EDA_of_Deliveries_in_IPL.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 Deliveries_production.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_Deliveries_production.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9gatp2PL6AKp",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 391
        },
        "outputId": "827a58bc-df93-46f7-8be0-49d55d6cdccf"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "df=pd.read_csv('deliveries.csv')\n",
        "df.head()\n"
      ],
      "execution_count": 1,
      "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": 1
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rHVAt5xc6AKs"
      },
      "source": [
        "#### indepth Analysis of David Warner(Australian Batsman) Performance"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "m78IYdpY6AKs",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 391
        },
        "outputId": "1f938f8b-319e-4108-fd20-eac1732e529c"
      },
      "source": [
        "filt=(df['batsman']=='DA Warner')\n",
        "df_warner=df[filt]\n",
        "df_warner.head()"
      ],
      "execution_count": 2,
      "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": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qFU-L8Kz6AKt",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "outputId": "29f6038f-5cc7-43c6-a394-794eac93253b"
      },
      "source": [
        "df_warner['dismissal_kind'].value_counts().plot.pie()"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f08358b49d0>"
            ]
          },
          "metadata": {},
          "execution_count": 3
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pj2VZtbD6AKt"
      },
      "source": [
        "#### total fours by da warner\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NB6XjXFU6AKt",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f36c3653-1f29-42c8-a698-bd2e7fb0c552"
      },
      "source": [
        "len(df_warner[df_warner['batsman_runs']==4])"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "401"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IToRlyeZ6AKu"
      },
      "source": [
        "##### total 6s by da warner"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "F3shI1rg6AKu",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d4d186e9-d979-4396-82fc-fbd077c82a66"
      },
      "source": [
        "len(df_warner[df_warner['batsman_runs']==6])"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "160"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wNgADLOk6AKv"
      },
      "source": [
        "##### total runs made by DA warner"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vHx4XGiR6AKv",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "619867c3-aa0f-4d33-91ae-31b1f5245f06"
      },
      "source": [
        "df_warner['total_runs'].sum()"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "4213"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rIdpbLTG6AKv"
      },
      "source": [
        "##### pie chart of Runs contribution of David Warner"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "q6uQ8Gr16AKv"
      },
      "source": [
        "def count(df,runs):\n",
        "    return len(df_warner[df_warner['batsman_runs']==runs])*runs"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RCrB9Rxy6AKw",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "abe7a4b8-1ec1-45af-f208-27171afedf2d"
      },
      "source": [
        "count(df_warner,1)"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "997"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NxazYgQ06AKw",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4e3a26ec-c9b8-4f7a-d56a-0691f6082f7f"
      },
      "source": [
        "count(df_warner,2)"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "414"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "19sufLBF6AKw",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "71a4524c-9edd-4370-bd4d-8f5e901768ea"
      },
      "source": [
        "count(df_warner,3)"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "39"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xpBc3PAc6AKw",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c8ff865d-d4dd-49bf-ac69-545da659e207"
      },
      "source": [
        "count(df_warner,4)"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1604"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XUEEAxUV6AKx",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "282c1093-8776-4dee-c050-fcb22e69defe"
      },
      "source": [
        "count(df_warner,6)"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "960"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7GsSoI-F6AKx",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "outputId": "00a60763-d7c8-4772-8882-a9fef2e869a5"
      },
      "source": [
        "slices=[997,414,39,1604,960]\n",
        "labels=[1,2,3,4,6]\n",
        "explode=[0,0,0,0,0.1]\n",
        "plt.pie(slices,labels=labels,autopct='%1.1f%%',explode=explode)\n",
        "plt.title(\"DA Warner total runs contribution\")\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GDE-V0Xi6AKx",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 391
        },
        "outputId": "a791fa23-5dec-49d0-93db-c39cecb06f36"
      },
      "source": [
        "df.head()"
      ],
      "execution_count": 14,
      "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": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dIFESL616AKx",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "db83ebe4-da57-4460-87b4-fc1caad5398a"
      },
      "source": [
        "df['bowling_team'].unique()"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Royal Challengers Bangalore', 'Sunrisers Hyderabad',\n",
              "       'Rising Pune Supergiant', 'Mumbai Indians',\n",
              "       'Kolkata Knight Riders', 'Gujarat Lions', 'Kings XI Punjab',\n",
              "       'Delhi Daredevils', 'Chennai Super Kings', 'Rajasthan Royals',\n",
              "       'Deccan Chargers', 'Kochi Tuskers Kerala', 'Pune Warriors',\n",
              "       'Rising Pune Supergiants'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-wyrexHJ6AKy"
      },
      "source": [
        "##### Replacing the Team Names with their abbreviations"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1kfAu5KZ6AKy"
      },
      "source": [
        "\n",
        "\n",
        "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": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zSeBvBoS6AKy"
      },
      "source": [
        "df['batting_team']=df['batting_team'].map(Teams)\n",
        "df['bowling_team']=df['bowling_team'].map(Teams)"
      ],
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WU1wEQec6AKy",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 307
        },
        "outputId": "32d4e50b-61dc-4c21-da13-0ab3f68031e1"
      },
      "source": [
        "df.head()"
      ],
      "execution_count": 18,
      "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>SRH</td>\n",
              "      <td>RCB</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>SRH</td>\n",
              "      <td>RCB</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>SRH</td>\n",
              "      <td>RCB</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>SRH</td>\n",
              "      <td>RCB</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>SRH</td>\n",
              "      <td>RCB</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 batting_team  ... player_dismissed  dismissal_kind  fielder\n",
              "0         1       1          SRH  ...              NaN             NaN      NaN\n",
              "1         1       1          SRH  ...              NaN             NaN      NaN\n",
              "2         1       1          SRH  ...              NaN             NaN      NaN\n",
              "3         1       1          SRH  ...              NaN             NaN      NaN\n",
              "4         1       1          SRH  ...              NaN             NaN      NaN\n",
              "\n",
              "[5 rows x 21 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jY2rosCK6AKz",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a88cd63b-ea9c-471f-c686-2d69ea9facaa"
      },
      "source": [
        "df.columns"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['match_id', 'inning', 'batting_team', 'bowling_team', 'over', 'ball',\n",
              "       'batsman', 'non_striker', 'bowler', 'is_super_over', 'wide_runs',\n",
              "       'bye_runs', 'legbye_runs', 'noball_runs', 'penalty_runs',\n",
              "       'batsman_runs', 'extra_runs', 'total_runs', 'player_dismissed',\n",
              "       'dismissal_kind', 'fielder'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UD1zg3W86AKz"
      },
      "source": [
        "#### Score Distribution For Teams by Innings"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bDw5N14f6AKz"
      },
      "source": [
        "runs=df.groupby(['match_id','inning','batting_team'])[['total_runs']].sum().reset_index()\n",
        "runs.drop('match_id',axis=1,inplace=True)"
      ],
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ufq62zXE6AKz",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 203
        },
        "outputId": "49fc4ef8-7875-43eb-a517-751a30403d2d"
      },
      "source": [
        "runs.head()"
      ],
      "execution_count": 21,
      "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>inning</th>\n",
              "      <th>batting_team</th>\n",
              "      <th>total_runs</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>SRH</td>\n",
              "      <td>207</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>RCB</td>\n",
              "      <td>172</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>MI</td>\n",
              "      <td>184</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2</td>\n",
              "      <td>RPS</td>\n",
              "      <td>187</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>GL</td>\n",
              "      <td>183</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   inning batting_team  total_runs\n",
              "0       1          SRH         207\n",
              "1       2          RCB         172\n",
