5_Fifa_2018_SHAP.ipynb

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    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "UWlyPP020uDk"
      },
      "outputs": [],
      "source": [
        "import glob\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "from sklearn.model_selection import train_test_split\n",
        "from tensorflow import keras\n",
        "from tensorflow.keras import layers\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from sklearn.metrics import mean_squared_error\n",
        "from sklearn.ensemble import RandomForestClassifier"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Chapter 4 - Model Agnostic Methods-SHAP\n",
        "\n",
        "gianfagna_l_di_cecco_a_explainable_ai_with_python (Book)"
      ],
      "metadata": {
        "id": "rEpEtf2H3yT-"
      }
    },
    {
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      "source": [
        "#download dataset here\n",
        "#https://www.kaggle.com/datasets/mathan/fifa-2018-match-statistics\n",
        "fifa = pd.read_csv('FIFA 2018 Statistics.csv')\n",
        "fifa"
      ],
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      "execution_count": 3,
      "outputs": [
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              "           Date          Team      Opponent  Goal Scored  Ball Possession %  \\\n",
              "0    14-06-2018        Russia  Saudi Arabia            5                 40   \n",
              "1    14-06-2018  Saudi Arabia        Russia            0                 60   \n",
              "2    15-06-2018         Egypt       Uruguay            0                 43   \n",
              "3    15-06-2018       Uruguay         Egypt            1                 57   \n",
              "4    15-06-2018       Morocco          Iran            0                 64   \n",
              "..          ...           ...           ...          ...                ...   \n",
              "123  11-07-2018       England       Croatia            1                 46   \n",
              "124  14-07-2018       Belgium       England            2                 43   \n",
              "125  14-07-2018       England       Belgium            0                 57   \n",
              "126  15-07-2018        France       Croatia            4                 39   \n",
              "127  15-07-2018       Croatia        France            2                 61   \n",
              "\n",
              "     Attempts  On-Target  Off-Target  Blocked  Corners  ...  Yellow Card  \\\n",
              "0          13          7           3        3        6  ...            0   \n",
              "1           6          0           3        3        2  ...            0   \n",
              "2           8          3           3        2        0  ...            2   \n",
              "3          14          4           6        4        5  ...            0   \n",
              "4          13          3           6        4        5  ...            1   \n",
              "..        ...        ...         ...      ...      ...  ...          ...   \n",
              "123        11          1           6        4        4  ...            1   \n",
              "124        12          4           3        5        4  ...            1   \n",
              "125        15          5           7        3        5  ...            2   \n",
              "126         8          6           1        1        2  ...            2   \n",
              "127        15          3           8        4        6  ...            1   \n",
              "\n",
              "     Yellow & Red  Red  Man of the Match  1st Goal         Round  PSO  \\\n",
              "0               0    0               Yes      12.0   Group Stage   No   \n",
              "1               0    0                No       NaN   Group Stage   No   \n",
              "2               0    0                No       NaN   Group Stage   No   \n",
              "3               0    0               Yes      89.0   Group Stage   No   \n",
              "4               0    0                No       NaN   Group Stage   No   \n",
              "..            ...  ...               ...       ...           ...  ...   \n",
              "123             0    0                No       5.0  Semi- Finals   No   \n",
              "124             0    0               Yes       4.0     3rd Place   No   \n",
              "125             0    0                No       NaN     3rd Place   No   \n",
