Virat_Kohli's_Performance.ipynb

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        "#importing Libraries\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import plotly.express as px\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.model_selection import train_test_split"
      ]
    },
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      "cell_type": "markdown",
      "source": [
        "#Preprocessing"
      ],
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      "source": [
        "## Dataset"
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      "source": [
        "deli = pd.read_csv(\"/content/deliveries.csv\")"
      ]
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              "   match_id   season  start_date                             venue  innings  \\\n",
              "0         1  2023/24  2023-10-05  Narendra Modi Stadium, Ahmedabad        1   \n",
              "\n",
              "   ball batting_team bowling_team      striker non_striker  ... extras  wides  \\\n",
              "0   0.1      England  New Zealand  JM Bairstow    DJ Malan  ...      0    NaN   \n",
              "\n",
              "   noballs  byes  legbyes  penalty  wicket_type  player_dismissed  \\\n",
              "0      NaN   NaN      NaN      NaN          NaN               NaN   \n",
              "\n",
              "  other_wicket_type other_player_dismissed  \n",
              "0               NaN                    NaN  \n",
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        "deli.head(1)"
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              "    season    team1        team2        date  match_number  \\\n",
              "0  2023/24  England  New Zealand  2023/10/05             1   \n",
              "\n",
              "                   venue       city  toss_winner toss_decision  \\\n",
              "0  Narendra Modi Stadium  Ahmedabad  New Zealand         field   \n",
              "\n",
              "  player_of_match          umpire1      umpire2 reserve_umpire match_referee  \\\n",
              "0      R Ravindra  HDPK Dharmasena  Nitin Menon   Sharfuddoula     J Srinath   \n",
              "\n",
              "        winner  winner_runs  winner_wickets match_type  \n",
              "0  New Zealand          NaN             9.0      Group  "
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        "matches = pd.read_csv(\"/content/matches.csv\")\n",
        "matches.head(1)"
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              "   Ranking          Team  Matches  Won  Lost  Tie  No Results  Points  \\\n",
              "0        1  South Africa        7    6     1    0           0      12   \n",
              "1        2         India        6    6     0    0           0      12   \n",
              "2        3     Australia        6    4     2    0           0       8   \n",
              "3        4   New Zealand        7    4     3    0           0       8   \n",
              "4        5      Pakistan        7    3     4    0           0       6   \n",
              "5        6   Afghanistan        6    3     3    0           0       6   \n",
              "6        7     Sri Lanka        6    2     4    0           0       4   \n",
              "7        8   Netherlands        6    2     4    0           0       4   \n",
              "8        9    Bangladesh        7    1     6    0           0       2   \n",
              "9       10       England        6    1     5    0           0       2   \n",
              "\n",
              "   Net Run Rate Series Form        Next Match         For     Against  \n",
              "0         2.290       LWWWW       vs IND, AFG  2355/340.2  1588/343.0  \n",
              "1         1.405       WWWWW    vs SL, SA, NED  1430/246.2  1320/300.0  \n",
              "2         0.970       LWWWW  vs ENG, AFG, BAN  1745/285.2  1499/291.2  \n",
              "3         0.484       WWLLL        vs PAK, SL  1964/329.1  1908/348.0  \n",
              "4        -0.024       LLLLW        vs NZ, ENG  1884/330.5  1869/326.5  \n",
              "5        -0.718       LWLWW   vs NED, AUS, SA  1379/294.2  1457/269.4  \n",
              "6        -0.275       LLWWL   vs IND, BAN, NZ  1543/274.0  1648/279.0  \n",
              "7        -1.277       LWLLW  vs AFG, ENG, IND  1254/293.0  1619/291.2  \n",
              "8        -1.446       LLLLL        vs SL, AUS  1465/334.4  1845/316.5  \n",
              "9        -1.652       WLLLL  vs AUS, NED, PAK  1316/300.0  1582/262.0  "
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              "      <th>Won</th>\n",
              "      <th>Lost</th>\n",
              "      <th>Tie</th>\n",
              "      <th>No Results</th>\n",
              "      <th>Points</th>\n",
              "      <th>Net Run Rate</th>\n",
              "      <th>Series Form</th>\n",
              "      <th>Next Match</th>\n",
              "      <th>For</th>\n",
              "      <th>Against</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>South Africa</td>\n",
              "      <td>7</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>12</td>\n",
              "      <td>2.290</td>\n",
              "      <td>LWWWW</td>\n",
              "      <td>vs IND, AFG</td>\n",
              "      <td>2355/340.2</td>\n",
              "      <td>1588/343.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>India</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>12</td>\n",
              "      <td>1.405</td>\n",
              "      <td>WWWWW</td>\n",
              "      <td>vs SL, SA, NED</td>\n",
              "      <td>1430/246.2</td>\n",
              "      <td>1320/300.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>Australia</td>\n",
              "      <td>6</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>8</td>\n",
              "      <td>0.970</td>\n",
              "      <td>LWWWW</td>\n",
              "      <td>vs ENG, AFG, BAN</td>\n",
              "      <td>1745/285.2</td>\n",
              "      <td>1499/291.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>New Zealand</td>\n",
              "      <td>7</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>8</td>\n",
              "      <td>0.484</td>\n",
              "      <td>WWLLL</td>\n",
              "      <td>vs PAK, SL</td>\n",
              "      <td>1964/329.1</td>\n",
              "      <td>1908/348.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>Pakistan</td>\n",
              "      <td>7</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>-0.024</td>\n",
              "      <td>LLLLW</td>\n",
              "      <td>vs NZ, ENG</td>\n",
              "      <td>1884/330.5</td>\n",
              "      <td>1869/326.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>6</td>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>6</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>-0.718</td>\n",
              "      <td>LWLWW</td>\n",
              "      <td>vs NED, AUS, SA</td>\n",
              "      <td>1379/294.2</td>\n",
              "      <td>1457/269.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>7</td>\n",
              "      <td>Sri Lanka</td>\n",
              "      <td>6</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>-0.275</td>\n",
              "      <td>LLWWL</td>\n",
              "      <td>vs IND, BAN, NZ</td>\n",
              "      <td>1543/274.0</td>\n",
              "      <td>1648/279.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>8</td>\n",
              "      <td>Netherlands</td>\n",
              "      <td>6</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>-1.277</td>\n",
              "      <td>LWLLW</td>\n",
              "      <td>vs AFG, ENG, IND</td>\n",
              "      <td>1254/293.0</td>\n",
              "      <td>1619/291.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>9</td>\n",
              "      <td>Bangladesh</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>-1.446</td>\n",
              "      <td>LLLLL</td>\n",
              "      <td>vs SL, AUS</td>\n",
              "      <td>1465/334.4</td>\n",
              "      <td>1845/316.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>10</td>\n",
              "      <td>England</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>-1.652</td>\n",
              "      <td>WLLLL</td>\n",
              "      <td>vs AUS, NED, PAK</td>\n",
              "      <td>1316/300.0</td>\n",
              "      <td>1582/262.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-95114a68-1710-4113-8534-cda872dc9a69')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-95114a68-1710-4113-8534-cda872dc9a69 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-95114a68-1710-4113-8534-cda872dc9a69');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-7ca3e5c8-7573-4b92-b6d6-105a47ea7aff\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-7ca3e5c8-7573-4b92-b6d6-105a47ea7aff')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-7ca3e5c8-7573-4b92-b6d6-105a47ea7aff button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 136
        }
      ],
      "source": [
        "points = pd.read_csv(\"/content/points_table.csv\")\n",
        "points"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:58.501358Z",
          "iopub.status.busy": "2023-11-03T07:55:58.500673Z",
          "iopub.status.idle": "2023-11-03T07:55:58.509553Z",
          "shell.execute_reply": "2023-11-03T07:55:58.508142Z",
          "shell.execute_reply.started": "2023-11-03T07:55:58.501315Z"
        },
        "id": "2fz2PYXM1qHG",
        "outputId": "56af7f27-bfb9-4c77-9098-9c4d29fea87a",
        "trusted": true
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['match_id', 'season', 'start_date', 'venue', 'innings', 'ball',\n",
              "       'batting_team', 'bowling_team', 'striker', 'non_striker', 'bowler',\n",
              "       'runs_off_bat', 'extras', 'wides', 'noballs', 'byes', 'legbyes',\n",
              "       'penalty', 'wicket_type', 'player_dismissed', 'other_wicket_type',\n",
              "       'other_player_dismissed'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 137
        }
      ],
      "source": [
        "deli.columns"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:58.511566Z",
          "iopub.status.busy": "2023-11-03T07:55:58.511126Z",
          "iopub.status.idle": "2023-11-03T07:55:58.522671Z",
          "shell.execute_reply": "2023-11-03T07:55:58.521344Z",
          "shell.execute_reply.started": "2023-11-03T07:55:58.511525Z"
        },
        "id": "JuEqA7U-9TrD",
        "outputId": "58727962-32d0-454b-924c-8a9e0015419c",
        "trusted": true
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['season', 'team1', 'team2', 'date', 'match_number', 'venue', 'city',\n",
              "       'toss_winner', 'toss_decision', 'player_of_match', 'umpire1', 'umpire2',\n",
              "       'reserve_umpire', 'match_referee', 'winner', 'winner_runs',\n",
              "       'winner_wickets', 'match_type'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 138
        }
      ],
      "source": [
        "matches.columns"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Missing value handling"
      ],
      "metadata": {
        "id": "UR1__-18j8G9"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:58.54157Z",
          "iopub.status.busy": "2023-11-03T07:55:58.541108Z",
          "iopub.status.idle": "2023-11-03T07:55:58.547971Z",
          "shell.execute_reply": "2023-11-03T07:55:58.546931Z",
          "shell.execute_reply.started": "2023-11-03T07:55:58.541537Z"
        },
        "id": "lsBF07ViALRa",
        "trusted": true
      },
      "outputs": [],
      "source": [
        "#renaming columns in matches\n",
        "matches.rename(columns={\"match_number\":\"match_id\", \"start_date\":\"date\"}, inplace=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:58.550219Z",
          "iopub.status.busy": "2023-11-03T07:55:58.549462Z",
          "iopub.status.idle": "2023-11-03T07:55:58.575392Z",
          "shell.execute_reply": "2023-11-03T07:55:58.574383Z",
          "shell.execute_reply.started": "2023-11-03T07:55:58.550174Z"
        },
        "id": "r-aRWCFvAgTE",
        "outputId": "77684eff-4a66-4e48-e7ec-a827e078b08b",
        "trusted": true
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "match_id                      0\n",
              "season                        0\n",
              "start_date                    0\n",
              "venue                         0\n",
              "innings                       0\n",
              "ball                          0\n",
              "batting_team                  0\n",
              "bowling_team                  0\n",
              "striker                       0\n",
              "non_striker                   0\n",
              "bowler                        0\n",
              "runs_off_bat                  0\n",
              "extras                        0\n",
              "wides                     16949\n",
              "noballs                   17338\n",
              "byes                      17354\n",
              "legbyes                   17263\n",
              "penalty                   17379\n",
              "wicket_type               16889\n",
              "player_dismissed          16889\n",
              "other_wicket_type         17380\n",
              "other_player_dismissed    17380\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 140
        }
      ],
      "source": [
        "deli.isna().sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:58.579679Z",
          "iopub.status.busy": "2023-11-03T07:55:58.579328Z",
          "iopub.status.idle": "2023-11-03T07:55:58.595586Z",
          "shell.execute_reply": "2023-11-03T07:55:58.594328Z",
          "shell.execute_reply.started": "2023-11-03T07:55:58.579651Z"
        },
        "id": "MEqcRB2rfb5j",
        "trusted": true
      },
      "outputs": [],
      "source": [
        "#creating a wicket column to get boolean of wicket fall\n",
        "deli[\"wicket\"] = deli[\"player_dismissed\"].apply(lambda x: 1 if isinstance(x, str) else 0)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:58.59728Z",
          "iopub.status.busy": "2023-11-03T07:55:58.596915Z",
          "iopub.status.idle": "2023-11-03T07:55:58.647244Z",
          "shell.execute_reply": "2023-11-03T07:55:58.646128Z",
          "shell.execute_reply.started": "2023-11-03T07:55:58.597249Z"
        },
        "id": "96zl54UefivJ",
        "outputId": "b454d85f-4391-471a-99e4-55191635d3c5",
        "trusted": true
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0        0\n",
              "1        0\n",
              "2        0\n",
              "3        0\n",
              "4        0\n",
              "        ..\n",
              "17375    0\n",
              "17376    0\n",
              "17377    0\n",
              "17378    0\n",
              "17379    1\n",
              "Name: wicket, Length: 17380, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 142
        }
      ],
      "source": [
        "deli[\"wicket\"]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:58.649902Z",
          "iopub.status.busy": "2023-11-03T07:55:58.648685Z",
          "iopub.status.idle": "2023-11-03T07:55:58.660847Z",
          "shell.execute_reply": "2023-11-03T07:55:58.65935Z",
          "shell.execute_reply.started": "2023-11-03T07:55:58.649853Z"
        },
        "id": "GIBxS1ctAup7",
        "trusted": true
      },
      "outputs": [],
      "source": [
        "#filling na values\n",
        "deli[[\"wides\", \"noballs\", \"byes\", \"legbyes\", \"penalty\"]] = deli[[\"wides\", \"noballs\", \"byes\", \"legbyes\", \"penalty\"]].fillna(0)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:58.662991Z",
          "iopub.status.busy": "2023-11-03T07:55:58.662431Z",
          "iopub.status.idle": "2023-11-03T07:55:58.671754Z",
          "shell.execute_reply": "2023-11-03T07:55:58.670122Z",
          "shell.execute_reply.started": "2023-11-03T07:55:58.662947Z"
        },
        "id": "kK-dXXWbFITs",
        "trusted": true
      },
      "outputs": [],
      "source": [
        "deli.wicket_type.fillna(\"no wicket\", inplace=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:58.673819Z",
          "iopub.status.busy": "2023-11-03T07:55:58.673364Z",
          "iopub.status.idle": "2023-11-03T07:55:58.686722Z",
          "shell.execute_reply": "2023-11-03T07:55:58.685825Z",
          "shell.execute_reply.started": "2023-11-03T07:55:58.673774Z"
        },
        "id": "KOmjt5sxJFK1",
        "trusted": true
      },
      "outputs": [],
      "source": [
        "deli.player_dismissed.fillna(\"no wicket\", inplace=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:58.689111Z",