              "2       1           MI         184\n",
              "3       2          RPS         187\n",
              "4       1           GL         183"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kkw2RNKs6AKz"
      },
      "source": [
        "inning1=runs[runs['inning']==1]\n",
        "inning2=runs[runs['inning']==2]"
      ],
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8gKNXzPM6AKz",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "outputId": "80f118ee-0a92-40de-eb18-66d89674eab6"
      },
      "source": [
        "sns.boxplot(x='batting_team',y='total_runs',data=inning1)"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f083487f610>"
            ]
          },
          "metadata": {},
          "execution_count": 23
        },
        {
          "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": "Q87f4XHH6AK0"
      },
      "source": [
        "##### According to this plot, the batting by CSK & RCB seems best. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JeiET3v66AK0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "outputId": "fc380eaf-45f5-4be7-d1a8-aa68f77eb6c9"
      },
      "source": [
        "sns.boxplot(x='batting_team',y='total_runs',data=inning2)"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f082bebe090>"
            ]
          },
          "metadata": {},
          "execution_count": 24
        },
        {
          "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": "uhadUgmt6AK0"
      },
      "source": [
        "##### this figure also conveys the same story.in this, we see a point near 0 for RCB which may seem to be outlier. But it is on account of the match was disrupted."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "u19iGyj_6AK0"
      },
      "source": [
        ""
      ],
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QQ2NsRPl6AK0"
      },
      "source": [
        "##### how many times teams scores more than 200"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "J_NEbYXP6AK0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417
        },
        "outputId": "bda087fe-18ea-4f98-936f-6b256133fd17"
      },
      "source": [
        "high_scores=df.groupby(['match_id', 'inning','batting_team','bowling_team'])['total_runs'].sum().reset_index() \n",
        "high_scores"
      ],
      "execution_count": 25,
      "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>total_runs</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>SRH</td>\n",
              "      <td>RCB</td>\n",
              "      <td>207</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>RCB</td>\n",
              "      <td>SRH</td>\n",
              "      <td>172</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>MI</td>\n",
              "      <td>RPS</td>\n",
              "      <td>184</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>RPS</td>\n",
              "      <td>MI</td>\n",
              "      <td>187</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>GL</td>\n",
              "      <td>KKR</td>\n",
              "      <td>183</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1279</th>\n",
              "      <td>634</td>\n",
              "      <td>2</td>\n",
              "      <td>KKR</td>\n",
              "      <td>SRH</td>\n",
              "      <td>140</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1280</th>\n",
              "      <td>635</td>\n",
              "      <td>1</td>\n",
              "      <td>GL</td>\n",
              "      <td>SRH</td>\n",
              "      <td>162</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1281</th>\n",
              "      <td>635</td>\n",
              "      <td>2</td>\n",
              "      <td>SRH</td>\n",
              "      <td>GL</td>\n",
              "      <td>163</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1282</th>\n",
              "      <td>636</td>\n",
              "      <td>1</td>\n",
              "      <td>SRH</td>\n",
              "      <td>RCB</td>\n",
              "      <td>208</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1283</th>\n",
              "      <td>636</td>\n",
              "      <td>2</td>\n",
              "      <td>RCB</td>\n",
              "      <td>SRH</td>\n",
              "      <td>200</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1284 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      match_id  inning batting_team bowling_team  total_runs\n",
              "0            1       1          SRH          RCB         207\n",
              "1            1       2          RCB          SRH         172\n",
              "2            2       1           MI          RPS         184\n",
              "3            2       2          RPS           MI         187\n",
              "4            3       1           GL          KKR         183\n",
              "...        ...     ...          ...          ...         ...\n",
              "1279       634       2          KKR          SRH         140\n",
              "1280       635       1           GL          SRH         162\n",
              "1281       635       2          SRH           GL         163\n",
              "1282       636       1          SRH          RCB         208\n",
              "1283       636       2          RCB          SRH         200\n",
              "\n",
              "[1284 rows x 5 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3j4Q0x6d6AK1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417
        },
        "outputId": "eb66e4f9-73a8-4659-d2d1-0ea8c129264f"
      },
      "source": [
        "score_200=high_scores[high_scores['total_runs']>=200]\n",
        "score_200"
      ],
      "execution_count": 26,
      "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>total_runs</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>SRH</td>\n",
              "      <td>RCB</td>\n",
              "      <td>207</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>9</td>\n",
              "      <td>1</td>\n",
              "      <td>DD</td>\n",
              "      <td>RPS</td>\n",
              "      <td>205</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>20</td>\n",
              "      <td>1</td>\n",
              "      <td>RCB</td>\n",
              "      <td>GL</td>\n",
              "      <td>213</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>62</th>\n",
              "      <td>32</td>\n",
              "      <td>1</td>\n",
              "      <td>SRH</td>\n",
              "      <td>KXIP</td>\n",
              "      <td>207</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>36</td>\n",
              "      <td>1</td>\n",
              "      <td>SRH</td>\n",
              "      <td>KKR</td>\n",
              "      <td>209</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1250</th>\n",
              "      <td>620</td>\n",
              "      <td>1</td>\n",
              "      <td>RCB</td>\n",
              "      <td>GL</td>\n",
              "      <td>248</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1256</th>\n",
              "      <td>623</td>\n",
              "      <td>1</td>\n",
              "      <td>MI</td>\n",
              "      <td>DD</td>\n",
              "      <td>206</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1262</th>\n",
              "      <td>626</td>\n",
              "      <td>1</td>\n",
              "      <td>RCB</td>\n",
              "      <td>KXIP</td>\n",
              "      <td>211</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1282</th>\n",
              "      <td>636</td>\n",
              "      <td>1</td>\n",
              "      <td>SRH</td>\n",
              "      <td>RCB</td>\n",
              "      <td>208</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1283</th>\n",
              "      <td>636</td>\n",
              "      <td>2</td>\n",
              "      <td>RCB</td>\n",
              "      <td>SRH</td>\n",
              "      <td>200</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>67 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      match_id  inning batting_team bowling_team  total_runs\n",
              "0            1       1          SRH          RCB         207\n",
              "16           9       1           DD          RPS         205\n",
              "38          20       1          RCB           GL         213\n",
              "62          32       1          SRH         KXIP         207\n",
              "72          36       1          SRH          KKR         209\n",
              "...        ...     ...          ...          ...         ...\n",
              "1250       620       1          RCB           GL         248\n",
              "1256       623       1           MI           DD         206\n",
              "1262       626       1          RCB         KXIP         211\n",
              "1282       636       1          SRH          RCB         208\n",
              "1283       636       2          RCB          SRH         200\n",
              "\n",
              "[67 rows x 5 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YyYH31W26AK1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 459
        },
        "outputId": "5273685d-da80-40d1-c73c-af4f2271d369"
      },
      "source": [
        "plt.figure(figsize=(10,6))\n",
        "sns.countplot(score_200['batting_team'])\n"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: 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",
            "  FutureWarning\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f082bfa4890>"
            ]
          },
          "metadata": {},
          "execution_count": 27
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "35ljmO-v6AK1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 350
        },
        "outputId": "727d673a-870e-4287-b1a3-50a70cee568a"
      },
      "source": [
        "sns.countplot(score_200['bowling_team'])"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: 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",
            "  FutureWarning\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f082bcf61d0>"
            ]
