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Sahitya77/IPLWinPredictor

sourceHugging Faceupdated 4y agoView on Hugging Face
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IPLWinPredictor.ipynb2163 linesDownload Raw Back to root
1{2  "nbformat": 4,3  "nbformat_minor": 0,4  "metadata": {5    "colab": {6      "provenance": []7    },8    "kernelspec": {9      "name": "python3",10      "display_name": "Python 3"11    },12    "language_info": {13      "name": "python"14    }15  },16  "cells": [17    {18      "cell_type": "code",19      "execution_count": 29,20      "metadata": {21        "id": "fNQEcD01-COc"22      },23      "outputs": [],24      "source": [25        "import numpy as np\n",26        "import pandas as pd\n",27        "from google.colab import drive"28      ]29    },30    {31      "cell_type": "code",32      "source": [33        "import numpy; print(\"NumPy\", numpy.__version__)\n",34        "import scipy; print(\"SciPy\", scipy.__version__)\n",35        "import sklearn; print(\"Scikit-Learn\", sklearn.__version__)"36      ],37      "metadata": {38        "colab": {39          "base_uri": "https://localhost:8080/"40        },41        "id": "eGuCWj7ucHo0",42        "outputId": "24ce6394-b3cc-40b7-9a4d-91630b87a870"43      },44      "execution_count": 2,45      "outputs": [46        {47          "output_type": "stream",48          "name": "stdout",49          "text": [50            "NumPy 1.21.6\n",51            "SciPy 1.7.3\n",52            "Scikit-Learn 1.0.2\n"53          ]54        }55      ]56    },57    {58      "cell_type": "code",59      "source": [60        "drive.mount('/content/MyDrive',force_remount=True)"61      ],62      "metadata": {63        "colab": {64          "base_uri": "https://localhost:8080/"65        },66        "id": "Q-9ahH5r-ImU",67        "outputId": "b81f7f39-b298-4df7-8e66-4b26856333b0"68      },69      "execution_count": 30,70      "outputs": [71        {72          "output_type": "stream",73          "name": "stdout",74          "text": [75            "Mounted at /content/MyDrive\n"76          ]77        }78      ]79    },80    {81      "cell_type": "code",82      "source": [83        "match=pd.read_csv('/content/MyDrive/MyDrive/IPLDataset/matches.csv')\n",84        "delivery=pd.read_csv('/content/MyDrive/MyDrive/IPLDataset/deliveries.csv')"85      ],86      "metadata": {87        "id": "-7f2Rw4w-aBg"88      },89      "execution_count": 31,90      "outputs": []91    },92    {93      "cell_type": "code",94      "source": [95        "match.shape"96      ],97      "metadata": {98        "colab": {99          "base_uri": "https://localhost:8080/"100        },101        "id": "VH8DbC1Y-7Id",102        "outputId": "22ae8ae9-6990-4904-f96e-c59f86bddf10"103      },104      "execution_count": 32,105      "outputs": [106        {107          "output_type": "execute_result",108          "data": {109            "text/plain": [110              "(756, 18)"111            ]112          },113          "metadata": {},114          "execution_count": 32115        }116      ]117    },118    {119      "cell_type": "code",120      "source": [121        "match.head()"122      ],123      "metadata": {124        "colab": {125          "base_uri": "https://localhost:8080/",126          "height": 496127        },128        "id": "9CwjVYNN_k8v",129        "outputId": "6a560a4c-3d30-499a-a0bf-8ef45f91f4d3"130      },131      "execution_count": 33,132      "outputs": [133        {134          "output_type": "execute_result",135          "data": {136            "text/plain": [137              "   id    Season       city        date                        team1  \\\n",138              "0   1  IPL-2017  Hyderabad  05-04-2017          Sunrisers Hyderabad   \n",139              "1   2  IPL-2017       Pune  06-04-2017               Mumbai Indians   \n",140              "2   3  IPL-2017     Rajkot  07-04-2017                Gujarat Lions   \n",141              "3   4  IPL-2017     Indore  08-04-2017       Rising Pune Supergiant   \n",142              "4   5  IPL-2017  Bangalore  08-04-2017  Royal Challengers Bangalore   \n",143              "\n",144              "                         team2                  toss_winner toss_decision  \\\n",145              "0  Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",146              "1       Rising Pune Supergiant       Rising Pune Supergiant         field   \n",147              "2        Kolkata Knight Riders        Kolkata Knight Riders         field   \n",148              "3              Kings XI Punjab              Kings XI Punjab         field   \n",149              "4             Delhi Daredevils  Royal Challengers Bangalore           bat   \n",150              "\n",151              "   result  dl_applied                       winner  win_by_runs  \\\n",152              "0  normal           0          Sunrisers Hyderabad           35   \n",153              "1  normal           0       Rising Pune Supergiant            0   \n",154              "2  normal           0        Kolkata Knight Riders            0   \n",155              "3  normal           0              Kings XI Punjab            0   \n",156              "4  normal           0  Royal Challengers Bangalore           15   \n",157              "\n",158              "   win_by_wickets player_of_match                                      