              "126             0    0               Yes      18.0         Final   No   \n",
              "127             0    0                No      28.0         Final   No   \n",
              "\n",
              "     Goals in PSO  Own goals  Own goal Time  \n",
              "0               0        NaN            NaN  \n",
              "1               0        NaN            NaN  \n",
              "2               0        NaN            NaN  \n",
              "3               0        NaN            NaN  \n",
              "4               0        1.0           90.0  \n",
              "..            ...        ...            ...  \n",
              "123             0        NaN            NaN  \n",
              "124             0        NaN            NaN  \n",
              "125             0        NaN            NaN  \n",
              "126             0        1.0           18.0  \n",
              "127             0        NaN            NaN  \n",
              "\n",
              "[128 rows x 27 columns]"
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              "      <th></th>\n",
              "      <th>Date</th>\n",
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              "      <td>14-06-2018</td>\n",
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              "      <td>15-06-2018</td>\n",
              "      <td>Egypt</td>\n",
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              "      <th>3</th>\n",
              "      <td>15-06-2018</td>\n",
              "      <td>Uruguay</td>\n",
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              "      <td>1</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>15-06-2018</td>\n",
              "      <td>Morocco</td>\n",
              "      <td>Iran</td>\n",
              "      <td>0</td>\n",
              "      <td>64</td>\n",
              "      <td>13</td>\n",
              "      <td>3</td>\n",
              "      <td>6</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Group Stage</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>90.0</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>123</th>\n",
              "      <td>11-07-2018</td>\n",
              "      <td>England</td>\n",
              "      <td>Croatia</td>\n",
              "      <td>1</td>\n",
              "      <td>46</td>\n",
              "      <td>11</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>5.0</td>\n",
              "      <td>Semi- Finals</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>124</th>\n",
              "      <td>14-07-2018</td>\n",
              "      <td>Belgium</td>\n",
              "      <td>England</td>\n",
              "      <td>2</td>\n",
              "      <td>43</td>\n",
              "      <td>12</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>4</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>4.0</td>\n",
              "      <td>3rd Place</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>125</th>\n",
              "      <td>14-07-2018</td>\n",
              "      <td>England</td>\n",
              "      <td>Belgium</td>\n",
              "      <td>0</td>\n",
              "      <td>57</td>\n",
              "      <td>15</td>\n",
              "      <td>5</td>\n",
              "      <td>7</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>...</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3rd Place</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>126</th>\n",
              "      <td>15-07-2018</td>\n",
              "      <td>France</td>\n",
              "      <td>Croatia</td>\n",
              "      <td>4</td>\n",
              "      <td>39</td>\n",
              "      <td>8</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>...</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>18.0</td>\n",
              "      <td>Final</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>18.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>127</th>\n",
              "      <td>15-07-2018</td>\n",
              "      <td>Croatia</td>\n",
              "      <td>France</td>\n",
              "      <td>2</td>\n",
              "      <td>61</td>\n",
              "      <td>15</td>\n",
              "      <td>3</td>\n",
              "      <td>8</td>\n",
              "      <td>4</td>\n",
              "      <td>6</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>28.0</td>\n",
