EDA_of_IPL_matches.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.7.4"
    },
    "colab": {
      "name": "Copy of IPL_matches.ipynb",
      "provenance": [],
      "include_colab_link": true
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/santanukumar666/data_analysis_projects/blob/main/Copy_of_IPL_matches.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5KO94IB10yLh"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n"
      ],
      "execution_count": 36,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "emnSo59X0yLj",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 442
        },
        "outputId": "860f1c3e-f830-4177-93ab-20d04020871c"
      },
      "source": [
        "df=pd.read_csv('matches.csv')\n",
        "df.head()"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>season</th>\n",
              "      <th>city</th>\n",
              "      <th>date</th>\n",
              "      <th>team1</th>\n",
              "      <th>team2</th>\n",
              "      <th>toss_winner</th>\n",
              "      <th>toss_decision</th>\n",
              "      <th>result</th>\n",
              "      <th>dl_applied</th>\n",
              "      <th>winner</th>\n",
              "      <th>win_by_runs</th>\n",
              "      <th>win_by_wickets</th>\n",
              "      <th>player_of_match</th>\n",
              "      <th>venue</th>\n",
              "      <th>umpire1</th>\n",
              "      <th>umpire2</th>\n",
              "      <th>umpire3</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>2017</td>\n",
              "      <td>Hyderabad</td>\n",
              "      <td>4/5/2017</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>field</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>35</td>\n",
              "      <td>0</td>\n",
              "      <td>Yuvraj Singh</td>\n",
              "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
              "      <td>AY Dandekar</td>\n",
              "      <td>NJ Llong</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>2017</td>\n",
              "      <td>Pune</td>\n",
              "      <td>4/6/2017</td>\n",
              "      <td>Mumbai Indians</td>\n",
              "      <td>Rising Pune Supergiant</td>\n",
              "      <td>Rising Pune Supergiant</td>\n",
              "      <td>field</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Rising Pune Supergiant</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>SPD Smith</td>\n",
              "      <td>Maharashtra Cricket Association Stadium</td>\n",
              "      <td>A Nand Kishore</td>\n",
              "      <td>S Ravi</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>2017</td>\n",
              "      <td>Rajkot</td>\n",
              "      <td>4/7/2017</td>\n",
              "      <td>Gujarat Lions</td>\n",
              "      <td>Kolkata Knight Riders</td>\n",
              "      <td>Kolkata Knight Riders</td>\n",
              "      <td>field</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Kolkata Knight Riders</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>CA Lynn</td>\n",
              "      <td>Saurashtra Cricket Association Stadium</td>\n",
              "      <td>Nitin Menon</td>\n",
              "      <td>CK Nandan</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>2017</td>\n",
              "      <td>Indore</td>\n",
              "      <td>4/8/2017</td>\n",
              "      <td>Rising Pune Supergiant</td>\n",
              "      <td>Kings XI Punjab</td>\n",
              "      <td>Kings XI Punjab</td>\n",
              "      <td>field</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Kings XI Punjab</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>GJ Maxwell</td>\n",
              "      <td>Holkar Cricket Stadium</td>\n",
              "      <td>AK Chaudhary</td>\n",
              "      <td>C Shamshuddin</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>2017</td>\n",
              "      <td>Bangalore</td>\n",
              "      <td>4/8/2017</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>Delhi Daredevils</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>bat</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>15</td>\n",
              "      <td>0</td>\n",
              "      <td>KM Jadhav</td>\n",
              "      <td>M Chinnaswamy Stadium</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   id  season       city  ...         umpire1        umpire2 umpire3\n",
              "0   1    2017  Hyderabad  ...     AY Dandekar       NJ Llong     NaN\n",
              "1   2    2017       Pune  ...  A Nand Kishore         S Ravi     NaN\n",
              "2   3    2017     Rajkot  ...     Nitin Menon      CK Nandan     NaN\n",
              "3   4    2017     Indore  ...    AK Chaudhary  C Shamshuddin     NaN\n",
              "4   5    2017  Bangalore  ...             NaN            NaN     NaN\n",
              "\n",
              "[5 rows x 18 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oTTklvWJ0yLk",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6b05afeb-d5ff-4c5f-8d3b-da6a2e1c38d5"
      },
      "source": [
        "df.isnull().sum()"
      ],
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "id                   0\n",
              "season               0\n",
              "city                 7\n",
              "date                 0\n",
              "team1                0\n",
              "team2                0\n",
              "toss_winner          0\n",
              "toss_decision        0\n",
              "result               0\n",
              "dl_applied           0\n",
              "winner               3\n",
              "win_by_runs          0\n",
              "win_by_wickets       0\n",
              "player_of_match      3\n",
              "venue                0\n",
              "umpire1              1\n",
              "umpire2              1\n",
              "umpire3            636\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "O1FyG9YM0yLl",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9ff96fb0-f917-40e7-bacd-458c17778916"
      },
      "source": [
        "df.shape"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(636, 18)"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YjjmN-Z-0yLl"
      },
      "source": [
        "df.drop(['umpire3'],axis=1,inplace=True)"
      ],
      "execution_count": 40,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7f4keCud0yLl",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "99d10558-701d-42b6-a465-58b3e238216e"
      },
      "source": [
        "df.columns"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['id', 'season', 'city', 'date', 'team1', 'team2', 'toss_winner',\n",
              "       'toss_decision', 'result', 'dl_applied', 'winner', 'win_by_runs',\n",
              "       'win_by_wickets', 'player_of_match', 'venue', 'umpire1', 'umpire2'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "doMxw9kB0yLl"
      },
      "source": [
        "Teams={\n",
        "    'Royal Challengers Bangalore':'RCB', \n",
        "    'Sunrisers Hyderabad':'SRH',\n",
        "       'Rising Pune Supergiant':'RPS',\n",
        "    'Mumbai Indians':'MI',\n",
        "       'Kolkata Knight Riders':'KKR', \n",
        "    'Gujarat Lions':'GL',\n",
        "    'Kings XI Punjab':'KXIP',\n",
        "       'Delhi Daredevils':'DD',\n",
        "    'Chennai Super Kings':'CSK',\n",
        "    'Rajasthan Royals':'RR',\n",
        "       'Deccan Chargers':'DC',\n",
        "    'Kochi Tuskers Kerala':'KTK',\n",
        "    'Pune Warriors':'PW',\n",
        "       'Rising Pune Supergiants':'RPS'\n",
        "}"
      ],
      "execution_count": 42,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KECPWdKL0yLm"
      },
      "source": [
        "df['team1']=df['team1'].map(Teams)\n",
        "df['team2']=df['team2'].map(Teams)"
      ],
      "execution_count": 43,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "W-NiNIEM0yLm",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 425
        },
        "outputId": "cad40d59-19d8-420e-b925-ff754bacb551"
      },
      "source": [
        "df.head()"
      ],
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>season</th>\n",
              "      <th>city</th>\n",
              "      <th>date</th>\n",
              "      <th>team1</th>\n",
              "      <th>team2</th>\n",
              "      <th>toss_winner</th>\n",
              "      <th>toss_decision</th>\n",
              "      <th>result</th>\n",
              "      <th>dl_applied</th>\n",
              "      <th>winner</th>\n",
              "      <th>win_by_runs</th>\n",
              "      <th>win_by_wickets</th>\n",
              "      <th>player_of_match</th>\n",
              "      <th>venue</th>\n",
              "      <th>umpire1</th>\n",
              "      <th>umpire2</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>2017</td>\n",
              "      <td>Hyderabad</td>\n",
              "      <td>4/5/2017</td>\n",
              "      <td>SRH</td>\n",
              "      <td>RCB</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>field</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>35</td>\n",
              "      <td>0</td>\n",
              "      <td>Yuvraj Singh</td>\n",
              "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
              "      <td>AY Dandekar</td>\n",
              "      <td>NJ Llong</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>2017</td>\n",
              "      <td>Pune</td>\n",
              "      <td>4/6/2017</td>\n",
              "      <td>MI</td>\n",
              "      <td>RPS</td>\n",
              "      <td>Rising Pune Supergiant</td>\n",
              "      <td>field</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Rising Pune Supergiant</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>SPD Smith</td>\n",
              "      <td>Maharashtra Cricket Association Stadium</td>\n",
              "      <td>A Nand Kishore</td>\n",
              "      <td>S Ravi</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>2017</td>\n",
              "      <td>Rajkot</td>\n",
              "      <td>4/7/2017</td>\n",
              "      <td>GL</td>\n",
              "      <td>KKR</td>\n",
              "      <td>Kolkata Knight Riders</td>\n",
              "      <td>field</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Kolkata Knight Riders</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>CA Lynn</td>\n",
              "      <td>Saurashtra Cricket Association Stadium</td>\n",
              "      <td>Nitin Menon</td>\n",
              "      <td>CK Nandan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>2017</td>\n",
              "      <td>Indore</td>\n",
              "      <td>4/8/2017</td>\n",
              "      <td>RPS</td>\n",
              "      <td>KXIP</td>\n",
              "      <td>Kings XI Punjab</td>\n",
              "      <td>field</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Kings XI Punjab</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>GJ Maxwell</td>\n",
              "      <td>Holkar Cricket Stadium</td>\n",
              "      <td>AK Chaudhary</td>\n",
              "      <td>C Shamshuddin</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>2017</td>\n",
              "      <td>Bangalore</td>\n",
              "      <td>4/8/2017</td>\n",
              "      <td>RCB</td>\n",
              "      <td>DD</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>bat</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>15</td>\n",
              "      <td>0</td>\n",
              "      <td>KM Jadhav</td>\n",
              "      <td>M Chinnaswamy Stadium</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   id  season  ...         umpire1        umpire2\n",
              "0   1    2017  ...     AY Dandekar       NJ Llong\n",
              "1   2    2017  ...  A Nand Kishore         S Ravi\n",
              "2   3    2017  ...     Nitin Menon      CK Nandan\n",
              "3   4    2017  ...    AK Chaudhary  C Shamshuddin\n",
              "4   5    2017  ...             NaN            NaN\n",
              "\n",
              "[5 rows x 17 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pGpSjdzn0yLn"
      },
      "source": [
        "#### Some Basic Analysis"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tQ16ELRw0yLn",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "362f4452-2b5e-4cd4-d173-88fa7378dc61"
      },
      "source": [
        "print('Total Matches Played:',df.shape[0])\n",
        "print(' \\n Venues Played At:',df['city'].unique())     \n",
        "print(' \\n Teams :',df['team1'].unique())"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Total Matches Played: 636\n",
            " \n",
            " Venues Played At: ['Hyderabad' 'Pune' 'Rajkot' 'Indore' 'Bangalore' 'Mumbai' 'Kolkata'\n",
            " 'Delhi' 'Chandigarh' 'Kanpur' 'Jaipur' 'Chennai' 'Cape Town'\n",
            " 'Port Elizabeth' 'Durban' 'Centurion' 'East London' 'Johannesburg'\n",
            " 'Kimberley' 'Bloemfontein' 'Ahmedabad' 'Cuttack' 'Nagpur' 'Dharamsala'\n",
            " 'Kochi' 'Visakhapatnam' 'Raipur' 'Ranchi' 'Abu Dhabi' 'Sharjah' nan]\n",
            " \n",
            " Teams : ['SRH' 'MI' 'GL' 'RPS' 'RCB' 'KKR' 'DD' 'KXIP' 'CSK' 'RR' 'DC' 'KTK' 'PW']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Z7CLvP_m0yLo"