venue  \\\n",159              "0               0    Yuvraj Singh  Rajiv Gandhi International Stadium, Uppal   \n",160              "1               7       SPD Smith    Maharashtra Cricket Association Stadium   \n",161              "2              10         CA Lynn     Saurashtra Cricket Association Stadium   \n",162              "3               6      GJ Maxwell                     Holkar Cricket Stadium   \n",163              "4               0       KM Jadhav                      M Chinnaswamy Stadium   \n",164              "\n",165              "          umpire1        umpire2 umpire3  \n",166              "0     AY Dandekar       NJ Llong     NaN  \n",167              "1  A Nand Kishore         S Ravi     NaN  \n",168              "2     Nitin Menon      CK Nandan     NaN  \n",169              "3    AK Chaudhary  C Shamshuddin     NaN  \n",170              "4             NaN            NaN     NaN  "171            ],172            "text/html": [173              "\n",174              "  <div id=\"df-e68083bf-2bf2-4252-bd1f-e325f170ef32\">\n",175              "    <div class=\"colab-df-container\">\n",176              "      <div>\n",177              "<style scoped>\n",178              "    .dataframe tbody tr th:only-of-type {\n",179              "        vertical-align: middle;\n",180              "    }\n",181              "\n",182              "    .dataframe tbody tr th {\n",183              "        vertical-align: top;\n",184              "    }\n",185              "\n",186              "    .dataframe thead th {\n",187              "        text-align: right;\n",188              "    }\n",189              "</style>\n",190              "<table border=\"1\" class=\"dataframe\">\n",191              "  <thead>\n",192              "    <tr style=\"text-align: right;\">\n",193              "      <th></th>\n",194              "      <th>id</th>\n",195              "      <th>Season</th>\n",196              "      <th>city</th>\n",197              "      <th>date</th>\n",198              "      <th>team1</th>\n",199              "      <th>team2</th>\n",200              "      <th>toss_winner</th>\n",201              "      <th>toss_decision</th>\n",202              "      <th>result</th>\n",203              "      <th>dl_applied</th>\n",204              "      <th>winner</th>\n",205              "      <th>win_by_runs</th>\n",206              "      <th>win_by_wickets</th>\n",207              "      <th>player_of_match</th>\n",208              "      <th>venue</th>\n",209              "      <th>umpire1</th>\n",210              "      <th>umpire2</th>\n",211              "      <th>umpire3</th>\n",212              "    </tr>\n",213              "  </thead>\n",214              "  <tbody>\n",215              "    <tr>\n",216              "      <th>0</th>\n",217              "      <td>1</td>\n",218              "      <td>IPL-2017</td>\n",219              "      <td>Hyderabad</td>\n",220              "      <td>05-04-2017</td>\n",221              "      <td>Sunrisers Hyderabad</td>\n",222              "      <td>Royal Challengers Bangalore</td>\n",223              "      <td>Royal Challengers Bangalore</td>\n",224              "      <td>field</td>\n",225              "      <td>normal</td>\n",226              "      <td>0</td>\n",227              "      <td>Sunrisers Hyderabad</td>\n",228              "      <td>35</td>\n",229              "      <td>0</td>\n",230              "      <td>Yuvraj Singh</td>\n",231              "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",232              "      <td>AY Dandekar</td>\n",233              "      <td>NJ Llong</td>\n",234              "      <td>NaN</td>\n",235              "    </tr>\n",236              "    <tr>\n",237              "      <th>1</th>\n",238              "      <td>2</td>\n",239              "      <td>IPL-2017</td>\n",240              "      <td>Pune</td>\n",241              "      <td>06-04-2017</td>\n",242              "      <td>Mumbai Indians</td>\n",243              "      <td>Rising Pune Supergiant</td>\n",244              "      <td>Rising Pune Supergiant</td>\n",245              "      <td>field</td>\n",246              "      <td>normal</td>\n",247              "      <td>0</td>\n",248              "      <td>Rising Pune Supergiant</td>\n",249              "      <td>0</td>\n",250              "      <td>7</td>\n",251              "      <td>SPD Smith</td>\n",252              "      <td>Maharashtra Cricket Association Stadium</td>\n",253              "      <td>A Nand Kishore</td>\n",254              "      <td>S Ravi</td>\n",255              "      <td>NaN</td>\n",256              "    </tr>\n",257              "    <tr>\n",258              "      <th>2</th>\n",259              "      <td>3</td>\n",260              "      <td>IPL-2017</td>\n",261              "      <td>Rajkot</td>\n",262              "      <td>07-04-2017</td>\n",263              "      <td>Gujarat Lions</td>\n",264              "      <td>Kolkata Knight Riders</td>\n",265              "      <td>Kolkata Knight Riders</td>\n",266              "      <td>field</td>\n",267              "      <td>normal</td>\n",268              "      <td>0</td>\n",269              "      <td>Kolkata Knight Riders</td>\n",270              "      <td>0</td>\n",271              "      <td>10</td>\n",272              "      <td>CA Lynn</td>\n",273              "      <td>Saurashtra Cricket Association Stadium</td>\n",274              "      <td>Nitin Menon</td>\n",275              "      <td>CK Nandan</td>\n",276              "      <td>NaN</td>\n",277              "    </tr>\n",278              "    <tr>\n",279              "      <th>3</th>\n",280              "      <td>4</td>\n",281              "      <td>IPL-2017</td>\n",282              "      <td>Indore</td>\n",283              "      <td>08-04-2017</td>\n",284              "      <td>Rising Pune Supergiant</td>\n",285              "      <td>Kings XI Punjab</td>\n",286              "      <td>Kings XI Punjab</td>\n",287              "      <td>field</td>\n",288              "      <td>normal</td>\n",289              "      <td>0</td>\n",290              "      <td>Kings XI Punjab</td>\n",291              "      <td>0</td>\n",292              "      <td>6</td>\n",293              "      <td>GJ Maxwell</td>\n",294              "      <td>Holkar Cricket Stadium</td>\n",295              "      <td>AK Chaudhary</td>\n",296              "      <td>C Shamshuddin</td>\n",297              "      <td>NaN</td>\n",298              "    </tr>\n",299              "    <tr>\n",300              "      <th>4</th>\n",301              "      <td>5</td>\n",302              "      <td>IPL-2017</td>\n",303              "      <td>Bangalore</td>\n",304              "      <td>08-04-2017</td>\n",305              "      <td>Royal Challengers Bangalore</td>\n",306              "      <td>Delhi Daredevils</td>\n",307              "      <td>Royal Challengers Bangalore</td>\n",308              "      <td>bat</td>\n",309              "      <td>normal</td>\n",310              "      <td>0</td>\n",311              "      <td>Royal Challengers Bangalore</td>\n",312              "      <td>15</td>\n",313              "      <td>0</td>\n",314              "      <td>KM Jadhav</td>\n",315              "      <td>M Chinnaswamy Stadium</td>\n",316              "      <td>NaN</td>\n",317              "      <td>NaN</td>\n",318              "      <td>NaN</td>\n",319              "    </tr>\n",320              "  </tbody>\n",321              "</table>\n",322              "</div>\n",323              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e68083bf-2bf2-4252-bd1f-e325f170ef32')\"\n",324              "              title=\"Convert this dataframe to an interactive table.\"\n",325              "              style=\"display:none;\">\n",326              "        \n",327              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",328              "       width=\"24px\">\n",329              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",330              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",331              "  </svg>\n",332              "      </button>\n",333              "      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'block' : 'none';\n",377              "\n",378              "        async function convertToInteractive(key) {\n",379              "          const element = document.querySelector('#df-e68083bf-2bf2-4252-bd1f-e325f170ef32');\n",380              "          const dataTable =\n",381              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",382              "                                                     [key], {});\n",383              "          if (!dataTable) return;\n",384              "\n",385              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",386              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",387              "            + ' to learn more about interactive tables.';\n",388              "          element.innerHTML = '';\n",389              "          dataTable['output_type'] = 'display_data';\n",390              "          await google.colab.output.renderOutput(dataTable, element);\n",391              "          const docLink = document.createElement('div');\n",392              "          docLink.innerHTML = docLinkHtml;\n",393              "          element.appendChild(docLink);\n",394              "        }\n",395              "      </script>\n",396              "    </div>\n",397              "  </div>\n",398              "  "399            ]400          },401          "metadata": {},402          "execution_count": 33403        }404      ]405    },406    {407      "cell_type": "code",408      "source": [409        "delivery.shape"410      ],411      "metadata": {412        "colab": {413          "base_uri": "https://localhost:8080/"414        },415        "id": "gx7DKlAp_pts",416        "outputId": "5de1c24e-79b0-4c86-f37c-d13dcec388ee"417      },418      "execution_count": 34,419      "outputs": [420        {421          "output_type": "execute_result",422          "data": {423            "text/plain": [424              "(179078, 21)"425            ]426          },427          "metadata": {},428          "execution_count": 34429        }430      ]431    },432    {433      "cell_type": "code",434      "source": [435        "delivery.head()"436      ],437      "metadata": {438        "colab": {439          "base_uri": "https://localhost:8080/",440          "height": 473441        },442        "id": "H9P2KVtj_mFS",443        "outputId": "5637c47e-e584-4142-e555-22826b3cac99"444      },445      "execution_count": 35,446      "outputs": [447        {448          "output_type": "execute_result",449          "data": {450            "text/plain": [451              "   match_id  inning         batting_team                 bowling_team  over  \\\n",452              "0         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     1   \n",453              "1         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     1   \n",454              "2         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     1   \n",455              "3         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     1   \n",456              "4         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     1   \n",457              "\n",458              "   ball    batsman non_striker    bowler  is_super_over  ...  