          },
          "metadata": {},
          "execution_count": 28
        },
        {
          "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": "4OnJmjFs6AK1"
      },
      "source": [
        "##### 1st graph shows the number of times a team has scored above 200 runs. 2nd graph shows the number of times a bowling team has conceeded above 200 runs."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TqtimK0k6AK2"
      },
      "source": [
        ""
      ],
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "C4tNYjQk6AK2"
      },
      "source": [
        "##### how many times team scores >200 runs against batting team"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EdQvfGbs6AK2"
      },
      "source": [
        "high_200=df.groupby(['match_id', 'inning','batting_team','bowling_team'])['total_runs'].sum().reset_index()\n",
        "high_200.set_index(['match_id'],inplace=True)\n"
      ],
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "11VTEPsf6AK2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b259fe03-fffd-4205-9ba5-f032e3af96ba"
      },
      "source": [
        "high_200['total_runs'].max()"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "263"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "s_3P5bOJ6AK2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a6d475a6-22d1-4d36-bf31-8b53297ad907"
      },
      "source": [
        "high_200.columns"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['inning', 'batting_team', 'bowling_team', 'total_runs'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OkK6tNQo6AK2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 234
        },
        "outputId": "e142d8b3-900f-4ad1-9f12-2c3511d0eabe"
      },
      "source": [
        "high_200.head()"
      ],
      "execution_count": 32,
      "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>inning</th>\n",
              "      <th>batting_team</th>\n",
              "      <th>bowling_team</th>\n",
              "      <th>total_runs</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>match_id</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>SRH</td>\n",
              "      <td>RCB</td>\n",
              "      <td>207</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>RCB</td>\n",
              "      <td>SRH</td>\n",
              "      <td>172</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>MI</td>\n",
              "      <td>RPS</td>\n",
              "      <td>184</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>RPS</td>\n",
              "      <td>MI</td>\n",
              "      <td>187</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>GL</td>\n",
              "      <td>KKR</td>\n",
              "      <td>183</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          inning batting_team bowling_team  total_runs\n",
              "match_id                                              \n",
              "1              1          SRH          RCB         207\n",
              "1              2          RCB          SRH         172\n",
              "2              1           MI          RPS         184\n",
              "2              2          RPS           MI         187\n",
              "3              1           GL          KKR         183"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7VDrqEFz6AK3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "7d59cfce-c656-4c67-9204-3095c5197236"
      },
      "source": [
        "high=high_200.rename(columns={'total_runs':'count'})\n",
        "high=high[high['count']>=200].groupby(['inning','batting_team','bowling_team']).count()\n",
        "high"
      ],
      "execution_count": 33,
      "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></th>\n",
              "      <th></th>\n",
              "      <th>count</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>inning</th>\n",
              "      <th>batting_team</th>\n",
              "      <th>bowling_team</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"38\" valign=\"top\">1</th>\n",
              "      <th rowspan=\"7\" valign=\"top\">CSK</th>\n",
              "      <th>DD</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>KKR</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>KXIP</th>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MI</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RCB</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RR</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SRH</th>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DC</th>\n",
              "      <th>RR</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">DD</th>\n",
              "      <th>KXIP</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MI</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RPS</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>GL</th>\n",
              "      <th>DD</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">KKR</th>\n",
              "      <th>DC</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>KXIP</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RCB</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">KXIP</th>\n",
              "      <th>CSK</th>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MI</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RCB</th>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RR</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">MI</th>\n",
              "      <th>CSK</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DD</th>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RCB</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RR</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"8\" valign=\"top\">RCB</th>\n",
              "      <th>CSK</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DD</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>GL</th>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>KXIP</th>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MI</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>PW</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RR</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SRH</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">RR</th>\n",
              "      <th>CSK</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DD</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>KXIP</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">SRH</th>\n",
              "      <th>KKR</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>KXIP</th>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RCB</th>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RR</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"16\" valign=\"top\">2</th>\n",
              "      <th rowspan=\"3\" valign=\"top\">CSK</th>\n",
              "      <th>KXIP</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RCB</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RR</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DD</th>\n",
              "      <th>GL</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>KKR</th>\n",
              "      <th>KXIP</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">KXIP</th>\n",
              "      <th>CSK</th>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DD</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>KKR</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SRH</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">MI</th>\n",
              "      <th>CSK</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>KXIP</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">RCB</th>\n",
              "      <th>KXIP</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SRH</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">RR</th>\n",
              "      <th>CSK</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DC</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MI</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                  count\n",
              "inning batting_team bowling_team       \n",
              "1      CSK          DD                1\n",
              "                    KKR               1\n",
              "                    KXIP              2\n",
              "                    MI                1\n",
              "                    RCB               1\n",
              "                    RR                1\n",
              "                    SRH               2\n",
              "       DC           RR                1\n",
              "       DD           KXIP              1\n",
              "                    MI                1\n",
              "                    RPS               1\n",
              "       GL           DD                1\n",
              "       KKR          DC                1\n",
              "                    KXIP              1\n",
              "                    RCB               1\n",
              "       KXIP         CSK               2\n",
              "                    MI                1\n",
              "                    RCB               2\n",
              "                    RR                1\n",
              "       MI           CSK               1\n",
              "                    DD                4\n",
              "                    RCB               1\n",
              "                    RR                1\n",
              "       RCB          CSK               1\n",
              "                    DD                1\n",
              "                    GL                2\n",
              "                    KXIP              3\n",
              "                    MI                1\n",
              "                    PW                1\n",
              "                    RR                1\n",
              "                    SRH               1\n",
              "       RR           CSK               1\n",
              "                    DD                1\n",
              "                    KXIP              1\n",
              "       SRH          KKR               1\n",
              "                    KXIP              2\n",