          "iopub.status.busy": "2023-11-03T07:55:58.688714Z",
          "iopub.status.idle": "2023-11-03T07:55:58.706391Z",
          "shell.execute_reply": "2023-11-03T07:55:58.704516Z",
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        },
        "id": "_ovEPH85JN8n",
        "trusted": true
      },
      "outputs": [],
      "source": [
        "deli[[\"other_wicket_type\", \"other_player_dismissed\"]] = deli[[\"other_wicket_type\", \"other_player_dismissed\"]].fillna(\"no dismissal\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:58.709132Z",
          "iopub.status.busy": "2023-11-03T07:55:58.708618Z",
          "iopub.status.idle": "2023-11-03T07:55:58.732512Z",
          "shell.execute_reply": "2023-11-03T07:55:58.731431Z",
          "shell.execute_reply.started": "2023-11-03T07:55:58.709086Z"
        },
        "id": "lj_W_kIRBeiV",
        "outputId": "7cf700e7-be41-4def-f06f-5d7b91678a07",
        "trusted": true
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "match_id                  0\n",
              "season                    0\n",
              "start_date                0\n",
              "venue                     0\n",
              "innings                   0\n",
              "ball                      0\n",
              "batting_team              0\n",
              "bowling_team              0\n",
              "striker                   0\n",
              "non_striker               0\n",
              "bowler                    0\n",
              "runs_off_bat              0\n",
              "extras                    0\n",
              "wides                     0\n",
              "noballs                   0\n",
              "byes                      0\n",
              "legbyes                   0\n",
              "penalty                   0\n",
              "wicket_type               0\n",
              "player_dismissed          0\n",
              "other_wicket_type         0\n",
              "other_player_dismissed    0\n",
              "wicket                    0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 147
        }
      ],
      "source": [
        "deli.isna().sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:58.733929Z",
          "iopub.status.busy": "2023-11-03T07:55:58.733586Z",
          "iopub.status.idle": "2023-11-03T07:55:58.744364Z",
          "shell.execute_reply": "2023-11-03T07:55:58.743151Z",
          "shell.execute_reply.started": "2023-11-03T07:55:58.7339Z"
        },
        "id": "1SYfSRehJB48",
        "outputId": "b8ec4bb6-56da-4014-880f-d2655aa8ee38",
        "trusted": true
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "season              0\n",
              "team1               0\n",
              "team2               0\n",
              "date                0\n",
              "match_id            0\n",
              "venue               0\n",
              "city                0\n",
              "toss_winner         0\n",
              "toss_decision       0\n",
              "player_of_match     0\n",
              "umpire1             0\n",
              "umpire2             0\n",
              "reserve_umpire      1\n",
              "match_referee       0\n",
              "winner              0\n",
              "winner_runs        16\n",
              "winner_wickets     16\n",
              "match_type          0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 148
        }
      ],
      "source": [
        "matches.isna().sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:58.747262Z",
          "iopub.status.busy": "2023-11-03T07:55:58.745739Z",
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          "shell.execute_reply": "2023-11-03T07:55:58.756012Z",
          "shell.execute_reply.started": "2023-11-03T07:55:58.747222Z"
        },
        "id": "-X6EY8vbR5H5",
        "trusted": true
      },
      "outputs": [],
      "source": [
        "matches.rename(columns={\"winner_runs\":\"win_by_runs\", \"winner_wickets\":\"win_by_wickets\"}, inplace=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:58.76002Z",
          "iopub.status.busy": "2023-11-03T07:55:58.759629Z",
          "iopub.status.idle": "2023-11-03T07:55:58.774759Z",
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        },
        "id": "Z3Lgw106TEBS",
        "trusted": true
      },
      "outputs": [],
      "source": [
        "matches.win_by_runs.fillna(0, inplace=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:58.777795Z",
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          "shell.execute_reply.started": "2023-11-03T07:55:58.777752Z"
        },
        "id": "_Ja-mBogTUpK",
        "trusted": true
      },
      "outputs": [],
      "source": [
        "matches.win_by_wickets.fillna(0, inplace=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:58.789096Z",
          "iopub.status.busy": "2023-11-03T07:55:58.788655Z",
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        },
        "id": "zVOXgk0caoTh",
        "trusted": true
      },
      "outputs": [],
      "source": [
        "matches.reserve_umpire.fillna(\"unknown\", inplace=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:58.802344Z",
          "iopub.status.busy": "2023-11-03T07:55:58.801943Z",
          "iopub.status.idle": "2023-11-03T07:55:58.817551Z",
          "shell.execute_reply": "2023-11-03T07:55:58.816141Z",
          "shell.execute_reply.started": "2023-11-03T07:55:58.80231Z"
        },
        "id": "Wh9Kr_gOavOo",
        "outputId": "acaa5021-0255-4268-99fe-f182dd008634",
        "trusted": true
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "season             0\n",
              "team1              0\n",
              "team2              0\n",
              "date               0\n",
              "match_id           0\n",
              "venue              0\n",
              "city               0\n",
              "toss_winner        0\n",
              "toss_decision      0\n",
              "player_of_match    0\n",
              "umpire1            0\n",
              "umpire2            0\n",
              "reserve_umpire     0\n",
              "match_referee      0\n",
              "winner             0\n",
              "win_by_runs        0\n",
              "win_by_wickets     0\n",
              "match_type         0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 153
        }
      ],
      "source": [
        "matches.isna().sum()"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Data Aggregation"
      ],
      "metadata": {
        "id": "DpJkNj7ulL8G"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:58.820462Z",
          "iopub.status.busy": "2023-11-03T07:55:58.819651Z",
          "iopub.status.idle": "2023-11-03T07:55:58.873808Z",
          "shell.execute_reply": "2023-11-03T07:55:58.872182Z",
          "shell.execute_reply.started": "2023-11-03T07:55:58.820416Z"
        },
        "id": "S4MfD4jagiKe",
        "trusted": true
      },
      "outputs": [],
      "source": [
        "#creating over and balls from ball column which is in 0.1, 0.2 format for first over\n",
        "deli[\"ball\"] = deli[\"ball\"].astype(str)\n",
        "deli[[\"over\", \"ball_num\"]] = deli[\"ball\"].str.split(\".\", expand=True).astype(int)\n",
        "deli[\"ball\"] = deli[\"ball\"].astype(float)\n",
        "deli[\"over\"] = deli[\"over\"] + 1\n",
        "deli[\"ball_left\"] = 306 - (deli[\"over\"]*6 + deli[\"ball_num\"])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:58.876031Z",
          "iopub.status.busy": "2023-11-03T07:55:58.875484Z",
          "iopub.status.idle": "2023-11-03T07:55:58.883352Z",
          "shell.execute_reply": "2023-11-03T07:55:58.881814Z",
          "shell.execute_reply.started": "2023-11-03T07:55:58.875953Z"
        },
        "id": "iLVqMrlFax0P",
        "trusted": true
      },
      "outputs": [],
      "source": [
        "#creating total runs column to calculate runs on each ball incusive of extras\n",
        "deli[\"total_runs\"] = deli[\"runs_off_bat\"] + deli[\"extras\"]"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Innings Dataset"
      ],
      "metadata": {
        "id": "vxMPaLxy3aN-"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:58.885856Z",
          "iopub.status.busy": "2023-11-03T07:55:58.884839Z",
          "iopub.status.idle": "2023-11-03T07:55:58.902009Z",
          "shell.execute_reply": "2023-11-03T07:55:58.900902Z",
          "shell.execute_reply.started": "2023-11-03T07:55:58.885817Z"
        },
        "id": "jdBl4k4y40FM",
        "trusted": true
      },
      "outputs": [],
      "source": [
        "#creating innings df so we can merger total runs for each innings with in original df\n",
        "innings = deli.groupby([\"match_id\", \"innings\"])[\"total_runs\"].sum().reset_index()\n",
        "innings.rename(columns={\"total_runs\":\"innings_total\"}, inplace=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "a3m-zPv2jyci",
        "outputId": "38147183-a881-4938-e776-3a88dc2923c6"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    match_id  innings  innings_total\n",
              "0          1        1            282\n",
              "1          1        2            283\n",
              "2          2        1            286\n",
              "3          2        2            205\n",
              "4          3        1            156\n",
              "..       ...      ...            ...\n",
              "59        30        2            242\n",
              "60        31        1            204\n",
              "61        31        2            205\n",
              "62        32        1            357\n",
              "63        32        2            167\n",
              "\n",
              "[64 rows x 3 columns]"
            ],
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              "\n",
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              "      <td>32</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>63</th>\n",
              "      <td>32</td>\n",
              "      <td>2</td>\n",
              "      <td>167</td>\n",
              "    </tr>\n",
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              "<p>64 rows × 3 columns</p>\n",
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              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-49341106-b3a3-4188-9fcf-ba8c459e9102 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-49341106-b3a3-4188-9fcf-ba8c459e9102');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-4ce93118-bdbf-4f57-a934-8d12014e9d80\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-4ce93118-bdbf-4f57-a934-8d12014e9d80')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-4ce93118-bdbf-4f57-a934-8d12014e9d80 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 157
        }
      ],
      "source": [
        "innings"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 182
        },
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:58.90447Z",
          "iopub.status.busy": "2023-11-03T07:55:58.903395Z",
          "iopub.status.idle": "2023-11-03T07:55:58.961003Z",
          "shell.execute_reply": "2023-11-03T07:55:58.959442Z",
          "shell.execute_reply.started": "2023-11-03T07:55:58.90441Z"
        },
        "id": "Hp_iOT2UOpUQ",
        "outputId": "2e15830c-3783-4bc3-bfc5-932fdee6ea08",
        "trusted": true
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   match_id   season  start_date                             venue  innings  \\\n",
              "0         1  2023/24  2023-10-05  Narendra Modi Stadium, Ahmedabad        1   \n",
              "\n",
              "   ball batting_team bowling_team      striker non_striker  ... wicket_type  \\\n",
              "0   0.1      England  New Zealand  JM Bairstow    DJ Malan  ...   no wicket   \n",
              "\n",
              "   player_dismissed  other_wicket_type  other_player_dismissed  wicket  over  \\\n",
              "0         no wicket       no dismissal            no dismissal       0     1   \n",
              "\n",
              "   ball_num  ball_left total_runs innings_total  \n",
              "0         1        299          0           282  \n",
              "\n",
              "[1 rows x 28 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-e9a4e82b-f02f-4a8d-8979-36c1e0af990b\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>match_id</th>\n",
              "      <th>season</th>\n",
              "      <th>start_date</th>\n",
              "      <th>venue</th>\n",
              "      <th>innings</th>\n",
              "      <th>ball</th>\n",
              "      <th>batting_team</th>\n",
              "      <th>bowling_team</th>\n",
              "      <th>striker</th>\n",
              "      <th>non_striker</th>\n",
              "      <th>...</th>\n",
              "      <th>wicket_type</th>\n",
              "      <th>player_dismissed</th>\n",
              "      <th>other_wicket_type</th>\n",
              "      <th>other_player_dismissed</th>\n",
              "      <th>wicket</th>\n",
              "      <th>over</th>\n",
              "      <th>ball_num</th>\n",
              "      <th>ball_left</th>\n",
              "      <th>total_runs</th>\n",
              "      <th>innings_total</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>2023/24</td>\n",
              "      <td>2023-10-05</td>\n",
              "      <td>Narendra Modi Stadium, Ahmedabad</td>\n",
              "      <td>1</td>\n",
              "      <td>0.1</td>\n",
              "      <td>England</td>\n",
              "      <td>New Zealand</td>\n",
              "      <td>JM Bairstow</td>\n",
              "      <td>DJ Malan</td>\n",
              "      <td>...</td>\n",
              "      <td>no wicket</td>\n",
              "      <td>no wicket</td>\n",
              "      <td>no dismissal</td>\n",
              "      <td>no dismissal</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>299</td>\n",
              "      <td>0</td>\n",
              "      <td>282</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1 rows × 28 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e9a4e82b-f02f-4a8d-8979-36c1e0af990b')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-e9a4e82b-f02f-4a8d-8979-36c1e0af990b button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-e9a4e82b-f02f-4a8d-8979-36c1e0af990b');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 158
        }
      ],
      "source": [
        "#creating deliveries df and adding total runs\n",
        "deliveries = deli.merge(innings, on=[\"match_id\", \"innings\"])\n",
        "deliveries.head(1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:58.963259Z",
          "iopub.status.busy": "2023-11-03T07:55:58.962569Z",
          "iopub.status.idle": "2023-11-03T07:55:58.971587Z",
          "shell.execute_reply": "2023-11-03T07:55:58.970392Z",
          "shell.execute_reply.started": "2023-11-03T07:55:58.963221Z"
        },
        "id": "wSs6jQBKQvZK",
        "trusted": true
      },
      "outputs": [],
      "source": [
        "#calculating cumulative runs\n",
        "deliveries[\"cumulative_runs\"] = deliveries.groupby([\"match_id\", \"innings\"])[\"total_runs\"].cumsum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 182
        },
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:58.979926Z",
          "iopub.status.busy": "2023-11-03T07:55:58.979495Z",
          "iopub.status.idle": "2023-11-03T07:55:59.025353Z",
          "shell.execute_reply": "2023-11-03T07:55:59.023706Z",
          "shell.execute_reply.started": "2023-11-03T07:55:58.979894Z"
        },
        "id": "wTVZCRz8SCsY",
        "outputId": "5712e0d1-051b-47ad-965d-472bb1a148e8",
        "trusted": true
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   match_id   season  start_date                             venue  innings  \\\n",
              "0         1  2023/24  2023-10-05  Narendra Modi Stadium, Ahmedabad        1   \n",
              "\n",
              "   ball batting_team bowling_team      striker non_striker  ...  \\\n",
              "0   0.1      England  New Zealand  JM Bairstow    DJ Malan  ...   \n",
              "\n",
              "  player_dismissed  other_wicket_type  other_player_dismissed  wicket  over  \\\n",
              "0        no wicket       no dismissal            no dismissal       0     1   \n",
              "\n",
              "   ball_num  ball_left  total_runs innings_total cumulative_runs  \n",
              "0         1        299           0           282               0  \n",
              "\n",
              "[1 rows x 29 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-27d9b7ff-d688-4a3f-93b2-b6ec4d58a1ec\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>match_id</th>\n",
              "      <th>season</th>\n",