bye_runs  \\\n",459              "0     1  DA Warner    S Dhawan  TS Mills              0  ...         0   \n",460              "1     2  DA Warner    S Dhawan  TS Mills              0  ...         0   \n",461              "2     3  DA Warner    S Dhawan  TS Mills              0  ...         0   \n",462              "3     4  DA Warner    S Dhawan  TS Mills              0  ...         0   \n",463              "4     5  DA Warner    S Dhawan  TS Mills              0  ...         0   \n",464              "\n",465              "   legbye_runs  noball_runs  penalty_runs  batsman_runs  extra_runs  \\\n",466              "0            0            0             0             0           0   \n",467              "1            0            0             0             0           0   \n",468              "2            0            0             0             4           0   \n",469              "3            0            0             0             0           0   \n",470              "4            0            0             0             0           2   \n",471              "\n",472              "   total_runs  player_dismissed dismissal_kind fielder  \n",473              "0           0               NaN            NaN     NaN  \n",474              "1           0               NaN            NaN     NaN  \n",475              "2           4               NaN            NaN     NaN  \n",476              "3           0               NaN            NaN     NaN  \n",477              "4           2               NaN            NaN     NaN  \n",478              "\n",479              "[5 rows x 21 columns]"480            ],481            "text/html": [482              "\n",483              "  <div id=\"df-d287ac09-c86c-4dd7-b871-fc044f186c90\">\n",484              "    <div class=\"colab-df-container\">\n",485              "      <div>\n",486              "<style scoped>\n",487              "    .dataframe tbody tr th:only-of-type {\n",488              "        vertical-align: middle;\n",489              "    }\n",490              "\n",491              "    .dataframe tbody tr th {\n",492              "        vertical-align: top;\n",493              "    }\n",494              "\n",495              "    .dataframe thead th {\n",496              "        text-align: right;\n",497              "    }\n",498              "</style>\n",499              "<table border=\"1\" class=\"dataframe\">\n",500              "  <thead>\n",501              "    <tr style=\"text-align: right;\">\n",502              "      <th></th>\n",503              "      <th>match_id</th>\n",504              "      <th>inning</th>\n",505              "      <th>batting_team</th>\n",506              "      <th>bowling_team</th>\n",507              "      <th>over</th>\n",508              "      <th>ball</th>\n",509              "      <th>batsman</th>\n",510              "      <th>non_striker</th>\n",511              "      <th>bowler</th>\n",512              "      <th>is_super_over</th>\n",513              "      <th>...</th>\n",514              "      <th>bye_runs</th>\n",515              "      <th>legbye_runs</th>\n",516              "      <th>noball_runs</th>\n",517              "      <th>penalty_runs</th>\n",518              "      <th>batsman_runs</th>\n",519              "      <th>extra_runs</th>\n",520              "      <th>total_runs</th>\n",521              "      <th>player_dismissed</th>\n",522              "      <th>dismissal_kind</th>\n",523              "      <th>fielder</th>\n",524              "    </tr>\n",525              "  </thead>\n",526              "  <tbody>\n",527              "    <tr>\n",528              "      <th>0</th>\n",529              "      <td>1</td>\n",530              "      <td>1</td>\n",531              "      <td>Sunrisers Hyderabad</td>\n",532              "      <td>Royal Challengers Bangalore</td>\n",533              "      <td>1</td>\n",534              "      <td>1</td>\n",535              "      <td>DA Warner</td>\n",536              "      <td>S Dhawan</td>\n",537              "      <td>TS Mills</td>\n",538              "      <td>0</td>\n",539              "      <td>...