      },
      "source": [
        "##### most man of the match awards"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CXZhYSwA0yLo",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "929f1350-04a9-4cf3-a538-5e1b47797097"
      },
      "source": [
        "print(df['player_of_match'].value_counts())"
      ],
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "CH Gayle          18\n",
            "YK Pathan         16\n",
            "DA Warner         15\n",
            "AB de Villiers    15\n",
            "SK Raina          14\n",
            "                  ..\n",
            "PP Ojha            1\n",
            "JC Buttler         1\n",
            "JDP Oram           1\n",
            "Z Khan             1\n",
            "LJ Wright          1\n",
            "Name: player_of_match, Length: 201, dtype: int64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lcZ1Coe30yLo"
      },
      "source": [
        "##### maximum win by runs"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pcOkwN4i0yLo",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 134
        },
        "outputId": "96ea41ad-63f9-48ba-80ab-94aa462c0418"
      },
      "source": [
        "df[df['win_by_runs']==df['win_by_runs'].max()]"
      ],
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>season</th>\n",
              "      <th>city</th>\n",
              "      <th>date</th>\n",
              "      <th>team1</th>\n",
              "      <th>team2</th>\n",
              "      <th>toss_winner</th>\n",
              "      <th>toss_decision</th>\n",
              "      <th>result</th>\n",
              "      <th>dl_applied</th>\n",
              "      <th>winner</th>\n",
              "      <th>win_by_runs</th>\n",
              "      <th>win_by_wickets</th>\n",
              "      <th>player_of_match</th>\n",
              "      <th>venue</th>\n",
              "      <th>umpire1</th>\n",
              "      <th>umpire2</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>44</td>\n",
              "      <td>2017</td>\n",
              "      <td>Delhi</td>\n",
              "      <td>5/6/2017</td>\n",
              "      <td>MI</td>\n",
              "      <td>DD</td>\n",
              "      <td>Delhi Daredevils</td>\n",
              "      <td>field</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Mumbai Indians</td>\n",
              "      <td>146</td>\n",
              "      <td>0</td>\n",
              "      <td>LMP Simmons</td>\n",
              "      <td>Feroz Shah Kotla</td>\n",
              "      <td>Nitin Menon</td>\n",
              "      <td>CK Nandan</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    id  season   city  ...             venue      umpire1    umpire2\n",
              "43  44    2017  Delhi  ...  Feroz Shah Kotla  Nitin Menon  CK Nandan\n",
              "\n",
              "[1 rows x 17 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oT1G-OCJ0yLo"
      },
      "source": [
        "##### Mumbai Indians(MI) defeated Delhi Daredevils(DD) with the highest run difference"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "f1w9gpSg0yLp"
      },
      "source": [
        ""
      ],
      "execution_count": 47,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LrfbBqON0yLp"
      },
      "source": [
        "#### highest wins by wickets"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "scrolled": true,
        "id": "aDT_1Qk10yLp",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 780
        },
        "outputId": "93a32611-d86e-454b-fa78-49bca74f4e0c"
      },
      "source": [
        "df[df['win_by_wickets']==df['win_by_wickets'].max()]"
      ],
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>season</th>\n",
              "      <th>city</th>\n",
              "      <th>date</th>\n",
              "      <th>team1</th>\n",
              "      <th>team2</th>\n",
              "      <th>toss_winner</th>\n",
              "      <th>toss_decision</th>\n",
              "      <th>result</th>\n",
              "      <th>dl_applied</th>\n",
              "      <th>winner</th>\n",
              "      <th>win_by_runs</th>\n",
              "      <th>win_by_wickets</th>\n",
              "      <th>player_of_match</th>\n",
              "      <th>venue</th>\n",
              "      <th>umpire1</th>\n",
              "      <th>umpire2</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>2017</td>\n",
              "      <td>Rajkot</td>\n",
              "      <td>4/7/2017</td>\n",
              "      <td>GL</td>\n",
              "      <td>KKR</td>\n",
              "      <td>Kolkata Knight Riders</td>\n",
              "      <td>field</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Kolkata Knight Riders</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>CA Lynn</td>\n",
              "      <td>Saurashtra Cricket Association Stadium</td>\n",
              "      <td>Nitin Menon</td>\n",
              "      <td>CK Nandan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>35</td>\n",
              "      <td>2017</td>\n",
              "      <td>Chandigarh</td>\n",
              "      <td>4/30/2017</td>\n",
              "      <td>DD</td>\n",
              "      <td>KXIP</td>\n",
              "      <td>Kings XI Punjab</td>\n",
              "      <td>field</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Kings XI Punjab</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>Sandeep Sharma</td>\n",
              "      <td>Punjab Cricket Association IS Bindra Stadium, ...</td>\n",
              "      <td>YC Barde</td>\n",
              "      <td>CK Nandan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>71</th>\n",
              "      <td>72</td>\n",
              "      <td>2008</td>\n",
              "      <td>Mumbai</td>\n",
              "      <td>4/27/2008</td>\n",
              "      <td>MI</td>\n",
              "      <td>DC</td>\n",
              "      <td>Deccan Chargers</td>\n",
              "      <td>field</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Deccan Chargers</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>AC Gilchrist</td>\n",
              "      <td>Dr DY Patil Sports Academy</td>\n",
              "      <td>Asad Rauf</td>\n",
              "      <td>SL Shastri</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119</th>\n",
              "      <td>120</td>\n",
              "      <td>2009</td>\n",
              "      <td>Cape Town</td>\n",
              "      <td>4/19/2009</td>\n",
              "      <td>KXIP</td>\n",
              "      <td>DD</td>\n",
              "      <td>Delhi Daredevils</td>\n",
              "      <td>field</td>\n",
              "      <td>normal</td>\n",
              "      <td>1</td>\n",
              "      <td>Delhi Daredevils</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>DL Vettori</td>\n",
              "      <td>Newlands</td>\n",
              "      <td>MR Benson</td>\n",
              "      <td>SD Ranade</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>183</th>\n",
              "      <td>184</td>\n",
              "      <td>2010</td>\n",
              "      <td>Bangalore</td>\n",
              "      <td>3/18/2010</td>\n",
              "      <td>RR</td>\n",
              "      <td>RCB</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>field</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>JH Kallis</td>\n",
              "      <td>M Chinnaswamy Stadium</td>\n",
              "      <td>K Hariharan</td>\n",
              "      <td>DJ Harper</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>298</th>\n",
              "      <td>299</td>\n",
              "      <td>2011</td>\n",
              "      <td>Mumbai</td>\n",
              "      <td>5/20/2011</td>\n",
              "      <td>MI</td>\n",
              "      <td>RR</td>\n",
              "      <td>Mumbai Indians</td>\n",
              "      <td>bat</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Rajasthan Royals</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>SR Watson</td>\n",
              "      <td>Wankhede Stadium</td>\n",
              "      <td>RE Koertzen</td>\n",
              "      <td>PR Reiffel</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>376</th>\n",
              "      <td>377</td>\n",
              "      <td>2012</td>\n",
              "      <td>Jaipur</td>\n",
              "      <td>5/20/2012</td>\n",
              "      <td>RR</td>\n",
              "      <td>MI</td>\n",
              "      <td>Rajasthan Royals</td>\n",
              "      <td>bat</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Mumbai Indians</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>DR Smith</td>\n",
              "      <td>Sawai Mansingh Stadium</td>\n",
              "      <td>HDPK Dharmasena</td>\n",
              "      <td>C Shamshuddin</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>390</th>\n",
              "      <td>391</td>\n",
              "      <td>2013</td>\n",
              "      <td>Chandigarh</td>\n",
              "      <td>4/10/2013</td>\n",
              "      <td>KXIP</td>\n",
              "      <td>CSK</td>\n",
              "      <td>Chennai Super Kings</td>\n",
              "      <td>field</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Chennai Super Kings</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>MEK Hussey</td>\n",
              "      <td>Punjab Cricket Association Stadium, Mohali</td>\n",
              "      <td>Aleem Dar</td>\n",
              "      <td>C Shamshuddin</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>542</th>\n",
              "      <td>543</td>\n",
              "      <td>2015</td>\n",
              "      <td>Delhi</td>\n",
              "      <td>4/26/2015</td>\n",
              "      <td>DD</td>\n",
              "      <td>RCB</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>field</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>VR Aaron</td>\n",
              "      <td>Feroz Shah Kotla</td>\n",
              "      <td>M Erasmus</td>\n",
              "      <td>S Ravi</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>590</th>\n",
              "      <td>591</td>\n",
              "      <td>2016</td>\n",
              "      <td>Rajkot</td>\n",
              "      <td>4/21/2016</td>\n",
              "      <td>GL</td>\n",
              "      <td>SRH</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>field</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>B Kumar</td>\n",
              "      <td>Saurashtra Cricket Association Stadium</td>\n",
              "      <td>K Bharatan</td>\n",
              "      <td>HDPK Dharmasena</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      id  season  ...          umpire1          umpire2\n",
              "2      3    2017  ...      Nitin Menon        CK Nandan\n",
              "34    35    2017  ...         YC Barde        CK Nandan\n",
              "71    72    2008  ...        Asad Rauf       SL Shastri\n",
              "119  120    2009  ...        MR Benson        SD Ranade\n",
              "183  184    2010  ...      K Hariharan        DJ Harper\n",
              "298  299    2011  ...      RE Koertzen       PR Reiffel\n",
              "376  377    2012  ...  HDPK Dharmasena    C Shamshuddin\n",
              "390  391    2013  ...        Aleem Dar    C Shamshuddin\n",
              "542  543    2015  ...        M Erasmus           S Ravi\n",
              "590  591    2016  ...       K Bharatan  HDPK Dharmasena\n",
              "\n",
              "[10 rows x 17 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kKhZE5v10yLp"
      },
      "source": [
        ""
      ],
      "execution_count": 48,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HEKjDKQd0yLp"
      },
      "source": [
        "##### Toss Decisions across Seasons"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Z6KuGKGT0yLp",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        },
        "outputId": "a41afb67-f3ee-4401-d5aa-5d4e5e0026d4"
      },
      "source": [
        "sns.countplot(x='season',hue='toss_decision',data=df)\n"
      ],
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f91a800d810>"
            ]
          },
          "metadata": {},
          "execution_count": 49
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yAevODjo0yLq"
      },
      "source": [
        "##### In some seasons, the probablity that toss winners opt for batting is high while In 2016, the majority of toss winners opted for fielding"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wedWzBY40yLq"
      },
      "source": [
        ""
      ],
      "execution_count": 49,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zIIsrE2R0yLq"
      },
      "source": [
        "### Maximum Toss Winners"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M_1NgA3N0yLq",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 416
        },
        "outputId": "ebf6e1b4-3ab7-49c1-92b3-62767bd1da1f"
      },
      "source": [
        "df['toss_winner'].value_counts().plot(kind='bar')"
      ],
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f91a7e3d610>"
            ]
          },
          "metadata": {},
          "execution_count": 50
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LjiEaiim0yLq"
      },