              "      <th>start_date</th>\n",
              "      <th>venue</th>\n",
              "      <th>innings</th>\n",
              "      <th>ball</th>\n",
              "      <th>batting_team</th>\n",
              "      <th>bowling_team</th>\n",
              "      <th>striker</th>\n",
              "      <th>non_striker</th>\n",
              "      <th>...</th>\n",
              "      <th>player_dismissed</th>\n",
              "      <th>other_wicket_type</th>\n",
              "      <th>other_player_dismissed</th>\n",
              "      <th>wicket</th>\n",
              "      <th>over</th>\n",
              "      <th>ball_num</th>\n",
              "      <th>ball_left</th>\n",
              "      <th>total_runs</th>\n",
              "      <th>innings_total</th>\n",
              "      <th>cumulative_runs</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>2023/24</td>\n",
              "      <td>2023-10-05</td>\n",
              "      <td>Narendra Modi Stadium, Ahmedabad</td>\n",
              "      <td>1</td>\n",
              "      <td>0.1</td>\n",
              "      <td>England</td>\n",
              "      <td>New Zealand</td>\n",
              "      <td>JM Bairstow</td>\n",
              "      <td>DJ Malan</td>\n",
              "      <td>...</td>\n",
              "      <td>no wicket</td>\n",
              "      <td>no dismissal</td>\n",
              "      <td>no dismissal</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>299</td>\n",
              "      <td>0</td>\n",
              "      <td>282</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1 rows × 29 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-27d9b7ff-d688-4a3f-93b2-b6ec4d58a1ec')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
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          "metadata": {},
          "execution_count": 160
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      ],
      "source": [
        "deliveries.head(1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:59.027896Z",
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          "shell.execute_reply": "2023-11-03T07:55:59.090586Z",
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        },
        "id": "tIpTXscvSJ43",
        "trusted": true
      },
      "outputs": [],
      "source": [
        "#creating run rate column\n",
        "deliveries[\"run_rate\"] = deliveries.groupby([\"match_id\",\"innings\"]).apply(lambda x: (x[\"cumulative_runs\"]*6)/(300-x[\"ball_left\"])).reset_index(level=[0,1], drop=True)"
      ]
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    {
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        "outputId": "4d250311-5044-4014-9aaa-33fe1b32bdf2",
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        {
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            "text/plain": [
              "   match_id   season  start_date                             venue  innings  \\\n",
              "0         1  2023/24  2023-10-05  Narendra Modi Stadium, Ahmedabad        1   \n",
              "\n",
              "   ball batting_team bowling_team      striker non_striker  ...  \\\n",
              "0   0.1      England  New Zealand  JM Bairstow    DJ Malan  ...   \n",
              "\n",
              "  other_wicket_type  other_player_dismissed  wicket  over  ball_num  \\\n",
              "0      no dismissal            no dismissal       0     1         1   \n",
              "\n",
              "   ball_left  total_runs  innings_total cumulative_runs run_rate  \n",
              "0        299           0            282               0      0.0  \n",
              "\n",
              "[1 rows x 30 columns]"
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              "      <th>0</th>\n",
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              "      <td>2023/24</td>\n",
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              "                                                    [key], {});\n",
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              "\n",
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              "          + ' to learn more about interactive tables.';\n",
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          "metadata": {},
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        }
      ],
      "source": [
        "deliveries.head(1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:59.139928Z",
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      "source": [
        "#filtering for innings1 and 2 so we can add some columns respectively\n",
        "innings_1 = deliveries[deliveries[\"innings\"] == 1]\n",
        "\n",
        "innings_1 = innings_1.groupby(\"match_id\")[\"cumulative_runs\"].max().reset_index()\n",
        "innings_1.rename(columns={\"cumulative_runs\": \"target\"}, inplace=True)\n",
        "\n",
        "innings_2 = deliveries[deliveries[\"innings\"] == 2]\n",
        "innings_2 = innings_2.merge(innings_1, on=\"match_id\", how=\"left\")\n",
        "innings_2[\"target\"] = innings_2[\"target\"]+1"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
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        "id": "VAIUkVX5l9K-",
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              "    match_id  target\n",
              "0          1     282\n",
              "1          2     286\n",
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              "22        23     382\n",
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              "26        27     388\n",
              "27        28     229\n",
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              "    60% {\n",
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              "      border-right-color: var(--fill-color);\n",
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              "    90% {\n",
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              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
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              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
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              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "        console.error('Error during call to suggestCharts:', error);\n",
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              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "    (() => {\n",
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              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 164
        }
      ],
      "source": [
        "innings_1"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "2UYdH_1xlCh-",
        "outputId": "f504261c-1f16-40cc-bd5c-83ed39aa51bf"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      match_id   season  start_date  \\\n",
              "0            1  2023/24  2023-10-05   \n",
              "1            1  2023/24  2023-10-05   \n",
              "2            1  2023/24  2023-10-05   \n",
              "3            1  2023/24  2023-10-05   \n",
              "4            1  2023/24  2023-10-05   \n",
              "...        ...      ...         ...   \n",
              "7882        32  2023/24  2023-11-01   \n",
              "7883        32  2023/24  2023-11-01   \n",
              "7884        32  2023/24  2023-11-01   \n",
              "7885        32  2023/24  2023-11-01   \n",
              "7886        32  2023/24  2023-11-01   \n",
              "\n",
              "                                              venue  innings  ball  \\\n",
              "0                  Narendra Modi Stadium, Ahmedabad        2   0.1   \n",
              "1                  Narendra Modi Stadium, Ahmedabad        2   0.2   \n",
              "2                  Narendra Modi Stadium, Ahmedabad        2   0.3   \n",
              "3                  Narendra Modi Stadium, Ahmedabad        2   0.4   \n",
              "4                  Narendra Modi Stadium, Ahmedabad        2   0.5   \n",
              "...                                             ...      ...   ...   \n",
              "7882  Maharashtra Cricket Association Stadium, Pune        2  34.5   \n",
              "7883  Maharashtra Cricket Association Stadium, Pune        2  34.6   \n",
              "7884  Maharashtra Cricket Association Stadium, Pune        2  35.1   \n",
              "7885  Maharashtra Cricket Association Stadium, Pune        2  35.2   \n",
              "7886  Maharashtra Cricket Association Stadium, Pune        2  35.3   \n",
              "\n",
              "     batting_team  bowling_team      striker  non_striker  ...  \\\n",
              "0     New Zealand       England    DP Conway     WA Young  ...   \n",
              "1     New Zealand       England    DP Conway     WA Young  ...   \n",
              "2     New Zealand       England    DP Conway     WA Young  ...   \n",
              "3     New Zealand       England    DP Conway     WA Young  ...   \n",
              "4     New Zealand       England    DP Conway     WA Young  ...   \n",
              "...           ...           ...          ...          ...  ...   \n",
              "7882  New Zealand  South Africa     MJ Henry  GD Phillips  ...   \n",
              "7883  New Zealand  South Africa     MJ Henry  GD Phillips  ...   \n",
              "7884  New Zealand  South Africa  GD Phillips     MJ Henry  ...   \n",
              "7885  New Zealand  South Africa  GD Phillips     MJ Henry  ...   \n",
              "7886  New Zealand  South Africa  GD Phillips     MJ Henry  ...   \n",
              "\n",
              "     other_player_dismissed  wicket  over  ball_num  ball_left  total_runs  \\\n",
              "0              no dismissal       0     1         1        299           4   \n",
              "1              no dismissal       0     1         2        298           0   \n",
              "2              no dismissal       0     1         3        297           0   \n",
              "3              no dismissal       0     1         4        296           2   \n",
              "4              no dismissal       0     1         5        295           4   \n",
              "...                     ...     ...   ...       ...        ...         ...   \n",
              "7882           no dismissal       0    35         5         91           0   \n",
              "7883           no dismissal       0    35         6         90           0   \n",
              "7884           no dismissal       0    36         1         89           0   \n",
              "7885           no dismissal       0    36         2         88           6   \n",
              "7886           no dismissal       1    36         3         87           0   \n",
              "\n",
              "      innings_total  cumulative_runs   run_rate target  \n",
              "0               283                4  24.000000    283  \n",
              "1               283                4  12.000000    283  \n",
              "2               283                4   8.000000    283  \n",
              "3               283                6   9.000000    283  \n",
              "4               283               10  12.000000    283  \n",
              "...             ...              ...        ...    ...  \n",
              "7882            167              161   4.622010    358  \n",
              "7883            167              161   4.600000    358  \n",
              "7884            167              161   4.578199    358  \n",
              "7885            167              167   4.726415    358  \n",
              "7886            167              167   4.704225    358  \n",
              "\n",
              "[7887 rows x 31 columns]"
            ],
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              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>match_id</th>\n",
              "      <th>season</th>\n",
              "      <th>start_date</th>\n",
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              "      <th>ball</th>\n",
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              "      <th>...</th>\n",
              "      <th>other_player_dismissed</th>\n",
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              "      <th>total_runs</th>\n",
              "      <th>innings_total</th>\n",
              "      <th>cumulative_runs</th>\n",
              "      <th>run_rate</th>\n",
              "      <th>target</th>\n",
              "    </tr>\n",
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              "      <th>0</th>\n",
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              "      <td>DP Conway</td>\n",
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              "      <td>2</td>\n",
              "      <td>0.2</td>\n",
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              "      <td>DP Conway</td>\n",
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              "      <td>England</td>\n",
              "      <td>DP Conway</td>\n",
              "      <td>WA Young</td>\n",
              "      <td>...</td>\n",
              "      <td>no dismissal</td>\n",
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              "      <td>1</td>\n",
              "      <td>3</td>\n",
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              "      <td>DP Conway</td>\n",
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              "      <td>1</td>\n",
              "      <td>2023/24</td>\n",
              "      <td>2023-10-05</td>\n",
              "      <td>Narendra Modi Stadium, Ahmedabad</td>\n",
              "      <td>2</td>\n",
              "      <td>0.5</td>\n",
              "      <td>New Zealand</td>\n",
              "      <td>England</td>\n",
              "      <td>DP Conway</td>\n",
              "      <td>WA Young</td>\n",
              "      <td>...</td>\n",
              "      <td>no dismissal</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
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              "      <td>4</td>\n",
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              "      <td>10</td>\n",
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              "      <td>283</td>\n",
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              "    <tr>\n",
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              "      <td>GD Phillips</td>\n",
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              "      <td>35</td>\n",
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              "      <td>0</td>\n",
              "      <td>167</td>\n",
              "      <td>161</td>\n",
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              "      <td>2023/24</td>\n",
              "      <td>2023-11-01</td>\n",
              "      <td>Maharashtra Cricket Association Stadium, Pune</td>\n",
              "      <td>2</td>\n",
              "      <td>34.6</td>\n",
              "      <td>New Zealand</td>\n",
              "      <td>South Africa</td>\n",
              "      <td>MJ Henry</td>\n",
              "      <td>GD Phillips</td>\n",
              "      <td>...</td>\n",
              "      <td>no dismissal</td>\n",
              "      <td>0</td>\n",
              "      <td>35</td>\n",
              "      <td>6</td>\n",
              "      <td>90</td>\n",
              "      <td>0</td>\n",
              "      <td>167</td>\n",
              "      <td>161</td>\n",
              "      <td>4.600000</td>\n",
              "      <td>358</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7884</th>\n",
              "      <td>32</td>\n",
              "      <td>2023/24</td>\n",
              "      <td>2023-11-01</td>\n",
              "      <td>Maharashtra Cricket Association Stadium, Pune</td>\n",
              "      <td>2</td>\n",
              "      <td>35.1</td>\n",
              "      <td>New Zealand</td>\n",
              "      <td>South Africa</td>\n",
              "      <td>GD Phillips</td>\n",
              "      <td>MJ Henry</td>\n",
              "      <td>...</td>\n",
              "      <td>no dismissal</td>\n",
              "      <td>0</td>\n",
              "      <td>36</td>\n",
              "      <td>1</td>\n",
              "      <td>89</td>\n",
              "      <td>0</td>\n",
              "      <td>167</td>\n",
              "      <td>161</td>\n",
              "      <td>4.578199</td>\n",
              "      <td>358</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7885</th>\n",
              "      <td>32</td>\n",
              "      <td>2023/24</td>\n",
              "      <td>2023-11-01</td>\n",
