IPL_Analysis_.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "RMeXg1Txj-kp"
   },
   "source": [
    "#**IPL Analysis- by Yash Shinde**\n",
    "\n",
    "The Indian Premier League (IPL) is a professional Twenty20 cricket league in India contested during March or April and May of every year by eight teams representing eight different cities in India. The league was founded by the Board of Control for Cricket in India (BCCI) in 2008. The IPL has an exclusive window in ICC Future Tours Programme.\n",
    "\n",
    "The IPL is the most-attended cricket league in the world and in 2014 ranked sixth by average attendance among all sports leagues. In 2010, the IPL became the first sporting event in the world to be broadcast live on YouTube. The brand value of the IPL in 2019 was ₹475 billion (US 6.7 billion dollars), according to Duff & Phelps. According to BCCI, the 2015 IPL season contributed ₹11.5 billion (US 160 million dollars) to the GDP of the Indian economy.\n",
    "\n",
    "There have been twelve seasons of the IPL tournament. The current IPL title holders are the Mumbai Indians, who won the 2019 season. The venue for the 2020 season has been moved, due to the ongoing COVID-19 pandemic; games will now take place in the United Arab Emirates from 19 September through 10 November.\n",
    "[To know more about IPL, click here](https://en.wikipedia.org/wiki/Indian_Premier_League)\n",
    "\n",
    "![IPL](https://upload.wikimedia.org/wikipedia/en/thumb/8/84/Indian_Premier_League_Official_Logo.svg/375px-Indian_Premier_League_Official_Logo.svg.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "executionInfo": {
     "elapsed": 3773,
     "status": "ok",
     "timestamp": 1601651959268,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "hy4pAlYej-kq"
   },
   "outputs": [],
   "source": [
    "project_name = \"IPL Analysis\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "executionInfo": {
     "elapsed": 6298,
     "status": "ok",
     "timestamp": 1601651961815,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "ANdlZ9Utj-ks"
   },
   "outputs": [],
   "source": [
    "!pip install jovian --upgrade -q"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "executionInfo": {
     "elapsed": 6277,
     "status": "ok",
     "timestamp": 1601651961819,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "qOsUEOTdj-kv"
   },
   "outputs": [],
   "source": [
    "import jovian"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 87
    },
    "executionInfo": {
     "elapsed": 8670,
     "status": "ok",
     "timestamp": 1601651964244,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
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     "user_tz": -330
    },
    "id": "iau61gaJj-kx",
    "outputId": "33e349c5-c111-4276-89b3-ea34a20c6009"
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "window.require && require([\"base/js/namespace\"],function(Jupyter){Jupyter.notebook.save_checkpoint()})"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[jovian] Attempting to save notebook..\u001b[0m\n",
      "[jovian] Updating notebook \"uayashu145/ipl-analysis\" on https://jovian.ml/\u001b[0m\n",
      "[jovian] Uploading notebook..\u001b[0m\n",
      "[jovian] Capturing environment..\u001b[0m\n",
      "[jovian] Committed successfully! https://jovian.ml/uayashu145/ipl-analysis\u001b[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'https://jovian.ml/uayashu145/ipl-analysis'"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jovian.commit(project=project_name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "KLmxth9Tj-k0"
   },
   "source": [
    "##**Loading Libraries and Datasets**\n",
    "Let us begin our analysis by loading the Dataset & Python Modules/ Packages/ Libraries.\n",
    "There are several options for getting the dataset into Jupyter:\n",
    "\n",
    "* Download the CSV manually and upload it via Jupyter's GUI\n",
    "* Use the urlretrieve function from the urllib.request to download CSV files from a raw URL directly\n",
    "* Use a helper library e.g. opendatasets, which contains a collection of curated datasets and provides a function for directly download.\n",
    "\n",
    "We'll use the ***Download the CSV manually and upload it via Jupyter's GUI*** method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "executionInfo": {
     "elapsed": 8633,
     "status": "ok",
     "timestamp": 1601651964247,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "Hyf2WJdfj-k0"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pandas in /srv/conda/envs/notebook/lib/python3.7/site-packages (1.1.2)\n",
      "Requirement already satisfied: pytz>=2017.2 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from pandas) (2020.1)\n",
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      "Requirement already satisfied: numpy>=1.15.4 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from pandas) (1.19.2)\n",
      "Requirement already satisfied: six>=1.5 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from python-dateutil>=2.7.3->pandas) (1.12.0)\n",
      "Requirement already satisfied: pandas in /srv/conda/envs/notebook/lib/python3.7/site-packages (1.1.2)\n",
      "Requirement already satisfied: matplotlib in /srv/conda/envs/notebook/lib/python3.7/site-packages (3.3.2)\n",
      "Requirement already satisfied: numpy>=1.15.4 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from pandas) (1.19.2)\n",
      "Requirement already satisfied: pytz>=2017.2 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from pandas) (2020.1)\n",
      "Requirement already satisfied: python-dateutil>=2.7.3 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from pandas) (2.8.0)\n",
      "Requirement already satisfied: pillow>=6.2.0 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from matplotlib) (7.2.0)\n",
      "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from matplotlib) (2.4.7)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from matplotlib) (1.2.0)\n",
      "Requirement already satisfied: certifi>=2020.06.20 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from matplotlib) (2020.6.20)\n",
      "Requirement already satisfied: cycler>=0.10 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from matplotlib) (0.10.0)\n",
      "Requirement already satisfied: six>=1.5 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from python-dateutil>=2.7.3->pandas) (1.12.0)\n",
      "Requirement already satisfied: seaborn in /srv/conda/envs/notebook/lib/python3.7/site-packages (0.11.0)\n",
      "Requirement already satisfied: pandas>=0.23 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from seaborn) (1.1.2)\n",
      "Requirement already satisfied: matplotlib>=2.2 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from seaborn) (3.3.2)\n",
      "Requirement already satisfied: numpy>=1.15 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from seaborn) (1.19.2)\n",
      "Requirement already satisfied: scipy>=1.0 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from seaborn) (1.5.2)\n",
      "Requirement already satisfied: pytz>=2017.2 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from pandas>=0.23->seaborn) (2020.1)\n",
      "Requirement already satisfied: python-dateutil>=2.7.3 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from pandas>=0.23->seaborn) (2.8.0)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from matplotlib>=2.2->seaborn) (1.2.0)\n",
      "Requirement already satisfied: pillow>=6.2.0 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from matplotlib>=2.2->seaborn) (7.2.0)\n",
      "Requirement already satisfied: certifi>=2020.06.20 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from matplotlib>=2.2->seaborn) (2020.6.20)\n",
      "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from matplotlib>=2.2->seaborn) (2.4.7)\n",
      "Requirement already satisfied: cycler>=0.10 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from matplotlib>=2.2->seaborn) (0.10.0)\n",
      "Requirement already satisfied: six>=1.5 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from python-dateutil>=2.7.3->pandas>=0.23->seaborn) (1.12.0)\n"
     ]
    }
   ],
   "source": [
    "!pip install pandas\n",
    "!pip install pandas matplotlib\n",
    "!pip install seaborn\n",
    "import numpy as np # numerical computing \n",
    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
    "from pandas import DataFrame\n",
    "import matplotlib.pyplot as plt #visualization\n",
    "%matplotlib inline\n",
    "import seaborn as sns #modern visualization\n",
    "from urllib.request import urlretrieve\n",
    "urlretrieve('https://www.kaggle.com/nowke9/ipldata?select=matches.csv')\n",
    "\n",
    "\n",
    "#plotting style settings\n",
    "sns.set_style(\"darkgrid\")\n",
    "plt.rcParams['figure.figsize'] = (14, 8)\n",
    "plt.rcParams['font.size'] = 14\n",
    "plt.rcParams['figure.facecolor'] = '#00000000'\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "SvmTgFbej-k5"
   },
   "source": [
    "##**Reading input dataset**\n",
    "\n",
    "In order to read the input data, let us first define the directory/path in which the input file is present.Since we have downloaded the CSV manually and uploaded it via Jupyter's GUI, we will read the input csv using **`pd.read_csv()`** function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "executionInfo": {
     "elapsed": 8611,
     "status": "ok",
     "timestamp": 1601651964248,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "bD5gBDloj-k5"
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "window.require && require([\"base/js/namespace\"],function(Jupyter){Jupyter.notebook.save_checkpoint()})"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[jovian] Attempting to save notebook..\u001b[0m\n",
      "[jovian] Updating notebook \"uayashu145/ipl-analysis\" on https://jovian.ml/\u001b[0m\n",
      "[jovian] Uploading notebook..\u001b[0m\n",
      "[jovian] Capturing environment..\u001b[0m\n",
      "[jovian] Uploading additional outputs...\u001b[0m\n",
      "[jovian] Committed successfully! https://jovian.ml/uayashu145/ipl-analysis\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "jovian.commit(outputs=['matches.csv'])\n",
    "matches = pd.read_csv('matches.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "oNsIcQRkj-k7"
   },
   "source": [
    "##**Get basic information of Data**\n",
    "Let us check the basic information of the dataset. The very basic information to know is the dimension of the dataset – rows and columns – that’s what we find out with the method ***`shape`***."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 35
    },
    "executionInfo": {
     "elapsed": 8595,
     "status": "ok",
     "timestamp": 1601651964251,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "pp-wKgrwj-k8",
    "outputId": "09be4e53-a131-49bc-c58a-861ba4638bb6"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(756, 18)"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "9WpzeJjfj-k-"
   },
   "source": [
    "Also, it’s important to know the different types of data/variables in the given dataset. This can be done by the method ***`info()`***."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 451
    },
    "executionInfo": {
     "elapsed": 8574,
     "status": "ok",
     "timestamp": 1601651964252,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
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    "id": "cKIvw4j6j-k-",
    "outputId": "f53c4d2c-9362-46ac-f51e-71f7c67064fb"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 756 entries, 0 to 755\n",
      "Data columns (total 18 columns):\n",
      " #   Column           Non-Null Count  Dtype \n",
      "---  ------           --------------  ----- \n",
      " 0   id               756 non-null    int64 \n",
      " 1   season           756 non-null    int64 \n",
      " 2   city             749 non-null    object\n",
      " 3   date             756 non-null    object\n",
      " 4   team1            756 non-null    object\n",
      " 5   team2            756 non-null    object\n",
      " 6   toss_winner      756 non-null    object\n",
      " 7   toss_decision    756 non-null    object\n",
      " 8   result           756 non-null    object\n",
      " 9   dl_applied       756 non-null    int64 \n",
      " 10  winner           752 non-null    object\n",
      " 11  win_by_runs      756 non-null    int64 \n",
      " 12  win_by_wickets   756 non-null    int64 \n",
      " 13  player_of_match  752 non-null    object\n",
      " 14  venue            756 non-null    object\n",
      " 15  umpire1          754 non-null    object\n",
      " 16  umpire2          754 non-null    object\n",
      " 17  umpire3          119 non-null    object\n",
      "dtypes: int64(5), object(13)\n",
      "memory usage: 106.4+ KB\n"
     ]
    }
   ],
   "source": [
    "matches.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "aK54hfcTj-lA"
   },
   "source": [
    "Now, let's perform a simple summary statistics using the method **`describe()`**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 294
    },
    "executionInfo": {
     "elapsed": 8498,
     "status": "ok",
     "timestamp": 1601651964253,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "tN71Xr0zj-lB",
    "outputId": "6986476e-dae6-4450-85f0-807d43902177"
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>season</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
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       "      <th>count</th>\n",
       "      <td>756.000000</td>\n",
       "      <td>756.000000</td>\n",
       "      <td>756.000000</td>\n",
       "      <td>756.000000</td>\n",
       "      <td>756.000000</td>\n",
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       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>378.500000</td>\n",
       "      <td>2013.444444</td>\n",
       "      <td>0.025132</td>\n",
       "      <td>13.283069</td>\n",
       "      <td>3.350529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>218.382692</td>\n",
       "      <td>3.366895</td>\n",
       "      <td>0.156630</td>\n",
       "      <td>23.471144</td>\n",
       "      <td>3.387963</td>\n",
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       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>2008.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <th>25%</th>\n",
       "      <td>189.750000</td>\n",
       "      <td>2011.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>378.500000</td>\n",
       "      <td>2013.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
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       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>567.250000</td>\n",
       "      <td>2016.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>6.000000</td>\n",
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       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>756.000000</td>\n",
       "      <td>2019.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>146.000000</td>\n",
       "      <td>10.000000</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               id       season  dl_applied  win_by_runs  win_by_wickets\n",
       "count  756.000000   756.000000  756.000000   756.000000      756.000000\n",
       "mean   378.500000  2013.444444    0.025132    13.283069        3.350529\n",
       "std    218.382692     3.366895    0.156630    23.471144        3.387963\n",
       "min      1.000000  2008.000000    0.000000     0.000000        0.000000\n",
       "25%    189.750000  2011.000000    0.000000     0.000000        0.000000\n",
       "50%    378.500000  2013.000000    0.000000     0.000000        4.000000\n",
       "75%    567.250000  2016.000000    0.000000    19.000000        6.000000\n",
       "max    756.000000  2019.000000    1.000000   146.000000       10.000000"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Y5Lp5cyOj-lD"
   },
   "source": [
    "\n",
    "And the final level of this basic information retrieval is to see a couple of actual rows of the input dataset using the method **`head()`**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "2Xo9YM7qj-lE"
   },
   "source": [
    " Let's see each unique team"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 121
    },
    "executionInfo": {
     "elapsed": 8475,
