_of_match  \\\n",
       "0               Rajasthan Royals         field        SE Marsh   \n",
       "1            Chennai Super Kings           bat       AM Rahane   \n",
       "2    Royal Challengers Bangalore         field        MA Starc   \n",
       "3    Royal Challengers Bangalore         field        CH Gayle   \n",
       "4          Kolkata Knight Riders         field        M Morkel   \n",
       "..                           ...           ...             ...   \n",
       "945        Kolkata Knight Riders         field        UT Yadav   \n",
       "946          Sunrisers Hyderabad         field       DA Warner   \n",
       "947               Mumbai Indians         field         SS Iyer   \n",
       "948        Kolkata Knight Riders         field      AD Russell   \n",
       "949          Chennai Super Kings         field        V Sehwag   \n",
       "\n",
       "                          winner  win_by winner_type eliminator  \\\n",
       "0                Kings XI Punjab    16.0        runs        NaN   \n",
       "1               Rajasthan Royals     8.0     wickets        NaN   \n",
       "2    Royal Challengers Bangalore     9.0     wickets        NaN   \n",
       "3    Royal Challengers Bangalore     3.0     wickets        NaN   \n",
       "4          Kolkata Knight Riders     7.0     wickets        NaN   \n",
       "..                           ...     ...         ...        ...   \n",
       "945        Kolkata Knight Riders     6.0     wickets        NaN   \n",
       "946          Sunrisers Hyderabad     6.0     wickets        NaN   \n",
       "947             Delhi Daredevils    37.0        runs        NaN   \n",
       "948        Kolkata Knight Riders     4.0     wickets        NaN   \n",
       "949              Kings XI Punjab    24.0        runs        NaN   \n",
       "\n",
       "    win_toss=win_match  \n",
       "0                 Lost  \n",
       "1                 Lost  \n",
       "2                  Win  \n",
       "3                  Win  \n",
       "4                  Win  \n",
       "..                 ...  \n",
       "945                Win  \n",
       "946                Win  \n",
       "947               Lost  \n",
       "948                Win  \n",
       "949               Lost  \n",
       "\n",
       "[950 rows x 11 columns]"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "bd6016aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>year</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by</th>\n",
       "      <th>winner_type</th>\n",
       "      <th>eliminator</th>\n",
       "      <th>win_toss=win_match</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>418</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>field</td>\n",
       "      <td>SV Samson</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>61.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>420</th>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>field</td>\n",
       "      <td>Kuldeep Yadav</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>4.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>421</th>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>Anuj Rawat</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>7.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422</th>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>Kuldeep Yadav</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>44.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>423</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>PWH de Silva</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>3.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>495</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>DR Sams</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>5.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>496</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>field</td>\n",
       "      <td>MR Marsh</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>8.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Win</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>497</th>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>bat</td>\n",
       "      <td>V Kohli</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>8.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>498</th>\n",
       "      <td>Punjab Kings</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>JM Bairstow</td>\n",
       "      <td>Punjab Kings</td>\n",
       "      <td>54.0</td>\n",
       "      <td>runs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>bat</td>\n",
       "      <td>HH Pandya</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>7.0</td>\n",
       "      <td>wickets</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lost</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>74 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     team1                        team2    year  \\\n",
       "418       Rajasthan Royals          Sunrisers Hyderabad  2022.0   \n",
       "420         Mumbai Indians               Delhi Capitals  2022.0   \n",
       "421         Mumbai Indians  Royal Challengers Bangalore  2022.0   \n",
       "422         Delhi Capitals        Kolkata Knight Riders  2022.0   \n",
       "423  Kolkata Knight Riders  Royal Challengers Bangalore  2022.0   \n",
       "..                     ...                          ...     ...   \n",
       "495    Chennai Super Kings               Mumbai Indians  2022.0   \n",