              "      <td>Maharashtra Cricket Association Stadium, Pune</td>\n",
              "      <td>2</td>\n",
              "      <td>35.2</td>\n",
              "      <td>New Zealand</td>\n",
              "      <td>South Africa</td>\n",
              "      <td>GD Phillips</td>\n",
              "      <td>MJ Henry</td>\n",
              "      <td>...</td>\n",
              "      <td>no dismissal</td>\n",
              "      <td>0</td>\n",
              "      <td>36</td>\n",
              "      <td>2</td>\n",
              "      <td>88</td>\n",
              "      <td>6</td>\n",
              "      <td>167</td>\n",
              "      <td>167</td>\n",
              "      <td>4.726415</td>\n",
              "      <td>358</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7886</th>\n",
              "      <td>32</td>\n",
              "      <td>2023/24</td>\n",
              "      <td>2023-11-01</td>\n",
              "      <td>Maharashtra Cricket Association Stadium, Pune</td>\n",
              "      <td>2</td>\n",
              "      <td>35.3</td>\n",
              "      <td>New Zealand</td>\n",
              "      <td>South Africa</td>\n",
              "      <td>GD Phillips</td>\n",
              "      <td>MJ Henry</td>\n",
              "      <td>...</td>\n",
              "      <td>no dismissal</td>\n",
              "      <td>1</td>\n",
              "      <td>36</td>\n",
              "      <td>3</td>\n",
              "      <td>87</td>\n",
              "      <td>0</td>\n",
              "      <td>167</td>\n",
              "      <td>167</td>\n",
              "      <td>4.704225</td>\n",
              "      <td>358</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>7887 rows × 31 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
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              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
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              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
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              "      height: 32px;\n",
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              "    .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "    .colab-df-buttons div {\n",
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              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "      const buttonEl =\n",
              "        document.querySelector('#df-4ae08d3d-5c6d-4384-a52b-cd2584f6999c button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "      async function convertToInteractive(key) {\n",
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              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
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              "        element.appendChild(docLink);\n",
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              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-65f58b35-1f8f-4c59-9716-0ce622590469')\"\n",
              "            title=\"Suggest charts\"\n",
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              "\n",
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              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
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              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
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              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
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              "    30% {\n",
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              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
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              "    40% {\n",
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              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-65f58b35-1f8f-4c59-9716-0ce622590469 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 165
        }
      ],
      "source": [
        "innings_2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:59.164652Z",
          "iopub.status.busy": "2023-11-03T07:55:59.163668Z",
          "iopub.status.idle": "2023-11-03T07:55:59.171312Z",
          "shell.execute_reply": "2023-11-03T07:55:59.170293Z",
          "shell.execute_reply.started": "2023-11-03T07:55:59.164619Z"
        },
        "id": "JOIWA-hJUc50",
        "trusted": true
      },
      "outputs": [],
      "source": [
        "#adding runs needed and rrr to innings 2\n",
        "innings_2[\"runs_needed\"] = innings_2[\"target\"] - innings_2[\"cumulative_runs\"]\n",
        "innings_2[\"required_run_rate\"] = (innings_2[\"runs_needed\"]*6) / innings_2[\"ball_left\"]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:59.173286Z",
          "iopub.status.busy": "2023-11-03T07:55:59.172393Z",
          "iopub.status.idle": "2023-11-03T07:55:59.196974Z",
          "shell.execute_reply": "2023-11-03T07:55:59.196133Z",
          "shell.execute_reply.started": "2023-11-03T07:55:59.173248Z"
        },
        "id": "yDor9j_JbwCg",
        "outputId": "efcc6d33-776a-42bb-ad70-31b29a7be1b9",
        "trusted": true
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-167-fab78a54e010>:2: FutureWarning: Not prepending group keys to the result index of transform-like apply. In the future, the group keys will be included in the index, regardless of whether the applied function returns a like-indexed object.\n",
            "To preserve the previous behavior, use\n",
            "\n",
            "\t>>> .groupby(..., group_keys=False)\n",
            "\n",
            "To adopt the future behavior and silence this warning, use \n",
            "\n",
            "\t>>> .groupby(..., group_keys=True)\n",
            "  innings_2[\"wickets_remaining\"] = innings_2.groupby(\"match_id\")[\"wicket\"].apply(lambda x: 10 - x.cumsum()).reset_index(level=0, drop=True)\n"
          ]
        }
      ],
      "source": [
        "#adding wickets remaining to innings 2\n",
        "innings_2[\"wickets_remaining\"] = innings_2.groupby(\"match_id\")[\"wicket\"].apply(lambda x: 10 - x.cumsum()).reset_index(level=0, drop=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:59.198691Z",
          "iopub.status.busy": "2023-11-03T07:55:59.198192Z",
          "iopub.status.idle": "2023-11-03T07:55:59.20701Z",
          "shell.execute_reply": "2023-11-03T07:55:59.205523Z",
          "shell.execute_reply.started": "2023-11-03T07:55:59.198662Z"
        },
        "id": "sN1biHb9Smll",
        "trusted": true
      },
      "outputs": [],
      "source": [
        "#innings 1 data\n",
        "innings_1_f = deliveries[deliveries[\"innings\"] == 1]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:59.20939Z",
          "iopub.status.busy": "2023-11-03T07:55:59.208992Z",
          "iopub.status.idle": "2023-11-03T07:55:59.232392Z",
          "shell.execute_reply": "2023-11-03T07:55:59.230218Z",
          "shell.execute_reply.started": "2023-11-03T07:55:59.209359Z"
        },
        "id": "thtRThXGkciS",
        "outputId": "8c0c9c8c-c58d-4815-8274-2930ce7d6b98",
        "trusted": true
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-169-39f3819f533a>:2: FutureWarning: Not prepending group keys to the result index of transform-like apply. In the future, the group keys will be included in the index, regardless of whether the applied function returns a like-indexed object.\n",
            "To preserve the previous behavior, use\n",
            "\n",
            "\t>>> .groupby(..., group_keys=False)\n",
            "\n",
            "To adopt the future behavior and silence this warning, use \n",
            "\n",
            "\t>>> .groupby(..., group_keys=True)\n",
            "  innings_1_f[\"wickets_remaining\"] = innings_1_f.groupby(\"match_id\")[\"wicket\"].apply(lambda x: 10 - x.cumsum()).reset_index(level=0, drop=True)\n",
            "<ipython-input-169-39f3819f533a>:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  innings_1_f[\"wickets_remaining\"] = innings_1_f.groupby(\"match_id\")[\"wicket\"].apply(lambda x: 10 - x.cumsum()).reset_index(level=0, drop=True)\n"
          ]
        }
      ],
      "source": [
        "#adding wickets remaining\n",
        "innings_1_f[\"wickets_remaining\"] = innings_1_f.groupby(\"match_id\")[\"wicket\"].apply(lambda x: 10 - x.cumsum()).reset_index(level=0, drop=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:59.234245Z",
          "iopub.status.busy": "2023-11-03T07:55:59.233772Z",
          "iopub.status.idle": "2023-11-03T07:55:59.248934Z",
          "shell.execute_reply": "2023-11-03T07:55:59.247396Z",
          "shell.execute_reply.started": "2023-11-03T07:55:59.234203Z"
        },
        "id": "EALJ1IJsSx01",
        "trusted": true
      },
      "outputs": [],
      "source": [
        "#concatinating innings1,2\n",
        "innings = pd.concat([innings_1_f,innings_2])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "mHj9Ih68ma4A",
        "outputId": "17532488-ac19-4a0e-f0dd-8641da587943"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      match_id   season  start_date  \\\n",
              "0            1  2023/24  2023-10-05   \n",
              "1            1  2023/24  2023-10-05   \n",
              "2            1  2023/24  2023-10-05   \n",
              "3            1  2023/24  2023-10-05   \n",
              "4            1  2023/24  2023-10-05   \n",
              "...        ...      ...         ...   \n",
              "7882        32  2023/24  2023-11-01   \n",
              "7883        32  2023/24  2023-11-01   \n",
              "7884        32  2023/24  2023-11-01   \n",
              "7885        32  2023/24  2023-11-01   \n",
              "7886        32  2023/24  2023-11-01   \n",
              "\n",
              "                                              venue  innings  ball  \\\n",
              "0                  Narendra Modi Stadium, Ahmedabad        1   0.1   \n",
              "1                  Narendra Modi Stadium, Ahmedabad        1   0.2   \n",
              "2                  Narendra Modi Stadium, Ahmedabad        1   0.3   \n",
              "3                  Narendra Modi Stadium, Ahmedabad        1   0.4   \n",
              "4                  Narendra Modi Stadium, Ahmedabad        1   0.5   \n",
              "...                                             ...      ...   ...   \n",
              "7882  Maharashtra Cricket Association Stadium, Pune        2  34.5   \n",
              "7883  Maharashtra Cricket Association Stadium, Pune        2  34.6   \n",
              "7884  Maharashtra Cricket Association Stadium, Pune        2  35.1   \n",
              "7885  Maharashtra Cricket Association Stadium, Pune        2  35.2   \n",
              "7886  Maharashtra Cricket Association Stadium, Pune        2  35.3   \n",
              "\n",
              "     batting_team  bowling_team      striker  non_striker  ... ball_num  \\\n",
              "0         England   New Zealand  JM Bairstow     DJ Malan  ...        1   \n",
              "1         England   New Zealand  JM Bairstow     DJ Malan  ...        2   \n",
              "2         England   New Zealand  JM Bairstow     DJ Malan  ...        3   \n",
              "3         England   New Zealand     DJ Malan  JM Bairstow  ...        4   \n",
              "4         England   New Zealand  JM Bairstow     DJ Malan  ...        5   \n",
              "...           ...           ...          ...          ...  ...      ...   \n",
              "7882  New Zealand  South Africa     MJ Henry  GD Phillips  ...        5   \n",
              "7883  New Zealand  South Africa     MJ Henry  GD Phillips  ...        6   \n",
              "7884  New Zealand  South Africa  GD Phillips     MJ Henry  ...        1   \n",
              "7885  New Zealand  South Africa  GD Phillips     MJ Henry  ...        2   \n",
              "7886  New Zealand  South Africa  GD Phillips     MJ Henry  ...        3   \n",
              "\n",
              "      ball_left  total_runs  innings_total  cumulative_runs   run_rate  \\\n",
              "0           299           0            282                0   0.000000   \n",
              "1           298           6            282                6  18.000000   \n",
              "2           297           1            282                7  14.000000   \n",
              "3           296           1            282                8  12.000000   \n",
              "4           295           4            282               12  14.400000   \n",
              "...         ...         ...            ...              ...        ...   \n",
              "7882         91           0            167              161   4.622010   \n",
              "7883         90           0            167              161   4.600000   \n",
              "7884         89           0            167              161   4.578199   \n",
              "7885         88           6            167              167   4.726415   \n",
              "7886         87           0            167              167   4.704225   \n",
              "\n",
              "      wickets_remaining  target runs_needed required_run_rate  \n",
              "0                  10.0     NaN         NaN               NaN  \n",
              "1                  10.0     NaN         NaN               NaN  \n",
              "2                  10.0     NaN         NaN               NaN  \n",
              "3                  10.0     NaN         NaN               NaN  \n",
              "4                  10.0     NaN         NaN               NaN  \n",
              "...                 ...     ...         ...               ...  \n",
              "7882                1.0   358.0       197.0         12.989011  \n",
              "7883                1.0   358.0       197.0         13.133333  \n",
              "7884                1.0   358.0       197.0         13.280899  \n",
              "7885                1.0   358.0       191.0         13.022727  \n",
              "7886                0.0   358.0       191.0         13.172414  \n",
              "\n",
              "[17380 rows x 34 columns]"
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              "      <td>2023-11-01</td>\n",
              "      <td>Maharashtra Cricket Association Stadium, Pune</td>\n",
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              "      <td>Maharashtra Cricket Association Stadium, Pune</td>\n",
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              "      <td>35.1</td>\n",
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              "      <td>GD Phillips</td>\n",
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              "      <td>35.2</td>\n",
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              "      <td>35.3</td>\n",
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              "      <td>13.172414</td>\n",
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              "<p>17380 rows × 34 columns</p>\n",
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              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-e521942e-829f-462d-b34e-eb84cd57c87e button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 173
        }
      ],
      "source": [
        "innings"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DBwa5_00HL9t",
        "outputId": "2492eac2-2d2a-4ddd-ebef-cc58f68f47c6"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['match_id', 'season', 'start_date', 'venue', 'innings', 'ball',\n",
              "       'batting_team', 'bowling_team', 'striker', 'non_striker', 'bowler',\n",
              "       'runs_off_bat', 'extras', 'wides', 'noballs', 'byes', 'legbyes',\n",
              "       'penalty', 'wicket_type', 'player_dismissed', 'other_wicket_type',\n",
              "       'other_player_dismissed', 'wicket', 'over', 'ball_num', 'ball_left',\n",
              "       'total_runs', 'innings_total', 'cumulative_runs', 'run_rate',\n",
              "       'wickets_remaining', 'target', 'runs_needed', 'required_run_rate'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 174
        }
      ],
      "source": [
        "innings.columns"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:59.278485Z",
          "iopub.status.busy": "2023-11-03T07:55:59.278036Z",
          "iopub.status.idle": "2023-11-03T07:55:59.286187Z",
          "shell.execute_reply": "2023-11-03T07:55:59.284628Z",
          "shell.execute_reply.started": "2023-11-03T07:55:59.278452Z"
        },
        "id": "KKxYQlv9TqEV",
        "outputId": "6de071e1-0b60-4c2a-e286-8325e92b37da",
        "trusted": true
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "17380"
            ]
          },
          "metadata": {},
          "execution_count": 175
        }
      ],