              "      <td>Final</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>128 rows × 27 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-2fbb6e4c-25a3-4bd9-8ca4-6a2f8cb7fe90')\"\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 0 24 24\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "\n",
              "\n",
              "\n",
              "    <div id=\"df-033006a6-26cc-42c7-bfca-8980bf51c670\">\n",
              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-033006a6-26cc-42c7-bfca-8980bf51c670')\"\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",
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              "    </g>\n",
              "</svg>\n",
              "      </button>\n",
              "    </div>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\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-quickchart: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",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart: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",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-033006a6-26cc-42c7-bfca-8980bf51c670 button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-2fbb6e4c-25a3-4bd9-8ca4-6a2f8cb7fe90 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-2fbb6e4c-25a3-4bd9-8ca4-6a2f8cb7fe90');\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",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y = (fifa['Man of the Match'] == \"Yes\")  # Convert from string \"Yes\"/\"No\" to binary\n",
        "feature_names = [i for i in fifa.columns if fifa[i].dtype in [np.int64]]\n",
        "X = fifa[feature_names]\n",
        "train_X, val_X, train_y, val_y = train_test_split(X, y, random_state=1)\n",
        "my_model = RandomForestClassifier(n_estimators=100, random_state=0).fit(train_X, train_y)\n",
        "\n",
        "#select match Uruguay-Russia\n",
        "row_to_show = 19\n",
        "data_for_prediction = val_X.iloc[row_to_show] #A\n",
        "data_for_prediction_array = data_for_prediction.values.reshape(1, -1)\n",
        "#see the prediction from our ML Random Forest model of having Uruguay assigned the “Man of The Match” award (52%):\n",
        "\"\"\"\n",
        "to remember\n",
        "predict() is used to predict the actual class (in your case one of 0, 1, or 2).\n",
        "predict_proba() is used to predict the class probabilities\n",
        "\"\"\"\n",
        "my_model.predict_proba(data_for_prediction_array)\n",
        "#A use 1 row of data here. Could use multiple rows if desired\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "V4DE9O584AhG",
        "outputId": "87f82008-9463-4942-bc4f-cbbda4eedc42"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/base.py:439: UserWarning: X does not have valid feature names, but RandomForestClassifier was fitted with feature names\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0.48, 0.52]])"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install shap"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NKNPyKot5YA8",
        "outputId": "d4cb5f0a-6db5-47e3-92e1-57eee019c2fe"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting shap\n",
            "  Downloading shap-0.42.1-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (547 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m547.9/547.9 kB\u001b[0m \u001b[31m6.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from shap) (1.23.5)\n",
            "Requirement already satisfied: scipy in /usr/local/lib/python3.10/dist-packages (from shap) (1.10.1)\n",
            "Requirement already satisfied: scikit-learn in /usr/local/lib/python3.10/dist-packages (from shap) (1.2.2)\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from shap) (1.5.3)\n",
            "Requirement already satisfied: tqdm>=4.27.0 in /usr/local/lib/python3.10/dist-packages (from shap) (4.66.1)\n",
            "Requirement already satisfied: packaging>20.9 in /usr/local/lib/python3.10/dist-packages (from shap) (23.1)\n",
            "Collecting slicer==0.0.7 (from shap)\n",
            "  Downloading slicer-0.0.7-py3-none-any.whl (14 kB)\n",
            "Requirement already satisfied: numba in /usr/local/lib/python3.10/dist-packages (from shap) (0.56.4)\n",
            "Requirement already satisfied: cloudpickle in /usr/local/lib/python3.10/dist-packages (from shap) (2.2.1)\n",