      "source": [
        ""
      ],
      "execution_count": 50,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "a_WfaXrQ0yLr"
      },
      "source": [
        "##### Total Matches vs Wins for Teams "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VJA5U8St0yLr",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "784fbc9c-6851-41dd-8fc8-03683c6328d9"
      },
      "source": [
        "df.shape"
      ],
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(636, 17)"
            ]
          },
          "metadata": {},
          "execution_count": 51
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oCBmE0QW0yLr",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 425
        },
        "outputId": "26865d11-f395-4485-d96d-a72d23fc4cc9"
      },
      "source": [
        "df.head()"
      ],
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>season</th>\n",
              "      <th>city</th>\n",
              "      <th>date</th>\n",
              "      <th>team1</th>\n",
              "      <th>team2</th>\n",
              "      <th>toss_winner</th>\n",
              "      <th>toss_decision</th>\n",
              "      <th>result</th>\n",
              "      <th>dl_applied</th>\n",
              "      <th>winner</th>\n",
              "      <th>win_by_runs</th>\n",
              "      <th>win_by_wickets</th>\n",
              "      <th>player_of_match</th>\n",
              "      <th>venue</th>\n",
              "      <th>umpire1</th>\n",
              "      <th>umpire2</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>2017</td>\n",
              "      <td>Hyderabad</td>\n",
              "      <td>4/5/2017</td>\n",
              "      <td>SRH</td>\n",
              "      <td>RCB</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>field</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>35</td>\n",
              "      <td>0</td>\n",
              "      <td>Yuvraj Singh</td>\n",
              "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
              "      <td>AY Dandekar</td>\n",
              "      <td>NJ Llong</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>2017</td>\n",
              "      <td>Pune</td>\n",
              "      <td>4/6/2017</td>\n",
              "      <td>MI</td>\n",
              "      <td>RPS</td>\n",
              "      <td>Rising Pune Supergiant</td>\n",
              "      <td>field</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Rising Pune Supergiant</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>SPD Smith</td>\n",
              "      <td>Maharashtra Cricket Association Stadium</td>\n",
              "      <td>A Nand Kishore</td>\n",
              "      <td>S Ravi</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>2017</td>\n",
              "      <td>Rajkot</td>\n",
              "      <td>4/7/2017</td>\n",
              "      <td>GL</td>\n",
              "      <td>KKR</td>\n",
              "      <td>Kolkata Knight Riders</td>\n",
              "      <td>field</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Kolkata Knight Riders</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>CA Lynn</td>\n",
              "      <td>Saurashtra Cricket Association Stadium</td>\n",
              "      <td>Nitin Menon</td>\n",
              "      <td>CK Nandan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>2017</td>\n",
              "      <td>Indore</td>\n",
              "      <td>4/8/2017</td>\n",
              "      <td>RPS</td>\n",
              "      <td>KXIP</td>\n",
              "      <td>Kings XI Punjab</td>\n",
              "      <td>field</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Kings XI Punjab</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>GJ Maxwell</td>\n",
              "      <td>Holkar Cricket Stadium</td>\n",
              "      <td>AK Chaudhary</td>\n",
              "      <td>C Shamshuddin</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>2017</td>\n",
              "      <td>Bangalore</td>\n",
              "      <td>4/8/2017</td>\n",
              "      <td>RCB</td>\n",
              "      <td>DD</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>bat</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>15</td>\n",
              "      <td>0</td>\n",
              "      <td>KM Jadhav</td>\n",
              "      <td>M Chinnaswamy Stadium</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   id  season  ...         umpire1        umpire2\n",
              "0   1    2017  ...     AY Dandekar       NJ Llong\n",
              "1   2    2017  ...  A Nand Kishore         S Ravi\n",
              "2   3    2017  ...     Nitin Menon      CK Nandan\n",
              "3   4    2017  ...    AK Chaudhary  C Shamshuddin\n",
              "4   5    2017  ...             NaN            NaN\n",
              "\n",
              "[5 rows x 17 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9utrriZ10yLr",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "789a76b3-18b1-4d52-f73d-513e11595e3b"
      },
      "source": [
        "df['team2']"
      ],
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0       RCB\n",
              "1       RPS\n",
              "2       KKR\n",
              "3      KXIP\n",
              "4        DD\n",
              "       ... \n",
              "631     RCB\n",
              "632     RCB\n",
              "633     KKR\n",
              "634     SRH\n",
              "635     RCB\n",
              "Name: team2, Length: 636, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 53
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dgawrzTe0yLr",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417
        },
        "outputId": "7002462b-2808-408c-e432-a696ffc8f1a0"
      },
      "source": [
        "matches_played_byteams=pd.concat([df['team1'],df['team2']],axis=1)\n",
        "matches_played_byteams"
      ],
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "execute_result",
          "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",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>SRH</td>\n",
              "      <td>RCB</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>MI</td>\n",
              "      <td>RPS</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>GL</td>\n",
              "      <td>KKR</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>RPS</td>\n",
              "      <td>KXIP</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>RCB</td>\n",
              "      <td>DD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>631</th>\n",
              "      <td>DD</td>\n",
              "      <td>RCB</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>632</th>\n",
              "      <td>GL</td>\n",
              "      <td>RCB</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>633</th>\n",
              "      <td>SRH</td>\n",
              "      <td>KKR</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>634</th>\n",
              "      <td>GL</td>\n",
              "      <td>SRH</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>635</th>\n",
              "      <td>SRH</td>\n",
              "      <td>RCB</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>636 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    team1 team2\n",
              "0     SRH   RCB\n",
              "1      MI   RPS\n",
              "2      GL   KKR\n",
              "3     RPS  KXIP\n",
              "4     RCB    DD\n",
              "..    ...   ...\n",
              "631    DD   RCB\n",
              "632    GL   RCB\n",
              "633   SRH   KKR\n",
              "634    GL   SRH\n",
              "635   SRH   RCB\n",
              "\n",
              "[636 rows x 2 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gQHvDuYU0yLs",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 450
        },
        "outputId": "4a9826e3-48a3-40d8-ccea-ba988bcf7d6e"
      },
      "source": [
        "teams=(matches_played_byteams['team1'].value_counts()+matches_played_byteams['team2'].value_counts()).reset_index()\n",
        "teams.columns=['team_name','Matches_played']\n",
        "teams"
      ],
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>team_name</th>\n",
              "      <th>Matches_played</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>CSK</td>\n",
              "      <td>131</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>DC</td>\n",
              "      <td>75</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>DD</td>\n",
              "      <td>147</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>GL</td>\n",
              "      <td>30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>KKR</td>\n",
              "      <td>148</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>KTK</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>KXIP</td>\n",
              "      <td>148</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>MI</td>\n",
              "      <td>157</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>PW</td>\n",
              "      <td>46</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>RCB</td>\n",
              "      <td>152</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>RPS</td>\n",
              "      <td>30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>RR</td>\n",
              "      <td>118</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>SRH</td>\n",
              "      <td>76</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   team_name  Matches_played\n",
              "0        CSK             131\n",
              "1         DC              75\n",
              "2         DD             147\n",
              "3         GL              30\n",
              "4        KKR             148\n",
              "5        KTK              14\n",
              "6       KXIP             148\n",
              "7         MI             157\n",
              "8         PW              46\n",
              "9        RCB             152\n",
              "10       RPS              30\n",
              "11        RR             118\n",
              "12       SRH              76"
            ]
          },
          "metadata": {},
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zk_1ssdi0yLs"
      },
      "source": [
        "df['winner']=df['winner'].map(Teams)"
      ],
      "execution_count": 56,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "O4JL5BNX0yLs",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 450
        },
        "outputId": "e87c8402-2fb4-4d3b-c44c-f3ddac57e883"
      },
      "source": [
        "wins=pd.DataFrame(df['winner'].value_counts()).reset_index()\n",
        "wins.columns=['team_name','wins']\n",
        "wins"
      ],
      "execution_count": 57,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>team_name</th>\n",
              "      <th>wins</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>MI</td>\n",
              "      <td>92</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>CSK</td>\n",
              "      <td>79</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>KKR</td>\n",
              "      <td>77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>RCB</td>\n",
              "      <td>73</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>KXIP</td>\n",
              "      <td>70</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>RR</td>\n",
              "      <td>63</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>DD</td>\n",
              "      <td>62</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>SRH</td>\n",
              "      <td>42</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>DC</td>\n",
              "      <td>29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>RPS</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>GL</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>PW</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>KTK</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   team_name  wins\n",
              "0         MI    92\n",
              "1        CSK    79\n",
              "2        KKR    77\n",
              "3        RCB    73\n",
              "4       KXIP    70\n",
              "5         RR    63\n",
              "6         DD    62\n",
              "7        SRH    42\n",
              "8         DC    29\n",
              "9        RPS    15\n",
              "10        GL    13\n",
              "11        PW    12\n",
              "12       KTK     6"
            ]
          },
          "metadata": {},
          "execution_count": 57
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IhJ5N5k40yLs"
      },
      "source": [
        "player=teams.merge(wins,left_on='team_name',right_on='team_name',how='inner')"
      ],
      "execution_count": 58,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zD_nzsER0yLs",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 450
        },
        "outputId": "2864aeba-97aa-47bb-9b86-0eef9631a4bf"
      },
      "source": [
        "player.columns=['team','matches_played','wins']\n",
        "player"
      ],
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>team</th>\n",
              "      <th>matches_played</th>\n",
              "      <th>wins</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>CSK</td>\n",
              "      <td>131</td>\n",