      "source": [
        "len(innings)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:59.288321Z",
          "iopub.status.busy": "2023-11-03T07:55:59.287961Z",
          "iopub.status.idle": "2023-11-03T07:55:59.30986Z",
          "shell.execute_reply": "2023-11-03T07:55:59.308303Z",
          "shell.execute_reply.started": "2023-11-03T07:55:59.288288Z"
        },
        "id": "98V8QGpZWQjM",
        "trusted": true
      },
      "outputs": [],
      "source": [
        "innings.fillna(0, inplace=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:59.33541Z",
          "iopub.status.busy": "2023-11-03T07:55:59.335017Z",
          "iopub.status.idle": "2023-11-03T07:55:59.364251Z",
          "shell.execute_reply": "2023-11-03T07:55:59.362668Z",
          "shell.execute_reply.started": "2023-11-03T07:55:59.335379Z"
        },
        "id": "bBC8TK4ixdz_",
        "trusted": true
      },
      "outputs": [],
      "source": [
        "#merging with matches data to get winners and other data that can help our model\n",
        "innings = innings.merge(matches[[\"match_id\",\"winner\", \"win_by_runs\", \"win_by_wickets\"]], on=\"match_id\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:59.365993Z",
          "iopub.status.busy": "2023-11-03T07:55:59.365646Z",
          "iopub.status.idle": "2023-11-03T07:55:59.376146Z",
          "shell.execute_reply": "2023-11-03T07:55:59.374383Z",
          "shell.execute_reply.started": "2023-11-03T07:55:59.365964Z"
        },
        "id": "fdBIkMSrxOJf",
        "outputId": "100605d1-76ab-4a83-cdf4-cb13c818f9e2",
        "trusted": true
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['season', 'team1', 'team2', 'date', 'match_id', 'venue', 'city',\n",
              "       'toss_winner', 'toss_decision', 'player_of_match', 'umpire1', 'umpire2',\n",
              "       'reserve_umpire', 'match_referee', 'winner', 'win_by_runs',\n",
              "       'win_by_wickets', 'match_type'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 178
        }
      ],
      "source": [
        "matches.columns"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:59.3779Z",
          "iopub.status.busy": "2023-11-03T07:55:59.377474Z",
          "iopub.status.idle": "2023-11-03T07:55:59.617621Z",
          "shell.execute_reply": "2023-11-03T07:55:59.616668Z",
          "shell.execute_reply.started": "2023-11-03T07:55:59.377863Z"
        },
        "id": "yCfpZiiMtkZR",
        "trusted": true
      },
      "outputs": [],
      "source": [
        "#adding result column\n",
        "innings[\"result\"] = innings.apply(lambda x: 1 if x[\"batting_team\"] == x[\"winner\"] else 0, axis=1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:59.622357Z",
          "iopub.status.busy": "2023-11-03T07:55:59.621898Z",
          "iopub.status.idle": "2023-11-03T07:55:59.646057Z",
          "shell.execute_reply": "2023-11-03T07:55:59.644747Z",
          "shell.execute_reply.started": "2023-11-03T07:55:59.622321Z"
        },
        "id": "sZhREJlH_Hyz",
        "trusted": true
      },
      "outputs": [],
      "source": [
        "#making the data random to avoid overfitting\n",
        "# innings = innings.sample(frac=1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "bSgDPy12qTIg",
        "outputId": "19969f0b-5c08-454c-a3fc-c3e4ba484fd8"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       match_id   season  start_date  \\\n",
              "0             1  2023/24  2023-10-05   \n",
              "1             1  2023/24  2023-10-05   \n",
              "2             1  2023/24  2023-10-05   \n",
              "3             1  2023/24  2023-10-05   \n",
              "4             1  2023/24  2023-10-05   \n",
              "...         ...      ...         ...   \n",
              "17375        32  2023/24  2023-11-01   \n",
              "17376        32  2023/24  2023-11-01   \n",
              "17377        32  2023/24  2023-11-01   \n",
              "17378        32  2023/24  2023-11-01   \n",
              "17379        32  2023/24  2023-11-01   \n",
              "\n",
              "                                               venue  innings  ball  \\\n",
              "0                   Narendra Modi Stadium, Ahmedabad        1   0.1   \n",
              "1                   Narendra Modi Stadium, Ahmedabad        1   0.2   \n",
              "2                   Narendra Modi Stadium, Ahmedabad        1   0.3   \n",
              "3                   Narendra Modi Stadium, Ahmedabad        1   0.4   \n",
              "4                   Narendra Modi Stadium, Ahmedabad        1   0.5   \n",
              "...                                              ...      ...   ...   \n",
              "17375  Maharashtra Cricket Association Stadium, Pune        2  34.5   \n",
              "17376  Maharashtra Cricket Association Stadium, Pune        2  34.6   \n",
              "17377  Maharashtra Cricket Association Stadium, Pune        2  35.1   \n",
              "17378  Maharashtra Cricket Association Stadium, Pune        2  35.2   \n",
              "17379  Maharashtra Cricket Association Stadium, Pune        2  35.3   \n",
              "\n",
              "      batting_team  bowling_team      striker  non_striker  ...  \\\n",
              "0          England   New Zealand  JM Bairstow     DJ Malan  ...   \n",
              "1          England   New Zealand  JM Bairstow     DJ Malan  ...   \n",
              "2          England   New Zealand  JM Bairstow     DJ Malan  ...   \n",
              "3          England   New Zealand     DJ Malan  JM Bairstow  ...   \n",
              "4          England   New Zealand  JM Bairstow     DJ Malan  ...   \n",
              "...            ...           ...          ...          ...  ...   \n",
              "17375  New Zealand  South Africa     MJ Henry  GD Phillips  ...   \n",
              "17376  New Zealand  South Africa     MJ Henry  GD Phillips  ...   \n",
              "17377  New Zealand  South Africa  GD Phillips     MJ Henry  ...   \n",
              "17378  New Zealand  South Africa  GD Phillips     MJ Henry  ...   \n",
              "17379  New Zealand  South Africa  GD Phillips     MJ Henry  ...   \n",
              "\n",
              "      cumulative_runs   run_rate  wickets_remaining  target  runs_needed  \\\n",
              "0                   0   0.000000               10.0     0.0          0.0   \n",
              "1                   6  18.000000               10.0     0.0          0.0   \n",
              "2                   7  14.000000               10.0     0.0          0.0   \n",
              "3                   8  12.000000               10.0     0.0          0.0   \n",
              "4                  12  14.400000               10.0     0.0          0.0   \n",
              "...               ...        ...                ...     ...          ...   \n",
              "17375             161   4.622010                1.0   358.0        197.0   \n",
              "17376             161   4.600000                1.0   358.0        197.0   \n",
              "17377             161   4.578199                1.0   358.0        197.0   \n",
              "17378             167   4.726415                1.0   358.0        191.0   \n",
              "17379             167   4.704225                0.0   358.0        191.0   \n",
              "\n",
              "       required_run_rate        winner  win_by_runs win_by_wickets result  \n",
              "0               0.000000   New Zealand          0.0            9.0      0  \n",
              "1               0.000000   New Zealand          0.0            9.0      0  \n",
              "2               0.000000   New Zealand          0.0            9.0      0  \n",
              "3               0.000000   New Zealand          0.0            9.0      0  \n",
              "4               0.000000   New Zealand          0.0            9.0      0  \n",
              "...                  ...           ...          ...            ...    ...  \n",
              "17375          12.989011  South Africa        190.0            0.0      0  \n",
              "17376          13.133333  South Africa        190.0            0.0      0  \n",
              "17377          13.280899  South Africa        190.0            0.0      0  \n",
              "17378          13.022727  South Africa        190.0            0.0      0  \n",
              "17379          13.172414  South Africa        190.0            0.0      0  \n",
              "\n",
              "[17380 rows x 38 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-3e270164-55e0-47f2-ae3b-504f52301202\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>match_id</th>\n",
              "      <th>season</th>\n",
              "      <th>start_date</th>\n",
              "      <th>venue</th>\n",
              "      <th>innings</th>\n",
              "      <th>ball</th>\n",
              "      <th>batting_team</th>\n",
              "      <th>bowling_team</th>\n",
              "      <th>striker</th>\n",
              "      <th>non_striker</th>\n",
              "      <th>...</th>\n",
              "      <th>cumulative_runs</th>\n",
              "      <th>run_rate</th>\n",
              "      <th>wickets_remaining</th>\n",
              "      <th>target</th>\n",
              "      <th>runs_needed</th>\n",
              "      <th>required_run_rate</th>\n",
              "      <th>winner</th>\n",
              "      <th>win_by_runs</th>\n",
              "      <th>win_by_wickets</th>\n",
              "      <th>result</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>2023/24</td>\n",
              "      <td>2023-10-05</td>\n",
              "      <td>Narendra Modi Stadium, Ahmedabad</td>\n",
              "      <td>1</td>\n",
              "      <td>0.1</td>\n",
              "      <td>England</td>\n",
              "      <td>New Zealand</td>\n",
              "      <td>JM Bairstow</td>\n",
              "      <td>DJ Malan</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>New Zealand</td>\n",
              "      <td>0.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>2023/24</td>\n",
              "      <td>2023-10-05</td>\n",
              "      <td>Narendra Modi Stadium, Ahmedabad</td>\n",
              "      <td>1</td>\n",
              "      <td>0.2</td>\n",
              "      <td>England</td>\n",
              "      <td>New Zealand</td>\n",
              "      <td>JM Bairstow</td>\n",
              "      <td>DJ Malan</td>\n",
              "      <td>...</td>\n",
              "      <td>6</td>\n",
              "      <td>18.000000</td>\n",
              "      <td>10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>New Zealand</td>\n",
              "      <td>0.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>2023/24</td>\n",
              "      <td>2023-10-05</td>\n",
              "      <td>Narendra Modi Stadium, Ahmedabad</td>\n",
              "      <td>1</td>\n",
              "      <td>0.3</td>\n",
              "      <td>England</td>\n",
              "      <td>New Zealand</td>\n",
              "      <td>JM Bairstow</td>\n",
              "      <td>DJ Malan</td>\n",
              "      <td>...</td>\n",
              "      <td>7</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>New Zealand</td>\n",
              "      <td>0.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>2023/24</td>\n",
              "      <td>2023-10-05</td>\n",
              "      <td>Narendra Modi Stadium, Ahmedabad</td>\n",
              "      <td>1</td>\n",
              "      <td>0.4</td>\n",
              "      <td>England</td>\n",
              "      <td>New Zealand</td>\n",
              "      <td>DJ Malan</td>\n",
              "      <td>JM Bairstow</td>\n",
              "      <td>...</td>\n",
              "      <td>8</td>\n",
              "      <td>12.000000</td>\n",
              "      <td>10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>New Zealand</td>\n",
              "      <td>0.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>2023/24</td>\n",
              "      <td>2023-10-05</td>\n",
              "      <td>Narendra Modi Stadium, Ahmedabad</td>\n",
              "      <td>1</td>\n",
              "      <td>0.5</td>\n",
              "      <td>England</td>\n",
              "      <td>New Zealand</td>\n",
              "      <td>JM Bairstow</td>\n",
              "      <td>DJ Malan</td>\n",
              "      <td>...</td>\n",
              "      <td>12</td>\n",
              "      <td>14.400000</td>\n",
              "      <td>10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>New Zealand</td>\n",
              "      <td>0.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17375</th>\n",
              "      <td>32</td>\n",
              "      <td>2023/24</td>\n",
              "      <td>2023-11-01</td>\n",
              "      <td>Maharashtra Cricket Association Stadium, Pune</td>\n",
              "      <td>2</td>\n",
              "      <td>34.5</td>\n",
              "      <td>New Zealand</td>\n",
              "      <td>South Africa</td>\n",
              "      <td>MJ Henry</td>\n",
              "      <td>GD Phillips</td>\n",
              "      <td>...</td>\n",
              "      <td>161</td>\n",
              "      <td>4.622010</td>\n",
              "      <td>1.0</td>\n",
              "      <td>358.0</td>\n",
              "      <td>197.0</td>\n",
              "      <td>12.989011</td>\n",
              "      <td>South Africa</td>\n",
              "      <td>190.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17376</th>\n",
              "      <td>32</td>\n",
              "      <td>2023/24</td>\n",
              "      <td>2023-11-01</td>\n",
              "      <td>Maharashtra Cricket Association Stadium, Pune</td>\n",
              "      <td>2</td>\n",
              "      <td>34.6</td>\n",
              "      <td>New Zealand</td>\n",
              "      <td>South Africa</td>\n",
              "      <td>MJ Henry</td>\n",
              "      <td>GD Phillips</td>\n",
              "      <td>...</td>\n",
              "      <td>161</td>\n",
              "      <td>4.600000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>358.0</td>\n",
              "      <td>197.0</td>\n",
              "      <td>13.133333</td>\n",
              "      <td>South Africa</td>\n",
              "      <td>190.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17377</th>\n",
              "      <td>32</td>\n",
              "      <td>2023/24</td>\n",
              "      <td>2023-11-01</td>\n",
              "      <td>Maharashtra Cricket Association Stadium, Pune</td>\n",
              "      <td>2</td>\n",
              "      <td>35.1</td>\n",
              "      <td>New Zealand</td>\n",
              "      <td>South Africa</td>\n",
              "      <td>GD Phillips</td>\n",
              "      <td>MJ Henry</td>\n",
              "      <td>...</td>\n",
              "      <td>161</td>\n",
              "      <td>4.578199</td>\n",
              "      <td>1.0</td>\n",
              "      <td>358.0</td>\n",
              "      <td>197.0</td>\n",
              "      <td>13.280899</td>\n",
              "      <td>South Africa</td>\n",
              "      <td>190.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17378</th>\n",
              "      <td>32</td>\n",
              "      <td>2023/24</td>\n",
              "      <td>2023-11-01</td>\n",
              "      <td>Maharashtra Cricket Association Stadium, Pune</td>\n",
              "      <td>2</td>\n",
              "      <td>35.2</td>\n",
              "      <td>New Zealand</td>\n",
              "      <td>South Africa</td>\n",
              "      <td>GD Phillips</td>\n",
              "      <td>MJ Henry</td>\n",
              "      <td>...</td>\n",
              "      <td>167</td>\n",
              "      <td>4.726415</td>\n",
              "      <td>1.0</td>\n",
              "      <td>358.0</td>\n",
              "      <td>191.0</td>\n",
              "      <td>13.022727</td>\n",
              "      <td>South Africa</td>\n",
              "      <td>190.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17379</th>\n",
              "      <td>32</td>\n",
              "      <td>2023/24</td>\n",
              "      <td>2023-11-01</td>\n",
              "      <td>Maharashtra Cricket Association Stadium, Pune</td>\n",
              "      <td>2</td>\n",
              "      <td>35.3</td>\n",
              "      <td>New Zealand</td>\n",
              "      <td>South Africa</td>\n",
              "      <td>GD Phillips</td>\n",
              "      <td>MJ Henry</td>\n",
              "      <td>...</td>\n",
              "      <td>167</td>\n",
              "      <td>4.704225</td>\n",