              "                    RCB               2\n",
              "                    RR                1\n",
              "2      CSK          KXIP              1\n",
              "                    RCB               1\n",
              "                    RR                1\n",
              "       DD           GL                1\n",
              "       KKR          KXIP              1\n",
              "       KXIP         CSK               2\n",
              "                    DD                1\n",
              "                    KKR               1\n",
              "                    SRH               1\n",
              "       MI           CSK               1\n",
              "                    KXIP              1\n",
              "       RCB          KXIP              1\n",
              "                    SRH               1\n",
              "       RR           CSK               1\n",
              "                    DC                1\n",
              "                    MI                1"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bDl9E4zy6AK3"
      },
      "source": [
        "##### Batsman Comparison"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TR3scLVi6AK3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417
        },
        "outputId": "fadbcf37-348c-4941-b598-0ded324880d7"
      },
      "source": [
        "balls=df.groupby(['batsman'])['ball'].count().reset_index()\n",
        "balls"
      ],
      "execution_count": 34,
      "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>batsman</th>\n",
              "      <th>ball</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>A Ashish Reddy</td>\n",
              "      <td>196</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>A Chandila</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>A Chopra</td>\n",
              "      <td>75</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>A Choudhary</td>\n",
              "      <td>20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>A Flintoff</td>\n",
              "      <td>57</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>456</th>\n",
              "      <td>YV Takawale</td>\n",
              "      <td>183</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>457</th>\n",
              "      <td>Yashpal Singh</td>\n",
              "      <td>67</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>458</th>\n",
              "      <td>Younis Khan</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>459</th>\n",
              "      <td>Yuvraj Singh</td>\n",
              "      <td>2050</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>460</th>\n",
              "      <td>Z Khan</td>\n",
              "      <td>141</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>461 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            batsman  ball\n",
              "0    A Ashish Reddy   196\n",
              "1        A Chandila     7\n",
              "2          A Chopra    75\n",
              "3       A Choudhary    20\n",
              "4        A Flintoff    57\n",
              "..              ...   ...\n",
              "456     YV Takawale   183\n",
              "457   Yashpal Singh    67\n",
              "458     Younis Khan     7\n",
              "459    Yuvraj Singh  2050\n",
              "460          Z Khan   141\n",
              "\n",
              "[461 rows x 2 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HdBrjxj26AK4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417
        },
        "outputId": "36e3b689-01a4-44ab-9b6a-97d0e4923447"
      },
      "source": [
        "runs=df.groupby(['batsman'])['batsman_runs'].sum().reset_index()\n",
        "runs.columns=['batsman','runs']\n",
        "runs\n",
        "\n",
        "###runs=df.groupby(['batsman'])['batsman_runs'].agg(sum).reset_index()"
      ],
      "execution_count": 35,
      "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>batsman</th>\n",
              "      <th>runs</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>A Ashish Reddy</td>\n",
              "      <td>280</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>A Chandila</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>A Chopra</td>\n",
              "      <td>53</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>A Choudhary</td>\n",
              "      <td>25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>A Flintoff</td>\n",
              "      <td>62</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>456</th>\n",
              "      <td>YV Takawale</td>\n",
              "      <td>192</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>457</th>\n",
              "      <td>Yashpal Singh</td>\n",
              "      <td>47</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>458</th>\n",
              "      <td>Younis Khan</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>459</th>\n",
              "      <td>Yuvraj Singh</td>\n",
              "      <td>2591</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>460</th>\n",
              "      <td>Z Khan</td>\n",
              "      <td>117</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>461 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            batsman  runs\n",
              "0    A Ashish Reddy   280\n",
              "1        A Chandila     4\n",
              "2          A Chopra    53\n",
              "3       A Choudhary    25\n",
              "4        A Flintoff    62\n",
              "..              ...   ...\n",
              "456     YV Takawale   192\n",
              "457   Yashpal Singh    47\n",
              "458     Younis Khan     3\n",
              "459    Yuvraj Singh  2591\n",
              "460          Z Khan   117\n",
              "\n",
              "[461 rows x 2 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LOoSHLkd6AK4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "615ab251-f4d4-4395-b982-ffc47d720439"
      },
      "source": [
        "df.groupby(['batsman'])['batsman_runs'].agg(sum)"
      ],
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "batsman\n",
              "A Ashish Reddy     280\n",
              "A Chandila           4\n",
              "A Chopra            53\n",
              "A Choudhary         25\n",
              "A Flintoff          62\n",
              "                  ... \n",
              "YV Takawale        192\n",
              "Yashpal Singh       47\n",
              "Younis Khan          3\n",
              "Yuvraj Singh      2591\n",
              "Z Khan             117\n",
              "Name: batsman_runs, Length: 461, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Y1ayeNCr6AK5"
      },
      "source": [
        "balls=balls.merge(runs,left_on='batsman',right_on='batsman',how='outer')"
      ],
      "execution_count": 37,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JEW_RViY6AK5"
      },
      "source": [
        "four=df[df['batsman_runs']==4]"
      ],
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mzWCxKL06AK5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417
        },
        "outputId": "05803ac5-af7b-4541-acf0-837a16e78382"
      },
      "source": [
        "''' df.groupby('batsman')['batsman_runs'].agg(lambda x: (x==4).sum()).reset_index()'''\n",
        "\n",
        "runs_4=four.groupby('batsman')['batsman_runs'].count().reset_index()\n",
        "runs_4.columns=['batsman','4s']\n",
        "runs_4\n"
      ],
      "execution_count": 39,
      "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>batsman</th>\n",
              "      <th>4s</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>A Ashish Reddy</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>A Chopra</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>A Choudhary</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>A Flintoff</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>A Kumble</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>363</th>\n",
              "      <td>YK Pathan</td>\n",
              "      <td>240</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>364</th>\n",
              "      <td>YV Takawale</td>\n",
              "      <td>26</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>365</th>\n",
              "      <td>Yashpal Singh</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>366</th>\n",
              "      <td>Yuvraj Singh</td>\n",
              "      <td>205</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>367</th>\n",
              "      <td>Z Khan</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>368 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            batsman   4s\n",
              "0    A Ashish Reddy   16\n",
              "1          A Chopra    7\n",
              "2       A Choudhary    1\n",
              "3        A Flintoff    5\n",
              "4          A Kumble    3\n",
              "..              ...  ...\n",
              "363       YK Pathan  240\n",
              "364     YV Takawale   26\n",
              "365   Yashpal Singh    5\n",
              "366    Yuvraj Singh  205\n",
              "367          Z Khan   11\n",
              "\n",
              "[368 rows x 2 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FJbONqmV6AK5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417
        },
        "outputId": "2fd76955-b87d-4c23-ef70-92f632a1f65c"
      },
      "source": [
        "six=df.groupby('batsman')['batsman_runs'].agg(lambda x: (x==6).sum()).reset_index()\n",
        "six.columns=['batsman','6s']\n",
        "six"
      ],
      "execution_count": 40,
      "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>batsman</th>\n",
              "      <th>6s</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>A Ashish Reddy</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>A Chandila</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>A Chopra</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>A Choudhary</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>A Flintoff</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>456</th>\n",