              "      <td>79</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>DC</td>\n",
              "      <td>75</td>\n",
              "      <td>29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>DD</td>\n",
              "      <td>147</td>\n",
              "      <td>62</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>GL</td>\n",
              "      <td>30</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>KKR</td>\n",
              "      <td>148</td>\n",
              "      <td>77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>KTK</td>\n",
              "      <td>14</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>KXIP</td>\n",
              "      <td>148</td>\n",
              "      <td>70</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>MI</td>\n",
              "      <td>157</td>\n",
              "      <td>92</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>PW</td>\n",
              "      <td>46</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>RCB</td>\n",
              "      <td>152</td>\n",
              "      <td>73</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>RPS</td>\n",
              "      <td>30</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>RR</td>\n",
              "      <td>118</td>\n",
              "      <td>63</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>SRH</td>\n",
              "      <td>76</td>\n",
              "      <td>42</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    team  matches_played  wins\n",
              "0    CSK             131    79\n",
              "1     DC              75    29\n",
              "2     DD             147    62\n",
              "3     GL              30    13\n",
              "4    KKR             148    77\n",
              "5    KTK              14     6\n",
              "6   KXIP             148    70\n",
              "7     MI             157    92\n",
              "8     PW              46    12\n",
              "9    RCB             152    73\n",
              "10   RPS              30    15\n",
              "11    RR             118    63\n",
              "12   SRH              76    42"
            ]
          },
          "metadata": {},
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TsSCjZtT0yLt",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 450
        },
        "outputId": "4c98a8e3-fa1f-493d-a778-945d3939dcd8"
      },
      "source": [
        "player['%win']=(player['wins']/player['matches_played'])*100\n",
        "player"
      ],
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>team</th>\n",
              "      <th>matches_played</th>\n",
              "      <th>wins</th>\n",
              "      <th>%win</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>CSK</td>\n",
              "      <td>131</td>\n",
              "      <td>79</td>\n",
              "      <td>60.305344</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>DC</td>\n",
              "      <td>75</td>\n",
              "      <td>29</td>\n",
              "      <td>38.666667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>DD</td>\n",
              "      <td>147</td>\n",
              "      <td>62</td>\n",
              "      <td>42.176871</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>GL</td>\n",
              "      <td>30</td>\n",
              "      <td>13</td>\n",
              "      <td>43.333333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>KKR</td>\n",
              "      <td>148</td>\n",
              "      <td>77</td>\n",
              "      <td>52.027027</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>KTK</td>\n",
              "      <td>14</td>\n",
              "      <td>6</td>\n",
              "      <td>42.857143</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>KXIP</td>\n",
              "      <td>148</td>\n",
              "      <td>70</td>\n",
              "      <td>47.297297</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>MI</td>\n",
              "      <td>157</td>\n",
              "      <td>92</td>\n",
              "      <td>58.598726</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>PW</td>\n",
              "      <td>46</td>\n",
              "      <td>12</td>\n",
              "      <td>26.086957</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>RCB</td>\n",
              "      <td>152</td>\n",
              "      <td>73</td>\n",
              "      <td>48.026316</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>RPS</td>\n",
              "      <td>30</td>\n",
              "      <td>15</td>\n",
              "      <td>50.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>RR</td>\n",
              "      <td>118</td>\n",
              "      <td>63</td>\n",
              "      <td>53.389831</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>SRH</td>\n",
              "      <td>76</td>\n",
              "      <td>42</td>\n",
              "      <td>55.263158</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    team  matches_played  wins       %win\n",
              "0    CSK             131    79  60.305344\n",
              "1     DC              75    29  38.666667\n",
              "2     DD             147    62  42.176871\n",
              "3     GL              30    13  43.333333\n",
              "4    KKR             148    77  52.027027\n",
              "5    KTK              14     6  42.857143\n",
              "6   KXIP             148    70  47.297297\n",
              "7     MI             157    92  58.598726\n",
              "8     PW              46    12  26.086957\n",
              "9    RCB             152    73  48.026316\n",
              "10   RPS              30    15  50.000000\n",
              "11    RR             118    63  53.389831\n",
              "12   SRH              76    42  55.263158"
            ]
          },
          "metadata": {},
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YM6oJU7m0yLt",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 17
        },
        "outputId": "e6f9c80b-7137-4bd0-dc09-59ad3c49a6c8"
      },
      "source": [
        "import plotly.offline as py\n",
        "py.init_notebook_mode(connected=True)\n",
        "import plotly.graph_objs as go"
      ],
      "execution_count": 61,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "        <script type=\"text/javascript\">\n",
              "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
              "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
              "        if (typeof require !== 'undefined') {\n",
              "        require.undef(\"plotly\");\n",
              "        requirejs.config({\n",
              "            paths: {\n",
              "                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n",
              "            }\n",
              "        });\n",
              "        require(['plotly'], function(Plotly) {\n",
              "            window._Plotly = Plotly;\n",
              "        });\n",
              "        }\n",
              "        </script>\n",
              "        "
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HAjqy3Fv0yLt"
      },
      "source": [
        "trace1 = go.Bar(\n",
        "    x=player['team'],\n",
        "    y=player['matches_played'],\n",
        "    name='Total Matches'\n",
        ")\n",
        "trace2 = go.Bar(\n",
        "    x=player.team,\n",
        "    y=player['wins'],\n",
        "    name='Matches Won'\n",
        ")\n",
        "\n"
      ],
      "execution_count": 62,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XgFAe_bE0yLt",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "outputId": "cdf616db-222e-4e6f-a25c-1d3a33627a8d"
      },
      "source": [
        "data = [trace1, trace2]\n",
        "py.iplot(data)"
      ],
      "execution_count": 63,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<div>\n",
              "        \n",
              "        \n",
              "            <div id=\"d8b05b70-5a86-4eee-90fd-80f0b8f2a1ba\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
              "            <script type=\"text/javascript\">\n",
              "                require([\"plotly\"], function(Plotly) {\n",
              "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
              "                    \n",
              "                if (document.getElementById(\"d8b05b70-5a86-4eee-90fd-80f0b8f2a1ba\")) {\n",
              "                    Plotly.newPlot(\n",
              "                        'd8b05b70-5a86-4eee-90fd-80f0b8f2a1ba',\n",
              "                        [{\"name\": \"Total Matches\", \"type\": \"bar\", \"x\": [\"CSK\", \"DC\", \"DD\", \"GL\", \"KKR\", \"KTK\", \"KXIP\", \"MI\", \"PW\", \"RCB\", \"RPS\", \"RR\", \"SRH\"], \"y\": [131, 75, 147, 30, 148, 14, 148, 157, 46, 152, 30, 118, 76]}, {\"name\": \"Matches Won\", \"type\": \"bar\", \"x\": [\"CSK\", \"DC\", \"DD\", \"GL\", \"KKR\", \"KTK\", \"KXIP\", \"MI\", \"PW\", \"RCB\", \"RPS\", \"RR\", \"SRH\"], \"y\": [79, 29, 62, 13, 77, 6, 70, 92, 12, 73, 15, 63, 42]}],\n",
              "                        {\"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}},\n",
              "                        {\"responsive\": true}\n",
              "                    ).then(function(){\n",
              "                            \n",
              "var gd = document.getElementById('d8b05b70-5a86-4eee-90fd-80f0b8f2a1ba');\n",
              "var x = new MutationObserver(function (mutations, observer) {{\n",
              "        var display = window.getComputedStyle(gd).display;\n",
              "        if (!display || display === 'none') {{\n",
              "            console.log([gd, 'removed!']);\n",
              "            Plotly.purge(gd);\n",
              "            observer.disconnect();\n",
              "        }}\n",
              "}});\n",
              "\n",
              "// Listen for the removal of the full notebook cells\n",
              "var notebookContainer = gd.closest('#notebook-container');\n",
              "if (notebookContainer) {{\n",
              "    x.observe(notebookContainer, {childList: true});\n",
              "}}\n",
              "\n",
              "// Listen for the clearing of the current output cell\n",
              "var outputEl = gd.closest('.output');\n",
              "if (outputEl) {{\n",
              "    x.observe(outputEl, {childList: true});\n",
              "}}\n",
              "\n",
              "                        })\n",
              "                };\n",
              "                });\n",
              "            </script>\n",
              "        </div>"
            ],
            "application/vnd.plotly.v1+json": {
              "data": [
                {
                  "y": [
                    131,
                    75,
                    147,
                    30,
                    148,
                    14,
                    148,
                    157,
                    46,
                    152,
                    30,
                    118,
                    76
                  ],
                  "x": [
                    "CSK",
                    "DC",
                    "DD",
                    "GL",
                    "KKR",
                    "KTK",
                    "KXIP",
                    "MI",
                    "PW",
                    "RCB",
                    "RPS",
                    "RR",
                    "SRH"
                  ],
                  "type": "bar",
                  "name": "Total Matches"
                },
                {
                  "y": [
                    79,
                    29,
                    62,
                    13,
                    77,
                    6,
                    70,
                    92,
                    12,
                    73,
                    15,
                    63,
                    42
                  ],
                  "x": [
                    "CSK",
                    "DC",
                    "DD",
                    "GL",
                    "KKR",
                    "KTK",
                    "KXIP",
                    "MI",
                    "PW",
                    "RCB",
                    "RPS",
                    "RR",
                    "SRH"
                  ],
                  "type": "bar",
                  "name": "Matches Won"
                }
              ],
              "config": {
                "plotlyServerURL": "https://plot.ly",
                "linkText": "Export to plot.ly",
                "showLink": false
              },
              "layout": {
                "template": {
                  "layout": {
                    "shapedefaults": {
                      "line": {
                        "color": "#2a3f5f"
                      }
                    },
                    "polar": {
                      "radialaxis": {
                        "ticks": "",
                        "gridcolor": "white",
                        "linecolor": "white"
                      },
                      "bgcolor": "#E5ECF6",
                      "angularaxis": {
                        "ticks": "",
                        "gridcolor": "white",
                        "linecolor": "white"
                      }
                    },