     "status": "ok",
     "timestamp": 1601651964254,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "nxaZkZ8hj-lE",
    "outputId": "a710eb7e-cdbb-4a73-d2dd-fcba421e3c74"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Kolkata Knight Riders', 'Chennai Super Kings', 'Rajasthan Royals',\n",
       "       'Mumbai Indians', 'Deccan Chargers', 'Kings XI Punjab',\n",
       "       'Royal Challengers Bangalore', 'Delhi Daredevils',\n",
       "       'Kochi Tuskers Kerala', 'Pune Warriors', 'Sunrisers Hyderabad',\n",
       "       'Rising Pune Supergiants', 'Gujarat Lions',\n",
       "       'Rising Pune Supergiant', 'Delhi Capitals'], dtype=object)"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches.team1.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "v62eo6nkj-lG"
   },
   "source": [
    "It can be seen that there is a redundancy here.Teams like ***`Rising Pune Supergiants`*** and ***`Rising Pune Supergiant`*** and ***`Delhi Daredevils`*** and ***`Delhi Capitals`*** points to same teams but yet two different entries are visible due to addition of 's'. So,let's correct the error.\n",
    "There will be three columns where the fix will be required-\n",
    "\n",
    "1. In team1 column\n",
    "2. In team2 column\n",
    "3. In winner column\n",
    "4. In toss winner column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "executionInfo": {
     "elapsed": 8451,
     "status": "ok",
     "timestamp": 1601651964256,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "bUZDoUkbj-lH"
   },
   "outputs": [],
   "source": [
    "matches.team1.replace({'Rising Pune Supergiants' : 'Rising Pune Supergiant', 'Delhi Daredevils':'Delhi Capitals'},inplace=True)\n",
    "matches.team2.replace({'Rising Pune Supergiants' : 'Rising Pune Supergiant', 'Delhi Daredevils':'Delhi Capitals'},inplace=True)\n",
    "matches.winner.replace({'Rising Pune Supergiants' : 'Rising Pune Supergiant', 'Delhi Daredevils':'Delhi Capitals'},inplace=True)\n",
    "matches.toss_winner.replace({'Rising Pune Supergiants' : 'Rising Pune Supergiant', 'Delhi Daredevils':'Delhi Capitals'},inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 104
    },
    "executionInfo": {
     "elapsed": 8414,
     "status": "ok",
     "timestamp": 1601651964257,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "PXc1an3Fj-lJ",
    "outputId": "590c5bbe-b825-48da-aa12-9bc0a1883ef1"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Kolkata Knight Riders', 'Chennai Super Kings', 'Rajasthan Royals',\n",
       "       'Mumbai Indians', 'Deccan Chargers', 'Kings XI Punjab',\n",
       "       'Royal Challengers Bangalore', 'Delhi Capitals',\n",
       "       'Kochi Tuskers Kerala', 'Pune Warriors', 'Sunrisers Hyderabad',\n",
       "       'Rising Pune Supergiant', 'Gujarat Lions'], dtype=object)"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches.team1.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 430
    },
    "executionInfo": {
     "elapsed": 8389,
     "status": "ok",
     "timestamp": 1601651964258,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "eZGT5CfHj-lL",
    "outputId": "30eca5f2-cce4-4542-a32c-f248834cc6f2"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>season</th>\n",
       "      <th>city</th>\n",
       "      <th>date</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>result</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>venue</th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "      <th>umpire3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2008</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>18-04-08</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>140</td>\n",
       "      <td>0</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>Asad Rauf</td>\n",
       "      <td>RE Koertzen</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2008</td>\n",
       "      <td>Chandigarh</td>\n",
       "      <td>19-04-08</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>33</td>\n",
       "      <td>0</td>\n",
       "      <td>MEK Hussey</td>\n",
       "      <td>Punjab Cricket Association Stadium, Mohali</td>\n",
       "      <td>MR Benson</td>\n",
       "      <td>SL Shastri</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2008</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>19-04-08</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>MF Maharoof</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>Aleem Dar</td>\n",
       "      <td>GA Pratapkumar</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2008</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>20-04-08</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>MV Boucher</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>SJ Davis</td>\n",
       "      <td>DJ Harper</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2008</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>20-04-08</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>DJ Hussey</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>BF Bowden</td>\n",
       "      <td>K Hariharan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id  season        city      date                  team1  \\\n",
       "0   1    2008   Bangalore  18-04-08  Kolkata Knight Riders   \n",
       "1   2    2008  Chandigarh  19-04-08    Chennai Super Kings   \n",
       "2   3    2008       Delhi  19-04-08       Rajasthan Royals   \n",
       "3   4    2008      Mumbai  20-04-08         Mumbai Indians   \n",
       "4   5    2008     Kolkata  20-04-08        Deccan Chargers   \n",
       "\n",
       "                         team2                  toss_winner toss_decision  \\\n",
       "0  Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
       "1              Kings XI Punjab          Chennai Super Kings           bat   \n",
       "2               Delhi Capitals             Rajasthan Royals           bat   \n",
       "3  Royal Challengers Bangalore               Mumbai Indians           bat   \n",
       "4        Kolkata Knight Riders              Deccan Chargers           bat   \n",
       "\n",
       "   result  dl_applied                       winner  win_by_runs  \\\n",
       "0  normal           0        Kolkata Knight Riders          140   \n",
       "1  normal           0          Chennai Super Kings           33   \n",
       "2  normal           0               Delhi Capitals            0   \n",
       "3  normal           0  Royal Challengers Bangalore            0   \n",
       "4  normal           0        Kolkata Knight Riders            0   \n",
       "\n",
       "   win_by_wickets player_of_match                                       venue  \\\n",
       "0               0     BB McCullum                       M Chinnaswamy Stadium   \n",
       "1               0      MEK Hussey  Punjab Cricket Association Stadium, Mohali   \n",
       "2               9     MF Maharoof                            Feroz Shah Kotla   \n",
       "3               5      MV Boucher                            Wankhede Stadium   \n",
       "4               5       DJ Hussey                                Eden Gardens   \n",
       "\n",
       "     umpire1         umpire2 umpire3  \n",
       "0  Asad Rauf     RE Koertzen     NaN  \n",
       "1  MR Benson      SL Shastri     NaN  \n",
       "2  Aleem Dar  GA Pratapkumar     NaN  \n",
       "3   SJ Davis       DJ Harper     NaN  \n",
       "4  BF Bowden     K Hariharan     NaN  "
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "lTf-Hr1Vj-lN"
   },
   "source": [
    "Finding the ***`Tied or No result`*** matches in the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 970
    },
    "executionInfo": {
     "elapsed": 8361,
     "status": "ok",
     "timestamp": 1601651964259,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "i9-EGeiGj-lN",
    "outputId": "22944793-6b49-4a74-c9b0-72681c528334"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>season</th>\n",
       "      <th>city</th>\n",
       "      <th>date</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>result</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>venue</th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "      <th>umpire3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>67</td>\n",
       "      <td>2009</td>\n",
       "      <td>Cape Town</td>\n",
       "      <td>23-04-09</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>tie</td>\n",
       "      <td>0</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>YK Pathan</td>\n",
       "      <td>Newlands</td>\n",
       "      <td>MR Benson</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>131</td>\n",
       "      <td>2010</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>21-03-10</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>tie</td>\n",
       "      <td>0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>J Theron</td>\n",
       "      <td>MA Chidambaram Stadium, Chepauk</td>\n",
       "      <td>K Hariharan</td>\n",
       "      <td>DJ Harper</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>242</td>\n",
       "      <td>2011</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>21-05-11</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Pune Warriors</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>bat</td>\n",
       "      <td>no result</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>SS Hazare</td>\n",
       "      <td>RJ Tucker</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>328</th>\n",
       "      <td>329</td>\n",
       "      <td>2013</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>07-04-13</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>bat</td>\n",
       "      <td>tie</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>GH Vihari</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>341</th>\n",
       "      <td>342</td>\n",
       "      <td>2013</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>16-04-13</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>tie</td>\n",
       "      <td>0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>V Kohli</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>VA Kulkarni</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>416</th>\n",
       "      <td>417</td>\n",
       "      <td>2014</td>\n",
       "      <td>Abu Dhabi</td>\n",
       "      <td>29-04-14</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>bat</td>\n",
       "      <td>tie</td>\n",
       "      <td>0</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>JP Faulkner</td>\n",
       "      <td>Sheikh Zayed Stadium</td>\n",
       "      <td>Aleem Dar</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>476</th>\n",
       "      <td>477</td>\n",
       "      <td>2015</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>21-04-15</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>tie</td>\n",
       "      <td>0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>SE Marsh</td>\n",
       "      <td>Sardar Patel Stadium, Motera</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>486</th>\n",
       "      <td>487</td>\n",
       "      <td>2015</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>29-04-15</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>no result</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>JD Cloete</td>\n",
       "      <td>PG Pathak</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>511</th>\n",
       "      <td>512</td>\n",
       "      <td>2015</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>17-05-15</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>no result</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>K Srinivasan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>610</th>\n",
       "      <td>611</td>\n",
       "      <td>2017</td>\n",
       "      <td>Rajkot</td>\n",
       "      <td>29-04-17</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>bat</td>\n",
       "      <td>tie</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>KH Pandya</td>\n",
       "      <td>Saurashtra Cricket Association Stadium</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>CB Gaffaney</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>705</th>\n",
       "      <td>706</td>\n",
       "      <td>2019</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>30-03-19</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>field</td>\n",
       "      <td>tie</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>P Shaw</td>\n",
       "      <td>Feroz Shah Kotla Ground</td>\n",
       "      <td>Anil Dandekar</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>Marais Erasmus</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>744</th>\n",
       "      <td>745</td>\n",
       "      <td>2019</td>\n",
       "      <td>Bengaluru</td>\n",
       "      <td>30-04-19</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>no result</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>M. Chinnaswamy Stadium</td>\n",
       "      <td>Nigel Llong</td>\n",
       "      <td>Ulhas Gandhe</td>\n",
       "      <td>Anil Chaudhary</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>746</th>\n",
       "      <td>747</td>\n",
       "      <td>2019</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>02-05-19</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>tie</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>JJ Bumrah</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>O Nandan</td>\n",
       "      <td>Nanda Kishore</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      id  season       city      date                        team1  \\\n",
       "66    67    2009  Cape Town  23-04-09             Rajasthan Royals   \n",
       "130  131    2010    Chennai  21-03-10              Kings XI Punjab   \n",
       "241  242    2011      Delhi  21-05-11               Delhi Capitals   \n",
       "328  329    2013  Hyderabad  07-04-13  Royal Challengers Bangalore   \n",
       "341  342    2013  Bangalore  16-04-13               Delhi Capitals   \n",
       "416  417    2014  Abu Dhabi  29-04-14             Rajasthan Royals   \n",
       "476  477    2015  Ahmedabad  21-04-15             Rajasthan Royals   \n",
       "486  487    2015  Bangalore  29-04-15  Royal Challengers Bangalore   \n",
       "511  512    2015  Bangalore  17-05-15               Delhi Capitals   \n",
       "610  611    2017     Rajkot  29-04-17                Gujarat Lions   \n",
       "705  706    2019      Delhi  30-03-19        Kolkata Knight Riders   \n",
       "744  745    2019  Bengaluru  30-04-19  Royal Challengers Bangalore   \n",
       "746  747    2019     Mumbai  02-05-19               Mumbai Indians   \n",
       "\n",
       "                           team2                  toss_winner toss_decision  \\\n",
       "66         Kolkata Knight Riders        Kolkata Knight Riders         field   \n",
       "130          Chennai Super Kings          Chennai Super Kings         field   \n",
       "241                Pune Warriors               Delhi Capitals           bat   \n",
       "328          Sunrisers Hyderabad  Royal Challengers Bangalore           bat   \n",
       "341  Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
       "416        Kolkata Knight Riders             Rajasthan Royals           bat   \n",
       "476              Kings XI Punjab              Kings XI Punjab         field   \n",
       "486             Rajasthan Royals             Rajasthan Royals         field   \n",
       "511  Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
       "610               Mumbai Indians                Gujarat Lions           bat   \n",
       "705               Delhi Capitals               Delhi Capitals         field   \n",
       "744             Rajasthan Royals             Rajasthan Royals         field   \n",
       "746          Sunrisers Hyderabad               Mumbai Indians           bat   \n",
       "\n",
       "        result  dl_applied                       winner  win_by_runs  \\\n",
       "66         tie           0             Rajasthan Royals            0   \n",
       "130        tie           0              Kings XI Punjab            0   \n",
       "241  no result           0                          NaN            0   \n",
       "328        tie           0          Sunrisers Hyderabad            0   \n",