            "Requirement already satisfied: llvmlite<0.40,>=0.39.0dev0 in /usr/local/lib/python3.10/dist-packages (from numba->shap) (0.39.1)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from numba->shap) (67.7.2)\n",
            "Requirement already satisfied: python-dateutil>=2.8.1 in /usr/local/lib/python3.10/dist-packages (from pandas->shap) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->shap) (2023.3)\n",
            "Requirement already satisfied: joblib>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from scikit-learn->shap) (1.3.2)\n",
            "Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn->shap) (3.2.0)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.1->pandas->shap) (1.16.0)\n",
            "Installing collected packages: slicer, shap\n",
            "Successfully installed shap-0.42.1 slicer-0.0.7\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import shap #A\n",
        "k_explainer = shap.KernelExplainer(my_model.predict_proba,\n",
        "train_X) #B\n",
        "k_shap_values = k_explainer.shap_values(data_for_prediction)\n",
        "#A package used to calculate Shap values\n",
        "#B # use KernelSHAP to explain test set predictions\n",
        "shap.initjs() #da mettere per visualizzare il grafico\n",
        "shap.force_plot(k_explainer.expected_value[1], k_shap_values[1], data_for_prediction)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 231
        },
        "id": "Uz5QOHl25i4T",
        "outputId": "22d949c2-8515-49ea-a9a5-55d84b8ee84f"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Using `tqdm.autonotebook.tqdm` in notebook mode. Use `tqdm.tqdm` instead to force console mode (e.g. in jupyter console)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
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n.childContextTypes?u(\"107\",this.getName()||\"ReactCompositeComponent\"):void 0;for(var i in e)i in n.childContextTypes?void 0:u(\"108\",this.getName()||\"ReactCompositeComponent\",i);return c({},t,e)}return t},_checkContextTypes:function(t,e,n){},receiveComponent:function(t,e,n){var r=this._currentElement,i=this._context;this._pendingElement=null,this.updateComponent(e,r,t,i,n)},performUpdateIfNecessary:function(t){null!=this._pendingElement?v.receiveComponent(this,this._pendingElement,t,this._context):null!==this._pendingStateQueue||this._pendingForceUpdate?this.updateComponent(t,this._currentElement,this._currentElement,this._context,this._context):this._updateBatchNumber=null},updateComponent:function(t,e,n,r,i){var o=this._instance;null==o?u(\"136\",this.getName()||\"ReactCompositeComponent\"):void 0;var a,c=!1;this._context===i?a=o.context:(a=this._processContext(i),c=!0);var s=e.props,l=n.props;e!==n&&(c=!0),c&&o.componentWillReceiveProps&&o.componentWillReceiveProps(l,a);var f=this._processPendingState(l,a),p=!0;this._pendingForceUpdate||(o.shouldComponentUpdate?p=o.shouldComponentUpdate(l,f,a):this._compositeType===_.PureClass&&(p=!m(s,l)||!m(o.state,f))),this._updateBatchNumber=null,p?(this._pendingForceUpdate=!1,this._performComponentUpdate(n,l,f,a,t,i)):(this._currentElement=n,this._context=i,o.props=l,o.state=f,o.context=a)},_processPendingState:function(t,e){var n=this._instance,r=this._pendingStateQueue,i=this._pendingReplaceState;if(this._pendingReplaceState=!1,this._pendingStateQueue=null,!r)return n.state;if(i&&1===r.length)return r[0];for(var o=c({},i?r[0]:n.state),a=i?1:0;a<r.length;a++){var u=r[a];c(o,\"function\"==typeof u?u.call(n,o,t,e):u)}return o},_performComponentUpdate:function(t,e,n,r,i,o){var a,u,c,s=this._instance,l=Boolean(s.componentDidUpdate);l&&(a=s.props,u=s.state,c=s.context),s.componentWillUpdate&&s.componentWillUpdate(e,n,r),this._currentElement=t,this._context=o,s.props=e,s.state=n,s.context=r,this._updateRenderedComponent(i,o),l&&i.getReactMountReady().enqueue(s.componentDidUpdate.bind(s,a,u,c),s)},_updateRenderedComponent:function(t,e){var n=this._renderedComponent,r=n._currentElement,i=this._renderValidatedComponent(),o=0;if(y(r,i))v.receiveComponent(n,i,t,this._processChildContext(e));else{var a=v.getHostNode(n);v.unmountComponent(n,!1);var u=d.getType(i);this._renderedNodeType=u;var c=this._instantiateReactComponent(i,u!==d.EMPTY);this._renderedComponent=c;var s=v.mountComponent(c,t,this._hostParent,this._hostContainerInfo,this._processChildContext(e),o);this._replaceNodeWithMarkup(a,s,n)}},_replaceNodeWithMarkup:function(t,e,n){l.replaceNodeWithMarkup(t,e,n)},_renderValidatedComponentWithoutOwnerOrContext:function(){var t,e=this._instance;return t=e.render()},_renderValidatedComponent:function(){var t;if(this._compositeType!