       "496       Rajasthan Royals               Delhi Capitals  2022.0   \n",
       "497         Gujarat Titans  Royal Challengers Bangalore  2022.0   \n",
       "498           Punjab Kings  Royal Challengers Bangalore  2022.0   \n",
       "499       Rajasthan Royals               Gujarat Titans  2022.0   \n",
       "\n",
       "                     toss_winner toss_decision player_of_match  \\\n",
       "418          Sunrisers Hyderabad         field       SV Samson   \n",
       "420               Delhi Capitals         field   Kuldeep Yadav   \n",
       "421  Royal Challengers Bangalore         field      Anuj Rawat   \n",
       "422        Kolkata Knight Riders         field   Kuldeep Yadav   \n",
       "423  Royal Challengers Bangalore         field    PWH de Silva   \n",
       "..                           ...           ...             ...   \n",
       "495               Mumbai Indians         field         DR Sams   \n",
       "496               Delhi Capitals         field        MR Marsh   \n",
       "497               Gujarat Titans           bat         V Kohli   \n",
       "498  Royal Challengers Bangalore         field     JM Bairstow   \n",
       "499             Rajasthan Royals           bat       HH Pandya   \n",
       "\n",
       "                          winner  win_by winner_type eliminator  \\\n",
       "418             Rajasthan Royals    61.0        runs        NaN   \n",
       "420               Delhi Capitals     4.0     wickets        NaN   \n",
       "421  Royal Challengers Bangalore     7.0     wickets        NaN   \n",
       "422               Delhi Capitals    44.0        runs        NaN   \n",
       "423  Royal Challengers Bangalore     3.0     wickets        NaN   \n",
       "..                           ...     ...         ...        ...   \n",
       "495               Mumbai Indians     5.0     wickets        NaN   \n",
       "496               Delhi Capitals     8.0     wickets        NaN   \n",
       "497  Royal Challengers Bangalore     8.0     wickets        NaN   \n",
       "498                 Punjab Kings    54.0        runs        NaN   \n",
       "499               Gujarat Titans     7.0     wickets        NaN   \n",
       "\n",
       "    win_toss=win_match  \n",
       "418               Lost  \n",
       "420                Win  \n",
       "421                Win  \n",
       "422               Lost  \n",
       "423                Win  \n",
       "..                 ...  \n",
       "495                Win  \n",
       "496                Win  \n",
       "497               Lost  \n",
       "498               Lost  \n",
       "499               Lost  \n",
       "\n",
       "[74 rows x 11 columns]"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "IPL2022=df2[df2['year']==2022]\n",
    "IPL2022"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b9b5ca9",
   "metadata": {},
   "source": [
    "## Which team won the toss maximum times in IPL 2022"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "4854afb0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "ax=sns.countplot(x='toss_winner', data=IPL2022,\n",
    "                order=IPL2022.toss_winner.value_counts(ascending=False).index)\n",
    "plt.xticks(rotation=90)\n",
    "\n",
    "value=IPL2022.toss_winner.value_counts(ascending=False).values\n",
    "ax.bar_label(container=ax.containers[0], labels=value);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4376c01",
   "metadata": {},
   "source": [
    "## How many times the batting first and batting second won the match in IPL 2022"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "40657517",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax=sns.countplot(x='winner_type', data=IPL2022, order=IPL2022.winner_type.value_counts(ascending=False).index)\n",
    "value=IPL2022.winner_type.value_counts(ascending=False).values\n",
    "ax.bar_label(container=ax.containers[0], labels=value);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "deed7753",
   "metadata": {},
   "source": [
    "#### both batting first and batting second team won the match equal times"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6fb0258",
   "metadata": {},
   "source": [
    "## Who won the player of the match most time in IPL 2022"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "ad45fda1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax=sns.countplot(x='player_of_match', data=IPL2022, \n",
    "                 order=IPL2022.player_of_match.value_counts(ascending=False)[:10].index)\n",
    "plt.xticks(rotation=90)\n",
    "value=IPL2022.player_of_match.value_counts(ascending=False)[:10].values\n",
    "ax.bar_label(container=ax.containers[0], labels=value);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90c34be2",
   "metadata": {},
   "source": [
    "## In IPL 2022 which are the top 4 teams that are qualified"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "fbacb00e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax=sns.countplot(x='winner', data=IPL2022, \n",
    "                 order=IPL2022.winner.value_counts(ascending=False)[:10].index)\n",
    "plt.xticks(rotation=90)\n",
    "value=IPL2022.winner.value_counts(ascending=False)[:10].values\n",
    "ax.bar_label(container=ax.containers[0], labels=value);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6abb7a7d",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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