       "341        tie           0  Royal Challengers Bangalore            0   \n",
       "416        tie           0             Rajasthan Royals            0   \n",
       "476        tie           0              Kings XI Punjab            0   \n",
       "486  no result           0                          NaN            0   \n",
       "511  no result           0                          NaN            0   \n",
       "610        tie           0               Mumbai Indians            0   \n",
       "705        tie           0               Delhi Capitals            0   \n",
       "744  no result           0                          NaN            0   \n",
       "746        tie           0               Mumbai Indians            0   \n",
       "\n",
       "     win_by_wickets player_of_match  \\\n",
       "66                0       YK Pathan   \n",
       "130               0        J Theron   \n",
       "241               0             NaN   \n",
       "328               0       GH Vihari   \n",
       "341               0         V Kohli   \n",
       "416               0     JP Faulkner   \n",
       "476               0        SE Marsh   \n",
       "486               0             NaN   \n",
       "511               0             NaN   \n",
       "610               0       KH Pandya   \n",
       "705               0          P Shaw   \n",
       "744               0             NaN   \n",
       "746               0       JJ Bumrah   \n",
       "\n",
       "                                         venue          umpire1       umpire2  \\\n",
       "66                                    Newlands        MR Benson     M Erasmus   \n",
       "130            MA Chidambaram Stadium, Chepauk      K Hariharan     DJ Harper   \n",
       "241                           Feroz Shah Kotla        SS Hazare     RJ Tucker   \n",
       "328  Rajiv Gandhi International Stadium, Uppal     AK Chaudhary        S Ravi   \n",
       "341                      M Chinnaswamy Stadium        M Erasmus   VA Kulkarni   \n",
       "416                       Sheikh Zayed Stadium        Aleem Dar  AK Chaudhary   \n",
       "476               Sardar Patel Stadium, Motera        M Erasmus        S Ravi   \n",
       "486                      M Chinnaswamy Stadium        JD Cloete     PG Pathak   \n",
       "511                      M Chinnaswamy Stadium  HDPK Dharmasena  K Srinivasan   \n",
       "610     Saurashtra Cricket Association Stadium     AK Chaudhary   CB Gaffaney   \n",
       "705                    Feroz Shah Kotla Ground    Anil Dandekar   Nitin Menon   \n",
       "744                     M. Chinnaswamy Stadium      Nigel Llong  Ulhas Gandhe   \n",
       "746                           Wankhede Stadium           S Ravi      O Nandan   \n",
       "\n",
       "            umpire3  \n",
       "66              NaN  \n",
       "130             NaN  \n",
       "241             NaN  \n",
       "328             NaN  \n",
       "341             NaN  \n",
       "416             NaN  \n",
       "476             NaN  \n",
       "486             NaN  \n",
       "511             NaN  \n",
       "610             NaN  \n",
       "705  Marais Erasmus  \n",
       "744  Anil Chaudhary  \n",
       "746   Nanda Kishore  "
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches[matches.result != 'normal']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "executionInfo": {
     "elapsed": 8330,
     "status": "ok",
     "timestamp": 1601651964260,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "xaG2xkIGj-lP"
   },
   "outputs": [],
   "source": [
    "import jovian"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 87
    },
    "executionInfo": {
     "elapsed": 10355,
     "status": "ok",
     "timestamp": 1601651966306,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "9pqtiravj-lS",
    "outputId": "fc2871c5-bc46-4ad8-dd8c-98498659cb9e"
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "window.require && require([\"base/js/namespace\"],function(Jupyter){Jupyter.notebook.save_checkpoint()})"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[jovian] Attempting to save notebook..\u001b[0m\n",
      "[jovian] Updating notebook \"uayashu145/ipl-analysis\" on https://jovian.ml/\u001b[0m\n",
      "[jovian] Uploading notebook..\u001b[0m\n",
      "[jovian] Capturing environment..\u001b[0m\n",
      "[jovian] Committed successfully! https://jovian.ml/uayashu145/ipl-analysis\u001b[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'https://jovian.ml/uayashu145/ipl-analysis'"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jovian.commit(project=project_name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "mvt2l-fYj-lT"
   },
   "source": [
    "#**Exploratory Analysis and Visualization**\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "hyqqeADWj-lU"
   },
   "source": [
    "Now let's start to analyze & study the given dataset and findout various results and usefull information."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "UUwe9omEj-lU"
   },
   "source": [
    "##**How many matches we’ve got in the dataset?**\n",
    "As we’ve seen above, ***`id`*** is a variable that counts each observation in the data while each observation is a match. So to get the number of matches in our dataset is as same as to get the number of rows in the dataset or maximum value of the variable ***`id`***."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 35
    },
    "executionInfo": {
     "elapsed": 10337,
     "status": "ok",
     "timestamp": 1601651966310,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "dXANd7S-j-lV",
    "outputId": "dc10f6c4-04b7-4ba9-dca7-7edeb72c7306"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total no. of matches played-  756\n"
     ]
    }
   ],
   "source": [
    "max_matches = matches['id'].max()\n",
    "print('Total no. of matches played- ', max_matches)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "n1Ufg59Rj-lW"
   },
   "source": [
    "##**The Number of matches played in each season?**\n",
    "We can get the number of counts/matches played in each season using ***`value_counts()`***."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 243
    },
    "executionInfo": {
     "elapsed": 10319,
     "status": "ok",
     "timestamp": 1601651966312,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "mAQhZZXvj-lX",
    "outputId": "4b0c7681-52f8-463e-95d9-33385d4ef5b2"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2013    76\n",
       "2012    74\n",
       "2011    73\n",
       "2019    60\n",
       "2018    60\n",
       "2016    60\n",
       "2014    60\n",
       "2010    60\n",
       "2017    59\n",
       "2015    59\n",
       "2008    58\n",
       "2009    57\n",
       "Name: season, dtype: int64"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches['season'].value_counts()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "3S72egplj-la"
   },
   "source": [
    "It's is seen that the ***`IPL 2013`*** season had the most no of matches since most no of teams had participated in that season.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "CFK5DAqnj-lb"
   },
   "source": [
    "##**Tied matches or matches with no result**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 970
    },
    "executionInfo": {
     "elapsed": 10300,
     "status": "ok",
     "timestamp": 1601651966315,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "wRSxiW85j-lb",
    "outputId": "485d2c15-333d-4b72-cb01-052f02c9a58f",
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>season</th>\n",
       "      <th>city</th>\n",
       "      <th>date</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>result</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>venue</th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "      <th>umpire3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>67</td>\n",
       "      <td>2009</td>\n",
       "      <td>Cape Town</td>\n",
       "      <td>23-04-09</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>tie</td>\n",
       "      <td>0</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>YK Pathan</td>\n",
       "      <td>Newlands</td>\n",
       "      <td>MR Benson</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>131</td>\n",
       "      <td>2010</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>21-03-10</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>tie</td>\n",
       "      <td>0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>J Theron</td>\n",
       "      <td>MA Chidambaram Stadium, Chepauk</td>\n",
       "      <td>K Hariharan</td>\n",
       "      <td>DJ Harper</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>242</td>\n",
       "      <td>2011</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>21-05-11</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Pune Warriors</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>bat</td>\n",
       "      <td>no result</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>SS Hazare</td>\n",
       "      <td>RJ Tucker</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>328</th>\n",
       "      <td>329</td>\n",
       "      <td>2013</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>07-04-13</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>bat</td>\n",
       "      <td>tie</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>GH Vihari</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>341</th>\n",
       "      <td>342</td>\n",
       "      <td>2013</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>16-04-13</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>tie</td>\n",
       "      <td>0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>V Kohli</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>VA Kulkarni</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>416</th>\n",
       "      <td>417</td>\n",
       "      <td>2014</td>\n",
       "      <td>Abu Dhabi</td>\n",
       "      <td>29-04-14</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>bat</td>\n",
       "      <td>tie</td>\n",
       "      <td>0</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>JP Faulkner</td>\n",
       "      <td>Sheikh Zayed Stadium</td>\n",
       "      <td>Aleem Dar</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>476</th>\n",
       "      <td>477</td>\n",
       "      <td>2015</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>21-04-15</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>tie</td>\n",
       "      <td>0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>SE Marsh</td>\n",
       "      <td>Sardar Patel Stadium, Motera</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>486</th>\n",
       "      <td>487</td>\n",
       "      <td>2015</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>29-04-15</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>no result</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>JD Cloete</td>\n",
       "      <td>PG Pathak</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>511</th>\n",
       "      <td>512</td>\n",
       "      <td>2015</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>17-05-15</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>no result</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>K Srinivasan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>610</th>\n",
       "      <td>611</td>\n",
       "      <td>2017</td>\n",
       "      <td>Rajkot</td>\n",
       "      <td>29-04-17</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>bat</td>\n",
       "      <td>tie</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>KH Pandya</td>\n",
       "      <td>Saurashtra Cricket Association Stadium</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>CB Gaffaney</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>705</th>\n",
       "      <td>706</td>\n",
       "      <td>2019</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>30-03-19</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>field</td>\n",
       "      <td>tie</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>P Shaw</td>\n",
       "      <td>Feroz Shah Kotla Ground</td>\n",
       "      <td>Anil Dandekar</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>Marais Erasmus</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>744</th>\n",
       "      <td>745</td>\n",
       "      <td>2019</td>\n",
       "      <td>Bengaluru</td>\n",
       "      <td>30-04-19</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>no result</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>M. Chinnaswamy Stadium</td>\n",
       "      <td>Nigel Llong</td>\n",
       "      <td>Ulhas Gandhe</td>\n",
       "      <td>Anil Chaudhary</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>746</th>\n",
       "      <td>747</td>\n",
       "      <td>2019</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>02-05-19</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>tie</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>JJ Bumrah</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>O Nandan</td>\n",
       "      <td>Nanda Kishore</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      id  season       city      date                        team1  \\\n",
       "66    67    2009  Cape Town  23-04-09             Rajasthan Royals   \n",
       "130  131    2010    Chennai  21-03-10              Kings XI Punjab   \n",
       "241  242    2011      Delhi  21-05-11               Delhi Capitals   \n",
       "328  329    2013  Hyderabad  07-04-13  Royal Challengers Bangalore   \n",
       "341  342    2013  Bangalore  16-04-13               Delhi Capitals   \n",
       "416  417    2014  Abu Dhabi  29-04-14             Rajasthan Royals   \n",
       "476  477    2015  Ahmedabad  21-04-15             Rajasthan Royals   \n",
       "486  487    2015  Bangalore  29-04-15  Royal Challengers Bangalore   \n",
       "511  512    2015  Bangalore  17-05-15               Delhi Capitals   \n",
       "610  611    2017     Rajkot  29-04-17                Gujarat Lions   \n",
       "705  706    2019      Delhi  30-03-19        Kolkata Knight Riders   \n",
       "744  745    2019  Bengaluru  30-04-19  Royal Challengers Bangalore   \n",
       "746  747    2019     Mumbai  02-05-19               Mumbai Indians   \n",
       "\n",
       "                           team2                  toss_winner toss_decision  \\\n",
       "66         Kolkata Knight Riders        Kolkata Knight Riders         field   \n",
       "130          Chennai Super Kings          Chennai Super Kings         field   \n",
       "241                Pune Warriors               Delhi Capitals           bat   \n",
       "328          Sunrisers Hyderabad  Royal Challengers Bangalore           bat   \n",
       "341  Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
       "416        Kolkata Knight Riders             Rajasthan Royals           bat   \n",
       "476              Kings XI Punjab              Kings XI Punjab         field   \n",
       "486             Rajasthan Royals             Rajasthan Royals         field   \n",
       "511  Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
       "610               Mumbai Indians                Gujarat Lions           bat   \n",
       "705               Delhi Capitals               Delhi Capitals         field   \n",
       "744             Rajasthan Royals             Rajasthan Royals         field   \n",
       "746          Sunrisers Hyderabad               Mumbai Indians           bat   \n",
       "\n",
       "        result  dl_applied                       winner  win_by_runs  \\\n",
       "66         tie           0             Rajasthan Royals            0   \n",
       "130        tie           0              Kings XI Punjab            0   \n",
       "241  no result           0                          NaN            0   \n",
       "328        tie           0          Sunrisers Hyderabad            0   \n",
       "341        tie           0  Royal Challengers Bangalore            0   \n",
       "416        tie           0             Rajasthan Royals            0   \n",
       "476        tie           0              Kings XI Punjab            0   \n",