==_.StatelessFunctional){f.current=this;try{t=this._renderValidatedComponentWithoutOwnerOrContext()}finally{f.current=null}}else t=this._renderValidatedComponentWithoutOwnerOrContext();return null===t||t===!1||s.isValidElement(t)?void 0:u(\"109\",this.getName()||\"ReactCompositeComponent\"),t},attachRef:function(t,e){var n=this.getPublicInstance();null==n?u(\"110\"):void 0;var r=e.getPublicInstance(),i=n.refs===g?n.refs={}:n.refs;i[t]=r},detachRef:function(t){var e=this.getPublicInstance().refs;delete e[t]},getName:function(){var t=this._currentElement.type,e=this._instance&&this._instance.constructor;return t.displayName||e&&e.displayName||t.name||e&&e.name||null},getPublicInstance:function(){var t=this._instance;return this._compositeType===_.StatelessFunctional?null:t},_instantiateReactComponent:null};t.exports=x},function(t,e,n){\"use strict\";var r=n(4),i=n(358),o=n(163),a=n(24),u=n(11),c=n(371),s=n(387),l=n(167),f=n(395);n(1);i.inject();var p={findDOMNode:s,render:o.render,unmountComponentAtNode:o.unmountComponentAtNode,version:c,unstable_batchedUpdates:u.batchedUpdates,unstable_renderSubtreeIntoContainer:f};\"undefined\"!=typeof __REACT_DEVTOOLS_GLOBAL_HOOK__&&\"function\"==typeof __REACT_DEVTOOLS_GLOBAL_HOOK__.inject&&__REACT_DEVTOOLS_GLOBAL_HOOK__.inject({ComponentTree:{getClosestInstanceFromNode:r.getClosestInstanceFromNode,getNodeFromInstance:function(t){return t._renderedComponent&&(t=l(t)),t?r.getNodeFromInstance(t):null}},Mount:o,Reconciler:a});t.exports=p},function(t,e,n){\"use strict\";function r(t){if(t){var e=t._currentElement._owner||null;if(e){var n=e.getName();if(n)return\" This DOM node was rendered by `\"+n+\"`.\"}}return\"\"}function i(t,e){e&&(G[t._tag]&&(null!=e.children||null!=e.dangerouslySetInnerHTML?v(\"137\",t._tag,t._currentElement._owner?\" Check the render method of \"+t._currentElement._owner.getName()+\".\":\"\"):void 0),null!=e.dangerouslySetInnerHTML&&(null!=e.children?v(\"60\"):void 0,\"object\"==typeof e.dangerouslySetInnerHTML&&V in e.dangerouslySetInnerHTML?void 0:v(\"61\")),null!=e.style&&\"object\"!=typeof e.style?v(\"62\",r(t)):void 0)}function o(t,e,n,r){if(!(r instanceof I)){var i=t._hostContainerInfo,o=i._node&&i._node.nodeType===H,u=o?i._node:i._ownerDocument;F(e,u),r.getReactMountReady().enqueue(a,{inst:t,registrationName:e,listener:n})}}function a(){var t=this;C.putListener(t.inst,t.registrationName,t.listener)}function u(){var t=this;S.postMountWrapper(t)}function c(){var t=this;A.postMountWrapper(t)}function s(){var t=this;P.postMountWrapper(t)}function l(){var t=this;t._rootNodeID?void 0:v(\"63\");var e=U(t);switch(e?void 0:v(\"64\"),t._tag){case\"iframe\":case\"object\":t._wrapperState.listeners=[k.trapBubbledEvent(\"topLoad\",\"load\",e)];break;case\"video\":case\"audio\":t._wrapperState.listeners=[];for(var n in q)q.hasOwnProperty(n)&&t._wrapperState.listeners.push(k.trapBubbledEvent(n,q[n],e));break;case\"source\":t._wrapperState.listeners=[k.trapBubbledEvent(\"topError\",\"error\",e)];break;case\"img\":t._wrapperState.listeners=[k.trapBubbledEvent(\"topError\",\"error\",e),k.trapBubbledEvent(\"topLoad\",\"load\",e)];break;case\"form\":t._wrapperState.listeners=[k.trapBubbledEvent(\"topReset\",\"reset\",e),k.trapBubbledEvent(\"topSubmit\",\"submit\",e)];break;case\"input\":case\"select\":case\"textarea\":t._wrapperState.listeners=[k.trapBubbledEvent(\"topInvalid\",\"invalid\",e)]}}function f(){N.postUpdateWrapper(this)}function p(t){Z.call(X,t)||($.test(t)?void 0:v(\"65\",t),X[t]=!0)}function h(t,e){return t.indexOf(\"-\")>=0||null!=e.is}function d(t){var e=t.type;p(e),this._currentElement=t,this._tag=e.toLowerCase(),this._namespaceURI=null,this._renderedChildren=null,this._previousStyle=null,this._previousStyleCopy=null,this._hostNode=null,this._hostParent=null,this._rootNodeID=0,this._domID=0,this._hostContainerInfo=null,this._wrapperState=null,this._topLevelWrapper=null,this._flags=0}var