              "      <td>YV Takawale</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>457</th>\n",
              "      <td>Yashpal Singh</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>458</th>\n",
              "      <td>Younis Khan</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>459</th>\n",
              "      <td>Yuvraj Singh</td>\n",
              "      <td>141</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>460</th>\n",
              "      <td>Z Khan</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>461 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            batsman   6s\n",
              "0    A Ashish Reddy   15\n",
              "1        A Chandila    0\n",
              "2          A Chopra    0\n",
              "3       A Choudhary    1\n",
              "4        A Flintoff    2\n",
              "..              ...  ...\n",
              "456     YV Takawale    3\n",
              "457   Yashpal Singh    0\n",
              "458     Younis Khan    0\n",
              "459    Yuvraj Singh  141\n",
              "460          Z Khan    2\n",
              "\n",
              "[461 rows x 2 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Bt-T2uQh6AK5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417
        },
        "outputId": "f140e89c-d074-4d76-ed42-55c847b46546"
      },
      "source": [
        "player=pd.concat([runs,balls.iloc[:,1],runs_4.iloc[:,1],six.iloc[:,1]],axis=1)\n",
        "player"
      ],
      "execution_count": 41,
      "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>batsman</th>\n",
              "      <th>runs</th>\n",
              "      <th>ball</th>\n",
              "      <th>4s</th>\n",
              "      <th>6s</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>A Ashish Reddy</td>\n",
              "      <td>280</td>\n",
              "      <td>196</td>\n",
              "      <td>16.0</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>A Chandila</td>\n",
              "      <td>4</td>\n",
              "      <td>7</td>\n",
              "      <td>7.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>A Chopra</td>\n",
              "      <td>53</td>\n",
              "      <td>75</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>A Choudhary</td>\n",
              "      <td>25</td>\n",
              "      <td>20</td>\n",
              "      <td>5.0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>A Flintoff</td>\n",
              "      <td>62</td>\n",
              "      <td>57</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>456</th>\n",
              "      <td>YV Takawale</td>\n",
              "      <td>192</td>\n",
              "      <td>183</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>457</th>\n",
              "      <td>Yashpal Singh</td>\n",
              "      <td>47</td>\n",
              "      <td>67</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>458</th>\n",
              "      <td>Younis Khan</td>\n",
              "      <td>3</td>\n",
              "      <td>7</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>459</th>\n",
              "      <td>Yuvraj Singh</td>\n",
              "      <td>2591</td>\n",
              "      <td>2050</td>\n",
              "      <td>NaN</td>\n",
              "      <td>141</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>460</th>\n",
              "      <td>Z Khan</td>\n",
              "      <td>117</td>\n",
              "      <td>141</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>461 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            batsman  runs  ball    4s   6s\n",
              "0    A Ashish Reddy   280   196  16.0   15\n",
              "1        A Chandila     4     7   7.0    0\n",
              "2          A Chopra    53    75   1.0    0\n",
              "3       A Choudhary    25    20   5.0    1\n",
              "4        A Flintoff    62    57   3.0    2\n",
              "..              ...   ...   ...   ...  ...\n",
              "456     YV Takawale   192   183   NaN    3\n",
              "457   Yashpal Singh    47    67   NaN    0\n",
              "458     Younis Khan     3     7   NaN    0\n",
              "459    Yuvraj Singh  2591  2050   NaN  141\n",
              "460          Z Khan   117   141   NaN    2\n",
              "\n",
              "[461 rows x 5 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-DbhhlSx6AK6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 203
        },
        "outputId": "9442e211-2c8f-45ff-f87b-d3226bc42330"
      },
      "source": [
        "player['strike_rate']=player['runs']/player['ball']\n",
        "player.head()"
      ],
      "execution_count": 42,
      "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>batsman</th>\n",
              "      <th>runs</th>\n",
              "      <th>ball</th>\n",
              "      <th>4s</th>\n",
              "      <th>6s</th>\n",
              "      <th>strike_rate</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>A Ashish Reddy</td>\n",
              "      <td>280</td>\n",
              "      <td>196</td>\n",
              "      <td>16.0</td>\n",
              "      <td>15</td>\n",
              "      <td>1.428571</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>A Chandila</td>\n",
              "      <td>4</td>\n",
              "      <td>7</td>\n",
              "      <td>7.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.571429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>A Chopra</td>\n",
              "      <td>53</td>\n",
              "      <td>75</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.706667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>A Choudhary</td>\n",
              "      <td>25</td>\n",
              "      <td>20</td>\n",
              "      <td>5.0</td>\n",
              "      <td>1</td>\n",
              "      <td>1.250000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>A Flintoff</td>\n",
              "      <td>62</td>\n",
              "      <td>57</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2</td>\n",
              "      <td>1.087719</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          batsman  runs  ball    4s  6s  strike_rate\n",
              "0  A Ashish Reddy   280   196  16.0  15     1.428571\n",
              "1      A Chandila     4     7   7.0   0     0.571429\n",
              "2        A Chopra    53    75   1.0   0     0.706667\n",
              "3     A Choudhary    25    20   5.0   1     1.250000\n",
              "4      A Flintoff    62    57   3.0   2     1.087719"
            ]
          },
          "metadata": {},
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "adCYoc5S6AK6",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "fe73f8f2-1b80-428a-a33b-8551f3328531"
      },
      "source": [
        "player.isna().sum()"
      ],
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "batsman         0\n",
              "runs            0\n",
              "ball            0\n",
              "4s             93\n",
              "6s              0\n",
              "strike_rate     0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qL4pz4606AK6"
      },
      "source": [
        "player['4s'].fillna(0,inplace=True)"
      ],
      "execution_count": 44,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "a1hmvo3I6AK7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "bf4f57d0-9c38-4164-f2c3-606ec6494dff"
      },
      "source": [
        "player.isnull().values.any()"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "H2Sha9BI6AK7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "057f6e63-1f18-4396-f1fd-514f767a4439"
      },
      "source": [
        "df.columns"
      ],
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['match_id', 'inning', 'batting_team', 'bowling_team', 'over', 'ball',\n",
              "       'batsman', 'non_striker', 'bowler', 'is_super_over', 'wide_runs',\n",
              "       'bye_runs', 'legbye_runs', 'noball_runs', 'penalty_runs',\n",
              "       'batsman_runs', 'extra_runs', 'total_runs', 'player_dismissed',\n",
              "       'dismissal_kind', 'fielder'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "514dgUde6AK7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417
        },
        "outputId": "418c8d52-8b25-4106-afac-bd5e1bbf09e2"
      },
      "source": [
        "grp=df.groupby(['match_id','batsman','batting_team'])['batsman_runs'].sum().reset_index()\n",
        "grp"
      ],
      "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>match_id</th>\n",
              "      <th>batsman</th>\n",
              "      <th>batting_team</th>\n",
              "      <th>batsman_runs</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>A Choudhary</td>\n",
              "      <td>RCB</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>BCJ Cutting</td>\n",
              "      <td>SRH</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>CH Gayle</td>\n",
              "      <td>RCB</td>\n",
              "      <td>32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>DA Warner</td>\n",
              "      <td>SRH</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>DJ Hooda</td>\n",
              "      <td>SRH</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9510</th>\n",
              "      <td>636</td>\n",
              "      <td>SR Watson</td>\n",
              "      <td>RCB</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9511</th>\n",
              "      <td>636</td>\n",
              "      <td>STR Binny</td>\n",
              "      <td>RCB</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9512</th>\n",
              "      <td>636</td>\n",
              "      <td>Sachin Baby</td>\n",
              "      <td>RCB</td>\n",
              "      <td>18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9513</th>\n",
              "      <td>636</td>\n",
              "      <td>V Kohli</td>\n",
              "      <td>RCB</td>\n",
              "      <td>54</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9514</th>\n",
              "      <td>636</td>\n",