       "486  no result           0                          NaN            0   \n",
       "511  no result           0                          NaN            0   \n",
       "610        tie           0               Mumbai Indians            0   \n",
       "705        tie           0               Delhi Capitals            0   \n",
       "744  no result           0                          NaN            0   \n",
       "746        tie           0               Mumbai Indians            0   \n",
       "\n",
       "     win_by_wickets player_of_match  \\\n",
       "66                0       YK Pathan   \n",
       "130               0        J Theron   \n",
       "241               0             NaN   \n",
       "328               0       GH Vihari   \n",
       "341               0         V Kohli   \n",
       "416               0     JP Faulkner   \n",
       "476               0        SE Marsh   \n",
       "486               0             NaN   \n",
       "511               0             NaN   \n",
       "610               0       KH Pandya   \n",
       "705               0          P Shaw   \n",
       "744               0             NaN   \n",
       "746               0       JJ Bumrah   \n",
       "\n",
       "                                         venue          umpire1       umpire2  \\\n",
       "66                                    Newlands        MR Benson     M Erasmus   \n",
       "130            MA Chidambaram Stadium, Chepauk      K Hariharan     DJ Harper   \n",
       "241                           Feroz Shah Kotla        SS Hazare     RJ Tucker   \n",
       "328  Rajiv Gandhi International Stadium, Uppal     AK Chaudhary        S Ravi   \n",
       "341                      M Chinnaswamy Stadium        M Erasmus   VA Kulkarni   \n",
       "416                       Sheikh Zayed Stadium        Aleem Dar  AK Chaudhary   \n",
       "476               Sardar Patel Stadium, Motera        M Erasmus        S Ravi   \n",
       "486                      M Chinnaswamy Stadium        JD Cloete     PG Pathak   \n",
       "511                      M Chinnaswamy Stadium  HDPK Dharmasena  K Srinivasan   \n",
       "610     Saurashtra Cricket Association Stadium     AK Chaudhary   CB Gaffaney   \n",
       "705                    Feroz Shah Kotla Ground    Anil Dandekar   Nitin Menon   \n",
       "744                     M. Chinnaswamy Stadium      Nigel Llong  Ulhas Gandhe   \n",
       "746                           Wankhede Stadium           S Ravi      O Nandan   \n",
       "\n",
       "            umpire3  \n",
       "66              NaN  \n",
       "130             NaN  \n",
       "241             NaN  \n",
       "328             NaN  \n",
       "341             NaN  \n",
       "416             NaN  \n",
       "476             NaN  \n",
       "486             NaN  \n",
       "511             NaN  \n",
       "610             NaN  \n",
       "705  Marais Erasmus  \n",
       "744  Anil Chaudhary  \n",
       "746   Nanda Kishore  "
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches[matches.result != 'normal']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "zwxUTgyTj-ld"
   },
   "source": [
    " There were ***`13 matches`*** with the result as ***`a tie(9) or no result(4)`***."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "rCp3Nayjj-ld"
   },
   "source": [
    "##**The Number of matches played in each venue?**\n",
    "We can find number of matches played in each venue by again using ***`value_counts()`***."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 745
    },
    "executionInfo": {
     "elapsed": 10283,
     "status": "ok",
     "timestamp": 1601651966317,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "AdYmTlIIj-le",
    "outputId": "77953539-372e-4024-f26a-352562a8fa4b"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Eden Gardens                                            77\n",
       "M Chinnaswamy Stadium                                   73\n",
       "Wankhede Stadium                                        73\n",
       "Feroz Shah Kotla                                        67\n",
       "Rajiv Gandhi International Stadium, Uppal               56\n",
       "MA Chidambaram Stadium, Chepauk                         49\n",
       "Sawai Mansingh Stadium                                  47\n",
       "Punjab Cricket Association Stadium, Mohali              35\n",
       "Maharashtra Cricket Association Stadium                 21\n",
       "Dr DY Patil Sports Academy                              17\n",
       "Subrata Roy Sahara Stadium                              17\n",
       "Kingsmead                                               15\n",
       "Punjab Cricket Association IS Bindra Stadium, Mohali    14\n",
       "Sardar Patel Stadium, Motera                            12\n",
       "SuperSport Park                                         12\n",
       "Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Stadium     11\n",
       "Brabourne Stadium                                       11\n",
       "Saurashtra Cricket Association Stadium                  10\n",
       "Holkar Cricket Stadium                                   9\n",
       "Himachal Pradesh Cricket Association Stadium             9\n",
       "New Wanderers Stadium                                    8\n",
       "M. A. Chidambaram Stadium                                8\n",
       "Rajiv Gandhi Intl. Cricket Stadium                       8\n",
       "JSCA International Stadium Complex                       7\n",
       "IS Bindra Stadium                                        7\n",
       "Dubai International Cricket Stadium                      7\n",
       "St George's Park                                         7\n",
       "Barabati Stadium                                         7\n",
       "Newlands                                                 7\n",
       "M. Chinnaswamy Stadium                                   7\n",
       "Feroz Shah Kotla Ground                                  7\n",
       "Sheikh Zayed Stadium                                     7\n",
       "Sharjah Cricket Stadium                                  6\n",
       "Shaheed Veer Narayan Singh International Stadium         6\n",
       "Nehru Stadium                                            5\n",
       "Green Park                                               4\n",
       "Vidarbha Cricket Association Stadium, Jamtha             3\n",
       "Buffalo Park                                             3\n",
       "De Beers Diamond Oval                                    3\n",
       "ACA-VDCA Stadium                                         2\n",
       "OUTsurance Oval                                          2\n",
       "Name: venue, dtype: int64"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches['venue'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "75wWcjKqj-lf"
   },
   "source": [
    "***`Eden Gardens `*** has hosted the most no of matches i.e ***`77`*** followed by ***`Wankhede Stadium & M Chinnaswamy Stadium (73).`***\n",
    "\n",
    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)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 260
    },
    "executionInfo": {
     "elapsed": 10268,
     "status": "ok",
     "timestamp": 1601651966319,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "9YY0-_rWj-lg",
    "outputId": "4aa66421-5c5a-482b-8773-f708c9050ceb"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Mumbai Indians                 109\n",
       "Chennai Super Kings            100\n",
       "Kolkata Knight Riders           92\n",
       "Royal Challengers Bangalore     84\n",
       "Kings XI Punjab                 82\n",
       "Delhi Capitals                  77\n",
       "Rajasthan Royals                75\n",
       "Sunrisers Hyderabad             58\n",
       "Deccan Chargers                 29\n",
       "Rising Pune Supergiant          15\n",
       "Gujarat Lions                   13\n",
       "Pune Warriors                   12\n",
       "Kochi Tuskers Kerala             6\n",
       "Name: winner, dtype: int64"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches['winner'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "6bLAEWYOj-li"
   },
   "source": [
    "***`Mumbai Indians`*** has won most no of matches- **`109`**\n",
    "\n",
    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)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "YPH6ermKj-li"
   },
   "source": [
    "##**Which Team had won by maximum runs?**\n",
    "\n",
    "To answer this question, we can divide the question logically – first we need to find maximum runs, then we can find the row (winning team) with this maximum runs – which would indeed be the team won by maximum runs. I’d like to emphasis here that it’s always important to divide your problem into logical sub-problems or modules and then build Python expressions/codes for those sub-modules finally adding them up to required code that will result in the solution.\n",
    "\n",
    "***`idxmax()`*** will return the id of the maximumth value which in turn is fed into ***`iloc[]`*** that takes an index value and returns the row.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 347
    },
    "executionInfo": {
     "elapsed": 10251,
     "status": "ok",
     "timestamp": 1601651966322,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "AJRW2jv4j-lj",
    "outputId": "b65ca860-0f25-4764-c4b5-876d55a955d1"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                              621\n",
       "season                         2017\n",
       "city                          Delhi\n",
       "date                       06-05-17\n",
       "team1                Mumbai Indians\n",
       "team2                Delhi Capitals\n",
       "toss_winner          Delhi Capitals\n",
       "toss_decision                 field\n",
       "result                       normal\n",
       "dl_applied                        0\n",
       "winner               Mumbai Indians\n",
       "win_by_runs                     146\n",
       "win_by_wickets                    0\n",
       "player_of_match         LMP Simmons\n",
       "venue              Feroz Shah Kotla\n",
       "umpire1                 Nitin Menon\n",
       "umpire2                   CK Nandan\n",
       "umpire3                         NaN\n",
       "Name: 620, dtype: object"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches.iloc[matches['win_by_runs'].idxmax()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "4SpkhNHfj-ll"
   },
   "source": [
    "If we’re interested only in the winning team in that row, then that could be retrieved as below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 35
    },
    "executionInfo": {
     "elapsed": 10232,
     "status": "ok",
     "timestamp": 1601651966324,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "GNGGfMQnj-ll",
    "outputId": "08c01cec-2953-45ce-9f56-2634d38ecc25"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Mumbai Indians'"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches.iloc[matches['win_by_runs'].idxmax()]['winner']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "5r4_VwvXj-ln"
   },
   "source": [
    "***`Mumbai Indians`*** has the record of winning by maximum runs-**`146`**\n",
    "\n",
    "![](data:image/png;base64,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)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "nliBo1lyj-ln"
   },
   "source": [
    "##**Which Team had won by (closest margin) minimum runs?**\n",
    "\n",
    "To know the team that was won by the closest margin, we have to do the opposite of what we’ve done in the above steps. But there’s a caveat in that. In Cricket, if the team that’s batting second wins the match (by chasing), it’ll be said “Team second won by x number of wickets” and if the team that’s bowling second (batted first) wins the match (by defending their score), it’ll be said “Team first won by x number of runs”. Hence, the minimum win by runs will always be 0 and the minimum win by wickets will also always be 0 in a tournament since sometimes chasing team or sometimes the team that batted first could win. To overcome this caveat, we just have to apply a simple workaround as you can see below.\n",
    "\n",
    "Instead of just getting the minimum score (which always would be 0), we have subsetted the data that has win_by_runs greater than or equal to 1 (there by eliminating the zero-issue)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 35
    },
    "executionInfo": {
     "elapsed": 10217,
     "status": "ok",
     "timestamp": 1601651966329,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "5DokcPUyj-lo",
    "outputId": "9e7c1a8c-fb85-4162-c49c-d93cfc7d906e"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Kings XI Punjab'"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches.iloc[matches[matches['win_by_runs'].ge(1)].win_by_runs.idxmin()]['winner']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "3KoJ6cXJj-lp"
   },
   "source": [
    "Even though other teams have won by `1 run` margin, but ***`Kings XI Punjab`*** had done this for the first time. So, we get the result as ***`Kings XI Punjab`***.\n",
    "\n",
    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)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "executionInfo": {
     "elapsed": 10203,
     "status": "ok",
     "timestamp": 1601651966331,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "cQ4ArvE2j-lq"
   },
   "outputs": [],
   "source": [
    "import jovian"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 87
    },
    "executionInfo": {
     "elapsed": 12788,
     "status": "ok",
     "timestamp": 1601651968929,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "GG5WNQ6zj-ls",
    "outputId": "59de6f03-1674-4c18-b2c2-314a68dd9f95"
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "window.require && require([\"base/js/namespace\"],function(Jupyter){Jupyter.notebook.save_checkpoint()})"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[jovian] Attempting to save notebook..\u001b[0m\n",
      "[jovian] Updating notebook \"uayashu145/ipl-analysis\" on https://jovian.ml/\u001b[0m\n",
      "[jovian] Uploading notebook..\u001b[0m\n",
      "[jovian] Capturing environment..\u001b[0m\n",
      "[jovian] Committed successfully! https://jovian.ml/uayashu145/ipl-analysis\u001b[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'https://jovian.ml/uayashu145/ipl-analysis'"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jovian.commit(project=project_name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "DK56bPQsj-lu"
   },
   "source": [
    "##**Which is the most successful IPL Team?**\n",
    "\n",
    "The most successful IPL team is the team that has won most number of times which also means, answer it to this is to count the number of instances in each winning team."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 523
    },
    "executionInfo": {
     "elapsed": 12769,
     "status": "ok",
     "timestamp": 1601651968932,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "PJkKHP-2j-lv",
    "outputId": "2ee04d40-aac4-45a8-9e0f-0fb67a4d8b73"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Teams')"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "data = matches.winner.value_counts()\n",
    "sns.barplot(y = data.index, x = data, orient='h');\n",
    "plt.ylabel('Teams')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "xUNWCv95j-lw"
   },
   "source": [
    "***`Mumbai Indians`*** is the most successful team in the IPL.\n",
    "\n",
    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)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "5xRl5qWhj-lx"
   },
   "source": [
    "## **Who is the  winner of most Man of the Match award amongst all the seasons?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 225
    },
    "executionInfo": {
     "elapsed": 12749,
     "status": "ok",
     "timestamp": 1601651968934,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "sWFyiMxej-lx",
    "outputId": "22f4073f-b0f9-4a3e-9904-ce9d8bdba090"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CH Gayle          21\n",
       "AB de Villiers    20\n",
       "RG Sharma         17\n",
       "MS Dhoni          17\n",
       "DA Warner         17\n",