                    "colorway": [
                      "#636efa",
                      "#EF553B",
                      "#00cc96",
                      "#ab63fa",
                      "#FFA15A",
                      "#19d3f3",
                      "#FF6692",
                      "#B6E880",
                      "#FF97FF",
                      "#FECB52"
                    ],
                    "xaxis": {
                      "automargin": true,
                      "title": {
                        "standoff": 15
                      },
                      "zerolinewidth": 2,
                      "ticks": "",
                      "zerolinecolor": "white",
                      "gridcolor": "white",
                      "linecolor": "white"
                    },
                    "colorscale": {
                      "diverging": [
                        [
                          0,
                          "#8e0152"
                        ],
                        [
                          0.1,
                          "#c51b7d"
                        ],
                        [
                          0.2,
                          "#de77ae"
                        ],
                        [
                          0.3,
                          "#f1b6da"
                        ],
                        [
                          0.4,
                          "#fde0ef"
                        ],
                        [
                          0.5,
                          "#f7f7f7"
                        ],
                        [
                          0.6,
                          "#e6f5d0"
                        ],
                        [
                          0.7,
                          "#b8e186"
                        ],
                        [
                          0.8,
                          "#7fbc41"
                        ],
                        [
                          0.9,
                          "#4d9221"
                        ],
                        [
                          1,
                          "#276419"
                        ]
                      ],
                      "sequential": [
                        [
                          0,
                          "#0d0887"
                        ],
                        [
                          0.1111111111111111,
                          "#46039f"
                        ],
                        [
                          0.2222222222222222,
                          "#7201a8"
                        ],
                        [
                          0.3333333333333333,
                          "#9c179e"
                        ],
                        [
                          0.4444444444444444,
                          "#bd3786"
                        ],
                        [
                          0.5555555555555556,
                          "#d8576b"
                        ],
                        [
                          0.6666666666666666,
                          "#ed7953"
                        ],
                        [
                          0.7777777777777778,
                          "#fb9f3a"
                        ],
                        [
                          0.8888888888888888,
                          "#fdca26"
                        ],
                        [
                          1,
                          "#f0f921"
                        ]
                      ],
                      "sequentialminus": [
                        [
                          0,
                          "#0d0887"
                        ],
                        [
                          0.1111111111111111,
                          "#46039f"
                        ],
                        [
                          0.2222222222222222,
                          "#7201a8"
                        ],
                        [
                          0.3333333333333333,
                          "#9c179e"
                        ],
                        [
                          0.4444444444444444,
                          "#bd3786"
                        ],
                        [
                          0.5555555555555556,
                          "#d8576b"
                        ],
                        [
                          0.6666666666666666,
                          "#ed7953"
                        ],
                        [
                          0.7777777777777778,
                          "#fb9f3a"
                        ],
                        [
                          0.8888888888888888,
                          "#fdca26"
                        ],
                        [
                          1,
                          "#f0f921"
                        ]
                      ]
                    },
                    "paper_bgcolor": "white",
                    "plot_bgcolor": "#E5ECF6",
                    "title": {
                      "x": 0.05
                    },
                    "scene": {
                      "zaxis": {
                        "backgroundcolor": "#E5ECF6",
                        "ticks": "",
                        "gridwidth": 2,
                        "showbackground": true,
                        "zerolinecolor": "white",
                        "gridcolor": "white",
                        "linecolor": "white"
                      },
                      "xaxis": {
                        "backgroundcolor": "#E5ECF6",
                        "ticks": "",
                        "gridwidth": 2,
                        "showbackground": true,
                        "zerolinecolor": "white",
                        "gridcolor": "white",
                        "linecolor": "white"
                      },
                      "yaxis": {
                        "backgroundcolor": "#E5ECF6",
                        "ticks": "",
                        "gridwidth": 2,
                        "showbackground": true,
                        "zerolinecolor": "white",
                        "gridcolor": "white",
                        "linecolor": "white"
                      }
                    },
                    "yaxis": {
                      "automargin": true,
                      "title": {
                        "standoff": 15
                      },
                      "zerolinewidth": 2,
                      "ticks": "",
                      "zerolinecolor": "white",
                      "gridcolor": "white",
                      "linecolor": "white"
                    },
                    "annotationdefaults": {
                      "arrowwidth": 1,
                      "arrowhead": 0,
                      "arrowcolor": "#2a3f5f"
                    },
                    "hoverlabel": {
                      "align": "left"
                    },
                    "ternary": {
                      "bgcolor": "#E5ECF6",
                      "baxis": {
                        "ticks": "",
                        "gridcolor": "white",
                        "linecolor": "white"
                      },
                      "caxis": {
                        "ticks": "",
                        "gridcolor": "white",
                        "linecolor": "white"
                      },
                      "aaxis": {
                        "ticks": "",
                        "gridcolor": "white",
                        "linecolor": "white"
                      }
                    },
                    "mapbox": {
                      "style": "light"
                    },
                    "hovermode": "closest",
                    "font": {
                      "color": "#2a3f5f"
                    },
                    "geo": {
                      "showland": true,
                      "landcolor": "#E5ECF6",
                      "showlakes": true,
                      "bgcolor": "white",
                      "subunitcolor": "white",
                      "lakecolor": "white"
                    },
                    "coloraxis": {
                      "colorbar": {
                        "outlinewidth": 0,
                        "ticks": ""
                      }
                    }
                  },
                  "data": {
                    "mesh3d": [
                      {
                        "colorbar": {
                          "outlinewidth": 0,
                          "ticks": ""
                        },
                        "type": "mesh3d"
                      }
                    ],
                    "scattercarpet": [
                      {
                        "marker": {
                          "colorbar": {
                            "outlinewidth": 0,
                            "ticks": ""
                          }
                        },
                        "type": "scattercarpet"
                      }
                    ],
                    "pie": [
                      {
                        "automargin": true,
                        "type": "pie"
                      }
                    ],
                    "surface": [
                      {
                        "colorbar": {
                          "outlinewidth": 0,
                          "ticks": ""
                        },
                        "type": "surface",
                        "colorscale": [
                          [
                            0,
                            "#0d0887"
                          ],
                          [
                            0.1111111111111111,
                            "#46039f"
                          ],
                          [
                            0.2222222222222222,
                            "#7201a8"
                          ],
                          [
                            0.3333333333333333,
                            "#9c179e"
                          ],
                          [
                            0.4444444444444444,
                            "#bd3786"
                          ],
                          [
                            0.5555555555555556,
                            "#d8576b"
                          ],
                          [
                            0.6666666666666666,
                            "#ed7953"
                          ],
                          [
                            0.7777777777777778,
                            "#fb9f3a"
                          ],
                          [
                            0.8888888888888888,
                            "#fdca26"
                          ],
                          [
                            1,
                            "#f0f921"
                          ]
                        ]
                      }
                    ],
                    "table": [
                      {
                        "header": {
                          "line": {
                            "color": "white"
                          },
                          "fill": {
                            "color": "#C8D4E3"
                          }
                        },
                        "cells": {
                          "line": {
                            "color": "white"
                          },
                          "fill": {
                            "color": "#EBF0F8"
                          }
                        },
                        "type": "table"
                      }
                    ],
                    "scatterpolargl": [
                      {
                        "marker": {
                          "colorbar": {
                            "outlinewidth": 0,
                            "ticks": ""
                          }
                        },
                        "type": "scatterpolargl"
                      }
                    ],
                    "contour": [
                      {
                        "colorbar": {
                          "outlinewidth": 0,
                          "ticks": ""
                        },
                        "type": "contour",
                        "colorscale": [
                          [
                            0,
                            "#0d0887"
                          ],
                          [
                            0.1111111111111111,
                            "#46039f"
                          ],
                          [
                            0.2222222222222222,
                            "#7201a8"
                          ],
                          [
                            0.3333333333333333,
                            "#9c179e"
                          ],
                          [
                            0.4444444444444444,
                            "#bd3786"
                          ],
                          [
                            0.5555555555555556,
                            "#d8576b"
                          ],
                          [
                            0.6666666666666666,
                            "#ed7953"
                          ],
                          [
                            0.7777777777777778,
                            "#fb9f3a"