              "      <td>Yuvraj Singh</td>\n",
              "      <td>SRH</td>\n",
              "      <td>38</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>9515 rows × 4 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      match_id       batsman batting_team  batsman_runs\n",
              "0            1   A Choudhary          RCB             6\n",
              "1            1   BCJ Cutting          SRH            16\n",
              "2            1      CH Gayle          RCB            32\n",
              "3            1     DA Warner          SRH            14\n",
              "4            1      DJ Hooda          SRH            16\n",
              "...        ...           ...          ...           ...\n",
              "9510       636     SR Watson          RCB            11\n",
              "9511       636     STR Binny          RCB             9\n",
              "9512       636   Sachin Baby          RCB            18\n",
              "9513       636       V Kohli          RCB            54\n",
              "9514       636  Yuvraj Singh          SRH            38\n",
              "\n",
              "[9515 rows x 4 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YV-gr6Kh6AK7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417
        },
        "outputId": "9e7160ea-bce6-48f0-df5a-e6de51036838"
      },
      "source": [
        "max=grp.groupby(['batsman'])['batsman_runs'].max().reset_index()\n",
        "max.columns=['batsman','max_runs']\n",
        "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>batsman</th>\n",
              "      <th>max_runs</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>A Ashish Reddy</td>\n",
              "      <td>36</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>A Chandila</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>A Chopra</td>\n",
              "      <td>24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>A Choudhary</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>A Flintoff</td>\n",
              "      <td>24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>456</th>\n",
              "      <td>YV Takawale</td>\n",
              "      <td>45</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>457</th>\n",
              "      <td>Yashpal Singh</td>\n",
              "      <td>20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>458</th>\n",
              "      <td>Younis Khan</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>459</th>\n",
              "      <td>Yuvraj Singh</td>\n",
              "      <td>83</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>460</th>\n",
              "      <td>Z Khan</td>\n",
              "      <td>23</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>461 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            batsman  max_runs\n",
              "0    A Ashish Reddy        36\n",
              "1        A Chandila         4\n",
              "2          A Chopra        24\n",
              "3       A Choudhary        15\n",
              "4        A Flintoff        24\n",
              "..              ...       ...\n",
              "456     YV Takawale        45\n",
              "457   Yashpal Singh        20\n",
              "458     Younis Khan         3\n",
              "459    Yuvraj Singh        83\n",
              "460          Z Khan        23\n",
              "\n",
              "[461 rows x 2 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Gv2SixfL6AK8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417
        },
        "outputId": "098c0cf0-250c-47ce-b6be-d94ea87f0bde"
      },
      "source": [
        "player2=pd.concat([player,max.iloc[:,1:3]],axis=1)\n",
        "player2"
      ],
      "execution_count": 49,
      "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>batsman</th>\n",
              "      <th>runs</th>\n",
              "      <th>ball</th>\n",
              "      <th>4s</th>\n",
              "      <th>6s</th>\n",
              "      <th>strike_rate</th>\n",
              "      <th>max_runs</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>A Ashish Reddy</td>\n",
              "      <td>280</td>\n",
              "      <td>196</td>\n",
              "      <td>16.0</td>\n",
              "      <td>15</td>\n",
              "      <td>1.428571</td>\n",
              "      <td>36</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>A Chandila</td>\n",
              "      <td>4</td>\n",
              "      <td>7</td>\n",
              "      <td>7.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.571429</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>A Chopra</td>\n",
              "      <td>53</td>\n",
              "      <td>75</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.706667</td>\n",
              "      <td>24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>A Choudhary</td>\n",
              "      <td>25</td>\n",
              "      <td>20</td>\n",
              "      <td>5.0</td>\n",
              "      <td>1</td>\n",
              "      <td>1.250000</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>A Flintoff</td>\n",
              "      <td>62</td>\n",
              "      <td>57</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2</td>\n",
              "      <td>1.087719</td>\n",
              "      <td>24</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>456</th>\n",
              "      <td>YV Takawale</td>\n",
              "      <td>192</td>\n",
              "      <td>183</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3</td>\n",
              "      <td>1.049180</td>\n",
              "      <td>45</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>457</th>\n",
              "      <td>Yashpal Singh</td>\n",
              "      <td>47</td>\n",
              "      <td>67</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.701493</td>\n",
              "      <td>20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>458</th>\n",
              "      <td>Younis Khan</td>\n",
              "      <td>3</td>\n",
              "      <td>7</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.428571</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>459</th>\n",
              "      <td>Yuvraj Singh</td>\n",
              "      <td>2591</td>\n",
              "      <td>2050</td>\n",
              "      <td>0.0</td>\n",
              "      <td>141</td>\n",
              "      <td>1.263902</td>\n",
              "      <td>83</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>460</th>\n",
              "      <td>Z Khan</td>\n",
              "      <td>117</td>\n",
              "      <td>141</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2</td>\n",
              "      <td>0.829787</td>\n",
              "      <td>23</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>461 rows × 7 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            batsman  runs  ball    4s   6s  strike_rate  max_runs\n",
              "0    A Ashish Reddy   280   196  16.0   15     1.428571        36\n",
              "1        A Chandila     4     7   7.0    0     0.571429         4\n",
              "2          A Chopra    53    75   1.0    0     0.706667        24\n",
              "3       A Choudhary    25    20   5.0    1     1.250000        15\n",
              "4        A Flintoff    62    57   3.0    2     1.087719        24\n",
              "..              ...   ...   ...   ...  ...          ...       ...\n",
              "456     YV Takawale   192   183   0.0    3     1.049180        45\n",
              "457   Yashpal Singh    47    67   0.0    0     0.701493        20\n",
              "458     Younis Khan     3     7   0.0    0     0.428571         3\n",
              "459    Yuvraj Singh  2591  2050   0.0  141     1.263902        83\n",
              "460          Z Khan   117   141   0.0    2     0.829787        23\n",
              "\n",
              "[461 rows x 7 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0hP96dL-6AK8",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a562120e-ad90-4ee9-ac25-29967aaf1dd4"
      },
      "source": [
        "player2.shape"
      ],
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(461, 7)"
            ]
          },
          "metadata": {},
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ws07CvQg6AK9"
      },
      "source": [
        "#### Top 10 Batsman"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bV7gR8mN6AK9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 352
        },
        "outputId": "e16e05f7-9f69-489b-aafd-84f30714364d"
      },
      "source": [
        "max_runs=df.groupby(['batsman'])['batsman_runs'].sum()\n",
        "max_runs.sort_values(ascending=False)[:10].plot.bar()"
      ],
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f082bbf7110>"
            ]
          },
          "metadata": {},
          "execution_count": 51
        },
        {
          "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": "BMo4REti6AK9"
      },
      "source": [
        "#### SK Raina has highest total runs across all seasons Whereas Virat Kohliis just few runs behind with the second spot "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zC0FwmFg6AK9"
      },
      "source": [
        ""
      ],
      "execution_count": 51,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xlU63Okc6AK9"
      },
      "source": [
        "#### Top Individual Scores"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MmgzubMP6AK9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 357
        },
        "outputId": "911fc623-2ab0-4375-8cc3-b441b9b8c527"
      },
      "source": [
        "df.groupby([\"match_id\",\"batsman\",'batting_team'])[\"batsman_runs\"].sum().reset_index().sort_values(by='batsman_runs', ascending=False).head(10)"
      ],
      "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>match_id</th>\n",
              "      <th>batsman</th>\n",
              "      <th>batting_team</th>\n",
              "      <th>batsman_runs</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>6200</th>\n",
              "      <td>411</td>\n",
              "      <td>CH Gayle</td>\n",