       "                  ..\n",
       "Kuldeep Yadav      1\n",
       "SA Asnodkar        1\n",
       "A Singh            1\n",
       "TM Dilshan         1\n",
       "YS Chahal          1\n",
       "Name: player_of_match, Length: 226, dtype: int64"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matches['player_of_match'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 583
    },
    "executionInfo": {
     "elapsed": 13729,
     "status": "ok",
     "timestamp": 1601651969933,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "4HEDlnpWj-lz",
    "outputId": "5125f4ed-0961-4d7a-8f06-591f1db46d35"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mom=matches['player_of_match'].value_counts().head(10)\n",
    "sns.barplot(y = mom, x = mom.index, orient='v');\n",
    "plt.xticks(rotation=70);\n",
    "plt.xlabel('Player');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "4p5Gy6oKj-l0"
   },
   "source": [
    "***`Chris Gayle`*** Tops the List with ***`21 MOMs`*** amongst all the players from the above data.\n",
    "\n",
    "![](data:image/jpeg;base64,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)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "rtEQGxv8j-l1"
   },
   "source": [
    "##**Most Toss wins**\n",
    "Let's see which team has won most no of tosses."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 693
    },
    "executionInfo": {
     "elapsed": 13714,
     "status": "ok",
     "timestamp": 1601651969936,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "_YQNo8Uij-l1",
    "outputId": "071c08de-7015-4f63-b4e8-5cfc8cd98ef3"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#tm=matches[matches.toss_winner==matches.winner]\n",
    "t=matches['toss_winner'].value_counts()\n",
    "plt.plot(t,\"bo-\")\n",
    "plt.xlabel('Teams')\n",
    "plt.ylabel('Toss_wins')\n",
    "plt.xticks(rotation=90);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "4iDy2s9gj-l3"
   },
   "source": [
    "Here, too ***`Mumbai Indians`*** stands above all.\n",
    "\n",
    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)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ldd3zimaj-l3"
   },
   "source": [
    "## **Toss win - Match win?**\n",
    "Let's see the impact of winning toss on the match result\n",
    "\n",
    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WCaSdashGxVl0Fs/Ovm8tu+rLnSTh+9nT+G9J6TQeTIcYumZHAhAYBQHRpAzAnGnrS5udCDVBoVRhS0QdsrtnOmrfitg8blu9p0szgS5DA9OoqggkKlmMxmAZjyihIAxsM9KwNCC+u9JWbBV1OlgECa1IHXC0jxAtzMt8WllyoHdq4kvgTkSyRMA2I3wUf5Y8fnVTxHSzAgknSoOU90irVhoVe4Gp92XJXSoUOMeRBOKjhuQC55UrRH3miiOF+vSl70YHTJxuR8RpyxuVjiQGYgOMsiS+J81+lb1q6FZbRyK6hweUrBdDAAv5eNfVpxoRIfarOQSo0W7hl9M43qvS72I58cYHQ91xjyVSc/hXTfIFX/FBQnujm8vc+NZ/TXsO/knfiCSb89UGe+GR8fLFF46yLj7ZFGp2KJCUHpvVfz0AX2uosysELI41fxNTtxel1bvRuq/GUA1fJgd6OHHpBZSTxhSVDBgpxqXpTlvLlDldRQdKSl8dtjUnD37xGxyPH09KrtWARu3dOGKIcEbkIG9a9O/ZRxMrc8snuzoV/3Luv8AWsD9vKeyxG0T7yIiBDnG2TVj2W4homtZQNIWSJtOrOwO9NSaknQn0fo360VHz186K7+ZnR5L2lfKQdc6mc43LeNLyXNwWjJkdUGiMgN3XXwBFd7Tq/JtCh0uu4P3tqm4txKCXlaYDE0Zi0zB8c1gO8HTod68aKfGzRvZVlM62IOdTfjVHczmOSOTroLawcgsM1pLfePcEhtWB9apOJ2+3z1EGmwRo5XEkeUIUMu2N9yKxcXD5EmCPgqrc138GQb5p3gUsscgUAtGx9oNOyA/F6VpL+wDIy6sBhsw+Gsr4Nr3LMZeXGt2OMhjnbyHSrDhcaNExaZ4wjYZVQOGHnVXd2hjYqd9O1McOuQiS94KWPczvvWkl9qoEWwsou8XlnkYHu8rQCynzGOtLC2i5oDSTvGyMyKsvJdSMZ1Y61WWXEdHMZ5SHYroz1/8Fde/gaVXV2aRYyDGqO5mzvt6jxqownY7H41gS4WP7PIEaN3KSyk6wOjhqYjtIg0kjQiSN1VYkLnCsT/TFUz8VtkYlhciYagyyjCRI3gi4z+NSRSXP2dWNlcctWWRJgmFdFJ76g+lVLBPTQuSHo1iH2kfZoWaMuyMUJOCNQHWjik3staQ2yhdDMAih1OsYK+ePGlnkm1RsbKVRdhY+80YDEodOnfxFM29tNnElhFKsPRJpkXTqHUjODU8Wmm3/oDglEmCyw8sr341hQNv4jArHA7nHutq0Z648Ksru5mhZEKqjRnUrBg4ZDvp8jSVzMruxEYjDHOheik1pjTjdsTJftrQrA6FxIY2RGVygUq/iPHY01ZcRaS4hJxjTgAKBuR3t/HeufZkKRGXUI40LSSIwDIC4GBnqTUz2sYu0MOhYmVTHEHy6bdX9TVacX+xHsf7NJMpcjwVoyB89X9qg7Wvq4laIceztZHHzeXT/wDSvv8AZeDpuj4Ew4+muo+0+3FIc7hrNQo/iWdz/WuiH/nRD/Ikv0jaVUfWoYRKDGuv138ahv8AhXLccmQTMdXcV++m3lUnFISZCQjO2mLSEznPzFLuvLdS8BLAZZZGI/6q59VtCGDdyAYm5pBKry7iHWnz142p634cEy8alFG8kI74x5xn+lWSKHzy52Ut8BcTqR5aDUWl4j3VCk6jyge5L56D8J9KqaVXdjRmu1mlowVYMv8ALn6GsLLFn18gK3HavRIrSxHSyaedFsmn+YedZO46A/erBKhlLcr69OopCd+tWd4u/Q/9NVc6EnYEnwA60xoqLk+NISdelXQXHMbTqKDOl1yMeNIcXjAZSowkoVlX7ua6cckJoSkUf2r4dR45B8xXw7fP0NfP5V0UQyXlAevrTNkCzBVUuzHuqvXNKwIzlEXvMxwo1fnWktk5XsLdS0zD20w3Prv4LUT0qbHEJOHxx73EpLeEEO7f7mPSoLfiEetVitUiBOOY7mRvx6VZQcHjwSwa6b4tL8iJT6yn3qUEsKuoX7MpHQRRTXLf8x2rFbTNGdSziaQmWXlq2oEKhyWxsM1JYQMnUFQGbRqxnHhVfdtI8gQKXClmRQmC3rTfCs6DnOeY5367VLT49geu/wD5RRWW/wCEtRWQGq7S8NxBFkbRyyxt8g7Bf0qvk7PObdZIzFKX7yLr0M2k9VB6natzx6z1w3Sgbg81B9M/qGrIa1jCBsSADPd+AHxqpx4yaZFlTZ2xKMc6lR2/Okby11Zx1z+VXXDApeUKciQMQ3TUV9PlRHbZf5HG3lXNkdKyomXv7RkXALLr0+7WisgeRFqAB0rkUxxO3UEd8AIMtnotZ/tBxBziKMlFKq8kvTu+nzrFXKkWV/G7qJtaqFdg37zTugHrSfBbphzo9KYcajlFcqendJ6UpK3gNlx1HVvnX1YLL3jEgdtlOTgLn61vxpUCZ9dneJyIJ0SQgHSzhFBIOKVsZy1683P18iNn+0L3NZI0jPkd96+p7m83VbAAoMIyQhNIPe/3VFc3F65WB44VLROVOYo10YywDDx3+ddcYPdefkltaGeMxLI1rOzrPy5UWVw2tZUJ7vzw21McUlluLuMy3c0KGFnWSNTINYONBXOAMVSxWN0vKgzEIpUccwZkj3BbDtjY5qWzsOIBcfaVgjdcuzXCHu56FeufSqUeNfctWL9Dk1i7QpGgeZoZoiMKcsqltT49B1pr/NtzlRqiUZPRu+RVVb8NmYzk37ZWTQ0ixSd5WTVlcbZP3a+rHhrEywyyyaYNJjzFtpY9eu30zWcoKty/5jX8EvGbQrpfktBHJqESu2fd97HpVXGeg89gPWr08Nj2QzSkZbQmgDZh3TufGq7h1t7YqTkRM2o+Gx60oyXFlMZveHyyvEkcLTFUVNKLkhiMn5bVzgcTc99XvIGVvHde7ivqPi5DqyIiAM5lkXOuUHoGbPu/wineCjPMfliMu2yqxIz6ZpSbjCiT2f8AZ1b6bYvjeVm/BSRSfblNN3wuTwcXUJ+ZCsv6GtN2ftOVb28eMFY11fM7t+Zqs7d2uq3WTGTaSxTjHkpw3/Sa71CsKXwZ+SMwM0kOmZoy8eQQ3vFDuPwp69yVyJVLR5KKVQsCOtVsMmYoZMleQ6sSveOlvMVcw8Nj1K+MyYyZMY16vMVzwi2mkB9QWqSJGWRWJVTrA0HPnkVDdxlQQ5MkRPv/ABReRPmBTdkpXUhOdJypHkanlGx2yPEeYNdHBShdbFZ5zx+LlzLIQWYezmx7sqN0c+tZe47sk0exCFipH3T0rYdtYCmgYGCGEbfwn4T9awvGLnMkRydTJpYdNxtXm7Umi61YveKBnxJ2peVAJLdkGVk2Kjqp3Bpq4bA6Akea4NL29zlJk3wntYmVNZUjYgVTXkF2I20ZDSMcaAWSVPHSerfSq+/4cwSNR3gpcxSbDUnUbmtJZyRyo7AfvFyVZt1ddiG8qoZZwi8vZwGZsFsohPl504SadFVZnpYHAUkbN0P/AHpdz+XWra6DMSS5Ynw6D8KRNtuN9z0HrXXGae2TxLDg0JVC4GqSY6Iu97o8Wq6iVIYz1Oo98/FcsfDP3a5ZWuMeSLoH8O3eqLiN+IcN70pGIs7iIeYHnWDm5yaRSVEfEoSwzc3Atk/y7dFLuo8gudvrSfDmg1kxRTNoDHVJKg+ukL/WqqaVnJZm1Ftyx+Krng1seWxxqaVlVBqx3R138K1aqNAfcXGGQjlSupwwlJ0jWD4LVhw2HXyFUNmZtg25y5AqqlsISkmgTPMH04GgooJx18a23YLh/NvrZAMpb6Wbw9wZ/Ws3GLaSEewf8GWirbPpRXV9AmyKdeh8CNLfI1nLCLlPLGEjzGzFXdO8ysMrpPp0rUEVUcat/dlAOY+7IB1ZCd/w60s+N/lElGb47AoZJk0KU3kWNAhZQe9qUfOmZLQZV1IKuqsuOjA709bcBh5iyBpJHZW1OrLoZW8CDSpgNsxiZj9mlObaY/8A87N1hf8AhPhXl58cq5M0izLdobfIlGdKyFWfHViP6Vl7licA90INMa9QorcccixqzgEea7bVieJjdvA4xt0rOHQWZ+7GM/D5gVFBfFNWMd4bnTnavu/HeO53Gw6ikHYeFdHFNbRSGJeLSZB1kgdFxtjFVt5xNmZGOAyMzKdI2J2r6elpYvTI8a6McYp9CdklxxOU4zKdgw222NfMnFZGVAZG7u2dXvetKmPrtXyFPyFbqMK6J2MJdyZPtH364cjwp9LhjjLFiuwJbJUUlBD02pj9KxnT0kVFE0k3qD61Z2saRoNcqwtMNTs6PJpUfDpG5JqHhFjnErrlc+wTTkzN6egqS/4e7c2RpUiaFcyRSv3kPgq4zmsmldFMmmjhMERiiCys7azzd2B6aY/hFa/sNwjm3FvHjKxaZJD6L/c1ieCQFsSN0UaY817p+zrg3Jg5rLiS5wwB6qnwj69aUIOeRL2IbpGwqC6hDo6N7rqyN8mGKnrhr1zIw3ZQkCa2k2aEvBJ8h7rfUFa0djK7RlAdEsR0FmXI26H8KoO1lsYLiK7XIjl0Q3WOikfu5fxODVs10RonA7vuXK+ng/0rgr6c2V4HoA4VWk3dMhivR186fUg49elJ3V2VUMkTTAgEaD4V2KUKFOCqNuNWxTPnXSml0xFX2xs9du5xkxnUK8g4/GBJD1AIYmvbONN7Nlzs6OD+FeKcQt+dcJFnBA2Py9K8/Ml9XRS6E5Ze7gEkHYE/D6VDw+7SMy62ZSdJj0rnXjbSfxpiThTZ2lYYODmHdRn9KUueCv38zYxufYnO/wBam4t7Y0mU045esZwz+9htlB8KVE//AKqwHAnPM9tHhCoXKHx8/KlpeDyAZ50bY97DOB+ON62+33Hv2FmnrtmwMkY8ytSvwGTpzYfTL4671Clk8MsOsKNTd0rKr6vwquMWnTHbNT9oADbABRk5+KsZf3Bd2Y536Z8qu+MXGmNsfGcZrLoWdgoBZmOFX7xNL02Ok2TJjlnAZXVBsW3ZvugdTVxxS0klEaQJrVNQ0hsHbx32xXzyvs0The9OQOcw6J6VX2/EXkMepjLIraY4guEIPyrT8na6QfA9waJg7M66BbjBUNjU5wF6V7R+x3hOmOa5YbzHlRn+FTlj9TXmfCeFmWWG1hG7P3zqyFY+8QfQV+ieFWKwRRQoMJCoRfpRhXObk10J6VDeKKKK7CLO1wiu0UwKJPYSaDkQzEiGTrynP+UfQ+H4VXrFdNcFZGjlgmgy0TROgXS+D/uOutLeQB0ZSNQYYIrKNxtrM8ucPNb9I7n3mi/gm/o1eXnioSqT0aLfQjxnh7KGwDcW6nc7mS0A8NPxJ61iOIw+OQwPuuOv/qtj2iNzHNBNbzh0QtHNpQ/4cP3laRc94eFU/FzbTDUx+wTgqJJkiaSCUn70ecrXJSQzz7iKHGfHLZFU7nw/OtRxW0dCO/HMpDYlgdZFb/b1Ws1drjw0nOCp2NdOPaEQBqkpbV61x5ceORWjhfRSYw4HlXxj0qCN2bAVGck4ARC+o/QVcxdn58B7h4uHRENh7l9Dtj7sI7x/CrUGuyrRWl/XAFXVlwtUCS3IJ1aeRYL+8uyfvY3SP8zUNtcwoWFqFmmXSRfXeIwpH+jD0GP4t6r+LwSZM/MeZHK5uGcFmc9R50+O6smyz4vBcyZcxFVjXL24UJ9mHgvXpjpS/AleUOqgJbgabklfeB8P5vKmezvDHu1uCSLW0AXm3khPdZTsif6jH7tbDs9wE3kiQ28Rt7SDTrc74/jY/FIayk2vsS2HzY92D7OfaJVZk021vp1DwYj3Y/717IB9MdBSnC+HR28SRRppRBgDxJ8z6mna7MGJY415MpOztcrtFbiFr61SWN43XUkisjj0NZHg9y9vK1nMchB7FyuRcxefzHQ1tqqO0HBRcovfMU0Lcy3nXrE4/VT4isskOS0NEcU3IZVIBtpP3cg/yifgb08qd4hd8tWPKeXusdKJqyBWe4NxZnaS1nh0TIGE0Jb96v8Aqx+aGi4u5LEJ3GnshqBK5eS3z0HyFc6yOKcWM+GczZltpTNCupZLVshoj0OkHpXlUrObqXS7QMX5YbYMuTp8a9Rsp/tGGtJhhS2dTjWhOfeTyzWE4/xJJZJIJ7DVdxNpaa3XQzMfHR8XXwrmlV2hraEb/gBSRx9s0suo4Dx610kDUd/Wqe54Y/fA4mX07t0fp/uqLiPClVmUymN/GOXr8tVV8/CZPCIuPONtf6U4K/P+FWWH/C5wp/8A2LBWGtvY6z5dc0tLwyZdI+3Bw5xhoiOm+etVEtvKP8uYY2AKSVJZxXBJ0wyucYIdHxW3GVeP6CyzksbnOTeQk+Hccn9Ko7ydxIod1co2QygjV+NWB4VdEjKJAB8ckohC58etfCWtvzAJJ3vZT0ii9mjEech6irivev0JjXFbGSflLHGW1amLHZUBA3Y1A/LtY35Lc+XurLc6e5Fn4UqPjck4G2pEPvQxNrVMeDEVyC+djAiyCQsv7tYY8K3TB2pRTUV7D8kMXFHKodUcZV8MI077+u/WruO2MbGV2Dzzfu+4AYlPxMPOobbh6wMXkCPcncRhQEh9Tjx9K9L/AGc9i2lZbu6UlQQ0Mbrgyt99h5DwqWub4w/YN0X37MOy32eP7RKuJ5x3VPWJP7mt8KAK7XZCKiqRkFFFFWAUUUUAcqp4xwsSg4xkjBU9HHlVvXKzyYo5I1JDTo8o4jw+eF3aFmGRpe3kdwGH8J/oaqbjikPImSWJre51IscybaWG6ylT5eODXsl3ZpIMOgYeB8RWO7Qdiy4OgLOv+m+FP0NeXP0k8buK5I0Ukzx6O25kgVpVJaTvStLoVwSPiqHjB5OpEmkkdXdHDqjooHTDeO1aHjHZYxnGiSDBXCsMgaTnbNZ7iPDJi7uHQl2yc5T+9KEldN/2MXsIJJQjabUK7OpknhwO6PhPxUlbcVPMVBDbIGbQJFtde+cDAz41YfZ7wxGJpFaNGDwRiZAIn3GaVi4NeCQSh4Y5FKssnOjGk+flXZGUd20IY4pxS6ijTF4VLFhKtsghWI+ALAZ1Urw5lISVkDzStLFzHlMjtt75U539adk4G8mOdxCCDXnmlGkuGlJOe8irineH8H4bFgmO54jKOmphZx59FUlqlzio1e/gdMy9lDI0+i1ja8YbIFhYnfbdfDFai37ORRLGb9xJLDnRw+3cZIY5xPMNl+Q3rY8K4JxGdRHb2ycJtW6rGn2ZXH8Te/JWz7N/s+trfS8n+KmG+p1wqn0T+9Uuc64qvkm0u2ZTgvZy64gYWlAtLKEYghROWqL92JP/ALGvUuF8Oit41jiQRovQDqT5nzNNgfhX1W+LCsa+SG7O0UUVsIKKKKACuV2uUAVHHuCJcBDqaCeE6re5j9+E/wBVPip61mJOIyW7cu7KwSSdxJm3trv6/A5+6a31L3lpHKjRyIssbjDxuuQw+VZZMSmhqR4/fw6JJWtzyZHGlkXowP3Gqv4dxApcF7hCMxvHzoYsurEYV2XqfmK13Hf2dSLl7GUBRv8AYZzlPlHJ1T61jOKPJb925gltT09smtGP8Mw2NedLBOD6s0TTKuzng1XHNlMiRRuY1kXQ7u/dGnVv1xUFnYxky5AURQc4MJSSxJ2zp6U5KUcdFceTYkH96SFtEurSkkZYaWMNwY9Q+RFK15GJwO7Ryt9rmQrIqR6XfSwPqajuAdMubyclJEUe2crpYZ86nksoTn2lwFY5KlkcbUueHW+G79wwbqvcQVqpq+wIDbQ6bhmIYZUIzOzlcjO2aQjlGYe5zjEcCMLkuPCreKC2XOm1Z/IyzZH4Cpo7mTIEYWLVsscEQy39atTX8ioSi4S+XZ5BYo5Y8sN38eQWnrJQuI7aIqz7cw9+WUn9K1HZ/wDZxeXBDSIbWM7tJNnW38qdfxr1bsz2OtbIAxprlx3p5Blj8vKrWOc+9IltIyHYj9m+Ck94uTsyWrb7+cn9q9RUbAAYA2AG1fQorphBQVIhuztFFFWAUUUUAFFFFABRRRQAUUUUARyxKwwyhx5MAw/CqHinZezZWJtUBz1UtH+hFFFY5opraKieX9oOGxRk6I9P+5j+pqgs4Fbqud/MiiivJa+828HonZTspZyaS9sHPrJL+mqt7w/gttDjlW0UXqsag/j1oor0sMVXRlJlhRRRXUQFFFFABRRRQAUUUUAFFFFABRRRQAVHNErAqyh1YYKsAwPzFFFAGB7bdjrBYzKlmkMhY5eJpIPyUivC5LyQTMgc6R0BAb8zRRWOSK9ikNGU+f5CobiYjofyBoorBJewzX/s84RDcugnj5oz01un6EV7hwvgNrbgcm1ihP3lQav+br+dFFdEEiWWQrtFFaiCiiigAooooAKKKKAP/9k=)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 834
    },
    "executionInfo": {
     "elapsed": 14758,
     "status": "ok",
     "timestamp": 1601651971001,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "JWpEjAQij-l3",
    "outputId": "fb512bfd-4655-4659-ed18-7aefaaaed4e3"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>season</th>\n",
       "      <th>city</th>\n",
       "      <th>date</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>result</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>venue</th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "      <th>umpire3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2008</td>\n",
       "      <td>Chandigarh</td>\n",
       "      <td>19-04-08</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>33</td>\n",
       "      <td>0</td>\n",
       "      <td>MEK Hussey</td>\n",
       "      <td>Punjab Cricket Association Stadium, Mohali</td>\n",
       "      <td>MR Benson</td>\n",
       "      <td>SL Shastri</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>2008</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>24-04-08</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>YK Pathan</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>Asad Rauf</td>\n",
       "      <td>MR Benson</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>2008</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>26-04-08</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>SR Watson</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>MR Benson</td>\n",
       "      <td>IL Howell</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>2008</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>27-04-08</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>AC Gilchrist</td>\n",
       "      <td>Dr DY Patil Sports Academy</td>\n",
       "      <td>Asad Rauf</td>\n",
       "      <td>SL Shastri</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>2008</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>28-04-08</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>MS Dhoni</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>BR Doctrove</td>\n",
       "      <td>RB Tiffin</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>750</th>\n",
       "      <td>751</td>\n",
       "      <td>2019</td>\n",
       "      <td>Mohali</td>\n",
       "      <td>05-05-19</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>KL Rahul</td>\n",
       "      <td>IS Bindra Stadium</td>\n",
       "      <td>KN Ananthapadmanabhan</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>Bruce Oxenford</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>751</th>\n",
       "      <td>752</td>\n",
       "      <td>2019</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>05-05-19</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>HH Pandya</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>Nanda Kishore</td>\n",
       "      <td>O Nandan</td>\n",
       "      <td>S Ravi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>753</th>\n",
       "      <td>754</td>\n",
       "      <td>2019</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>08-05-19</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>RR Pant</td>\n",
       "      <td>ACA-VDCA Stadium</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>754</th>\n",
       "      <td>755</td>\n",
       "      <td>2019</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>10-05-19</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>F du Plessis</td>\n",
       "      <td>ACA-VDCA Stadium</td>\n",
       "      <td>Sundaram Ravi</td>\n",
       "      <td>Bruce Oxenford</td>\n",
       "      <td>Chettithody Shamshuddin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>755</th>\n",
       "      <td>756</td>\n",
       "      <td>2019</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>12-05-19</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>JJ Bumrah</td>\n",
       "      <td>Rajiv Gandhi Intl. Cricket Stadium</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>Ian Gould</td>\n",
       "      <td>Nigel Llong</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>393 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      id  season           city      date                        team1  \\\n",
       "1      2    2008     Chandigarh  19-04-08          Chennai Super Kings   \n",
       "8      9    2008      Hyderabad  24-04-08              Deccan Chargers   \n",
       "10    11    2008      Bangalore  26-04-08  Royal Challengers Bangalore   \n",
       "12    13    2008         Mumbai  27-04-08               Mumbai Indians   \n",
       "14    15    2008      Bangalore  28-04-08          Chennai Super Kings   \n",
       "..   ...     ...            ...       ...                          ...   \n",
       "750  751    2019         Mohali  05-05-19          Chennai Super Kings   \n",
       "751  752    2019         Mumbai  05-05-19        Kolkata Knight Riders   \n",
       "753  754    2019  Visakhapatnam  08-05-19          Sunrisers Hyderabad   \n",
       "754  755    2019  Visakhapatnam  10-05-19               Delhi Capitals   \n",
       "755  756    2019      Hyderabad  12-05-19               Mumbai Indians   \n",
       "\n",
       "                           team2          toss_winner toss_decision  result  \\\n",
       "1                Kings XI Punjab  Chennai Super Kings           bat  normal   \n",
       "8               Rajasthan Royals     Rajasthan Royals         field  normal   \n",
       "10              Rajasthan Royals     Rajasthan Royals         field  normal   \n",
       "12               Deccan Chargers      Deccan Chargers         field  normal   \n",