v=n(2),g=n(3),m=n(332),y=n(334),_=n(20),b=n(82),x=n(21),w=n(156),C=n(22),M=n(83),k=n(51),E=n(157),T=n(4),S=n(351),P=n(352),N=n(158),A=n(355),O=(n(9),n(364)),I=n(369),D=(n(8),n(54)),R=(n(0),n(94),n(80),n(96),n(1),E),L=C.deleteListener,U=T.getNodeFromInstance,F=k.listenTo,j=M.registrationNameModules,B={string:!0,number:!0},W=\"style\",V=\"__html\",z={children:null,dangerouslySetInnerHTML:null,suppressContentEditableWarning:null},H=11,q={topAbort:\"abort\",topCanPlay:\"canplay\",topCanPlayThrough:\"canplaythrough\",topDurationChange:\"durationchange\",topEmptied:\"emptied\",topEncrypted:\"encrypted\",topEnded:\"ended\",topError:\"error\",topLoadedData:\"loadeddata\",topLoadedMetadata:\"loadedmetadata\",topLoadStart:\"loadstart\",topPause:\"pause\",topPlay:\"play\",topPlaying:\"playing\",topProgress:\"progress\",topRateChange:\"ratechange\",topSeeked:\"seeked\",topSeeking:\"seeking\",topStalled:\"stalled\",topSuspend:\"suspend\",topTimeUpdate:\"timeupdate\",topVolumeChange:\"volumechange\",topWaiting:\"waiting\"},Y={area:!0,base:!0,br:!0,col:!0,embed:!0,hr:!0,img:!0,input:!0,keygen:!0,link:!0,meta:!0,param:!0,source:!0,track:!0,wbr:!0},K={listing:!0,pre:!0,textarea:!0},G=g({menuitem:!0},Y),$=/^[a-zA-Z][a-zA-Z:_\\.\\-\\d]*$/,X={},Z={}.hasOwnProperty,Q=1;d.displayName=\"ReactDOMComponent\",d.Mixin={mountComponent:function(t,e,n,r){this._rootNodeID=Q++,this._domID=n._idCounter++,this._hostParent=e,this._hostContainerInfo=n;var o=this._currentElement.props;switch(this._tag){case\"audio\":case\"form\":case\"iframe\":case\"img\":case\"link\":case\"object\":case\"source\":case\"video\":this._wrapperState={listeners:null},t.getReactMountReady().enqueue(l,this);break;case\"input\":S.mountWrapper(this,o,e),o=S.getHostProps(this,o),t.getReactMountReady().enqueue(l,this);break;case\"option\":P.mountWrapper(this,o,e),o=P.getHostProps(this,o);break;case\"select\":N.mountWrapper(this,o,e),o=N.getHostProps(this,o),t.getReactMountReady().enqueue(l,this);break;case\"textarea\":A.mountWrapper(this,o,e),o=A.getHostProps(this,o),t.getReactMountReady().enqueue(l,this)}i(this,o);var a,f;null!=e?(a=e._namespaceURI,f=e._tag):n._tag&&(a=n._namespaceURI,f=n._tag),(null==a||a===b.svg&&\"foreignobject\"===f)&&(a=b.html),a===b.html&&(\"svg\"===this._tag?a=b.svg:\"math\"===this._tag&&(a=b.mathml)),this._namespaceURI=a;var p;if(t.useCreateElement){var h,d=n._ownerDocument;if(a===b.html)if(\"script\"===this._tag){var v=d.createElement(\"div\"),g=this._currentElement.type;v.innerHTML=\"<\"+g+\"></\"+g+\">\",h=v.removeChild(v.firstChild)}else h=o.is?d.createElement(this._currentElement.type,o.is):d.createElement(this._currentElement.type);else h=d.createElementNS(a,this._currentElement.type);T.precacheNode(this,h),this._flags|=R.hasCachedChildNodes,this._hostParent||w.setAttributeForRoot(h),this._updateDOMProperties(null,o,t);var y=_(h);this._createInitialChildren(t,o,r,y),p=y}else{var x=this._createOpenTagMarkupAndPutListeners(t,o),C=this._createContentMarkup(t,o,r);p=!C&&Y[this._tag]?x+\"/>\":x+\">\"+C+\"</\"+this._currentElement.type+\">\"}switch(this._tag){case\"input\":t.getReactMountReady().enqueue(u,this),o.autoFocus&&t.getReactMountReady().enqueue(m.focusDOMComponent,this);break;case\"textarea\":t.getReactMountReady().enqueue(c,this),o.autoFocus&&t.getReactMountReady().enqueue(m.focusDOMComponent,this);break;case\"select\":o.autoFocus&&t.getReactMountReady().enqueue(m.focusDOMComponent,this);break;case\"button\":o.autoFocus&&t.getReactMountReady().enqueue(m.focusDOMComponent,this);break;case\"option\":t.getReactMountReady().enqueue(s,this)}return p},_createOpenTagMarkupAndPutListeners:function(t,e){var n=\"<\"+this._currentElement.type;for(var r in e)if(e.hasOwnProperty(r)){var i=e[r];if(null!=i)if(j.hasOwnProperty(r))i&&o(this,r,i,t);else{r===W&&(i&&(i=this._previousStyleCopy=g({},e.style)),i=y.createMarkupForStyles(i,this));var a=null;null!=this._tag&&h(this._tag,e)?z.hasOwnProperty(r)||(a=w.createMarkupForCustomAttribute(r,i)):a=w.createMarkupForProperty(r,i),a&&(n+=\" \"+a)}}return t.renderToStaticMarkup?n:(this._hostParent||(n+=\" \"+w.createMarkupForRoot()),n+=\" \"+w.createMarkupForID(this._domID))},_createContentMarkup:function(t,e,n){var r=\"\",i=e.dangerouslySetInnerHTML;if(null!=i)null!=i.__html&&(r=i.__html);else{var o=B[typeof e.children]?e.children:null,a=null!=o?null:e.children;if(null!=o)r=D(o);else if(null!=a){var u=this.mountChildren(a,t,n);r=u.join(\"\")}}return K[this._tag]&&\"\\n\"===r.charAt(0)?\"\\n\"+r:r},_createInitialChildren:function(t,e,n,r){var i=e.dangerouslySetInnerHTML;if(null!=i)null!=i.__html&&_.queueHTML(r,i.__html);else{var o=B[typeof e.children]?e.children:null,a=null!=o?null:e.children;if(null!=o)\"\"!==o&&_.queueText(r,o);else if(null!