              "      <td>RCB</td>\n",
              "      <td>175</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>900</th>\n",
              "      <td>60</td>\n",
              "      <td>BB McCullum</td>\n",
              "      <td>KKR</td>\n",
              "      <td>158</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8426</th>\n",
              "      <td>562</td>\n",
              "      <td>AB de Villiers</td>\n",
              "      <td>RCB</td>\n",
              "      <td>133</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9257</th>\n",
              "      <td>620</td>\n",
              "      <td>AB de Villiers</td>\n",
              "      <td>RCB</td>\n",
              "      <td>129</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5585</th>\n",
              "      <td>372</td>\n",
              "      <td>CH Gayle</td>\n",
              "      <td>RCB</td>\n",
              "      <td>128</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3135</th>\n",
              "      <td>206</td>\n",
              "      <td>M Vijay</td>\n",
              "      <td>CSK</td>\n",
              "      <td>127</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>529</th>\n",
              "      <td>36</td>\n",
              "      <td>DA Warner</td>\n",
              "      <td>SRH</td>\n",
              "      <td>126</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7752</th>\n",
              "      <td>516</td>\n",
              "      <td>V Sehwag</td>\n",
              "      <td>KXIP</td>\n",
              "      <td>122</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3686</th>\n",
              "      <td>243</td>\n",
              "      <td>PC Valthaty</td>\n",
              "      <td>KXIP</td>\n",
              "      <td>120</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4223</th>\n",
              "      <td>279</td>\n",
              "      <td>V Sehwag</td>\n",
              "      <td>DD</td>\n",
              "      <td>119</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      match_id         batsman batting_team  batsman_runs\n",
              "6200       411        CH Gayle          RCB           175\n",
              "900         60     BB McCullum          KKR           158\n",
              "8426       562  AB de Villiers          RCB           133\n",
              "9257       620  AB de Villiers          RCB           129\n",
              "5585       372        CH Gayle          RCB           128\n",
              "3135       206         M Vijay          CSK           127\n",
              "529         36       DA Warner          SRH           126\n",
              "7752       516        V Sehwag         KXIP           122\n",
              "3686       243     PC Valthaty         KXIP           120\n",
              "4223       279        V Sehwag           DD           119"
            ]
          },
          "metadata": {},
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hHcK_cZa6AK-"
      },
      "source": [
        "#### Not only Gayle but there are many RCB players on the top scores list. Looks like RCB is a very formidable batting side."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "T-qE_0M26AK-"
      },
      "source": [
        ""
      ],
      "execution_count": 52,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tqqdDqmL6AK-"
      },
      "source": [
        "##### Highest Wicket Taker"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Jf-hl2Em6AK-",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "27b24a79-fa95-4ed1-bf8a-0f0d50f905ad"
      },
      "source": [
        "df['dismissal_kind'].unique()"
      ],
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([nan, 'caught', 'bowled', 'run out', 'lbw', 'caught and bowled',\n",
              "       'stumped', 'retired hurt', 'hit wicket', 'obstructing the field'],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 53
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oKcS2g8j6AK-"
      },
      "source": [
        "dismissal_kinds = ['caught', 'bowled', 'lbw', 'caught and bowled',\n",
        "       'stumped', 'hit wicket']"
      ],
      "execution_count": 54,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-fOrUEU86AK_",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 307
        },
        "outputId": "624978a6-9351-4dd5-c1ad-e7ec152b245f"
      },
      "source": [
        "hwt=df[df[\"dismissal_kind\"].isin(dismissal_kinds)]\n",
        "hwt.head()"
      ],
      "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>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>11</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>SRH</td>\n",
              "      <td>RCB</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>DA Warner</td>\n",
              "      <td>S Dhawan</td>\n",
              "      <td>A Choudhary</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>DA Warner</td>\n",
              "      <td>caught</td>\n",
              "      <td>Mandeep Singh</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>64</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>SRH</td>\n",
              "      <td>RCB</td>\n",
              "      <td>11</td>\n",
              "      <td>3</td>\n",
              "      <td>S Dhawan</td>\n",
              "      <td>MC Henriques</td>\n",
              "      <td>STR Binny</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>S Dhawan</td>\n",
              "      <td>caught</td>\n",
              "      <td>Sachin Baby</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>94</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>SRH</td>\n",
              "      <td>RCB</td>\n",
              "      <td>16</td>\n",
              "      <td>2</td>\n",
              "      <td>MC Henriques</td>\n",
              "      <td>Yuvraj Singh</td>\n",
              "      <td>YS Chahal</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>MC Henriques</td>\n",
              "      <td>caught</td>\n",
              "      <td>Sachin Baby</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>116</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>SRH</td>\n",
              "      <td>RCB</td>\n",
              "      <td>19</td>\n",
              "      <td>4</td>\n",
              "      <td>Yuvraj Singh</td>\n",
              "      <td>DJ Hooda</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>Yuvraj Singh</td>\n",
              "      <td>bowled</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>160</th>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>RCB</td>\n",
              "      <td>SRH</td>\n",
              "      <td>6</td>\n",
              "      <td>4</td>\n",
              "      <td>Mandeep Singh</td>\n",
              "      <td>CH Gayle</td>\n",
              "      <td>Rashid Khan</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>Mandeep Singh</td>\n",
              "      <td>bowled</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     match_id  inning  ... dismissal_kind        fielder\n",
              "11          1       1  ...         caught  Mandeep Singh\n",
              "64          1       1  ...         caught    Sachin Baby\n",
              "94          1       1  ...         caught    Sachin Baby\n",
              "116         1       1  ...         bowled            NaN\n",
              "160         1       2  ...         bowled            NaN\n",
              "\n",
              "[5 rows x 21 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dd5xLW5r6AK_",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 357
        },
        "outputId": "bf2cc44c-7ce6-4c41-ddee-6ae521bdcc94"
      },
      "source": [
        "hwt['bowler'].value_counts()[:10].plot.bar()"
      ],
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f082bb6e190>"
            ]
          },
          "metadata": {},
          "execution_count": 56
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAAFDCAYAAADBK05FAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nO3de5xdZX3v8c+XREBAbmZAJEBQQYtcRAPFgopSLQgKL6sIBytSPKlKkQrnoNgeqdaeop5a77YpoKFGhCIVrFhFioAol4T7tcYIEgpkkIsUChL4nj+eNWQzmZkks2evtfea7/v1mtfsvdbe+/llZa/fPOtZz0W2iYiIdlmn6QAiImLqJblHRLRQkntERAsluUdEtFCSe0RECyW5R0S00GqTu6TTJS2XdNOo7cdKuk3SzZI+3bH9JElLJN0u6Q96EXRERExs5hq85uvAl4AzRjZIej1wMLCb7SckbVFt3wk4DHg58ELgR5J2tP3URAXMmjXLc+bMmdQ/ICJiulq8ePH9tofG2rfa5G77UklzRm1+P3CK7Seq1yyvth8MfKva/ktJS4A9gZ9NVMacOXNYtGjR6kKJiIgOku4cb99k29x3BF4j6UpJl0jao9q+NXBXx+uWVdvGCmqepEWSFg0PD08yjIiIGMtkk/tMYHNgL+B/A2dL0tp8gO35tufanjs0NOZVRURETNJkk/sy4FwXVwFPA7OAu4FtOl43u9oWERE1mmxy/w7wegBJOwLrAvcD5wOHSVpP0vbADsBVUxFoRESsudXeUJV0JrAvMEvSMuBk4HTg9Kp75G+BI12ml7xZ0tnALcAK4JjV9ZSJiIipp36Y8nfu3LlOb5mIiLUjabHtuWPtywjViIgWSnKPiGihNRmh2hfmfOR7Xb3/jlMOnKJIIiL6X2ruEREtlOQeEdFCSe4RES2U5B4R0UJJ7hERLZTkHhHRQknuEREtlOQeEdFCSe4RES2U5B4R0UJJ7hERLZTkHhHRQknuEREtlOQeEdFCSe4RES202uQu6XRJy6v1UkfvO0GSJc2qnkvSFyQtkXSDpFf2IuiIiJjYmtTcvw7sP3qjpG2ANwG/6th8ALBD9TMP+Gr3IUZExNpabXK3fSnwwBi7/g44EehcYftg4AwXVwCbStpqSiKNiIg1Nqk2d0kHA3fbvn7Urq2BuzqeL6u2jfUZ8yQtkrRoeHh4MmFERMQ41jq5S9oA+CjwsW4Ktj3f9lzbc4eGhrr5qIiIGGUyC2S/GNgeuF4SwGzgGkl7AncD23S8dna1LSIiarTWNXfbN9rewvYc23MoTS+vtH0vcD7w7qrXzF7Aw7bvmdqQIyJiddakK+SZwM+Al0paJunoCV5+AbAUWAL8I/CBKYkyIiLWymqbZWwfvpr9czoeGzim+7AiIqIbGaEaEdFCSe4RES00md4y09acj3yv68+445QDpyCSiIiJpeYeEdFCSe4RES2U5B4R0UJJ7hERLZTkHhHRQknuEREtlOQeEdFCSe4RES2U5B4R0UIZoTqAuh0pm1GyEe2X5B6TkqkYIvpbmmUiIlooyT0iooWS3CMiWijJPSKihVZ7Q1XS6cBBwHLbO1fbPgO8Bfgt8AvgKNsPVftOAo4GngI+aPsHPYo9prnc1I0Y35rU3L8O7D9q24XAzrZ3Bf4DOAlA0k7AYcDLq/d8RdKMKYs2IiLWyGqTu+1LgQdGbfuh7RXV0yuA2dXjg4Fv2X7C9i+BJcCeUxhvRESsgaloc/9j4PvV462Buzr2Lau2rULSPEmLJC0aHh6egjAiImJEV8ld0p8DK4CFa/te2/Ntz7U9d2hoqJswIiJilEmPUJX0HsqN1v1su9p8N7BNx8tmV9siIqJGk6q5S9ofOBF4q+3HOnadDxwmaT1J2wM7AFd1H2ZERKyNNekKeSawLzBL0jLgZErvmPWACyUBXGH7fbZvlnQ2cAulueYY20/1KviIiBjbapO77cPH2HzaBK//a+CvuwkqIiK6kxGqEREtlOQeEdFCSe4RES2U5B4R0UJJ7hERLZTkHhHRQllDNaJLmXo4+lFq7hERLZTkHhHRQknuEREtlOQeEdFCSe4RES2U5B4R0ULpChnRAumOGaOl5h4R0UJJ7hERLZTkHhHRQmlzj4gpk7b//rEma6ieDhwELLe9c7Vtc+AsYA5wB3Co7QdVFlT9PPBm4DHgPbav6U3oERGryh+YYk2aZb4O7D9q20eAi2zvAFxUPQc4ANih+pkHfHVqwoyIiLWx2uRu+1LggVGbDwYWVI8XAId0bD/DxRXAppK2mqpgIyJizUy2zX1L2/dUj+8Ftqwebw3c1fG6ZdW2exhF0jxK7Z5tt912kmFERPSnppuHuu4tY9uAJ/G++bbn2p47NDTUbRgREdFhssn9vpHmlur38mr73cA2Ha+bXW2LiIgaTTa5nw8cWT0+EjivY/u7VewFPNzRfBMRETVZk66QZwL7ArMkLQNOBk4BzpZ0NHAncGj18gso3SCXULpCHtWDmCMiYjVWm9xtHz7Orv3GeK2BY7oNKiIiupPpByIiWijJPSKihZLcIyJaKMk9IqKFktwjIlooyT0iooWS3CMiWijJPSKihZLcIyJaKMk9IqKFktwjIlooyT0iooWS3CMiWijJPSKihZLcIyJaKMk9IqKFktwjIlooyT0iooW6Su6SPiTpZkk3STpT0vqStpd0paQlks6StO5UBRsREWtm0sld0tbAB4G5tncGZgCHAZ8C/s72S4AHgaOnItCIiFhz3TbLzASeK2kmsAFwD/AG4Jxq/wLgkC7LiIiItTTp5G77buD/Ab+iJPWHgcXAQ7ZXVC9bBmw91vslzZO0SNKi4eHhyYYRERFj6KZZZjPgYGB74IXAhsD+a/p+2/Ntz7U9d2hoaLJhRETEGLpplvl94Je2h20/CZwL7A1sWjXTAMwG7u4yxoiIWEvdJPdfAXtJ2kCSgP2AW4CLgbdXrzkSOK+7ECMiYm110+Z+JeXG6TXAjdVnzQc+DBwvaQnwfOC0KYgzIiLWwszVv2R8tk8GTh61eSmwZzefGxER3ckI1YiIFkpyj4hooST3iIgWSnKPiGihJPeIiBZKco+IaKEk94iIFkpyj4hooST3iIgWSnKPiGihJPeIiBZKco+IaKEk94iIFkpyj4hooST3iIgWSnKPiGihJPeIiBZKco+IaKGukrukTSWdI+k2SbdKerWkzSVdKOnn1e/NpirYiIhYM93W3D8P/JvtlwG7AbcCHwEusr0DcFH1PCIiajTp5C5pE+C1wGkAtn9r+yHgYGBB9bIFwCHdBhkREWunm5r79sAw8DVJ10o6VdKGwJa276lecy+w5VhvljRP0iJJi4aHh7sIIyIiRusmuc8EXgl81fbuwKOMaoKxbcBjvdn2fNtzbc8dGhrqIoyIiBitm+S+DFhm+8rq+TmUZH+fpK0Aqt/LuwsxIiLW1qSTu+17gbskvbTatB9wC3A+cGS17UjgvK4ijIiItTazy/cfCyyUtC6wFDiK8gfjbElHA3cCh3ZZRkRErKWukrvt64C5Y+zar5vPjYiI7mSEakRECyW5R0S0UJJ7REQLJblHRLRQkntERAsluUdEtFCSe0RECyW5R0S0UJJ7REQLJblHRLRQkntERAsluUdEtFCSe0RECyW5R0S0UJJ7REQLJblHRLRQkntERAsluUdEtFDXyV3SDEnXSvrX6vn2kq6UtETSWdX6qhERUaOpqLkfB9za8fxTwN/ZfgnwIHD0FJQRERFroavkLmk2cCBwavVcwBuAc6qXLAAO6aaMiIhYe93W3D8HnAg8XT1/PvCQ7RXV82XA1mO9UdI8SYskLRoeHu4yjIiI6DTp5C7pIGC57cWTeb/t+bbn2p47NDQ02TAiImIMM7t4797AWyW9GVgf2Bj4PLCppJlV7X02cHf3YUZExNqYdM3d9km2Z9ueAxwG/LvtI4CLgbdXLzsSOK/rKCMiYq30op/7h4HjJS2htMGf1oMyIiJiAt00yzzD9o+BH1ePlwJ7TsXnRkTE5GSEakRECyW5R0S0UJJ7REQLJblHRLRQkntERAsluUdEtFCSe0RECyW5R0S0UJJ7REQLJblHRLRQkntERAsluUdEtFCSe0RECyW5R0S0UJJ7REQLJblHRLRQkntERAtNOrlL2kbSxZJukXSzpOOq7ZtLulDSz6vfm01duBERsSa6qbmvAE6wvROwF3CMpJ2AjwAX2d4BuKh6HhERNZp0crd9j+1rqsePALcCWwMHAwuqly0ADuk2yIiIWDtT0uYuaQ6wO3AlsKXte6pd9wJbTkUZERGx5rpO7pI2Ar4N/Jnt33Tus23A47xvnqRFkhYNDw93G0ZERHToKrlLeg4lsS+0fW61+T5JW1X7twKWj/Ve2/Ntz7U9d2hoqJswIiJilG56ywg4DbjV9mc7dp0PHFk9PhI4b/LhRUTEZMzs4r17A38E3CjpumrbR4FTgLMlHQ3cCRzaXYgREbG2Jp3cbf8E0Di795vs50ZERPcyQjUiooWS3CMiWijJPSKihZLcIyJaKMk9IqKFktwjIlooyT0iooWS3CMiWijJPSKihZLcIyJaKMk9IqKFktwjIlooyT0iooWS3CMiWijJPSKihZLcIyJaKMk9IqKFktwjIlqoZ8ld0v6Sbpe0RNJHelVORESsqifJXdIM4MvAAcBOwOGSdupFWRERsape1dz3BJbYXmr7t8C3gIN7VFZERIzSq+S+NXBXx/Nl1baIiKiBbE/9h0pvB/a3/d7q+R8Bv2v7TzteMw+YVz19KXB7l8XOAu7v8jO61Q8xQH/E0Q8xQH/E0Q8xQH/E0Q8xQH/EMRUxbGd7aKwdM7v84PHcDWzT8Xx2te0ZtucD86eqQEmLbM+dqs8b1Bj6JY5+iKFf4uiHGPoljn6IoV/i6HUMvWqWuRrYQdL2ktYFDgPO71FZERExSk9q7rZXSPpT4AfADOB02zf3oqyIiFhVr5plsH0BcEGvPn8MU9bE04V+iAH6I45+iAH6I45+iAH6I45+iAH6I46extCTG6oREdGsTD8QEdFCSe4RES2U5B6tI2ldSTtXP8+puex1JP1enWX2qxyLZg10m7uknSlz16w/ss32GTXHcCDw8lExfKLOGKo4fg+YQ8dN8jqPhaQh4MOs+v/xhrpiqOLYF1gA3AGIMt7iSNuX1hjDtbZ3r6u8iTR9jvTLsZC0HvCHrHqO1HauSnob8ClgC8p3UyUEb9yL8nrWW6bXJJ0M7Ev54l5AmaTsJ0CdX9y/BzYAXg+cCrwduKqu8jvi+CfgxcB1wFPVZlPjsQAWAmcBBwLvA44Ehmssf8TfAm+yfTuApB2BM4FX1RjDRZL+EDjXDdae+uEcoU+OBXAe8DCwGHiioRg+DbzF9q11FDawNXdJNwK7Adfa3k3SlsA3bL+xxhhusL1rx++NgO/bfk1dMVRx3Ars1HAiWWz7VSPHotp2te09ao7jmfIn2tbjGB4BNgRWAI/T4xraBHH0wznSL8fiJts711nmGDFcbnvvusob2Jo78N+2n5a0QtLGwHKePeVBHR6vfj8m6YXAr4Gtao4B4CbgBcA9DZQ94snq9z1VU9V/Aps3EMciSacC36ieHwEsqjMA28+rs7wJNH6O9NGx+KmkXWzf2GAMiySdBXyHjqsH2+f2orBBTu6LJG0K/CPlUuu/gJ/VHMN3qxg+A1xDaQr5x7oKl/TdqsznAbdIuopnf2neWlcswCclbQKcAHwR2Bj4UI3lj3g/cAzwwer5ZcBX6g5C0mbADjy7rbu2dv9KP5wj/XIs9gHeI+mXlHNk5Aqitis6yjnxGPCmjm0GepLcB7ZZppOkOcDGtm+oscx1gL1s/7R6vh6wvu2Ha4zhdRPtt31JXbH0i+qm1fdsN9WuiqT3AsdRJsy7DtgL+FmdN5clCZht+67q+RxqPkeqchs/FlUc24213faddcZRp4FN7pJeOcbmh4E7ba+oKYa+6AnQJElfpNQ+xmT7g+Pt6wVJXwPeAFxKucH7b3V9HzpiuBHYA7jC9iskvQz4v7bfVncctneps8yxYqAPjkVHPFvw7CuIX9VQ5om2Pz3eudKrc2SQm2W+ArwSuIFyibUzcDOwiaT32/5hDTH0RU+A6qbV6PIfprQ1n2B7aQ+Lr7U9e3VsH1X1bT8AOBz4sqQLR9YWqMnjth+XhKT1bN8m6aU1lj/iGkl72L66gbJH9MWxkPRWSk+qF1LuPWwH3ErpxtxrI71jaj1XBjm5/ydw9Mhsk9UarZ8ATqS0YdWR3P8EOB5YIamxngDA5yirXX2ziuEwStfIa4DTKd3hesL2AgBJL7b9i16VszZsPynp+5Q/eM8FDgHqTO7Lqrbu7wAXSnoQaOLy/3eBIyTdCTxKM+3M/XIs/orSJPQj27tLej3wrjoKtv3d6uFP6jxHBrlZZpWuTSPbJF1n+xVNxVY3Sdfb3m3Utuuqy+BV9vUohkso7apXU25iXtpEzwRJBwDvpPxB+zFwNvDDuptmOuJ5HbAJpXnotzWX3VftzA0fi0W250q6Hti96kVUy7nREUOt58gg19xvlvRVyuLbUE7oW6obm0+O/7apJWlryiVe56i3unsCPCbpUOCc6vnbWdlNs5a/3rZfVy3MsgclsX5P0ka26+4O+W5KW/ufNHxTdTNKt8NHqp+dKVdStbF9p6QZwJY0eK73w7EAHqrGoVwKLJS0nHI1U5u6z5FBrrk/F/gApYsTwOWUdvjHgQ1s/1cNMXyK6o8KHSNDa+6CiKQXAZ8HXk1J5ldQuiHeDbzK9k9qiGEf4DXVz6aUnhGX2T6z12X3G0l/BbwHWAo8XW12Az1EjgVOBu4bFUedA7r65VhsyMpBVEdQriAW2v51jTHUeo4MbHLvB5JuB3ZtsobYLyStoPSl/hvggrovuzvi2IvSz/53gHUpK4E9Wud9kOp7sUtTx6AjjiWUhelrS2BjxNAXx6If1H2ODGyzjKS9gb9k1SaRF9UYxlLgOTQ3VwXwzKRd/5NVJ0X64xrDmAXsDbwW+KCkpyn9mf9PjTEAfIlyQ/mfgbmUZpoda47hJkrNbHnN5Y52F6XXVJP64lio5km7xlHrOTKwyR04jdL0sJiVTSK16Oiv+hhwnaSLePbI0Fr7dlMmRboM+BE1H4sRth+StJTStjob+D3KH74mYlkiaYbtp4CvSboWOKnGEP4GuFbSTTQwYljS8dXDpcCPJX1vVByfrSOOSqPHokOtk3aNpe5zZJCT+8O2v99Q2SP9VRcD5zcUQ6cNbH+4yQCqL+1tlFkHvwoc1dCl+GPVTavrJH2aMt9O3esWLKDUEm9kZTtznUbmc/lV9bNu9dOEpo/FiPuaTOxQ/zkysG3ukk6htKeey7NrBHXfhR+JZzNgm7qHd1dlfxL4qcui5I2QtI7tJk/ekTi2o9xAXJdyZbcJ8BXbS2qMofbZMCciaQPbjzVUdqPHomqOAXgdZXK9WibtGieWWs+RQU7uF4+xuda78JJ+DLyVcgW0mNKueLnt4yd6Xw/iGJlW9QlKN9Da2xMlrQ8czaoLl9TW7l91+zvD9hF1lTlOHJ+l/F+cT4MVD0mvpjRfbmR7W0m7UbqIfqDGGBo9FtV0FONxzd/PWu+NDWyzjO3XNx0DsInt31STI51h+2RJtdfc3R/Tqv4T5ZLzDygjhY9g5bDrWth+StJ2ktZtuHfGyHxDe3VsM2XOmzp9jvL/cT6A7eslvbbmGJo+Fh9zNXnaaJIOqimGEbXeGxu45C7pXba/0XHT6Flqvlk0U9JWwKHAn9dYLgCSXlbN1THWJGp11xRfYvsdkg62vUDSNylf5LotBS6XdD4dg1Tq/F70ScUDANt3SercVOsN9z44FhdK2t/2HZ0bJR0F/AXwrzXGUuu9sYFL7pTmB1h506hJnwB+QJkz4upqMNHPayz/eGAeZUKk0equKY6MCn5IZd3Oeyndzur2i+pnHRr6jkj62FjbXf/auneprK3rajK146j5aqoPjsXxwA8lHWj751VMJwH/g9IOX6d/lfTmuu6NDWybe/SXqmnq28CuwNeAjSiXxH/faGANkHRCx9P1gYOAW2sed4CkWZSRy79PuQ/zQ+C4mkdlNn4sJO0H/AMrJ5DbEzjQ9oM1lT8ya6uo8d7YwCV3SV+YaH8dfczV0PzMY8SxB3CX7Xur5++mrPB+J/CXth+oI45+UCWyY4AHKTNhfoYyzPsXlGmPa+stM0Zs6wE/sL1vUzH0i6aOhaTXAP8C/BQ41Pbjq3nLwBvEZpnFTQdAQ/Mzj+EfKLUyqhtlpwDHAq8A5lMmEKtFddL+Iav2BKjr8vublP+PHYCrKFcPn6ck+FPp4bTHa2ADyqCVWozXFFKx7b+qK5Yx1H0sOmvN6wH7ActVbkTU3aNsb+A6249KehdlPYrPuUcLhgxczT1W6pyyVNKXgWHbf1k9r3XaY0n/Rhnq/qwRw7bHuh/Qi/Kvt71bddLeaXvbjn11H4sbWXlFNwMYAj5h+0s1lX/CGJs3pHRVfb7tjeqIo4ql0WPRT6qedLtRmi6/Tql0HGq7J23/g1hzB57pM/phYCee3a+65zcRq54Y46pxaPUMSTNd5irfj3JzdUTd/7ezbe9fc5mdnoJSFZN0/6h9tQwckbRN1e2us4vdCsqgqtqOTecfVEnPo9xIPYoyPXZdf2z74lj0mRXV9/Ng4Eu2T5N0dK8KG9jkDiykzNt9IPA+4EhguKayX02ZlOlM4ErKJV8TzgQuqZLZf1N1PZT0EuqfMOqnknZxAwt0VF5U/dFVx2Oq59vXFEPfdLuTtDmlp8gRlCkAXlnXDcRK3xyLPvJI1VPnXcBrJa1DD+eWGdhmGUmLbb9K0g2u5qeua6hzNRLyjZQ1OncFvgec6WrJvzqpTHG7FWW1oUerbTtSRiX2vJ97x2X3TEp791JKb4Bal3RTWeVnXLYvqSGGN1MGDo3V7e4A28t6HUNV5meAt1Huu3zZNaxtMEYMfXEs+omkF1D+/VfbvkzStsC+ts/oSXkDnNyvsL2XpB8AX6CsqXqO7RfXHMd6lCT/GeDj060tUeMs5TbCDS3p1pSmu91VMTxN+QO7gmf35qr1JmKfHIs/sP2Dcfa9w/Y/1xXLGOW/BjjM9jE9+fwBTu4HUZohtqEszrAxJbnWMktjldQPpCT2OZQh3qfbvruO8vtF1R1zlkfN0Kmyluly2/3Qu6lW07Hb3XiaPhaSnqIsrfeu0eempGtsjzm6u4fx7E6pvb8D+CXw7V5VCAc2uTdJ0hmUdSAvAL5l+6aGQ2qMpH+nTF1656jt2wFfq+MGd78Yo9vdk5QbvU0sDNGofjkWKnP5fwX4GPAh2+d07rO9+7hvnroYdqRUAg8H7qfcK/xftie86u263EFL7n0yiOlpVs5b0thlbz+Y6D5H5/2QiCaM1M6rBLuQsjLUMbYfq6vmXuWLy4CjRwbTSVrqHq8aN4i9Zd5H+Q86m9LOXntPFdt1L/4wITW7hNhmE+zboIbyAZD0XcYYLVx5gjJS9cseZ4bAaDfb/6EyBfInKStDvbvG4t9GWfrx4mo8yLeoIW8NYs39+ZT2qndSbhidRbmR+lCjgTVIZSHkRpYQk/T3wK+Bv3D1ZaoGEn0ceIHteRO9fwrjmKi3zEzKPPOH2351HfH0I0n7UI5BT27g9aOxml4k7UuZomLINU6XLWlD4GBK88wbgDOAf7H9w56UN2jJvZOk2ZS/iMcDH7b9Tw2H1AhJl9veu6GyN6SMtNsTuK7avBtlKoD3NtQNbwjA9vCo7afafm/d8TRpjBt459r+YrNR1UfSIba/M8b2zSgLl5zSQFgj5b8DeKft/XpSxqAmd5U5zA+n9DdfDPyt7VuajaoZkj5P80uIvYhSOwa42fbSusruiOFkytw661Aue1cAX6xxfpuxYpoF/No1nmhN3cAbJ5ZjgW/UPIAqqH/h4K5J+oSkxZTa+iXAXNtH90Nil7RPNcdL3TYGHgPeBLyl+ql1lRnbS21/t/ppIrEfD+wD7GF7c9ubAb8L7C3pQzXFsJekH0s6V9Lukm6i3B+6T1KdQ+5vo1z2H2R7n6qmXusiHR22BK6WdLak/asmu6jBwNXcqzvPv6QkM1h5E63WEZEd8Uzry95+UXV5e6Pt+0dtH6KM3q2jy9si4KOURbnnU0ZiXiHpZZQRzD2PoYrjEEpz5d7AyA28U23XNQ3D6HhEqXgcBcyldIY4zfYvmohnuhjE3jKNfEE7jXPZKze0pJj6YHHqPvCc0YkdSru7yipEdZg5cnNM0idsX1HFcFudFdaqjfk7HTfw/gzYQtJX6eENvAnisaR7KatzraD0sDpH0oW2T6wzln5SzS1zuO2Fvfj8gWuWsX3nRD81hdFPl71QFqd+AWUx5Eso82U/UkfBktaX9GeSviTpTyQ1VWGYaEHsuhbL7px98r9H7av9Etn2o7a/afstlO/EtZSZVGsj6biqGfXTwOXALrbfD7yKMv9/60naWNJJ1TnyJhXHUuZhOrRn5Q5as0w/6MPL3mtt7z4yaKiqqV5me6/Vvrn7ss+ijD68DDiAMpf6cb0ud4w4nqJjQezOXcD6tntee++IQcBzWdl0WFsM/UbSxynTcqxS8ZL0O010362bpPMoK4T9jDI198h4lONsXzfRe7sqN8l98urutzpBHFfZ3lPSpcAHKJe/V/V6BFxV9o22d6kez6zKrXW+juh/krbg2U2GPVl9qB+NOkdmAPcA2/Z6np2Ba5aZSFWLrE0/XPZW5lf9Zv8PZQKzWyiXwXV4cuSBy6IhEc+Q9BZJP6d0NrgEuAP4/oRvap/Oc+QpYFmvEzu0rOYu6VfuWF4tem9UUwSsbI6YdvPsxKokXU+5qv1R1XT4esoMjT1bgajfjGoy7Gyy6+k5Moi9ZaIi6V22v1H18R7NwAPA+b0cQGJ7Rq8+O1rhSdu/lrSOpHVsXyzpc00HVaemzpGBS+7VyNQxd9HDJav61IbV7/Hmx9geeD/QsxurVTfM9wEvAW6g3DxL80yMeEjSRpQ51RdKWs7YN75jig1cs4ykiyfa31Rf835V9bf+WA8/vy96y0R/qjodPE6pfB1BGR8aFZAAAAQDSURBVOC10PavGw1sGhi45B6ranIQU3rLRPSngestI2kPlYVmR56/W9J5kr6gsuL7dNTYICbSWyYmIOltkn4u6WFJv5H0iKTfNB3XdDBwNXdJ1wC/b/sBSa+lDCA6FngF8Du2395ogA1oeBBTIz0BYjCowbUGpruBu6EKzLD9QPX4ncB8298Gvi2pZ6O9+txI7fkhSTtTBjFtUUfB6S0Tq3FfEnszBjK5S5pZNQHsB3Su9DOI/56pMHoQ00aUBYEjmraouune2FoD09UgJsMzgUsk3U+ZnOkyAEkvAR5uMrCm2D61engJ0PMpByLWQudaAyMMJLn32MC1uUNZFAHYijJP96PVth2BjWxf02hwDZC0HmWGvTl0/MFucgWiiGjWINbcGZkne9S2/2gilj5xHuWqZTEdl74RTZF0ou1PS/oiY0x3bPuDDYQ1rQxkco9VzLZd5zJuEaszsuzlokajmMaS3Nvhp5J2sX1j04FEVA6Q9KDtBU0HMl0NZJt7FJJupFzyzgR2oKzs8gQNrScbMULScZQFbbairJl6pu1rm41qeklyH2CStptof43LDkaMqfqOHlb9PJfS2+3MaX6PrBZJ7i1RzZa5D6Umf/l07DUU/U3S7sDpwK4Z/NZ7Aze3TKxK0seABcDzgVnA1yT9RbNRRZTJ5KrVmBZSVmC6HXhbw2FNC6m5t4Ck24HdRpbukvRc4DrbL202spiuJL2Rsrbwm4GrKHNAnTcyLiV6L71l2uE/KVP9jqzLuB5wd3PhRHAS8E3ghF6uBBbjS3IfYB0DRB4GbpZ0YfX8jZTaUkQjbL+h6RimuzTLDDBJR060P32MI6avJPcBJ2kGcIbtI5qOJSL6R3rLDDjbTwHbSVq36VgiVkfSOpJSEalB2tzbYSlwuaTz6VhZ3vZnmwsppjNJGwPHAFtT1hi4EPhT4ATgemBhc9FND0nu7fCL6mcd4HkNxxIBZV3fB4GfAe8FPkqZFuMQ29N1xbRapc09IqacpBtt71I9ngHcA2w7MhYjei819xaQNAScCLyc0t8dSHe0aNTIur7YfkrSsiT2euWGajssBG4Dtgc+DtwBXN1kQDHt7SbpN9XPI8CuI48l/abp4KaDNMu0gKTFtl8l6YaRaX4lXW17j6Zji4hmpFmmHUYuge+RdCBlOoLNG4wnIhqW5N4On5S0CaWb2RcpK85/qNmQIqJJaZaJiGih1NwH2Hgry4/ICvMR01eS+2DrXFn+48DJTQUSEf0lzTItIela27s3HUdE9If0c2+P/JWOiGckuUdEtFCaZQZYNfJv5D9wA+CxkV2AbW/cSGAR0bgk94iIFkqzTERECyW5R0S0UJJ7REQLJblHRLRQkntERAv9fzqXvDC9Ga6VAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fjBiuaXA6AK_"
      },
      "source": [
        "##### Lasith Malinga leads the chart, "
      ]
    }
  ]
}