       "14   Royal Challengers Bangalore  Chennai Super Kings           bat  normal   \n",
       "..                           ...                  ...           ...     ...   \n",
       "750              Kings XI Punjab      Kings XI Punjab         field  normal   \n",
       "751               Mumbai Indians       Mumbai Indians         field  normal   \n",
       "753               Delhi Capitals       Delhi Capitals         field  normal   \n",
       "754          Chennai Super Kings  Chennai Super Kings         field  normal   \n",
       "755          Chennai Super Kings       Mumbai Indians           bat  normal   \n",
       "\n",
       "     dl_applied               winner  win_by_runs  win_by_wickets  \\\n",
       "1             0  Chennai Super Kings           33               0   \n",
       "8             0     Rajasthan Royals            0               3   \n",
       "10            0     Rajasthan Royals            0               7   \n",
       "12            0      Deccan Chargers            0              10   \n",
       "14            0  Chennai Super Kings           13               0   \n",
       "..          ...                  ...          ...             ...   \n",
       "750           0      Kings XI Punjab            0               6   \n",
       "751           0       Mumbai Indians            0               9   \n",
       "753           0       Delhi Capitals            0               2   \n",
       "754           0  Chennai Super Kings            0               6   \n",
       "755           0       Mumbai Indians            1               0   \n",
       "\n",
       "    player_of_match                                       venue  \\\n",
       "1        MEK Hussey  Punjab Cricket Association Stadium, Mohali   \n",
       "8         YK Pathan   Rajiv Gandhi International Stadium, Uppal   \n",
       "10        SR Watson                       M Chinnaswamy Stadium   \n",
       "12     AC Gilchrist                  Dr DY Patil Sports Academy   \n",
       "14         MS Dhoni                       M Chinnaswamy Stadium   \n",
       "..              ...                                         ...   \n",
       "750        KL Rahul                           IS Bindra Stadium   \n",
       "751       HH Pandya                            Wankhede Stadium   \n",
       "753         RR Pant                            ACA-VDCA Stadium   \n",
       "754    F du Plessis                            ACA-VDCA Stadium   \n",
       "755       JJ Bumrah          Rajiv Gandhi Intl. Cricket Stadium   \n",
       "\n",
       "                   umpire1         umpire2                  umpire3  \n",
       "1                MR Benson      SL Shastri                      NaN  \n",
       "8                Asad Rauf       MR Benson                      NaN  \n",
       "10               MR Benson       IL Howell                      NaN  \n",
       "12               Asad Rauf      SL Shastri                      NaN  \n",
       "14             BR Doctrove       RB Tiffin                      NaN  \n",
       "..                     ...             ...                      ...  \n",
       "750  KN Ananthapadmanabhan   C Shamshuddin           Bruce Oxenford  \n",
       "751          Nanda Kishore        O Nandan                   S Ravi  \n",
       "753                    NaN             NaN                      NaN  \n",
       "754          Sundaram Ravi  Bruce Oxenford  Chettithody Shamshuddin  \n",
       "755            Nitin Menon       Ian Gould              Nigel Llong  \n",
       "\n",
       "[393 rows x 18 columns]"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toss_winner = matches[matches['toss_winner']==matches['winner']]\n",
    "toss_winner"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 35
    },
    "executionInfo": {
     "elapsed": 14741,
     "status": "ok",
     "timestamp": 1601651971003,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "eAXFwJh1j-l5",
    "outputId": "ed05c000-aabd-4d62-e05f-844066d3505b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 393 matches in IPL played till now where toss winner is the winner of the match.\n"
     ]
    }
   ],
   "source": [
    "print('There are {} matches in IPL played till now where toss winner is the winner of the match.'.format(toss_winner.id.count()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 466
    },
    "executionInfo": {
     "elapsed": 14725,
     "status": "ok",
     "timestamp": 1601651971005,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "k2Ix2wJxj-l7",
    "outputId": "ac68c972-3ce2-4e6e-c076-ddccfcd995d6"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig1,ax1 = plt.subplots()\n",
    "labels = ['Toss won,match won','Toss won,match lost']\n",
    "sizes=[toss_winner.id.count(),(max_matches-toss_winner.id.count())]\n",
    "explode = (0.1, 0) \n",
    "ax1.pie(sizes, explode=explode, labels=labels, autopct='%1.1f%%',shadow=True, startangle=90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "sczD0WyLj-l9"
   },
   "source": [
    "It can be seen that impact of winning the toss has an almost ***`Equal amount`*** of impact on the result of match.\n",
    "So, it can be said that winning toss doesn't necessarily creates an impact on the result of match. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "U9_YXKdfj-l-"
   },
   "source": [
    "# **The MI VS CSK Battle!!!**\n",
    "Let's now see the stats related to MI vs CSK \n",
    "\n",
    "![](https://encrypted-tbn0.gstatic.com/images?q=tbn%3AANd9GcRA9ywYq1afSZ9yV5rE0tRLZcHra9mT4JfkTQ&usqp=CAU)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "executionInfo": {
     "elapsed": 14710,
     "status": "ok",
     "timestamp": 1601651971008,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "BJIAvCK3j-l-",
    "outputId": "ee1cf42d-0a8a-430a-8f32-c2f40385a02a"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>season</th>\n",
       "      <th>city</th>\n",
       "      <th>date</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>result</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>venue</th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "      <th>umpire3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>2008</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>23-04-08</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>ML Hayden</td>\n",
       "      <td>MA Chidambaram Stadium, Chepauk</td>\n",
       "      <td>DJ Harper</td>\n",
       "      <td>GA Pratapkumar</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>37</td>\n",
       "      <td>2008</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>14-05-08</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>ST Jayasuriya</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>BR Doctrove</td>\n",
       "      <td>AM Saheba</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>59</td>\n",
       "      <td>2009</td>\n",
       "      <td>Cape Town</td>\n",
       "      <td>18-04-09</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>SR Tendulkar</td>\n",
       "      <td>Newlands</td>\n",
       "      <td>BR Doctrove</td>\n",
       "      <td>K Hariharan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>103</td>\n",
       "      <td>2009</td>\n",
       "      <td>Port Elizabeth</td>\n",
       "      <td>16-05-09</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>ML Hayden</td>\n",
       "      <td>St George's Park</td>\n",
       "      <td>SK Tarapore</td>\n",
       "      <td>SJA Taufel</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>135</td>\n",
       "      <td>2010</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>25-03-10</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>SR Tendulkar</td>\n",
       "      <td>Brabourne Stadium</td>\n",
       "      <td>BF Bowden</td>\n",
       "      <td>AM Saheba</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>152</td>\n",
       "      <td>2010</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>06-04-10</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>24</td>\n",
       "      <td>0</td>\n",
       "      <td>SK Raina</td>\n",
       "      <td>MA Chidambaram Stadium, Chepauk</td>\n",
       "      <td>S Asnani</td>\n",
       "      <td>DJ Harper</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>175</td>\n",
       "      <td>2010</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>25-04-10</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>SK Raina</td>\n",
       "      <td>Dr DY Patil Sports Academy</td>\n",
       "      <td>RE Koertzen</td>\n",
       "      <td>SJA Taufel</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>198</td>\n",
       "      <td>2011</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>22-04-11</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>Harbhajan Singh</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>Asad Rauf</td>\n",
       "      <td>AM Saheba</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>249</td>\n",
       "      <td>2012</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>04-04-12</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>RE Levi</td>\n",
       "      <td>MA Chidambaram Stadium, Chepauk</td>\n",
       "      <td>JD Cloete</td>\n",
       "      <td>SJA Taufel</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>295</th>\n",
       "      <td>296</td>\n",
       "      <td>2012</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>06-05-12</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>DR Smith</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>Asad Rauf</td>\n",
       "      <td>S Asnani</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>319</th>\n",
       "      <td>320</td>\n",
       "      <td>2012</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>23-05-12</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>38</td>\n",
       "      <td>0</td>\n",
       "      <td>MS Dhoni</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>BF Bowden</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>326</th>\n",
       "      <td>327</td>\n",
       "      <td>2013</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>06-04-13</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>KA Pollard</td>\n",
       "      <td>MA Chidambaram Stadium, Chepauk</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>VA Kulkarni</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>370</th>\n",
       "      <td>371</td>\n",
       "      <td>2013</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>05-05-13</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>MG Johnson</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>CK Nandan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>394</th>\n",
       "      <td>395</td>\n",
       "      <td>2013</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>21-05-13</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>48</td>\n",
       "      <td>0</td>\n",
       "      <td>MEK Hussey</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>NJ Llong</td>\n",
       "      <td>RJ Tucker</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>397</th>\n",
       "      <td>398</td>\n",
       "      <td>2013</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>26-05-13</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>KA Pollard</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>SJA Taufel</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>410</th>\n",
       "      <td>411</td>\n",
       "      <td>2014</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25-04-14</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>MM Sharma</td>\n",
       "      <td>Dubai International Cricket Stadium</td>\n",
       "      <td>BF Bowden</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>430</th>\n",
       "      <td>431</td>\n",
       "      <td>2014</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>10-05-14</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>DR Smith</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>VA Kulkarni</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>455</th>\n",
       "      <td>456</td>\n",
       "      <td>2014</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>28-05-14</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>SK Raina</td>\n",
       "      <td>Brabourne Stadium</td>\n",
       "      <td>VA Kulkarni</td>\n",
       "      <td>BNJ Oxenford</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>470</th>\n",
       "      <td>471</td>\n",
       "      <td>2015</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>17-04-15</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>A Nehra</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>500</td>\n",
       "      <td>2015</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>08-05-15</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>HH Pandya</td>\n",
       "      <td>MA Chidambaram Stadium, Chepauk</td>\n",
       "      <td>CB Gaffaney</td>\n",
       "      <td>CK Nandan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>513</th>\n",
       "      <td>514</td>\n",
       "      <td>2015</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>19-05-15</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>25</td>\n",
       "      <td>0</td>\n",
       "      <td>KA Pollard</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>RK Illingworth</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>516</th>\n",
       "      <td>517</td>\n",
       "      <td>2015</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>24-05-15</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>RG Sharma</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>RK Illingworth</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>636</th>\n",
       "      <td>637</td>\n",
       "      <td>2018</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>07-04-18</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>DJ Bravo</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>Chris Gaffaney</td>\n",
       "      <td>A Nanda Kishore</td>\n",
       "      <td>Anil Chaudhary</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>662</th>\n",
       "      <td>663</td>\n",
       "      <td>2018</td>\n",
       "      <td>Pune</td>\n",
       "      <td>28-04-18</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>RG Sharma</td>\n",
       "      <td>Maharashtra Cricket Association Stadium</td>\n",
       "      <td>Chris Gaffaney</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>Anil Dandekar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>710</th>\n",
       "      <td>711</td>\n",
       "      <td>2019</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>03-04-19</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>37</td>\n",
       "      <td>0</td>\n",
       "      <td>HH Pandya</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>Bruce Oxenford</td>\n",
       "      <td>Rod Tucker</td>\n",
       "      <td>Yeshwant Barde</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>739</th>\n",
       "      <td>740</td>\n",
       "      <td>2019</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>26-04-19</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>46</td>\n",
       "      <td>0</td>\n",
       "      <td>RG Sharma</td>\n",
       "      <td>M. A. Chidambaram Stadium</td>\n",
       "      <td>Nigel Llong</td>\n",
       "      <td>Anil Chaudhary</td>\n",
       "      <td>Vineet Kulkarni</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752</th>\n",
       "      <td>753</td>\n",
       "      <td>2019</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>07-05-19</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>AS Yadav</td>\n",
       "      <td>M. A. Chidambaram Stadium</td>\n",
       "      <td>Nigel Llong</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>Ian Gould</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>755</th>\n",
       "      <td>756</td>\n",
       "      <td>2019</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>12-05-19</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>JJ Bumrah</td>\n",
       "      <td>Rajiv Gandhi Intl. Cricket Stadium</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>Ian Gould</td>\n",