</td>\n",540              "      <td>0</td>\n",541              "      <td>0</td>\n",542              "      <td>0</td>\n",543              "      <td>0</td>\n",544              "      <td>0</td>\n",545              "      <td>0</td>\n",546              "      <td>0</td>\n",547              "      <td>NaN</td>\n",548              "      <td>NaN</td>\n",549              "      <td>NaN</td>\n",550              "    </tr>\n",551              "    <tr>\n",552              "      <th>1</th>\n",553              "      <td>1</td>\n",554              "      <td>1</td>\n",555              "      <td>Sunrisers Hyderabad</td>\n",556              "      <td>Royal Challengers Bangalore</td>\n",557              "      <td>1</td>\n",558              "      <td>2</td>\n",559              "      <td>DA Warner</td>\n",560              "      <td>S Dhawan</td>\n",561              "      <td>TS Mills</td>\n",562              "      <td>0</td>\n",563              "      <td>...</td>\n",564              "      <td>0</td>\n",565              "      <td>0</td>\n",566              "      <td>0</td>\n",567              "      <td>0</td>\n",568              "      <td>0</td>\n",569              "      <td>0</td>\n",570              "      <td>0</td>\n",571              "      <td>NaN</td>\n",572              "      <td>NaN</td>\n",573              "      <td>NaN</td>\n",574              "    </tr>\n",575              "    <tr>\n",576              "      <th>2</th>\n",577              "      <td>1</td>\n",578              "      <td>1</td>\n",579              "      <td>Sunrisers Hyderabad</td>\n",580              "      <td>Royal Challengers Bangalore</td>\n",581              "      <td>1</td>\n",582              "      <td>3</td>\n",583              "      <td>DA Warner</td>\n",584              "      <td>S Dhawan</td>\n",585              "      <td>TS Mills</td>\n",586              "      <td>0</td>\n",587              "      <td>...</td>\n",588              "      <td>0</td>\n",589              "      <td>0</td>\n",590              "      <td>0</td>\n",591              "      <td>0</td>\n",592              "      <td>4</td>\n",593              "      <td>0</td>\n",594              "      <td>4</td>\n",595              "      <td>NaN</td>\n",596              "      <td>NaN</td>\n",597              "      <td>NaN</td>\n",598              "    </tr>\n",599              "    <tr>\n",600              "      <th>3</th>\n",601              "      <td>1</td>\n",602              "      <td>1</td>\n",603              "      <td>Sunrisers Hyderabad</td>\n",604              "      <td>Royal Challengers Bangalore</td>\n",605              "      <td>1</td>\n",606              "      <td>4</td>\n",607              "      <td>DA Warner</td>\n",608              "      <td>S Dhawan</td>\n",609              "      <td>TS Mills</td>\n",610              "      <td>0</td>\n",611              "      <td>...</td>\n",612              "      <td>0</td>\n",613              "      <td>0</td>\n",614              "      <td>0</td>\n",615              "      <td>0</td>\n",616              "      <td>0</td>\n",617              "      <td>0</td>\n",618              "      <td>0</td>\n",619              "      <td>NaN</td>\n",620              "      <td>NaN</td>\n",621              "      <td>NaN</td>\n",622              "    </tr>\n",623              "    <tr>\n",624              "      <th>4</th>\n",625              "      <td>1</td>\n",626              "      <td>1</td>\n",627              "      <td>Sunrisers Hyderabad</td>\n",628              "      <td>Royal Challengers Bangalore</td>\n",629              "      <td>1</td>\n",630              "      <td>5</td>\n",631              "      <td>DA Warner</td>\n",632              "      <td>S Dhawan</td>\n",633              "      <td>TS Mills</td>\n",634              "      <td>0</td>\n",635              "      <td>...</td>\n",636              "      <td>0</td>\n",637              "      <td>0</td>\n",638              "      <td>0</td>\n",639              "      <td>0</td>\n",640              "      <td>0</td>\n",641              "      <td>2</td>\n",642              "      <td>2</td>\n",643              "      <td>NaN</td>\n",644              "      <td>NaN</td>\n",645              "      <td>NaN</td>\n",646              "    </tr>\n",647              "  </tbody>\n",648              "</table>\n",649              "<p>5 rows × 21 columns</p>\n",650              "</div>\n",651              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d287ac09-c86c-4dd7-b871-fc044f186c90')\"\n",652              "              title=\"Convert this dataframe to an interactive table.\"\n",653              "              style=\"display:none;\">\n",654              "        \n",655              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",656              "       width=\"24px\">\n",657              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",658              "    <path d=\"M18.56 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50%;\n",673              "      cursor: pointer;\n",674              "      display: none;\n",675              "      fill: #1967D2;\n",676              "      height: 32px;\n",677              "      padding: 0 0 0 0;\n",678              "      width: 32px;\n",679              "    }\n",680              "\n",681              "    .colab-df-convert:hover {\n",682              "      background-color: #E2EBFA;\n",683              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",684              "      fill: #174EA6;\n",685              "    }\n",686              "\n",687              "    [theme=dark] .colab-df-convert {\n",688              "      background-color: #3B4455;\n",689              "      fill: #D2E3FC;\n",690              "    }\n",691              "\n",692              "    [theme=dark] .colab-df-convert:hover {\n",693              "      background-color: #434B5C;\n",694              "      box-shadow: 0px 1px 3px 1px 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'block' : 'none';\n",705              "\n",706              "        async function convertToInteractive(key) {\n",707              "          const element = document.querySelector('#df-d287ac09-c86c-4dd7-b871-fc044f186c90');\n",708              "          const dataTable =\n",709              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",710              "                                                     [key], {});\n",711              "          if (!dataTable) return;\n",712              "\n",713              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",714              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",715              "            + ' to learn more about interactive tables.';\n",716              "          element.innerHTML = '';\n",717              "          dataTable['output_type'] = 'display_data';\n",718              "          await google.colab.output.renderOutput(dataTable, element);\n",719              "          const docLink = document.createElement('div');\n",720              "          docLink.innerHTML = docLinkHtml;\n",721              "          element.appendChild(docLink);\n",722              "        }\n",723              "      </script>\n",724              "    </div>\n",725              "  </div>\n",726              "  "727            ]728          },729          "metadata": {},730          "execution_count": 35731        }732      ]733    },734    {735      "cell_type": "code",736      "source": [737        "total_score_df=delivery.groupby(['match_id','inning']).sum()['total_runs'].reset_index()"738      ],739      "metadata": {740        "id": "YX4u0npV_t3O"741      },742      "execution_count": 36,743      "outputs": []744    },745    {746      "cell_type": "code",747      "source": [748        "total_score_df=total_score_df[total_score_df['inning']==1]"749      ],750      "metadata": {751        "id": "rZGLNlIyAYIW"752      },753      "execution_count": 37,754      "outputs": []755    },756    {757      "cell_type": "code",758      "source": [759        "match_df=match.merge(total_score_df[['match_id','total_runs']],left_on='id',right_on='match_id')"760      ],761      "metadata": {762        "id": "da3fK7jYAupu"763      },764      "execution_count": 38,765      "outputs": []766    },767    {768      "cell_type": "code",769      "source": [770        "match_df['team1'].unique()"771      ],772      "metadata": {773        "colab": {774          "base_uri": "https://localhost:8080/"775        },776        "id": "vvVxwWR_BL7W",777        "outputId": "52152b25-ce02-4708-b597-6a58054aaa63"778      },779      "execution_count": 39,780      "outputs": [781        {782          "output_type": "execute_result",783          "data": {784            "text/plain": [785              "array(['Sunrisers Hyderabad', 'Mumbai Indians', 'Gujarat Lions',\n",786              "       'Rising Pune Supergiant', 'Royal Challengers Bangalore',\n",787              "       'Kolkata Knight Riders', 'Delhi Daredevils', 'Kings XI Punjab',\n",788              "       'Chennai Super Kings', 'Rajasthan Royals', 'Deccan Chargers',\n",789              "       'Kochi Tuskers Kerala', 'Pune Warriors', 'Rising Pune Supergiants',\n",790              "       'Delhi Capitals'], dtype=object)"791            ]792          },793          "metadata": {},794          "execution_count": 39795        }796      ]797    },798    {799      "cell_type": "code",800      "source": [801        "teams = [\n",802        "    'Sunrisers Hyderabad',\n",803        "    'Mumbai Indians',\n",804        "    'Royal Challengers Bangalore',\n",805        "    'Kolkata Knight Riders',\n",806        "    'Kings XI Punjab',\n",807        "    'Chennai Super Kings',\n",808        "    'Rajasthan Royals',\n",809        "    'Delhi Capitals'\n",810        "]"811      ],812      "metadata": {813        "id": "KeE4TTjBBRzE"814      },815      "execution_count": 40,816      "outputs": []817    },818    {819      "cell_type": "code",820      "source": [821        "match_df['team1'] = match_df['team1'].str.replace('Delhi Daredevils','Delhi Capitals')\n",822        "match_df['team2'] = match_df['team2'].str.replace('Delhi Daredevils','Delhi Capitals')\n",823        "\n",824        "match_df['team1'] = match_df['team1'].str.replace('Deccan Chargers','Sunrisers Hyderabad')\n",825        "match_df['team2'] = match_df['team2'].str.replace('Deccan Chargers','Sunrisers Hyderabad')"826      ],827      "metadata": {828        "id": "HiwfbPdxB5qe"829      },830      "execution_count": 41,831      "outputs": []832    },833    {834      "cell_type": "code",835      "source": [836        "match_df = match_df[match_df['team1'].isin(teams)]\n",837        "match_df = match_df[match_df['team2'].isin(teams)]"838      ],839      "metadata": {840        "id": "wl9bWaQEB67e"841      },842      "execution_count": 42,843      "outputs": []844    },845    {846      "cell_type": "code",847      "source": [848        "match_df.shape"849      ],850      "metadata": {851        "colab": {852          "base_uri": "https://localhost:8080/"853        },854        "id": "9ZTX_L3hB9X3",855        "outputId": "fe97ab3d-d917-48b5-9c95-c714bfff15c7"856      },857      "execution_count": 43,858      "outputs": [859        {860          "output_type": "execute_result",861          "data": {862            "text/plain": [863              "(641, 20)"864            ]865          },866          "metadata": {},867          "execution_count": 43868        }869      ]870    },871    {872      "cell_type": "code",873      "source": [874        "match_df=match_df[match_df['dl_applied']==0]"875      ],876      "metadata": {877        "id": "G840rx92B-dO"878      },879      "execution_count": 44,880      "outputs": []881    },882    {883      "cell_type": "code",884      "source": [885        "match_df = match_df[['match_id','city','winner','total_runs']]"886      ],887      "metadata": {888        "id": "osdGWtZCCZQ9"889      },890      "execution_count": 46,891      "outputs": []892    },893    {894      "cell_type": "code",895      "source": [896        "delivery_df=match_df.merge(delivery,on='match_id')"897      ],898      "metadata": {899        "id": "Dn-EcbTTCbD6"900      },901      "execution_count": 48,902      "outputs": []903    },904    {905      "cell_type": "code",906      "source": [907        "delivery_df=delivery_df[delivery_df['inning']==2]"908      ],909      "metadata": {910        "id": "FUxwOB-bCyml"911      },912      "execution_count": 50,913      "outputs": []914    },915    {916      "cell_type": "code",917      "source": [918        "delivery_df['current_score']=delivery_df.groupby('match_id').cumsum()['total_runs_y']"919      ],920      "metadata": {921        "id": "C6tuuE6JC_Ge"922      },923      "execution_count": 52,924      "outputs": []925    },926    {927      "cell_type": "code",928      "source": [929        "delivery_df['runs_left']=delivery_df['total_runs_x']-delivery_df['current_score']"930      ],931      "metadata": {932        "id": "PEbxpPssDbmx"933      },934      "execution_count": 54,935      "outputs": []936    },937    {938      "cell_type": "code",939      "source": [940        "delivery_df['balls_left'] = 126 - (delivery_df['over']*6 + delivery_df['ball'])"941      ],942      "metadata": {943        "id": "ZN7PAJfxDoND"944      },945      "execution_count": 56,946      "outputs": []947    },948    {949      "cell_type": "code",950      "source": [951        "delivery_df['player_dismissed']=delivery_df['player_dismissed'].fillna(\"0\")\n",952        "delivery_df['player_dismissed']=delivery_df['player_dismissed'].apply(lambda x:x if x==\"0\" else \"1\")\n",953        "delivery_df['player_dismissed']=delivery_df['player_dismissed'].astype('int')\n",954        "wickets=delivery_df.groupby('match_id').cumsum()['player_dismissed'].values\n",955        "delivery_df['wickets']=10-wickets\n"956      ],957      "metadata": {958        "id": "Tmn6xx2VEeSI"959      },960      "execution_count": 58,961      "outputs": []962    },963    {964      "cell_type": "code",965      "source": [966        "delivery_df['crr'] = (delivery_df['current_score']*6)/(120 - delivery_df['balls_left'])"967      ],968      "metadata": {969        "id": "xw1E6hfmG2SN"970      },971      "execution_count": 60,972      "outputs": []973    },974    {975      "cell_type": "code",976      "source": [977        "delivery_df['rrr'] = (delivery_df['runs_left']*6)/delivery_df['balls_left']"978      ],979      "metadata": {980        "id": "Eua3yfcuG34P"981      },982      "execution_count": 61,983      "outputs": []984    },985    {986      "cell_type": "code",987      "source": [988        "def result(row):\n",989        "    return 1 if row['batting_team'] == row['winner'] else 0"990      ],991      "metadata": {992        "id": "NmGWwEVVHZbT"993      },994      "execution_count": 62,995      "outputs": []996    },997    {998      "cell_type": "code",999      "source": [1000        "delivery_df['result'] = delivery_df.apply(result,axis=1)"1001      ],1002      "metadata": {1003        "id": "rjul4hXWHk3a"1004      },1005      "execution_count": 63,1006      "outputs": []1007    },1008    {1009      "cell_type": "code",1010      "source": [1011        "final_df = delivery_df[['batting_team','bowling_team','city','runs_left','balls_left','wickets','total_runs_x','crr','rrr','result']]"1012      ],1013      "metadata": {1014        "id": "cwCjWuCUHnPj"1015      },1016      "execution_count": 66,1017      "outputs": []1018    },1019    {1020      "cell_type": "code",1021      "source": [1022        "final_df=final_df.sample(final_df.shape[0])"1023      ],1024      "metadata": {1025        "id": "ywcx2XLJHpKE"1026      },1027      "execution_count": 67,1028      "outputs": []1029    },1030    {1031      "cell_type": "code",1032      "source": [1033        "final_df.sample()"1034      ],1035      "metadata": {1036        "colab": {1037          "base_uri": "https://localhost:8080/",1038          "height": 811039        },1040        "id": "fYy4oxNlIvuR",1041        "outputId": "76e56250-10b0-406a-91bf-7ba31cdd8813"1042      },1043      "execution_count": 68,1044      "outputs": [1045        {1046          "output_type": "execute_result",1047          "data": {1048            "text/plain": [1049              "           batting_team         bowling_team    city  runs_left  balls_left  \\\n",1050              "20128  Rajasthan Royals  Chennai Super Kings  Mumbai        137          98   \n",1051              "\n",1052              "       wickets  total_runs_x       crr       rrr  result  \n",1053              "20128        9           163  7.090909  8.387755       1  "1054            ],1055            "text/html": [1056              "\n",1057              "  <div id=\"df-019e3217-71d5-4c56-b8d9-c1b1da0e2182\">\n",1058              "    <div class=\"colab-df-container\">\n",1059              "      <div>\n",1060              "<style scoped>\n",1061              "    .dataframe tbody tr th:only-of-type {\n",1062              "        vertical-align: middle;\n",1063              "    }\n",1064              "\n",1065              "    .dataframe tbody tr th {\n",1066              "        vertical-align: top;\n",1067              "    }\n",1068              "\n",1069              "    .dataframe thead th {\n",1070              "        text-align: right;\n",1071         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   <td>Mumbai</td>\n",1095              "      <td>137</td>\n",1096              "      <td>98</td>\n",1097              "      <td>9</td>\n",1098              "      <td>163</td>\n",1099              "      <td>7.090909</td>\n",1100              "      <td>8.387755</td>\n",1101              "      <td>1</td>\n",1102              "    </tr>\n",1103              "  </tbody>\n",1104              "</table>\n",1105              "</div>\n",1106              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-019e3217-71d5-4c56-b8d9-c1b1da0e2182')\"\n",1107              "              title=\"Convert this dataframe to an interactive table.\"\n",1108              "              style=\"display:none;\">\n",1109              "        \n",1110              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",1111              "       width=\"24px\">\n",1112              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",1113              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         "      border-radius: 50%;\n",1128              "      cursor: pointer;\n",1129              "      display: none;\n",1130              "      fill: #1967D2;\n",1131              "      height: 32px;\n",1132              "      padding: 0 0 0 0;\n",1133              "      width: 32px;\n",1134              "    }\n",1135              "\n",1136              "    .colab-df-convert:hover {\n",1137              "      background-color: #E2EBFA;\n",1138              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",1139              "      fill: #174EA6;\n",1140              "    }\n",1141              "\n",1142              "    [theme=dark] .colab-df-convert {\n",1143              "      background-color: #3B4455;\n",1144              "      fill: #D2E3FC;\n",1145              "    }\n",1146              "\n",1147              "    [theme=dark] .colab-df-convert:hover {\n",1148              "      background-color: #434B5C;\n",1149              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",1150              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",1151              "      fill: #FFFFFF;\n",1152              "    }\n",1153              "  </style>\n",1154              "\n",1155              "      <script>\n",1156              "        const buttonEl =\n",1157              "          document.querySelector('#df-019e3217-71d5-4c56-b8d9-c1b1da0e2182 button.colab-df-convert');\n",1158              "        buttonEl.style.display =\n",1159              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",1160              "\n",1161              "        async function convertToInteractive(key) {\n",1162              "          const element = document.querySelector('#df-019e3217-71d5-4c56-b8d9-c1b1da0e2182');\n",1163              "          const dataTable =\n",1164              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",1165              "                                                     [key], {});\n",1166              "          if (!dataTable) return;\n",1167              "\n",1168              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",1169              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",1170              "            + ' to learn more about interactive tables.';\n",1171              "          element.innerHTML = '';\n",1172              "          dataTable['output_type'] = 'display_data';\n",1173              "          await google.colab.output.renderOutput(dataTable, element);\n",1174              "          const docLink = document.createElement('div');\n",1175              "          docLink.innerHTML = docLinkHtml;\n",1176              "          element.appendChild(docLink);\n",1177              "        }\n",1178              "      </script>\n",1179              "    </div>\n",1180              "  </div>\n",1181              "  "1182            ]1183          },1184          "metadata": {},1185          "execution_count": 681186        }1187      ]1188    },1189    {1190      "cell_type": "code",1191      "source": [1192        "final_df.dropna(inplace=True)"1193      ],1194      "metadata": {1195        "id": "BQkY9wd3IxE9"1196      },1197      "execution_count": 69,1198      "outputs": []1199    },1200    {

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