              "      <td>0.0</td>\n",
              "      <td>358.0</td>\n",
              "      <td>191.0</td>\n",
              "      <td>13.172414</td>\n",
              "      <td>South Africa</td>\n",
              "      <td>190.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>17380 rows × 38 columns</p>\n",
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              "\n",
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              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
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              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
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              "\n",
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              "      --disabled-bg-color: #3B4455;\n",
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              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
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              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
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              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
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              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
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              "  @keyframes spin {\n",
              "    0% {\n",
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              "      border-right-color: var(--fill-color);\n",
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              "      border-color: transparent;\n",
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              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
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              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
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              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 181
        }
      ],
      "source": [
        "innings"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:59.648313Z",
          "iopub.status.busy": "2023-11-03T07:55:59.647813Z",
          "iopub.status.idle": "2023-11-03T07:55:59.661277Z",
          "shell.execute_reply": "2023-11-03T07:55:59.659866Z",
          "shell.execute_reply.started": "2023-11-03T07:55:59.64827Z"
        },
        "id": "hojLLlKApjZu",
        "trusted": true
      },
      "outputs": [],
      "source": [
        "#defining model data for prediction\n",
        "model_cols = innings[[\"venue\", \"batting_team\", \"bowling_team\", \"ball\", \"innings_total\", \"wickets_remaining\", \"run_rate\", \"required_run_rate\",\n",
        "                      \"ball_left\", \"runs_needed\", \"win_by_runs\", \"win_by_wickets\", \"target\", \"result\"]]"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Assuming your DataFrame is named 'kohli'\n",
        "innings.to_csv('/content/innings_data.csv', index=False)\n"
      ],
      "metadata": {
        "id": "OXSBDExdO0Wp"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "execution": {
          "iopub.execute_input": "2023-11-03T07:55:59.664284Z",
          "iopub.status.busy": "2023-11-03T07:55:59.66295Z",
          "iopub.status.idle": "2023-11-03T07:55:59.681036Z",
          "shell.execute_reply": "2023-11-03T07:55:59.679308Z",
          "shell.execute_reply.started": "2023-11-03T07:55:59.664235Z"
        },
        "id": "fmMYdIFf2BlH",
        "outputId": "3625759c-77f1-4d9f-c9c1-31712347026a",
        "trusted": true
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "venue                0\n",
              "batting_team         0\n",
              "bowling_team         0\n",
              "ball                 0\n",
              "innings_total        0\n",
              "wickets_remaining    0\n",
              "run_rate             0\n",
              "required_run_rate    0\n",
              "ball_left            0\n",
              "runs_needed          0\n",
              "win_by_runs          0\n",
              "win_by_wickets       0\n",
              "target               0\n",
              "result               0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 184
        }
      ],
      "source": [
        "model_cols.isna().sum()"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Player performance - Virat Kohli\n",
        "\n"
      ],
      "metadata": {
        "id": "CsoTyvDN3vVx"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Creating dataframe were Virat Kohli is striker"
      ],
      "metadata": {
        "id": "9aYLk2O-sBqJ"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "K0Zz-ouXsAHd"
      },
      "outputs": [],
      "source": [
        "#data for Virat Kohli\n",
        "\n",
        "kohli = innings[innings[\"striker\"] == \"V Kohli\"]"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "kohli.head(1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 199
        },
        "id": "mVMRmsVUEghg",
        "outputId": "a9846fe5-510a-4e7c-a56e-1cf7b18df266"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      match_id   season  start_date                                     venue  \\\n",
              "2425         5  2023/24  2023-10-08  MA Chidambaram Stadium, Chepauk, Chennai   \n",
              "\n",
              "      innings  ball batting_team bowling_team  striker non_striker  ...  \\\n",
              "2425        2   0.6        India    Australia  V Kohli   RG Sharma  ...   \n",
              "\n",
              "     cumulative_runs  run_rate  wickets_remaining  target  runs_needed  \\\n",
              "2425               2       2.0                9.0   200.0        198.0   \n",
              "\n",
              "      required_run_rate  winner  win_by_runs win_by_wickets result  \n",
              "2425           4.040816   India          0.0            6.0      1  \n",
              "\n",
              "[1 rows x 38 columns]"
            ],
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              "      <th>required_run_rate</th>\n",
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              "      <th>win_by_wickets</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2425</th>\n",
              "      <td>5</td>\n",
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              "      <td>2023-10-08</td>\n",
              "      <td>MA Chidambaram Stadium, Chepauk, Chennai</td>\n",
              "      <td>2</td>\n",
              "      <td>0.6</td>\n",
              "      <td>India</td>\n",
              "      <td>Australia</td>\n",
              "      <td>V Kohli</td>\n",
              "      <td>RG Sharma</td>\n",
              "      <td>...</td>\n",
              "      <td>2</td>\n",
              "      <td>2.0</td>\n",
              "      <td>9.0</td>\n",
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              "      <td>198.0</td>\n",
              "      <td>4.040816</td>\n",
              "      <td>India</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1 rows × 38 columns</p>\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-8cdf1836-8d47-4fbe-b81d-08434be258eb button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-8cdf1836-8d47-4fbe-b81d-08434be258eb');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 220
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "kZpSQhvWHL9v",
        "outputId": "88d71f5f-7419-4dd3-857c-95a98f7984a8"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-221-b1cf3a8ce4ce>:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  kohli[\"innings_score\"] = kohli.groupby(\"match_id\")[\"runs_off_bat\"].cumsum()\n",
            "<ipython-input-221-b1cf3a8ce4ce>:5: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  kohli[\"balls_faced\"] = kohli.groupby(\"match_id\").cumcount() + 1\n",
            "<ipython-input-221-b1cf3a8ce4ce>:8: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  kohli[\"times_out\"] = kohli[\"wicket\"].cumsum()\n",
            "<ipython-input-221-b1cf3a8ce4ce>:11: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  kohli[\"total_kohli_runs\"] = kohli[\"runs_off_bat\"].cumsum()\n",
            "<ipython-input-221-b1cf3a8ce4ce>:14: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  kohli[\"total_kohli_balls\"] = range(1, len(kohli) + 1)\n",
            "<ipython-input-221-b1cf3a8ce4ce>:17: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  kohli[\"average\"] = kohli[\"total_kohli_runs\"] / np.where(kohli[\"times_out\"] > 0, kohli[\"times_out\"], 1)\n",
            "<ipython-input-221-b1cf3a8ce4ce>:20: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  kohli[\"strike_rate\"] = (kohli[\"total_kohli_runs\"] * 100) / kohli[\"total_kohli_balls\"]\n",
            "<ipython-input-221-b1cf3a8ce4ce>:23: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  kohli[\"average\"] = kohli[\"average\"].astype(float)\n",
            "<ipython-input-221-b1cf3a8ce4ce>:24: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  kohli[\"strike_rate\"] = kohli[\"strike_rate\"].astype(float)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      match_id   season  start_date                                     venue  \\\n",
              "2425         5  2023/24  2023-10-08  MA Chidambaram Stadium, Chepauk, Chennai   \n",
              "2426         5  2023/24  2023-10-08  MA Chidambaram Stadium, Chepauk, Chennai   \n",
              "2433         5  2023/24  2023-10-08  MA Chidambaram Stadium, Chepauk, Chennai   \n",
              "2434         5  2023/24  2023-10-08  MA Chidambaram Stadium, Chepauk, Chennai   \n",
              "2435         5  2023/24  2023-10-08  MA Chidambaram Stadium, Chepauk, Chennai   \n",
              "\n",
              "      innings  ball batting_team bowling_team  striker non_striker  ...  \\\n",
              "2425        2   0.6        India    Australia  V Kohli   RG Sharma  ...   \n",
              "2426        2   0.7        India    Australia  V Kohli   RG Sharma  ...   \n",
              "2433        2   2.1        India    Australia  V Kohli    KL Rahul  ...   \n",
              "2434        2   2.2        India    Australia  V Kohli    KL Rahul  ...   \n",
              "2435        2   2.3        India    Australia  V Kohli    KL Rahul  ...   \n",
              "\n",
              "     win_by_runs  win_by_wickets  result  innings_score  balls_faced  \\\n",
              "2425         0.0             6.0       1              0            1   \n",
              "2426         0.0             6.0       1              0            2   \n",
              "2433         0.0             6.0       1              2            3   \n",
              "2434         0.0             6.0       1              2            4   \n",
              "2435         0.0             6.0       1              2            5   \n",
              "\n",
              "      times_out  total_kohli_runs  total_kohli_balls average strike_rate  \n",
              "2425          0                 0                  1     0.0    0.000000  \n",
              "2426          0                 0                  2     0.0    0.000000  \n",
              "2433          0                 2                  3     2.0   66.666667  \n",
              "2434          0                 2                  4     2.0   50.000000  \n",
              "2435          0                 2                  5     2.0   40.000000  \n",
              "\n",
              "[5 rows x 45 columns]"
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>match_id</th>\n",
              "      <th>season</th>\n",
              "      <th>start_date</th>\n",
              "      <th>venue</th>\n",
              "      <th>innings</th>\n",
              "      <th>ball</th>\n",
              "      <th>batting_team</th>\n",
              "      <th>bowling_team</th>\n",
              "      <th>striker</th>\n",
              "      <th>non_striker</th>\n",
              "      <th>...</th>\n",
              "      <th>win_by_runs</th>\n",
              "      <th>win_by_wickets</th>\n",
              "      <th>result</th>\n",
              "      <th>innings_score</th>\n",
              "      <th>balls_faced</th>\n",
              "      <th>times_out</th>\n",
              "      <th>total_kohli_runs</th>\n",
              "      <th>total_kohli_balls</th>\n",
              "      <th>average</th>\n",
              "      <th>strike_rate</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2425</th>\n",
              "      <td>5</td>\n",
              "      <td>2023/24</td>\n",
              "      <td>2023-10-08</td>\n",
              "      <td>MA Chidambaram Stadium, Chepauk, Chennai</td>\n",
              "      <td>2</td>\n",
              "      <td>0.6</td>\n",
              "      <td>India</td>\n",
              "      <td>Australia</td>\n",
              "      <td>V Kohli</td>\n",
              "      <td>RG Sharma</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2426</th>\n",
              "      <td>5</td>\n",
              "      <td>2023/24</td>\n",
              "      <td>2023-10-08</td>\n",
              "      <td>MA Chidambaram Stadium, Chepauk, Chennai</td>\n",
              "      <td>2</td>\n",
              "      <td>0.7</td>\n",
              "      <td>India</td>\n",
              "      <td>Australia</td>\n",
              "      <td>V Kohli</td>\n",
              "      <td>RG Sharma</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>1</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0.000000</td>\n",
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              "    <tr>\n",
              "      <th>2433</th>\n",
              "      <td>5</td>\n",
              "      <td>2023/24</td>\n",
              "      <td>2023-10-08</td>\n",
              "      <td>MA Chidambaram Stadium, Chepauk, Chennai</td>\n",
              "      <td>2</td>\n",
              "      <td>2.1</td>\n",
              "      <td>India</td>\n",
              "      <td>Australia</td>\n",
              "      <td>V Kohli</td>\n",
              "      <td>KL Rahul</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>2.0</td>\n",
              "      <td>66.666667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2434</th>\n",
              "      <td>5</td>\n",
              "      <td>2023/24</td>\n",
              "      <td>2023-10-08</td>\n",
              "      <td>MA Chidambaram Stadium, Chepauk, Chennai</td>\n",
              "      <td>2</td>\n",
              "      <td>2.2</td>\n",
              "      <td>India</td>\n",
              "      <td>Australia</td>\n",
              "      <td>V Kohli</td>\n",
              "      <td>KL Rahul</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>2.0</td>\n",
              "      <td>50.000000</td>\n",
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              "    <tr>\n",
              "      <th>2435</th>\n",
              "      <td>5</td>\n",
              "      <td>2023/24</td>\n",
              "      <td>2023-10-08</td>\n",
              "      <td>MA Chidambaram Stadium, Chepauk, Chennai</td>\n",
              "      <td>2</td>\n",
              "      <td>2.3</td>\n",
              "      <td>India</td>\n",
              "      <td>Australia</td>\n",
              "      <td>V Kohli</td>\n",
              "      <td>KL Rahul</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6.0</td>\n",
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              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>2.0</td>\n",
              "      <td>40.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 45 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "  </style>\n",
              "\n",
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              "        document.querySelector('#df-f3d99335-1fb0-47ae-8aa5-4939186a5695 button.colab-df-convert');\n",
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              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
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              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-7303707c-000e-432a-acce-fd54ec0a5c26 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 221
        }
      ],
      "source": [
        "#Virat Kohli's innings score\n",
        "kohli[\"innings_score\"] = kohli.groupby(\"match_id\")[\"runs_off_bat\"].cumsum()\n",
        "\n",
        "#Kohli's balls faced till now\n",
        "kohli[\"balls_faced\"] = kohli.groupby(\"match_id\").cumcount() + 1\n",
        "\n",
        "#Number of times Kohli got out till now\n",
        "kohli[\"times_out\"] = kohli[\"wicket\"].cumsum()\n",
        "\n",
        "#Total runs of Kohli till now\n",
        "kohli[\"total_kohli_runs\"] = kohli[\"runs_off_bat\"].cumsum()\n",
        "\n",
        "#yotal balls faced by Kohli till now\n",