       "      <td>Nigel Llong</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      id  season            city      date                team1  \\\n",
       "7      8    2008         Chennai  23-04-08  Chennai Super Kings   \n",
       "36    37    2008          Mumbai  14-05-08  Chennai Super Kings   \n",
       "58    59    2009       Cape Town  18-04-09       Mumbai Indians   \n",
       "102  103    2009  Port Elizabeth  16-05-09       Mumbai Indians   \n",
       "134  135    2010          Mumbai  25-03-10  Chennai Super Kings   \n",
       "151  152    2010         Chennai  06-04-10  Chennai Super Kings   \n",
       "174  175    2010          Mumbai  25-04-10  Chennai Super Kings   \n",
       "197  198    2011          Mumbai  22-04-11       Mumbai Indians   \n",
       "248  249    2012         Chennai  04-04-12  Chennai Super Kings   \n",
       "295  296    2012          Mumbai  06-05-12  Chennai Super Kings   \n",
       "319  320    2012       Bangalore  23-05-12  Chennai Super Kings   \n",
       "326  327    2013         Chennai  06-04-13       Mumbai Indians   \n",
       "370  371    2013          Mumbai  05-05-13       Mumbai Indians   \n",
       "394  395    2013           Delhi  21-05-13  Chennai Super Kings   \n",
       "397  398    2013         Kolkata  26-05-13       Mumbai Indians   \n",
       "410  411    2014             NaN  25-04-14       Mumbai Indians   \n",
       "430  431    2014          Mumbai  10-05-14       Mumbai Indians   \n",
       "455  456    2014          Mumbai  28-05-14       Mumbai Indians   \n",
       "470  471    2015          Mumbai  17-04-15       Mumbai Indians   \n",
       "499  500    2015         Chennai  08-05-15  Chennai Super Kings   \n",
       "513  514    2015          Mumbai  19-05-15       Mumbai Indians   \n",
       "516  517    2015         Kolkata  24-05-15       Mumbai Indians   \n",
       "636  637    2018          Mumbai  07-04-18       Mumbai Indians   \n",
       "662  663    2018            Pune  28-04-18  Chennai Super Kings   \n",
       "710  711    2019          Mumbai  03-04-19       Mumbai Indians   \n",
       "739  740    2019         Chennai  26-04-19       Mumbai Indians   \n",
       "752  753    2019         Chennai  07-05-19  Chennai Super Kings   \n",
       "755  756    2019       Hyderabad  12-05-19       Mumbai Indians   \n",
       "\n",
       "                   team2          toss_winner toss_decision  result  \\\n",
       "7         Mumbai Indians       Mumbai Indians         field  normal   \n",
       "36        Mumbai Indians       Mumbai Indians         field  normal   \n",
       "58   Chennai Super Kings  Chennai Super Kings         field  normal   \n",
       "102  Chennai Super Kings       Mumbai Indians           bat  normal   \n",
       "134       Mumbai Indians       Mumbai Indians         field  normal   \n",
       "151       Mumbai Indians  Chennai Super Kings           bat  normal   \n",
       "174       Mumbai Indians  Chennai Super Kings           bat  normal   \n",
       "197  Chennai Super Kings  Chennai Super Kings         field  normal   \n",
       "248       Mumbai Indians       Mumbai Indians         field  normal   \n",
       "295       Mumbai Indians       Mumbai Indians         field  normal   \n",
       "319       Mumbai Indians       Mumbai Indians         field  normal   \n",
       "326  Chennai Super Kings       Mumbai Indians           bat  normal   \n",
       "370  Chennai Super Kings       Mumbai Indians           bat  normal   \n",
       "394       Mumbai Indians  Chennai Super Kings           bat  normal   \n",
       "397  Chennai Super Kings       Mumbai Indians           bat  normal   \n",
       "410  Chennai Super Kings       Mumbai Indians           bat  normal   \n",
       "430  Chennai Super Kings  Chennai Super Kings         field  normal   \n",
       "455  Chennai Super Kings  Chennai Super Kings         field  normal   \n",
       "470  Chennai Super Kings       Mumbai Indians           bat  normal   \n",
       "499       Mumbai Indians  Chennai Super Kings           bat  normal   \n",
       "513  Chennai Super Kings       Mumbai Indians           bat  normal   \n",
       "516  Chennai Super Kings  Chennai Super Kings         field  normal   \n",
       "636  Chennai Super Kings  Chennai Super Kings         field  normal   \n",
       "662       Mumbai Indians       Mumbai Indians         field  normal   \n",
       "710  Chennai Super Kings  Chennai Super Kings         field  normal   \n",
       "739  Chennai Super Kings  Chennai Super Kings         field  normal   \n",
       "752       Mumbai Indians  Chennai Super Kings           bat  normal   \n",
       "755  Chennai Super Kings       Mumbai Indians           bat  normal   \n",
       "\n",
       "     dl_applied               winner  win_by_runs  win_by_wickets  \\\n",
       "7             0  Chennai Super Kings            6               0   \n",
       "36            0       Mumbai Indians            0               9   \n",
       "58            0       Mumbai Indians           19               0   \n",
       "102           0  Chennai Super Kings            0               7   \n",
       "134           0       Mumbai Indians            0               5   \n",
       "151           0  Chennai Super Kings           24               0   \n",
       "174           0  Chennai Super Kings           22               0   \n",
       "197           0       Mumbai Indians            8               0   \n",
       "248           0       Mumbai Indians            0               8   \n",
       "295           0       Mumbai Indians            0               2   \n",
       "319           0  Chennai Super Kings           38               0   \n",
       "326           0       Mumbai Indians            9               0   \n",
       "370           0       Mumbai Indians           60               0   \n",
       "394           0  Chennai Super Kings           48               0   \n",
       "397           0       Mumbai Indians           23               0   \n",
       "410           0  Chennai Super Kings            0               7   \n",
       "430           0  Chennai Super Kings            0               4   \n",
       "455           0  Chennai Super Kings            0               7   \n",
       "470           0  Chennai Super Kings            0               6   \n",
       "499           0       Mumbai Indians            0               6   \n",
       "513           0       Mumbai Indians           25               0   \n",
       "516           0       Mumbai Indians           41               0   \n",
       "636           0  Chennai Super Kings            0               1   \n",
       "662           0       Mumbai Indians            0               8   \n",
       "710           0       Mumbai Indians           37               0   \n",
       "739           0       Mumbai Indians           46               0   \n",
       "752           0       Mumbai Indians            0               6   \n",
       "755           0       Mumbai Indians            1               0   \n",
       "\n",
       "     player_of_match                                    venue  \\\n",
       "7          ML Hayden          MA Chidambaram Stadium, Chepauk   \n",
       "36     ST Jayasuriya                         Wankhede Stadium   \n",
       "58      SR Tendulkar                                 Newlands   \n",
       "102        ML Hayden                         St George's Park   \n",
       "134     SR Tendulkar                        Brabourne Stadium   \n",
       "151         SK Raina          MA Chidambaram Stadium, Chepauk   \n",
       "174         SK Raina               Dr DY Patil Sports Academy   \n",
       "197  Harbhajan Singh                         Wankhede Stadium   \n",
       "248          RE Levi          MA Chidambaram Stadium, Chepauk   \n",
       "295         DR Smith                         Wankhede Stadium   \n",
       "319         MS Dhoni                    M Chinnaswamy Stadium   \n",
       "326       KA Pollard          MA Chidambaram Stadium, Chepauk   \n",
       "370       MG Johnson                         Wankhede Stadium   \n",
       "394       MEK Hussey                         Feroz Shah Kotla   \n",
       "397       KA Pollard                             Eden Gardens   \n",
       "410        MM Sharma      Dubai International Cricket Stadium   \n",
       "430         DR Smith                         Wankhede Stadium   \n",
       "455         SK Raina                        Brabourne Stadium   \n",
       "470          A Nehra                         Wankhede Stadium   \n",
       "499        HH Pandya          MA Chidambaram Stadium, Chepauk   \n",
       "513       KA Pollard                         Wankhede Stadium   \n",
       "516        RG Sharma                             Eden Gardens   \n",
       "636         DJ Bravo                         Wankhede Stadium   \n",
       "662        RG Sharma  Maharashtra Cricket Association Stadium   \n",
       "710        HH Pandya                         Wankhede Stadium   \n",
       "739        RG Sharma                M. A. Chidambaram Stadium   \n",
       "752         AS Yadav                M. A. Chidambaram Stadium   \n",
       "755        JJ Bumrah       Rajiv Gandhi Intl. Cricket Stadium   \n",
       "\n",
       "             umpire1          umpire2          umpire3  \n",
       "7          DJ Harper   GA Pratapkumar              NaN  \n",
       "36       BR Doctrove        AM Saheba              NaN  \n",
       "58       BR Doctrove      K Hariharan              NaN  \n",
       "102      SK Tarapore       SJA Taufel              NaN  \n",
       "134        BF Bowden        AM Saheba              NaN  \n",
       "151         S Asnani        DJ Harper              NaN  \n",
       "174      RE Koertzen       SJA Taufel              NaN  \n",
       "197        Asad Rauf        AM Saheba              NaN  \n",
       "248        JD Cloete       SJA Taufel              NaN  \n",
       "295        Asad Rauf         S Asnani              NaN  \n",
       "319        BF Bowden  HDPK Dharmasena              NaN  \n",
       "326        M Erasmus      VA Kulkarni              NaN  \n",
       "370  HDPK Dharmasena        CK Nandan              NaN  \n",
       "394         NJ Llong        RJ Tucker              NaN  \n",
       "397  HDPK Dharmasena       SJA Taufel              NaN  \n",
       "410        BF Bowden        M Erasmus              NaN  \n",
       "430  HDPK Dharmasena      VA Kulkarni              NaN  \n",
       "455      VA Kulkarni     BNJ Oxenford              NaN  \n",
       "470     AK Chaudhary        M Erasmus              NaN  \n",
       "499      CB Gaffaney        CK Nandan              NaN  \n",
       "513  HDPK Dharmasena   RK Illingworth              NaN  \n",
       "516  HDPK Dharmasena   RK Illingworth              NaN  \n",
       "636   Chris Gaffaney  A Nanda Kishore   Anil Chaudhary  \n",
       "662   Chris Gaffaney      Nitin Menon    Anil Dandekar  \n",
       "710   Bruce Oxenford       Rod Tucker   Yeshwant Barde  \n",
       "739      Nigel Llong   Anil Chaudhary  Vineet Kulkarni  \n",
       "752      Nigel Llong      Nitin Menon        Ian Gould  \n",
       "755      Nitin Menon        Ian Gould      Nigel Llong  "
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mi_csk=matches[((matches.team1 ==\"Mumbai Indians\") & (matches.team2 ==\"Chennai Super Kings\")) | \n",
    "               ((matches.team2 ==\"Mumbai Indians\") & (matches.team1 ==\"Chennai Super Kings\"))]\n",
    "mi_csk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 35
    },
    "executionInfo": {
     "elapsed": 14694,
     "status": "ok",
     "timestamp": 1601651971010,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "i-LOXUzvj-mA",
    "outputId": "997ad4b9-99b7-4adb-ca18-b972435e85ac"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The no of matches played between MI and CSK is 28-the most between any teams\n"
     ]
    }
   ],
   "source": [
    "print('The no of matches played between MI and CSK is {}-the most between any teams'.format(mi_csk.id.count()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "GRUHdqA2j-mE"
   },
   "source": [
    "## **Let's see which team has the dominance in MI vs CSK rivalry.**\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 525
    },
    "executionInfo": {
     "elapsed": 14677,
     "status": "ok",
     "timestamp": 1601651971012,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "Q2BN_Odbj-mE",
    "outputId": "4b529acf-07bb-4802-9ecf-b4fed18736b1"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title('MI vs CSK')\n",
    "sns.countplot(x=mi_csk['winner'],palette=['#FFFF48','#87ceeb'])\n",
    "plt.text(-0.009,9,s=mi_csk['winner'].value_counts()['Chennai Super Kings'], color='white')\n",
    "plt.text(1,15,s=mi_csk['winner'].value_counts()['Mumbai Indians'], color='white');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "C_wI7dG0j-mG"
   },
   "source": [
    "***`Mumbai Indians`*** leads the rivalry with ***`6`*** extra wins as compared to ***`CSK`***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "otrRJlvEj-mG"
   },
   "source": [
    "## **Let's find the statistics related to IPL Finals**\n",
    "\n",
    "Find the final winner of IPL for each season. For this let's create a new dataframe for finals."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 905
    },
    "executionInfo": {
     "elapsed": 14660,
     "status": "ok",
     "timestamp": 1601651971014,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
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    },
    "id": "ypnH-aCZj-mH",
    "outputId": "d6728069-3c08-4ed3-ad3a-e687d8c0e957"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>id</th>\n",
       "      <th>season</th>\n",
       "      <th>city</th>\n",
       "      <th>date</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>result</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>venue</th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "      <th>umpire3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>57</td>\n",
       "      <td>58</td>\n",
       "      <td>2008</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>01-06-08</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>YK Pathan</td>\n",
       "      <td>Dr DY Patil Sports Academy</td>\n",
       "      <td>BF Bowden</td>\n",
       "      <td>RE Koertzen</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>114</td>\n",
       "      <td>115</td>\n",
       "      <td>2009</td>\n",
       "      <td>Johannesburg</td>\n",
       "      <td>24-05-09</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>A Kumble</td>\n",
       "      <td>New Wanderers Stadium</td>\n",
       "      <td>RE Koertzen</td>\n",
       "      <td>SJA Taufel</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>174</td>\n",
       "      <td>175</td>\n",
       "      <td>2010</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>25-04-10</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>SK Raina</td>\n",
       "      <td>Dr DY Patil Sports Academy</td>\n",
       "      <td>RE Koertzen</td>\n",
       "      <td>SJA Taufel</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>247</td>\n",
       "      <td>248</td>\n",
       "      <td>2011</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>28-05-11</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>58</td>\n",
       "      <td>0</td>\n",
       "      <td>M Vijay</td>\n",
       "      <td>MA Chidambaram Stadium, Chepauk</td>\n",
       "      <td>Asad Rauf</td>\n",
       "      <td>SJA Taufel</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>321</td>\n",
       "      <td>322</td>\n",
       "      <td>2012</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>27-05-12</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>MS Bisla</td>\n",
       "      <td>MA Chidambaram Stadium, Chepauk</td>\n",
       "      <td>BF Bowden</td>\n",
       "      <td>SJA Taufel</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>397</td>\n",
       "      <td>398</td>\n",
       "      <td>2013</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>26-05-13</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>KA Pollard</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>SJA Taufel</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>457</td>\n",