                          ],
                          [
                            0.8888888888888888,
                            "#fdca26"
                          ],
                          [
                            1,
                            "#f0f921"
                          ]
                        ]
                      }
                    ],
                    "carpet": [
                      {
                        "type": "carpet",
                        "baxis": {
                          "minorgridcolor": "white",
                          "gridcolor": "white",
                          "linecolor": "white",
                          "endlinecolor": "#2a3f5f",
                          "startlinecolor": "#2a3f5f"
                        },
                        "aaxis": {
                          "minorgridcolor": "white",
                          "gridcolor": "white",
                          "linecolor": "white",
                          "endlinecolor": "#2a3f5f",
                          "startlinecolor": "#2a3f5f"
                        }
                      }
                    ],
                    "contourcarpet": [
                      {
                        "colorbar": {
                          "outlinewidth": 0,
                          "ticks": ""
                        },
                        "type": "contourcarpet"
                      }
                    ],
                    "heatmap": [
                      {
                        "colorbar": {
                          "outlinewidth": 0,
                          "ticks": ""
                        },
                        "type": "heatmap",
                        "colorscale": [
                          [
                            0,
                            "#0d0887"
                          ],
                          [
                            0.1111111111111111,
                            "#46039f"
                          ],
                          [
                            0.2222222222222222,
                            "#7201a8"
                          ],
                          [
                            0.3333333333333333,
                            "#9c179e"
                          ],
                          [
                            0.4444444444444444,
                            "#bd3786"
                          ],
                          [
                            0.5555555555555556,
                            "#d8576b"
                          ],
                          [
                            0.6666666666666666,
                            "#ed7953"
                          ],
                          [
                            0.7777777777777778,
                            "#fb9f3a"
                          ],
                          [
                            0.8888888888888888,
                            "#fdca26"
                          ],
                          [
                            1,
                            "#f0f921"
                          ]
                        ]
                      }
                    ],
                    "scattermapbox": [
                      {
                        "marker": {
                          "colorbar": {
                            "outlinewidth": 0,
                            "ticks": ""
                          }
                        },
                        "type": "scattermapbox"
                      }
                    ],
                    "scatter3d": [
                      {
                        "marker": {
                          "colorbar": {
                            "outlinewidth": 0,
                            "ticks": ""
                          }
                        },
                        "line": {
                          "colorbar": {
                            "outlinewidth": 0,
                            "ticks": ""
                          }
                        },
                        "type": "scatter3d"
                      }
                    ],
                    "scattergl": [
                      {
                        "marker": {
                          "colorbar": {
                            "outlinewidth": 0,
                            "ticks": ""
                          }
                        },
                        "type": "scattergl"
                      }
                    ],
                    "scatterternary": [
                      {
                        "marker": {
                          "colorbar": {
                            "outlinewidth": 0,
                            "ticks": ""
                          }
                        },
                        "type": "scatterternary"
                      }
                    ],
                    "histogram": [
                      {
                        "marker": {
                          "colorbar": {
                            "outlinewidth": 0,
                            "ticks": ""
                          }
                        },
                        "type": "histogram"
                      }
                    ],
                    "heatmapgl": [
                      {
                        "colorbar": {
                          "outlinewidth": 0,
                          "ticks": ""
                        },
                        "type": "heatmapgl",
                        "colorscale": [
                          [
                            0,
                            "#0d0887"
                          ],
                          [
                            0.1111111111111111,
                            "#46039f"
                          ],
                          [
                            0.2222222222222222,
                            "#7201a8"
                          ],
                          [
                            0.3333333333333333,
                            "#9c179e"
                          ],
                          [
                            0.4444444444444444,
                            "#bd3786"
                          ],
                          [
                            0.5555555555555556,
                            "#d8576b"
                          ],
                          [
                            0.6666666666666666,
                            "#ed7953"
                          ],
                          [
                            0.7777777777777778,
                            "#fb9f3a"
                          ],
                          [
                            0.8888888888888888,
                            "#fdca26"
                          ],
                          [
                            1,
                            "#f0f921"
                          ]
                        ]
                      }
                    ],
                    "scatterpolar": [
                      {
                        "marker": {
                          "colorbar": {
                            "outlinewidth": 0,
                            "ticks": ""
                          }
                        },
                        "type": "scatterpolar"
                      }
                    ],
                    "histogram2d": [
                      {
                        "colorbar": {
                          "outlinewidth": 0,
                          "ticks": ""
                        },
                        "type": "histogram2d",
                        "colorscale": [
                          [
                            0,
                            "#0d0887"
                          ],
                          [
                            0.1111111111111111,
                            "#46039f"
                          ],
                          [
                            0.2222222222222222,
                            "#7201a8"
                          ],
                          [
                            0.3333333333333333,
                            "#9c179e"
                          ],
                          [
                            0.4444444444444444,
                            "#bd3786"
                          ],
                          [
                            0.5555555555555556,
                            "#d8576b"
                          ],
                          [
                            0.6666666666666666,
                            "#ed7953"
                          ],
                          [
                            0.7777777777777778,
                            "#fb9f3a"
                          ],
                          [
                            0.8888888888888888,
                            "#fdca26"
                          ],
                          [
                            1,
                            "#f0f921"
                          ]
                        ]
                      }
                    ],
                    "scattergeo": [
                      {
                        "marker": {
                          "colorbar": {
                            "outlinewidth": 0,
                            "ticks": ""
                          }
                        },
                        "type": "scattergeo"
                      }
                    ],
                    "bar": [
                      {
                        "marker": {
                          "line": {
                            "color": "#E5ECF6",
                            "width": 0.5
                          }
                        },
                        "type": "bar",
                        "error_x": {
                          "color": "#2a3f5f"
                        },
                        "error_y": {
                          "color": "#2a3f5f"
                        }
                      }
                    ],
                    "choropleth": [
                      {
                        "colorbar": {
                          "outlinewidth": 0,
                          "ticks": ""
                        },
                        "type": "choropleth"
                      }
                    ],
                    "parcoords": [
                      {
                        "line": {
                          "colorbar": {
                            "outlinewidth": 0,
                            "ticks": ""
                          }
                        },
                        "type": "parcoords"
                      }
                    ],
                    "barpolar": [
                      {
                        "marker": {
                          "line": {
                            "color": "#E5ECF6",
                            "width": 0.5
                          }
                        },
                        "type": "barpolar"
                      }
                    ],
                    "histogram2dcontour": [
                      {
                        "colorbar": {
                          "outlinewidth": 0,
                          "ticks": ""
                        },
                        "type": "histogram2dcontour",
                        "colorscale": [
                          [
                            0,
                            "#0d0887"
                          ],
                          [
                            0.1111111111111111,
                            "#46039f"
                          ],
                          [
                            0.2222222222222222,
                            "#7201a8"
                          ],
                          [
                            0.3333333333333333,
                            "#9c179e"
                          ],
                          [
                            0.4444444444444444,
                            "#bd3786"
                          ],
                          [
                            0.5555555555555556,
                            "#d8576b"
                          ],
                          [
                            0.6666666666666666,
                            "#ed7953"
                          ],
                          [
                            0.7777777777777778,
                            "#fb9f3a"
                          ],
                          [
                            0.8888888888888888,
                            "#fdca26"
                          ],
                          [
                            1,
                            "#f0f921"
                          ]
                        ]
                      }
                    ],
                    "scatter": [
                      {
                        "marker": {
                          "colorbar": {
                            "outlinewidth": 0,
                            "ticks": ""
                          }
                        },
                        "type": "scatter"
                      }
                    ]
                  }
                }
              }
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "W9-B5-dO0yLt"
      },
      "source": [
        "##### Matches played across each season"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4OVYjQ3X0yLu",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 383