=a)for(var u=this.mountChildren(a,t,n),c=0;c<u.length;c++)_.queueChild(r,u[c])}},receiveComponent:function(t,e,n){var r=this._currentElement;this._currentElement=t,this.updateComponent(e,r,t,n)},updateComponent:function(t,e,n,r){var o=e.props,a=this._currentElement.props;switch(this._tag){case\"input\":o=S.getHostProps(this,o),a=S.getHostProps(this,a);break;case\"option\":o=P.getHostProps(this,o),a=P.getHostProps(this,a);break;case\"select\":o=N.getHostProps(this,o),a=N.getHostProps(this,a);break;case\"textarea\":o=A.getHostProps(this,o),a=A.getHostProps(this,a)}switch(i(this,a),this._updateDOMProperties(o,a,t),this._updateDOMChildren(o,a,t,r),this._tag){case\"input\":S.updateWrapper(this);break;case\"textarea\":A.updateWrapper(this);break;case\"select\":t.getReactMountReady().enqueue(f,this)}},_updateDOMProperties:function(t,e,n){var r,i,a;for(r in t)if(!e.hasOwnProperty(r)&&t.hasOwnProperty(r)&&null!=t[r])if(r===W){var u=this._previousStyleCopy;for(i in u)u.hasOwnProperty(i)&&(a=a||{},a[i]=\"\");this._previousStyleCopy=null}else j.hasOwnProperty(r)?t[r]&&L(this,r):h(this._tag,t)?z.hasOwnProperty(r)||w.deleteValueForAttribute(U(this),r):(x.properties[r]||x.isCustomAttribute(r))&&w.deleteValueForProperty(U(this),r);for(r in e){var c=e[r],s=r===W?this._previousStyleCopy:null!=t?t[r]:void 0;if(e.hasOwnProperty(r)&&c!==s&&(null!=c||null!=s))if(r===W)if(c?c=this._previousStyleCopy=g({},c):this._previousStyleCopy=null,s){for(i in s)!s.hasOwnProperty(i)||c&&c.hasOwnProperty(i)||(a=a||{},a[i]=\"\");for(i in c)c.hasOwnProperty(i)&&s[i]!==c[i]&&(a=a||{},a[i]=c[i])}else a=c;else if(j.hasOwnProperty(r))c?o(this,r,c,n):s&&L(this,r);else if(h(this._tag,e))z.hasOwnProperty(r)||w.setValueForAttribute(U(this),r,c);else if(x.properties[r]||x.isCustomAttribute(r)){var l=U(this);null!=c?w.setValueForProperty(l,r,c):w.deleteValueForProperty(l,r)}}a&&y.setValueForStyles(U(this),a,this)},_updateDOMChildren:function(t,e,n,r){var i=B[typeof t.children]?t.children:null,o=B[typeof e.children]?e.children:null,a=t.dangerouslySetInnerHTML&&t.dangerouslySetInnerHTML.__html,u=e.dangerouslySetInnerHTML&&e.dangerouslySetInnerHTML.__html,c=null!=i?null:t.children,s=null!=o?null:e.children,l=null!=i||null!=a,f=null!=o||null!=u;null!=c&&null==s?this.updateChildren(null,n,r):l&&!f&&this.updateTextContent(\"\"),null!=o?i!==o&&this.updateTextContent(\"\"+o):null!=u?a!==u&&this.updateMarkup(\"\"+u):null!=s&&this.updateChildren(s,n,r)},getHostNode:function(){return U(this)},unmountComponent:function(t){switch(this._tag){case\"audio\":case\"form\":case\"iframe\":case\"img\":case\"link\":case\"object\":case\"source\":case\"video\":var e=this._wrapperState.listeners;if(e)for(var n=0;n<e.length;n++)e[n].remove();break;case\"html\":case\"head\":case\"body\":v(\"66\",this._tag)}this.unmountChildren(t),T.uncacheNode(this),C.deleteAllListeners(this),this._rootNodeID=0,this._domID=0,this._wrapperState=null},getPublicInstance:function(){return U(this)}},g(d.prototype,d.Mixin,O.Mixin),t.exports=d},function(t,e,n){\"use strict\";function r(t,e){var n={_topLevelWrapper:t,_idCounter:1,_ownerDocument:e?e.nodeType===i?e:e.ownerDocument:null,_node:e,_tag:e?e.nodeName.toLowerCase():null,_namespaceURI:e?e.namespaceURI:null};return n}var i=(n(96),9);t.exports=r},function(t,e,n){\"use strict\";var r=n(3),i=n(20),o=n(4),a=function(t){this._currentElement=null,this._hostNode=null,this._hostParent=null,this._hostContainerInfo=null,this._domID=0};r(a.prototype,{mountComponent:function(t,e,n,r){var a=n._idCounter++;this._domID=a,this._hostParent=e,this._hostContainerInfo=n;var u=\" react-empty: \"+this._domID+\" \";if(t.useCreateElement){var c=n._ownerDocument,s=c.createComment(u);return o.precacheNode(this,s),i(s)}return t.renderToStaticMarkup?\"\":\"<!--\"+u+\"-->\"},receiveComponent:function(){},getHostNode:function(){return o.getNodeFromInstance(this)},unmountComponent:function(){o.uncacheNode(this)}}),t.exports=a},function(t,e,n){\"use strict\";var r={useCreateElement:!0,useFiber:!1};t.exports=r},function(t,e,n){\"use strict\";var r=n(81),i=n(4),o={dangerouslyProcessChildrenUpdates:function(t,e){var n=i.getNodeFromInstance(t);r.processUpdates(n,e)}};t.exports=o},function(t,e,n){\"use strict\";function r(){this._rootNodeID&&f.updateWrapper(this)}function i(t){var e=this._currentElement.props,n=c.executeOnChange(e,t);l.asap(r,this);var i=e.name;if(\"radio\"===e.type&&null!=i){for(var a=s.getNodeFromInstance(this),u=a;u.parentNode;)u=u.parentNode;for(var f=u.querySelectorAll(\"input[name=\"+JSON.stringify(\"\"+i)+'][type=\"radio\"]'),p=0;p<f.length;p++){var h=f[p];if(h!==a&&h.form===a.form){var d=s.getInstanceFromNode(h);d?void 0:o(\"90\"),l.asap(r,d)}}}return n}var o=n(2),a=n(3),u=n(156),c=n(85),s=n(4),l=n(11),f=(n(0),n(1),{getHostProps:function(t,e){var n=c.getValue(e),r=c.getChecked(e),i=a({type:void 0,step:void 0,min:void 0,max:void 0},e,{defaultChecked:void 0,defaultValue:void 0,value:null!