        "kohli[\"total_kohli_balls\"] = range(1, len(kohli) + 1)\n",
        "\n",
        "#Virat Kohli's average (handle division by zero)\n",
        "kohli[\"average\"] = kohli[\"total_kohli_runs\"] / np.where(kohli[\"times_out\"] > 0, kohli[\"times_out\"], 1)\n",
        "\n",
        "#Virat Kohli's strike rate\n",
        "kohli[\"strike_rate\"] = (kohli[\"total_kohli_runs\"] * 100) / kohli[\"total_kohli_balls\"]\n",
        "\n",
        "kohli[\"average\"] = kohli[\"average\"].astype(float)\n",
        "kohli[\"strike_rate\"] = kohli[\"strike_rate\"].astype(float)\n",
        "\n",
        "kohli.head()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aULQ6JGGHL9v",
        "outputId": "e01b7bde-421c-409f-8fb9-ff73c0336c1a"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['match_id', 'season', 'start_date', 'venue', 'innings', 'ball',\n",
              "       'batting_team', 'bowling_team', 'striker', 'non_striker', 'bowler',\n",
              "       'runs_off_bat', 'extras', 'wides', 'noballs', 'byes', 'legbyes',\n",
              "       'penalty', 'wicket_type', 'player_dismissed', 'other_wicket_type',\n",
              "       'other_player_dismissed', 'wicket', 'over', 'ball_num', 'ball_left',\n",
              "       'total_runs', 'innings_total', 'cumulative_runs', 'run_rate',\n",
              "       'wickets_remaining', 'target', 'runs_needed', 'required_run_rate',\n",
              "       'winner', 'win_by_runs', 'win_by_wickets', 'result', 'innings_score',\n",
              "       'balls_faced', 'times_out', 'total_kohli_runs', 'total_kohli_balls',\n",
              "       'average', 'strike_rate'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 222
        }
      ],
      "source": [
        "kohli.columns"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IX1baEfGHL9v",
        "outputId": "07392426-5f78-48dc-9d9e-edf42ab25ae4"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-223-c1b002f1e891>:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  kohli[\"team_total\"] = kohli[\"innings_total\"]\n"
          ]
        }
      ],
      "source": [
        "kohli[\"team_total\"] = kohli[\"innings_total\"]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Bh7YTUnRHL9v"
      },
      "outputs": [],
      "source": [
        "kohli = kohli[[\"match_id\", \"venue\", \"innings\", \"bowling_team\", \"runs_off_bat\", \"ball_left\", \"run_rate\", \"team_total\", \"wickets_remaining\", \"target\", \"runs_needed\",\"required_run_rate\" ,\"average\", \"strike_rate\"]]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Xa-VXzhcHL9w",
        "outputId": "b759352c-a660-4dac-cac7-0a7f46cb44ca"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "match_id             0\n",
              "venue                0\n",
              "innings              0\n",
              "bowling_team         0\n",
              "runs_off_bat         0\n",
              "ball_left            0\n",
              "run_rate             0\n",
              "team_total           0\n",
              "wickets_remaining    0\n",
              "target               0\n",
              "runs_needed          0\n",
              "required_run_rate    0\n",
              "average              0\n",
              "strike_rate          0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 225
        }
      ],
      "source": [
        "kohli.isna().sum()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Check the number of rows with inf values in the entire DataFrame\n",
        "num_rows_with_inf = (kohli.select_dtypes(include=[np.number]).applymap(np.isinf)).any(axis=1).sum()\n",
        "\n",
        "print(\"Number of rows with inf values:\", num_rows_with_inf)\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "X-szwuTcMnOa",
        "outputId": "59de5141-e351-4a97-a142-dd18d86a6414"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of rows with inf values: 0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "SUeirVOXHL9w"
      },
      "outputs": [],
      "source": [
        "# one hot encoding on venue and bowling team\n",
        "kohli = pd.get_dummies(kohli, columns=[\"venue\", \"bowling_team\"])\n",
        "# kohli = kohli.drop([\"venue\", \"bowling_team\"], axis=1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9ZSpWP4wHL9w",
        "outputId": "f695a1e9-1512-44eb-a1f8-c7309effc37d"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['match_id', 'innings', 'runs_off_bat', 'ball_left', 'run_rate',\n",
              "       'team_total', 'wickets_remaining', 'target', 'runs_needed',\n",
              "       'required_run_rate', 'average', 'strike_rate',\n",
              "       'venue_Arun Jaitley Stadium, Delhi',\n",
              "       'venue_Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cricket Stadium, Lucknow',\n",
              "       'venue_Himachal Pradesh Cricket Association Stadium, Dharamsala',\n",
              "       'venue_MA Chidambaram Stadium, Chepauk, Chennai',\n",
              "       'venue_Maharashtra Cricket Association Stadium, Pune',\n",
              "       'venue_Narendra Modi Stadium, Ahmedabad', 'bowling_team_Afghanistan',\n",
              "       'bowling_team_Australia', 'bowling_team_Bangladesh',\n",
              "       'bowling_team_England', 'bowling_team_New Zealand',\n",
              "       'bowling_team_Pakistan'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 228
        }
      ],
      "source": [
        "kohli.columns"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "wTmQHmqlNmjH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Extract the correlation of 'runs_off_bat' with every other column\n",
        "correlation_with_runs = correlation_matrix['runs_off_bat'].sort_values(ascending=False)\n",
        "\n",
        "# Print the correlation values\n",
        "print(correlation_with_runs)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oA0NTX2ML6ah",
        "outputId": "da8cd93d-45d7-4239-9af1-bc0da8d121bb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "runs_off_bat                                                                   1.000000\n",
            "strike_rate                                                                    0.132047\n",
            "target                                                                         0.130968\n",
            "run_rate                                                                       0.127525\n",
            "innings                                                                        0.105996\n",
            "average                                                                        0.097578\n",
            "team_total                                                                     0.088208\n",
            "bowling_team_Bangladesh                                                        0.085012\n",
            "venue_Maharashtra Cricket Association Stadium, Pune                            0.085012\n",
            "wickets_remaining                                                              0.072129\n",
            "venue_Arun Jaitley Stadium, Delhi                                              0.032652\n",
            "bowling_team_Afghanistan                                                       0.032652\n",
            "match_id                                                                       0.025932\n",
            "venue_Himachal Pradesh Cricket Association Stadium, Dharamsala                 0.010849\n",
            "bowling_team_New Zealand                                                       0.010849\n",
            "venue_Narendra Modi Stadium, Ahmedabad                                        -0.004220\n",
            "bowling_team_Pakistan                                                         -0.004220\n",
            "required_run_rate                                                             -0.058064\n",
            "venue_MA Chidambaram Stadium, Chepauk, Chennai                                -0.079097\n",
            "bowling_team_Australia                                                        -0.079097\n",
            "runs_needed                                                                   -0.088673\n",
            "venue_Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cricket Stadium, Lucknow   -0.105996\n",
            "bowling_team_England                                                          -0.105996\n",
            "ball_left                                                                     -0.122997\n",
            "Name: runs_off_bat, dtype: float64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Separate target variable and features\n",
        "kohli_train = kohli.drop([\"runs_off_bat\"], axis=1)\n",
        "kohli_test = kohli[\"runs_off_bat\"]"
      ],
      "metadata": {
        "id": "0Cj_GeGuNnhR"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Split the data into training and testing sets\n",
        "X_train, X_test, y_train, y_test = train_test_split(kohli_train, kohli_test, test_size=0.2, random_state=42)"
      ],
      "metadata": {
        "id": "QC69uI-4nr9c"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ayt8KNHVHL9w",
        "outputId": "8d64a800-c93d-4fa3-e140-5348ffcbd6c8"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(327, 24)"
            ]
          },
          "metadata": {},
          "execution_count": 245
        }
      ],
      "source": [
        "X_train.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Rw0hez0qHL9w",
        "outputId": "8ecaff80-aab3-4b81-941c-d716062650c7"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(82, 24)"
            ]
          },
          "metadata": {},
          "execution_count": 246
        }
      ],
      "source": [
        "X_test.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 513
        },
        "id": "S4mwKInoHL9x",
        "outputId": "a36a3402-8489-4ebb-d6c6-75c98dff5005"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       match_id  innings  ball_left  run_rate  team_total  wickets_remaining  \\\n",
              "2631          5        2         93  4.318841         201                7.0   \n",
              "10891        21        2         46  5.669291         274                5.0   \n",
              "8586         17        2        130  6.141176         261                8.0   \n",
              "4993          9        2         90  7.800000         273                8.0   \n",
              "2434          5        2        286  1.714286         201                7.0   \n",
              "...         ...      ...        ...       ...         ...                ...   \n",
              "2567          5        2        154  3.863014         201                7.0   \n",
              "2628          5        2         96  4.294118         201                7.0   \n",
              "8643         17        2         74  6.026549         261                7.0   \n",
              "10815        21        2        121  5.597765         274                7.0   \n",
              "2623          5        2        101  4.221106         201                7.0   \n",
              "\n",
              "       target  runs_needed  required_run_rate  average  ...  \\\n",
              "2631    200.0         51.0           3.290323     79.0  ...   \n",
              "10891   274.0         34.0           4.434783    167.0  ...   \n",
              "8586    257.0         83.0           3.830769    104.0  ...   \n",
              "4993    273.0          0.0           0.000000    140.0  ...   \n",
              "2434    200.0        196.0           4.111888      2.0  ...   \n",
              "...       ...          ...                ...      ...  ...   \n",
              "2567    200.0        106.0           4.129870     46.0  ...   \n",
              "2628    200.0         54.0           3.375000     77.0  ...   \n",
              "8643    257.0         30.0           2.432432    114.0  ...   \n",
              "10815   274.0        107.0           5.305785    150.5  ...   \n",
              "2623    200.0         60.0           3.564356     72.0  ...   \n",
              "\n",
              "       venue_MA Chidambaram Stadium, Chepauk, Chennai  \\\n",
              "2631                                                1   \n",
              "10891                                               0   \n",
              "8586                                                0   \n",
              "4993                                                0   \n",
              "2434                                                1   \n",
              "...                                               ...   \n",
              "2567                                                1   \n",
              "2628                                                1   \n",
              "8643                                                0   \n",
              "10815                                               0   \n",
              "2623                                                1   \n",
              "\n",
              "       venue_Maharashtra Cricket Association Stadium, Pune  \\\n",
              "2631                                                   0     \n",
              "10891                                                  0     \n",
              "8586                                                   1     \n",
              "4993                                                   0     \n",
              "2434                                                   0     \n",
              "...                                                  ...     \n",
              "2567                                                   0     \n",
              "2628                                                   0     \n",
              "8643                                                   1     \n",
              "10815                                                  0     \n",
              "2623                                                   0     \n",
              "\n",
              "       venue_Narendra Modi Stadium, Ahmedabad  bowling_team_Afghanistan  \\\n",
              "2631                                        0                         0   \n",
              "10891                                       0                         0   \n",
              "8586                                        0                         0   \n",
              "4993                                        0                         1   \n",
              "2434                                        0                         0   \n",
              "...                                       ...                       ...   \n",
              "2567                                        0                         0   \n",
              "2628                                        0                         0   \n",
              "8643                                        0                         0   \n",
              "10815                                       0                         0   \n",
              "2623                                        0                         0   \n",
              "\n",
              "       bowling_team_Australia  bowling_team_Bangladesh  bowling_team_England  \\\n",
              "2631                        1                        0                     0   \n",
              "10891                       0                        0                     0   \n",
              "8586                        0                        1                     0   \n",
              "4993                        0                        0                     0   \n",
              "2434                        1                        0                     0   \n",
              "...                       ...                      ...                   ...   \n",
              "2567                        1                        0                     0   \n",
              "2628                        1                        0                     0   \n",
              "8643                        0                        1                     0   \n",
              "10815                       0                        0                     0   \n",
              "2623                        1                        0                     0   \n",
              "\n",
              "       bowling_team_New Zealand  bowling_team_Pakistan  runs_per_ball  \n",
              "2631                          0                      0       0.009174  \n",
              "10891                         1                      0       0.000000  \n",
              "8586                          0                      0       0.000000  \n",
              "4993                          0                      0       0.022727  \n",