        },
        "outputId": "75d23d81-2341-4d1d-e030-b04776a3fcf8"
      },
      "source": [
        "sns.countplot(df['season'])"
      ],
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning:\n",
            "\n",
            "Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f91a80ee890>"
            ]
          },
          "metadata": {},
          "execution_count": 64
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pvsFIOlo0yLu"
      },
      "source": [
        "##### Runs Across the Seasons"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vJVHv0Cx0yLu",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 425
        },
        "outputId": "cca28103-9a27-452d-9d68-3e821e042334"
      },
      "source": [
        "df.head()"
      ],
      "execution_count": 65,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>season</th>\n",
              "      <th>city</th>\n",
              "      <th>date</th>\n",
              "      <th>team1</th>\n",
              "      <th>team2</th>\n",
              "      <th>toss_winner</th>\n",
              "      <th>toss_decision</th>\n",
              "      <th>result</th>\n",
              "      <th>dl_applied</th>\n",
              "      <th>winner</th>\n",
              "      <th>win_by_runs</th>\n",
              "      <th>win_by_wickets</th>\n",
              "      <th>player_of_match</th>\n",
              "      <th>venue</th>\n",
              "      <th>umpire1</th>\n",
              "      <th>umpire2</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>2017</td>\n",
              "      <td>Hyderabad</td>\n",
              "      <td>4/5/2017</td>\n",
              "      <td>SRH</td>\n",
              "      <td>RCB</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>field</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>SRH</td>\n",
              "      <td>35</td>\n",
              "      <td>0</td>\n",
              "      <td>Yuvraj Singh</td>\n",
              "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
              "      <td>AY Dandekar</td>\n",
              "      <td>NJ Llong</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>2017</td>\n",
              "      <td>Pune</td>\n",
              "      <td>4/6/2017</td>\n",
              "      <td>MI</td>\n",
              "      <td>RPS</td>\n",
              "      <td>Rising Pune Supergiant</td>\n",
              "      <td>field</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>RPS</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>SPD Smith</td>\n",
              "      <td>Maharashtra Cricket Association Stadium</td>\n",
              "      <td>A Nand Kishore</td>\n",
              "      <td>S Ravi</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>2017</td>\n",
              "      <td>Rajkot</td>\n",
              "      <td>4/7/2017</td>\n",
              "      <td>GL</td>\n",
              "      <td>KKR</td>\n",
              "      <td>Kolkata Knight Riders</td>\n",
              "      <td>field</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>KKR</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>CA Lynn</td>\n",
              "      <td>Saurashtra Cricket Association Stadium</td>\n",
              "      <td>Nitin Menon</td>\n",
              "      <td>CK Nandan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>2017</td>\n",
              "      <td>Indore</td>\n",
              "      <td>4/8/2017</td>\n",
              "      <td>RPS</td>\n",
              "      <td>KXIP</td>\n",
              "      <td>Kings XI Punjab</td>\n",
              "      <td>field</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>KXIP</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>GJ Maxwell</td>\n",
              "      <td>Holkar Cricket Stadium</td>\n",
              "      <td>AK Chaudhary</td>\n",
              "      <td>C Shamshuddin</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>2017</td>\n",
              "      <td>Bangalore</td>\n",
              "      <td>4/8/2017</td>\n",
              "      <td>RCB</td>\n",
              "      <td>DD</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>bat</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>RCB</td>\n",
              "      <td>15</td>\n",
              "      <td>0</td>\n",
              "      <td>KM Jadhav</td>\n",
              "      <td>M Chinnaswamy Stadium</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   id  season  ...         umpire1        umpire2\n",
              "0   1    2017  ...     AY Dandekar       NJ Llong\n",
              "1   2    2017  ...  A Nand Kishore         S Ravi\n",
              "2   3    2017  ...     Nitin Menon      CK Nandan\n",
              "3   4    2017  ...    AK Chaudhary  C Shamshuddin\n",
              "4   5    2017  ...             NaN            NaN\n",
              "\n",
              "[5 rows x 17 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 65
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MosqE3fy0yLu",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 391
        },
        "outputId": "c52bdee2-1167-4e72-86d0-3e383a596af2"
      },
      "source": [
        "df2=pd.read_csv('deliveries.csv')\n",
        "df2.head()\n"
      ],
      "execution_count": 66,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>match_id</th>\n",
              "      <th>inning</th>\n",
              "      <th>batting_team</th>\n",
              "      <th>bowling_team</th>\n",
              "      <th>over</th>\n",
              "      <th>ball</th>\n",
              "      <th>batsman</th>\n",
              "      <th>non_striker</th>\n",
              "      <th>bowler</th>\n",
              "      <th>is_super_over</th>\n",
              "      <th>wide_runs</th>\n",
              "      <th>bye_runs</th>\n",
              "      <th>legbye_runs</th>\n",
              "      <th>noball_runs</th>\n",
              "      <th>penalty_runs</th>\n",
              "      <th>batsman_runs</th>\n",
              "      <th>extra_runs</th>\n",
              "      <th>total_runs</th>\n",
              "      <th>player_dismissed</th>\n",
              "      <th>dismissal_kind</th>\n",
              "      <th>fielder</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>DA Warner</td>\n",
              "      <td>S Dhawan</td>\n",
              "      <td>TS Mills</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>DA Warner</td>\n",
              "      <td>S Dhawan</td>\n",
              "      <td>TS Mills</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>DA Warner</td>\n",
              "      <td>S Dhawan</td>\n",
              "      <td>TS Mills</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>DA Warner</td>\n",
              "      <td>S Dhawan</td>\n",
              "      <td>TS Mills</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>DA Warner</td>\n",
              "      <td>S Dhawan</td>\n",
              "      <td>TS Mills</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   match_id  inning  ... dismissal_kind fielder\n",
              "0         1       1  ...            NaN     NaN\n",
              "1         1       1  ...            NaN     NaN\n",
              "2         1       1  ...            NaN     NaN\n",
              "3         1       1  ...            NaN     NaN\n",
              "4         1       1  ...            NaN     NaN\n",
              "\n",
              "[5 rows x 21 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "36ejZyPU0yLu",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 773
        },
        "outputId": "64e34d17-09ac-478e-8944-aa30ad0398c1"
      },
      "source": [
        "season=df[['id','season']].merge(df2, left_on = 'id', right_on = 'match_id', how = 'left').drop('id', axis = 1)\n",
        "season"
      ],
      "execution_count": 67,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>season</th>\n",
              "      <th>match_id</th>\n",
              "      <th>inning</th>\n",
              "      <th>batting_team</th>\n",
              "      <th>bowling_team</th>\n",
              "      <th>over</th>\n",
              "      <th>ball</th>\n",
              "      <th>batsman</th>\n",
              "      <th>non_striker</th>\n",
              "      <th>bowler</th>\n",
              "      <th>is_super_over</th>\n",
              "      <th>wide_runs</th>\n",
              "      <th>bye_runs</th>\n",
              "      <th>legbye_runs</th>\n",
              "      <th>noball_runs</th>\n",
              "      <th>penalty_runs</th>\n",
              "      <th>batsman_runs</th>\n",
              "      <th>extra_runs</th>\n",
              "      <th>total_runs</th>\n",
              "      <th>player_dismissed</th>\n",
              "      <th>dismissal_kind</th>\n",
              "      <th>fielder</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2017</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>DA Warner</td>\n",
              "      <td>S Dhawan</td>\n",
              "      <td>TS Mills</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2017</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>DA Warner</td>\n",
              "      <td>S Dhawan</td>\n",
              "      <td>TS Mills</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2017</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>DA Warner</td>\n",
              "      <td>S Dhawan</td>\n",
              "      <td>TS Mills</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2017</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>DA Warner</td>\n",
              "      <td>S Dhawan</td>\n",
              "      <td>TS Mills</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2017</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>DA Warner</td>\n",
              "      <td>S Dhawan</td>\n",
              "      <td>TS Mills</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</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>150455</th>\n",
              "      <td>2016</td>\n",
              "      <td>636</td>\n",
              "      <td>2</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>20</td>\n",
              "      <td>2</td>\n",
              "      <td>Sachin Baby</td>\n",
              "      <td>CJ Jordan</td>\n",
              "      <td>B Kumar</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>150456</th>\n",
              "      <td>2016</td>\n",
              "      <td>636</td>\n",
              "      <td>2</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>20</td>\n",
              "      <td>3</td>\n",
              "      <td>Sachin Baby</td>\n",
              "      <td>CJ Jordan</td>\n",
              "      <td>B Kumar</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>CJ Jordan</td>\n",
              "      <td>run out</td>\n",
              "      <td>NV Ojha</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>150457</th>\n",
              "      <td>2016</td>\n",
              "      <td>636</td>\n",
              "      <td>2</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>20</td>\n",
              "      <td>4</td>\n",
              "      <td>Iqbal Abdulla</td>\n",
              "      <td>Sachin Baby</td>\n",
              "      <td>B Kumar</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>150458</th>\n",
              "      <td>2016</td>\n",
              "      <td>636</td>\n",
              "      <td>2</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>20</td>\n",
              "      <td>5</td>\n",
              "      <td>Sachin Baby</td>\n",
              "      <td>Iqbal Abdulla</td>\n",
              "      <td>B Kumar</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>150459</th>\n",
              "      <td>2016</td>\n",
              "      <td>636</td>\n",
              "      <td>2</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>20</td>\n",
              "      <td>6</td>\n",
              "      <td>Iqbal Abdulla</td>\n",
              "      <td>Sachin Baby</td>\n",
              "      <td>B Kumar</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>150460 rows × 22 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "        season  match_id  inning  ... player_dismissed dismissal_kind  fielder\n",
              "0         2017         1       1  ...              NaN            NaN      NaN\n",
              "1         2017         1       1  ...              NaN            NaN      NaN\n",
              "2         2017         1       1  ...              NaN            NaN      NaN\n",
              "3         2017         1       1  ...              NaN            NaN      NaN\n",
              "4         2017         1       1  ...              NaN            NaN      NaN\n",
              "...        ...       ...     ...  ...              ...            ...      ...\n",
              "150455    2016       636       2  ...              NaN            NaN      NaN\n",
              "150456    2016       636       2  ...        CJ Jordan        run out  NV Ojha\n",
              "150457    2016       636       2  ...              NaN            NaN      NaN\n",
              "150458    2016       636       2  ...              NaN            NaN      NaN\n",
              "150459    2016       636       2  ...              NaN            NaN      NaN\n",