       "      <td>458</td>\n",
       "      <td>2014</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>01-06-14</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>MK Pandey</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>BNJ Oxenford</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>516</td>\n",
       "      <td>517</td>\n",
       "      <td>2015</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>24-05-15</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>RG Sharma</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>RK Illingworth</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>576</td>\n",
       "      <td>577</td>\n",
       "      <td>2016</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>29-05-16</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>BCJ Cutting</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>BNJ Oxenford</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>635</td>\n",
       "      <td>636</td>\n",
       "      <td>2017</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>21-05-17</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>KH Pandya</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>NJ Llong</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>695</td>\n",
       "      <td>696</td>\n",
       "      <td>2018</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>27-05-18</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>SR Watson</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>Marais Erasmus</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>Nitin Menon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>755</td>\n",
       "      <td>756</td>\n",
       "      <td>2019</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>12-05-19</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>JJ Bumrah</td>\n",
       "      <td>Rajiv Gandhi Intl. Cricket Stadium</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>Ian Gould</td>\n",
       "      <td>Nigel Llong</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    index   id  season          city      date                team1  \\\n",
       "0      57   58    2008        Mumbai  01-06-08  Chennai Super Kings   \n",
       "1     114  115    2009  Johannesburg  24-05-09      Deccan Chargers   \n",
       "2     174  175    2010        Mumbai  25-04-10  Chennai Super Kings   \n",
       "3     247  248    2011       Chennai  28-05-11  Chennai Super Kings   \n",
       "4     321  322    2012       Chennai  27-05-12  Chennai Super Kings   \n",
       "5     397  398    2013       Kolkata  26-05-13       Mumbai Indians   \n",
       "6     457  458    2014     Bangalore  01-06-14      Kings XI Punjab   \n",
       "7     516  517    2015       Kolkata  24-05-15       Mumbai Indians   \n",
       "8     576  577    2016     Bangalore  29-05-16  Sunrisers Hyderabad   \n",
       "9     635  636    2017     Hyderabad  21-05-17       Mumbai Indians   \n",
       "10    695  696    2018        Mumbai  27-05-18  Sunrisers Hyderabad   \n",
       "11    755  756    2019     Hyderabad  12-05-19       Mumbai Indians   \n",
       "\n",
       "                          team2                  toss_winner toss_decision  \\\n",
       "0              Rajasthan Royals             Rajasthan Royals         field   \n",
       "1   Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
       "2                Mumbai Indians          Chennai Super Kings           bat   \n",
       "3   Royal Challengers Bangalore          Chennai Super Kings           bat   \n",
       "4         Kolkata Knight Riders          Chennai Super Kings           bat   \n",
       "5           Chennai Super Kings               Mumbai Indians           bat   \n",
       "6         Kolkata Knight Riders        Kolkata Knight Riders         field   \n",
       "7           Chennai Super Kings          Chennai Super Kings         field   \n",
       "8   Royal Challengers Bangalore          Sunrisers Hyderabad           bat   \n",
       "9        Rising Pune Supergiant               Mumbai Indians           bat   \n",
       "10          Chennai Super Kings          Chennai Super Kings         field   \n",
       "11          Chennai Super Kings               Mumbai Indians           bat   \n",
       "\n",
       "    result  dl_applied                 winner  win_by_runs  win_by_wickets  \\\n",
       "0   normal           0       Rajasthan Royals            0               3   \n",
       "1   normal           0        Deccan Chargers            6               0   \n",
       "2   normal           0    Chennai Super Kings           22               0   \n",
       "3   normal           0    Chennai Super Kings           58               0   \n",
       "4   normal           0  Kolkata Knight Riders            0               5   \n",
       "5   normal           0         Mumbai Indians           23               0   \n",
       "6   normal           0  Kolkata Knight Riders            0               3   \n",
       "7   normal           0         Mumbai Indians           41               0   \n",
       "8   normal           0    Sunrisers Hyderabad            8               0   \n",
       "9   normal           0         Mumbai Indians            1               0   \n",
       "10  normal           0    Chennai Super Kings            0               8   \n",
       "11  normal           0         Mumbai Indians            1               0   \n",
       "\n",
       "   player_of_match                                      venue  \\\n",
       "0        YK Pathan                 Dr DY Patil Sports Academy   \n",
       "1         A Kumble                      New Wanderers Stadium   \n",
       "2         SK Raina                 Dr DY Patil Sports Academy   \n",
       "3          M Vijay            MA Chidambaram Stadium, Chepauk   \n",
       "4         MS Bisla            MA Chidambaram Stadium, Chepauk   \n",
       "5       KA Pollard                               Eden Gardens   \n",
       "6        MK Pandey                      M Chinnaswamy Stadium   \n",
       "7        RG Sharma                               Eden Gardens   \n",
       "8      BCJ Cutting                      M Chinnaswamy Stadium   \n",
       "9        KH Pandya  Rajiv Gandhi International Stadium, Uppal   \n",
       "10       SR Watson                           Wankhede Stadium   \n",
       "11       JJ Bumrah         Rajiv Gandhi Intl. Cricket Stadium   \n",
       "\n",
       "            umpire1         umpire2      umpire3  \n",
       "0         BF Bowden     RE Koertzen          NaN  \n",
       "1       RE Koertzen      SJA Taufel          NaN  \n",
       "2       RE Koertzen      SJA Taufel          NaN  \n",
       "3         Asad Rauf      SJA Taufel          NaN  \n",
       "4         BF Bowden      SJA Taufel          NaN  \n",
       "5   HDPK Dharmasena      SJA Taufel          NaN  \n",
       "6   HDPK Dharmasena    BNJ Oxenford          NaN  \n",
       "7   HDPK Dharmasena  RK Illingworth          NaN  \n",
       "8   HDPK Dharmasena    BNJ Oxenford          NaN  \n",
       "9          NJ Llong          S Ravi          NaN  \n",
       "10   Marais Erasmus          S Ravi  Nitin Menon  \n",
       "11      Nitin Menon       Ian Gould  Nigel Llong  "
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_match = matches.groupby('season').tail(1).sort_values('season').reset_index()\n",
    "final_match"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "cPe4lIO2j-mJ"
   },
   "source": [
    "#**IPL Final match appearences**\n",
    "\n",
    "Now let's find out how many times each team have appeared into finals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 173
    },
    "executionInfo": {
     "elapsed": 14642,
     "status": "ok",
     "timestamp": 1601651971016,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "DZ5CYkoDj-mK",
    "outputId": "1e9da11a-c602-40ef-ac2a-9252ea05d33a"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Chennai Super Kings': 8,\n",
       " 'Mumbai Indians': 5,\n",
       " 'Royal Challengers Bangalore': 3,\n",
       " 'Kolkata Knight Riders': 2,\n",
       " 'Sunrisers Hyderabad': 2,\n",
       " 'Rajasthan Royals': 1,\n",
       " 'Deccan Chargers': 1,\n",
       " 'Rising Pune Supergiant': 1,\n",
       " 'Kings XI Punjab': 1}"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_match_team = pd.concat([final_match['team1'],final_match['team2']])\n",
    "final_match_team_d=dict(final_match_team.value_counts())\n",
    "final_match_team_d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 706
    },
    "executionInfo": {
     "elapsed": 14625,
     "status": "ok",
     "timestamp": 1601651971018,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "lvipcX7bj-mN",
    "outputId": "e39e94b7-116c-4d43-8de6-99f50ea6aaef"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title('Count of appearances in IPL Finals')\n",
    "plt.xlabel('Teams')\n",
    "sns.countplot(x=final_match_team)\n",
    "plt.ylabel('Final Matches Played')\n",
    "plt.xticks(rotation=70);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "executionInfo": {
     "elapsed": 14609,
     "status": "ok",
     "timestamp": 1601651971020,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "4S8pE5nVj-mP"
   },
   "outputs": [],
   "source": [
    "final_winner=final_match['winner'].value_counts()\n",
    "final_winner_d=dict(final_winner)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 657
    },
    "executionInfo": {
     "elapsed": 15247,
     "status": "ok",
     "timestamp": 1601651971674,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "XHO7sdUKj-mQ",
    "outputId": "d2d67f24-ab30-4a2e-eea3-8a14bf8e8714"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x=final_match['winner'])\n",
    "plt.xticks(rotation=70);\n",
    "plt.title(\"Count of IPL Final winners\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 104
    },
    "executionInfo": {
     "elapsed": 15229,
     "status": "ok",
     "timestamp": 1601651971675,
     "user": {
      "displayName": "Yash Shinde",
      "photoUrl": "https://lh5.googleusercontent.com/-8f8D8TQVBv8/AAAAAAAAAAI/AAAAAAAAHzg/6SjI9zzbbYg/s64/photo.jpg",
      "userId": "16704968411796438469"
     },
     "user_tz": -330
    },
    "id": "Jmx9LFefj-mT",
    "outputId": "775bb804-304d-4c56-e03c-666e6069a022"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Kings XI Punjab',\n",
       " 'Royal Challengers Bangalore',\n",
       " 'Royal Challengers Bangalore',\n",
       " 'Royal Challengers Bangalore',\n",
       " 'Rising Pune Supergiant']"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "not_final_winners=[]\n",
    "for i in final_match_team:\n",
    "    if i in final_winner:\n",
    "         continue\n",
    "    else:\n",
    "        not_final_winners= not_final_winners+[i]     \n",
    "not_final_winners"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "executionInfo": {
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   "source": [
    "import jovian"
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      "[jovian] Updating notebook \"uayashu145/ipl-analysis\" on https://jovian.ml/\u001b[0m\n",
      "[jovian] Uploading notebook..\u001b[0m\n",
      "[jovian] Capturing environment..\u001b[0m\n",
      "[jovian] Committed successfully! https://jovian.ml/uayashu145/ipl-analysis\u001b[0m\n"
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       "'https://jovian.ml/uayashu145/ipl-analysis'"
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   "source": [
    "## **Inferences and Conclusion**\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "lJWTOZjFnEQb"
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   "source": [
    "## ***The following are the inferences and conclusions after performing data analysis on the dataset `'matches.csv'`*** \n",
    "\n",
    "---\n",
    "\n",
    "\n",
    "1. So, we have ***`6`*** unique teams that have won the IPL Final.\n",
    "   ***`Mumbai Indians`*** have won most ***`(4)`*** IPL titles followed   by ***`Chennai Super Kings (3)`***. Thus, it is obvious that these 2 teams are the most successful teams in the IPL history. \n",
    "\n",
    "2. ***`Royal Challengers Bangalore`*** have appeared for ***`3 times`*** in IPL Finals but still is without any title wins. Followed to ***`Royal Challengers Bangalore`*** ***`Rising Pune Supergiant`*** , ***`Kings XI Punjab`*** have appeared *`1 time each`* without title wins. \n",
    "\n",
    "3. ***`Chennai Super Kings`*** have appeared for ***`(8) times`*** in IPL Finals -the most by any team in IPL. At second place, it's ***`Mumbai Indians`*** with ***`(5) times`***.\n",
    "\n",
    "4. Even though ***`Mumbai Indians`*** have greater number of wins but winning percentage of ***`Chennai Super Kings`*** is higher than ***`Mumbai Indians`***. But it may also be noted that when comparing the head to head matches between ***`Mumbai Indians and Chennai Super Kings, Mumbai Indians`*** have won most matches.\n",
    "\n",
    "5. ***` Kolkata (Eden Gardens)`*** has hosted most number of matches in the IPL.\n",
    "\n",
    "6. ***`Chris Gayle`*** has received highest number of Man of the Match Awards.\n",
    "\n",
    "7. There were ***`13 matches`*** with the result as a t***`ie(9) or no result(4)`***.\n",
    "\n",
    "8. It can be seen that impact of winning the toss has an ***`almost Equal amount of impact`*** on the result of match. So, it can be said that winning toss doesn't necessarily creates an impact on the result of match.\n",
    "\n",
    "9. The teams in ***`2011,2012 and 2013 are greater`*** than other seasons due to which matches played in those seasons are greater.\n",
    "\n",
    "10. The mean value of ***`win_by_runs and\twin_by_wickets is 13.283069\tand 3.350529 respectively. `***"
   ]
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    "id": "Pk5D2jhdj-mf"
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   "outputs": [],
   "source": [
    "import jovian"
   ]
  },
  {
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   "execution_count": null,
   "metadata": {
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    {
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     "text": [
      "[jovian] Attempting to save notebook..\u001b[0m\n"
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   "source": [
    "jovian.commit(project=project_name)"
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  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "OIzVDtFkj-mi"
   },
   "source": [
    "## **References and Future Work**\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "hPVkYlFLvX0x"
   },
   "source": [
    "##**Future Work**\n",
    "The dataset for IPL(2008-2019) consisted two .csv files i.e ***`matches.csv and deliveries.csv`***. Here ***`matches.csv`*** is considered in this project for the analysis. For performing more data analysis related to ***`scores, runs by individuals, wickets etc`*** can be retrieved from ***`deliveries.csv`***. Moreover ***`matches.csv and deliveries.csv`*** can be merged together with respect to their ***`match id`*** and interesting data can be explored from the merged data.\n",
    "\n",
    "##**References**\n",
    "*  ZerotoPandas Tutorial by JovianML- https://jovian.ml/learn/data-analysis-with-python-zero-to-pandas\n",
    "*  Indian Premier League 2008-2019 dataset-  https://www.kaggle.com/nowke9/ipldata\n",
    "*   Markdown Syntax- https://learnxinyminutes.com/docs/markdown/\n",
    "*  For errors and bugs correction- https://stackoverflow.com/ \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "tIHP9Pak7KVT"
   },
   "source": [
    "# **Thank You!!!**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
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     },
     "user_tz": -330
    },
    "id": "uISz4DxEj-mi"
   },
   "outputs": [],
   "source": [
    "import jovian"
   ]
  },
  {
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    "outputId": "320a1a2b-3f0d-45b5-d770-33fade2f6b05"
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   "outputs": [],
   "source": [
    "jovian.commit(project=project_name)"
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