              "2434                          0                      0       0.000000  \n",
              "...                         ...                    ...            ...  \n",
              "2567                          0                      0       0.013889  \n",
              "2628                          0                      0       0.009346  \n",
              "8643                          0                      0       0.003690  \n",
              "10815                         1                      0       0.002865  \n",
              "2623                          0                      0       0.009709  \n",
              "\n",
              "[327 rows x 24 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-bef341a7-1f80-43fb-a213-1924c1f5582f\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>match_id</th>\n",
              "      <th>innings</th>\n",
              "      <th>ball_left</th>\n",
              "      <th>run_rate</th>\n",
              "      <th>team_total</th>\n",
              "      <th>wickets_remaining</th>\n",
              "      <th>target</th>\n",
              "      <th>runs_needed</th>\n",
              "      <th>required_run_rate</th>\n",
              "      <th>average</th>\n",
              "      <th>...</th>\n",
              "      <th>venue_MA Chidambaram Stadium, Chepauk, Chennai</th>\n",
              "      <th>venue_Maharashtra Cricket Association Stadium, Pune</th>\n",
              "      <th>venue_Narendra Modi Stadium, Ahmedabad</th>\n",
              "      <th>bowling_team_Afghanistan</th>\n",
              "      <th>bowling_team_Australia</th>\n",
              "      <th>bowling_team_Bangladesh</th>\n",
              "      <th>bowling_team_England</th>\n",
              "      <th>bowling_team_New Zealand</th>\n",
              "      <th>bowling_team_Pakistan</th>\n",
              "      <th>runs_per_ball</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2631</th>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>93</td>\n",
              "      <td>4.318841</td>\n",
              "      <td>201</td>\n",
              "      <td>7.0</td>\n",
              "      <td>200.0</td>\n",
              "      <td>51.0</td>\n",
              "      <td>3.290323</td>\n",
              "      <td>79.0</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.009174</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10891</th>\n",
              "      <td>21</td>\n",
              "      <td>2</td>\n",
              "      <td>46</td>\n",
              "      <td>5.669291</td>\n",
              "      <td>274</td>\n",
              "      <td>5.0</td>\n",
              "      <td>274.0</td>\n",
              "      <td>34.0</td>\n",
              "      <td>4.434783</td>\n",
              "      <td>167.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8586</th>\n",
              "      <td>17</td>\n",
              "      <td>2</td>\n",
              "      <td>130</td>\n",
              "      <td>6.141176</td>\n",
              "      <td>261</td>\n",
              "      <td>8.0</td>\n",
              "      <td>257.0</td>\n",
              "      <td>83.0</td>\n",
              "      <td>3.830769</td>\n",
              "      <td>104.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4993</th>\n",
              "      <td>9</td>\n",
              "      <td>2</td>\n",
              "      <td>90</td>\n",
              "      <td>7.800000</td>\n",
              "      <td>273</td>\n",
              "      <td>8.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>140.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.022727</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2434</th>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>286</td>\n",
              "      <td>1.714286</td>\n",
              "      <td>201</td>\n",
              "      <td>7.0</td>\n",
              "      <td>200.0</td>\n",
              "      <td>196.0</td>\n",
              "      <td>4.111888</td>\n",
              "      <td>2.0</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2567</th>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>154</td>\n",
              "      <td>3.863014</td>\n",
              "      <td>201</td>\n",
              "      <td>7.0</td>\n",
              "      <td>200.0</td>\n",
              "      <td>106.0</td>\n",
              "      <td>4.129870</td>\n",
              "      <td>46.0</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.013889</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2628</th>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>96</td>\n",
              "      <td>4.294118</td>\n",
              "      <td>201</td>\n",
              "      <td>7.0</td>\n",
              "      <td>200.0</td>\n",
              "      <td>54.0</td>\n",
              "      <td>3.375000</td>\n",
              "      <td>77.0</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.009346</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8643</th>\n",
              "      <td>17</td>\n",
              "      <td>2</td>\n",
              "      <td>74</td>\n",
              "      <td>6.026549</td>\n",
              "      <td>261</td>\n",
              "      <td>7.0</td>\n",
              "      <td>257.0</td>\n",
              "      <td>30.0</td>\n",
              "      <td>2.432432</td>\n",
              "      <td>114.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.003690</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10815</th>\n",
              "      <td>21</td>\n",
              "      <td>2</td>\n",
              "      <td>121</td>\n",
              "      <td>5.597765</td>\n",
              "      <td>274</td>\n",
              "      <td>7.0</td>\n",
              "      <td>274.0</td>\n",
              "      <td>107.0</td>\n",
              "      <td>5.305785</td>\n",
              "      <td>150.5</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0.002865</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2623</th>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>101</td>\n",
              "      <td>4.221106</td>\n",
              "      <td>201</td>\n",
              "      <td>7.0</td>\n",
              "      <td>200.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>3.564356</td>\n",
              "      <td>72.0</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.009709</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>327 rows × 24 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
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              "\n",
              "  <style>\n",
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              "      display:flex;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
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              "      border-radius: 50%;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
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              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "  </style>\n",
              "\n",
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              "      const buttonEl =\n",
              "        document.querySelector('#df-bef341a7-1f80-43fb-a213-1924c1f5582f button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-bef341a7-1f80-43fb-a213-1924c1f5582f');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
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              "  </div>\n",
              "\n",
              "\n",
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              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-0c559e4d-5316-49ad-99c6-76c3089b5929')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
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              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
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              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
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              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-0c559e4d-5316-49ad-99c6-76c3089b5929 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 247
        }
      ],
      "source": [
        "X_train"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Regression for predicting run scored by Virat Kohli"
      ],
      "metadata": {
        "id": "ak_78RywqArq"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.pipeline import Pipeline\n",
        "from sklearn.ensemble import RandomForestRegressor\n",
        "from xgboost import XGBRegressor\n",
        "from sklearn.linear_model import LinearRegression\n",
        "from sklearn.neural_network import MLPRegressor\n",
        "from sklearn.model_selection import GridSearchCV\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from sklearn.metrics import mean_squared_error\n",
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "# Separate target variable and features\n",
        "X = kohli.drop([\"runs_off_bat\"], axis=1)\n",
        "y = kohli[\"runs_off_bat\"]\n",
        "\n",
        "# Split the data into training and testing sets\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
        "\n",
        "# Create a pipeline for RandomForestRegressor\n",
        "rf_pipeline = Pipeline([\n",
        "    ('scaler', StandardScaler()),  # Include any preprocessing steps if needed\n",
        "    ('regressor', RandomForestRegressor())\n",
        "])\n",
        "\n",
        "# Create a pipeline for Linear Regression\n",
        "linear_params = {}\n",
        "linear_pipeline = Pipeline([\n",
        "    ('scaler', StandardScaler()),  # Include any preprocessing steps if needed\n",
        "    ('regressor', LinearRegression())\n",
        "])\n",
        "\n",
        "# Define hyperparameters to tune for RandomForestRegressor\n",
        "rf_params = {\n",
        "    'regressor__n_estimators': [50, 100, 200],\n",
        "    'regressor__max_depth': [5, 10, 20]\n",
        "}\n",
        "\n",
        "# Create a pipeline for XGBRegressor\n",
        "xgb_pipeline = Pipeline([\n",
        "    ('regressor', XGBRegressor())\n",
        "])\n",
        "\n",
        "# Define hyperparameters to tune for XGBRegressor\n",
        "xgb_params = {\n",
        "    'regressor__n_estimators': [50, 100, 200],\n",
        "    'regressor__max_depth': [5, 10, 20]\n",
        "}\n",
        "\n",
        "# Create a pipeline for MLPRegressor (Neural Network)\n",
        "mlp_pipeline = Pipeline([\n",
        "    ('scaler', StandardScaler()),  # Standardize input features for Neural Network\n",
        "    ('regressor', MLPRegressor())\n",
        "])\n",
        "\n",
        "# Define hyperparameters to tune for MLPRegressor\n",
        "mlp_params = {\n",
        "    'regressor__hidden_layer_sizes': [(50, 50), (100, 50, 100)],\n",
        "    'regressor__max_iter': [100, 200, 300],\n",
        "}\n",
        "\n",
        "# Create a dictionary of models and their respective hyperparameters\n",
        "models = {\n",
        "    'LinearRegression': (linear_pipeline, linear_params),\n",
        "    'RandomForest': (rf_pipeline, rf_params),\n",
        "    'XGBoost': (xgb_pipeline, xgb_params),\n",
        "    'NeuralNetwork': (mlp_pipeline, mlp_params),\n",
        "}\n",
        "\n",
        "# Loop through each model, perform grid search for hyperparameter tuning, and print results\n",
        "for model_name, (pipeline, params) in models.items():\n",
        "    print(f\"\\nTraining and evaluating {model_name} as a regression problem...\")\n",
        "    grid_search = GridSearchCV(pipeline, params, scoring='neg_mean_squared_error', cv=5)\n",
        "    grid_search.fit(X_train, y_train)\n",
        "\n",
        "    # Print best parameters and score\n",
        "    print(f\"Best parameters for {model_name}: {grid_search.best_params_}\")\n",
        "    print(f\"Best mean squared error: {-grid_search.best_score_}\")\n",
        "\n",
        "    # Evaluate the model on the test set\n",
        "    y_pred = grid_search.predict(X_test)\n",
        "    print(\"Test results\")\n",
        "    print(f\"{model_name}'s predicted runs: {y_pred.sum()}\")\n",
        "    print(f\"{model_name}'s actual runs: {y_test.sum()}\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dXZYftxSX4pq",
        "outputId": "663c83cb-0ec7-4ae1-a832-3f76b7909b0c"
      },
      "execution_count": 258,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Training and evaluating LinearRegression as a regression problem...\n",
            "Best parameters for LinearRegression: {}\n",
            "Best mean squared error: 4.550011388176189\n",
            "Test results\n",
            "LinearRegression's predicted runs: 69.47783023030684\n",
            "LinearRegression's actual runs: 59\n",
            "\n",
            "Training and evaluating RandomForest as a regression problem...\n",
            "Best parameters for RandomForest: {'regressor__max_depth': 10, 'regressor__n_estimators': 50}\n",
            "Best mean squared error: 0.1739497808857809\n",
            "Test results\n",
            "RandomForest's predicted runs: 58.1\n",
            "RandomForest's actual runs: 59\n",
            "\n",
            "Training and evaluating XGBoost as a regression problem...\n",
            "Best parameters for XGBoost: {'regressor__max_depth': 5, 'regressor__n_estimators': 200}\n",
            "Best mean squared error: 0.1357182851654382\n",
            "Test results\n",
            "XGBoost's predicted runs: 58.17915725708008\n",
            "XGBoost's actual runs: 59\n",
            "\n",
            "Training and evaluating NeuralNetwork as a regression problem...\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:686: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:686: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:686: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:686: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:686: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:686: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (200) reached and the optimization hasn't converged yet.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:686: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (200) reached and the optimization hasn't converged yet.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:686: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (200) reached and the optimization hasn't converged yet.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:686: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (200) reached and the optimization hasn't converged yet.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:686: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (200) reached and the optimization hasn't converged yet.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:686: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (300) reached and the optimization hasn't converged yet.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:686: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (300) reached and the optimization hasn't converged yet.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:686: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (300) reached and the optimization hasn't converged yet.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:686: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (300) reached and the optimization hasn't converged yet.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:686: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:686: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:686: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:686: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:686: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:686: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (200) reached and the optimization hasn't converged yet.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:686: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (200) reached and the optimization hasn't converged yet.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Best parameters for NeuralNetwork: {'regressor__hidden_layer_sizes': (50, 50), 'regressor__max_iter': 200}\n",
            "Best mean squared error: 2.4304867870494724\n",
            "Test results\n",
            "NeuralNetwork's predicted runs: 58.77629452066582\n",
            "NeuralNetwork's actual runs: 59\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:686: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (200) reached and the optimization hasn't converged yet.\n",
            "  warnings.warn(\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "FdkyXvanX49Y"
      },
      "execution_count": null,
      "outputs": []
    }
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