              "\n",
              "[150460 rows x 22 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fhg8BYQN0yLv",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "outputId": "3cdce7b8-8ec2-4b31-dd2d-a97d9416b94d"
      },
      "source": [
        "season=season.groupby(['season'])['total_runs'].sum().reset_index()\n",
        "season.set_index('season').plot()\n",
        "plt.title('Total Runs Across the Seasons')\n",
        "plt.show()"
      ],
      "execution_count": 68,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GiGFFr8_0yLv"
      },
      "source": [
        "##### There was a decline in total runs from 2008 to 2009.But there after there was a  increase in runs in every season until 2013, but from next season there was a slump in the total runs. But the number of matches are not equal in all seasons. We should check the average runs per match in each season"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "scUdolEk0yLv",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 357
        },
        "outputId": "ac3eb263-fc5c-4ca4-f123-81bf07ad0dba"
      },
      "source": [
        "avg_runs=df.groupby(['season'])['id'].count().reset_index().rename(columns={'id':'matches'})\n",
        "avg_runs"
      ],
      "execution_count": 69,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>season</th>\n",
              "      <th>matches</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2008</td>\n",
              "      <td>58</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2009</td>\n",
              "      <td>57</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2010</td>\n",
              "      <td>60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2011</td>\n",
              "      <td>73</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2012</td>\n",
              "      <td>74</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2013</td>\n",
              "      <td>76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2014</td>\n",
              "      <td>60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2015</td>\n",
              "      <td>59</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>2016</td>\n",
              "      <td>60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>2017</td>\n",
              "      <td>59</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   season  matches\n",
              "0    2008       58\n",
              "1    2009       57\n",
              "2    2010       60\n",
              "3    2011       73\n",
              "4    2012       74\n",
              "5    2013       76\n",
              "6    2014       60\n",
              "7    2015       59\n",
              "8    2016       60\n",
              "9    2017       59"
            ]
          },
          "metadata": {},
          "execution_count": 69
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Qy6UkTiU0yLv",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 357
        },
        "outputId": "c1525439-988c-4022-9a4c-d159980eb852"
      },
      "source": [
        "season"
      ],
      "execution_count": 70,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>season</th>\n",
              "      <th>total_runs</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2008</td>\n",
              "      <td>17937</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2009</td>\n",
              "      <td>16353</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2010</td>\n",
              "      <td>18883</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2011</td>\n",
              "      <td>21154</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2012</td>\n",
              "      <td>22453</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2013</td>\n",
              "      <td>22602</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2014</td>\n",
              "      <td>18931</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2015</td>\n",
              "      <td>18353</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>2016</td>\n",
              "      <td>18862</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>2017</td>\n",
              "      <td>18786</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   season  total_runs\n",
              "0    2008       17937\n",
              "1    2009       16353\n",
              "2    2010       18883\n",
              "3    2011       21154\n",
              "4    2012       22453\n",
              "5    2013       22602\n",
              "6    2014       18931\n",
              "7    2015       18353\n",
              "8    2016       18862\n",
              "9    2017       18786"
            ]
          },
          "metadata": {},
          "execution_count": 70
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QvvVcL7V0yLw",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 357
        },
        "outputId": "d31fdb89-a211-4713-ec6b-54b76be564f4"
      },
      "source": [
        "final=pd.concat([avg_runs,season.iloc[:,1]],axis=1)\n",
        "final"
      ],
      "execution_count": 71,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>season</th>\n",
              "      <th>matches</th>\n",
              "      <th>total_runs</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2008</td>\n",
              "      <td>58</td>\n",
              "      <td>17937</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2009</td>\n",
              "      <td>57</td>\n",
              "      <td>16353</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2010</td>\n",
              "      <td>60</td>\n",
              "      <td>18883</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2011</td>\n",
              "      <td>73</td>\n",
              "      <td>21154</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2012</td>\n",
              "      <td>74</td>\n",
              "      <td>22453</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2013</td>\n",
              "      <td>76</td>\n",
              "      <td>22602</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2014</td>\n",
              "      <td>60</td>\n",
              "      <td>18931</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2015</td>\n",
              "      <td>59</td>\n",
              "      <td>18353</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>2016</td>\n",
              "      <td>60</td>\n",
              "      <td>18862</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>2017</td>\n",
              "      <td>59</td>\n",
              "      <td>18786</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   season  matches  total_runs\n",
              "0    2008       58       17937\n",
              "1    2009       57       16353\n",
              "2    2010       60       18883\n",
              "3    2011       73       21154\n",
              "4    2012       74       22453\n",
              "5    2013       76       22602\n",
              "6    2014       60       18931\n",
              "7    2015       59       18353\n",
              "8    2016       60       18862\n",
              "9    2017       59       18786"
            ]
          },
          "metadata": {},
          "execution_count": 71
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "w2HuyTOe0yLw"
      },
      "source": [
        "final['per_match_runs']=final['total_runs']/final['matches']\n",
        "final.set_index('season',inplace=True)"
      ],
      "execution_count": 72,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jCVaiPM20yLw",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 388
        },
        "outputId": "0960c4e7-2861-44bc-f517-dd04d8d11684"
      },
      "source": [
        "final"
      ],
      "execution_count": 73,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>matches</th>\n",
              "      <th>total_runs</th>\n",
              "      <th>per_match_runs</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>season</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2008</th>\n",
              "      <td>58</td>\n",
              "      <td>17937</td>\n",
              "      <td>309.258621</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2009</th>\n",
              "      <td>57</td>\n",
              "      <td>16353</td>\n",
              "      <td>286.894737</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010</th>\n",
              "      <td>60</td>\n",
              "      <td>18883</td>\n",
              "      <td>314.716667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2011</th>\n",
              "      <td>73</td>\n",
              "      <td>21154</td>\n",
              "      <td>289.780822</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2012</th>\n",
              "      <td>74</td>\n",
              "      <td>22453</td>\n",
              "      <td>303.418919</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2013</th>\n",
              "      <td>76</td>\n",
              "      <td>22602</td>\n",
              "      <td>297.394737</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2014</th>\n",
              "      <td>60</td>\n",
              "      <td>18931</td>\n",
              "      <td>315.516667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015</th>\n",
              "      <td>59</td>\n",
              "      <td>18353</td>\n",
              "      <td>311.067797</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016</th>\n",
              "      <td>60</td>\n",
              "      <td>18862</td>\n",
              "      <td>314.366667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017</th>\n",
              "      <td>59</td>\n",
              "      <td>18786</td>\n",
              "      <td>318.406780</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        matches  total_runs  per_match_runs\n",
              "season                                     \n",
              "2008         58       17937      309.258621\n",
              "2009         57       16353      286.894737\n",
              "2010         60       18883      314.716667\n",
              "2011         73       21154      289.780822\n",
              "2012         74       22453      303.418919\n",
              "2013         76       22602      297.394737\n",
              "2014         60       18931      315.516667\n",
              "2015         59       18353      311.067797\n",
              "2016         60       18862      314.366667\n",
              "2017         59       18786      318.406780"
            ]
          },
          "metadata": {},
          "execution_count": 73
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "C98aFAnx0yLw",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        },
        "outputId": "db662915-042c-4099-8bef-3ab7bdfe3046"
      },
      "source": [
        "final['per_match_runs'].plot()"
      ],
      "execution_count": 74,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f91a8192cd0>"
            ]
          },
          "metadata": {},
          "execution_count": 74
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1AfJabHw0yLw"
      },
      "source": [
        ""
      ],
      "execution_count": 74,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "thHBdzzp0yLw"
      },
      "source": [
        "##### most lucky grounds for teams"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "n96nRB8Q0yLx"
      },
      "source": [
        "def lucky(df,team_name):\n",
        "    return df[df['winner']==team_name]['venue'].value_counts().nlargest(5)"
      ],
      "execution_count": 75,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7qX4blKB0yLx",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 482
        },
        "outputId": "13f9729f-976b-482d-cb62-046be447e2af"
      },
      "source": [
        "lucky(df,'MI').plot(kind='bar')"
      ],
      "execution_count": 76,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f91a83325d0>"
            ]
          },
          "metadata": {},
          "execution_count": 76
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NCy2vGvn0yLx"
      },
      "source": [
        ""
      ],
      "execution_count": 76,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lcBrALAL0yLx"
      },
      "source": [
        "##### comparison between 2 teams on the basis of their wins"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KGyf83rs0yLx"
      },
      "source": [
        "def comparison(team1,team2):\n",
        "    compare=df[((df['team1']==team1)|(df['team2']==team1))&((df['team1']==team2)|(df['team2']==team2))]\n",
        "    sns.countplot(x='season', hue='winner',data=compare)"
      ],
      "execution_count": 77,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OtXFb8xd0yLx",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        },
        "outputId": "aa17d103-f391-4fd6-c45c-a9e36ebeff94"
      },
      "source": [
        "comparison('MI','CSK')"
      ],
      "execution_count": 78,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "w-xYd3uO0yLy"
      },
      "source": [
        "#### Here we can see that MI and CSK have played against each other in more than 2 matches, and MI dominates"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gOA9KF1Y0yL1"
      },
      "source": [
        ""
      ],
      "execution_count": 78,
      "outputs": []
    }
  ]
}