=n?n:t._wrapperState.initialValue,checked:null!=r?r:t._wrapperState.initialChecked,onChange:t._wrapperState.onChange});return i},mountWrapper:function(t,e){var n=e.defaultValue;t._wrapperState={initialChecked:null!=e.checked?e.checked:e.defaultChecked,initialValue:null!=e.value?e.value:n,listeners:null,onChange:i.bind(t)}},updateWrapper:function(t){var e=t._currentElement.props,n=e.checked;null!=n&&u.setValueForProperty(s.getNodeFromInstance(t),\"checked\",n||!1);var r=s.getNodeFromInstance(t),i=c.getValue(e);if(null!=i){var o=\"\"+i;o!==r.value&&(r.value=o)}else null==e.value&&null!=e.defaultValue&&r.defaultValue!==\"\"+e.defaultValue&&(r.defaultValue=\"\"+e.defaultValue),null==e.checked&&null!=e.defaultChecked&&(r.defaultChecked=!!e.defaultChecked)},postMountWrapper:function(t){var e=t._currentElement.props,n=s.getNodeFromInstance(t);switch(e.type){case\"submit\":case\"reset\":break;case\"color\":case\"date\":case\"datetime\":case\"datetime-local\":case\"month\":case\"time\":case\"week\":n.value=\"\",n.value=n.defaultValue;break;default:n.value=n.value}var r=n.name;\"\"!==r&&(n.name=\"\"),n.defaultChecked=!n.defaultChecked,n.defaultChecked=!n.defaultChecked,\"\"!==r&&(n.name=r)}});t.exports=f},function(t,e,n){\"use strict\";function r(t){var e=\"\";return o.Children.forEach(t,function(t){null!=t&&(\"string\"==typeof t||\"number\"==typeof t?e+=t:c||(c=!0))}),e}var i=n(3),o=n(26),a=n(4),u=n(158),c=(n(1),!1),s={mountWrapper:function(t,e,n){var i=null;if(null!=n){var o=n;\"optgroup\"===o._tag&&(o=o._hostParent),null!=o&&\"select\"===o._tag&&(i=u.getSelectValueContext(o))}var a=null;if(null!=i){var c;if(c=null!=e.value?e.value+\"\":r(e.children),a=!1,Array.isArray(i)){for(var s=0;s<i.length;s++)if(\"\"+i[s]===c){a=!0;break}}else a=\"\"+i===c}t._wrapperState={selected:a}},postMountWrapper:function(t){var e=t._currentElement.props;if(null!=e.value){var n=a.getNodeFromInstance(t);n.setAttribute(\"value\",e.value)}},getHostProps:function(t,e){var n=i({selected:void 0,children:void 0},e);null!=t._wrapperState.selected&&(n.selected=t._wrapperState.selected);var o=r(e.children);return o&&(n.children=o),n}};t.exports=s},function(t,e,n){\"use strict\";function r(t,e,n,r){return t===n&&e===r}function i(t){var e=document.selection,n=e.createRange(),r=n.text.length,i=n.duplicate();i.moveToElementText(t),i.setEndPoint(\"EndToStart\",n);var o=i.text.length,a=o+r;return{start:o,end:a}}function o(t){var e=window.getSelection&&window.getSelection();if(!e||0===e.rangeCount)return null;var n=e.anchorNode,i=e.anchorOffset,o=e.focusNode,a=e.focusOffset,u=e.getRangeAt(0);try{u.startContainer.nodeType,u.endContainer.nodeType}catch(t){return null}var c=r(e.anchorNode,e.anchorOffset,e.focusNode,e.focusOffset),s=c?0:u.toString().length,l=u.cloneRange();l.selectNodeContents(t),l.setEnd(u.startContainer,u.startOffset);var f=r(l.startContainer,l.startOffset,l.endContainer,l.endOffset),p=f?0:l.toString().length,h=p+s,d=document.createRange();d.setStart(n,i),d.setEnd(o,a);var v=d.collapsed;return{start:v?h:p,end:v?p:h}}function a(t,e){var n,r,i=document.selection.createRange().duplicate();void 0===e.end?(n=e.start,r=n):e.start>e.end?(n=e.end,r=e.start):(n=e.start,r=e.end),i.moveToElementText(t),i.moveStart(\"character\",n),i.setEndPoint(\"EndToStart\",i),i.moveEnd(\"character\",r-n),i.select()}function u(t,e){if(window.getSelection){var n=window.getSelection(),r=t[l()].length,i=Math.min(e.start,r),o=void 0===e.end?i:Math.min(e.end,r);if(!n.extend&&i>o){var a=o;o=i,i=a}var u=s(t,i),c=s(t,o);if(u&&c){var f=document.createRange();f.setStart(u.node,u.offset),n.removeAllRanges(),i>o?(n.addRange(f),n.extend(c.node,c.offset)):(f.setEnd(c.node,c.offset),n.addRange(f))}}}var c=n(6),s=n(392),l=n(168),f=c.canUseDOM&&\"selection\"in document&&!(\"getSelection\"in window),p={getOffsets:f?i:o,setOffsets:f?a:u};t.exports=p},function(t,e,n){\"use strict\";var r=n(2),i=n(3),o=n(81),a=n(20),u=n(4),c=n(54),s=(n(0),n(96),function(t){this._currentElement=t,this._stringText=\"\"+t,this._hostNode=null,this._hostParent=null,this._domID=0,this._mountIndex=0,this._closingComment=null,this._commentNodes=null});i(s.prototype,{mountComponent:function(t,e,n,r){var i=n._idCounter++,o=\" react-text: \"+i+\" \",s=\" /react-text \";if(this._domID=i,this._hostParent=e,t.useCreateElement){var l=n._ownerDocument,f=l.createComment(o),p=l.createComment(s),h=a(l.createDocumentFragment());return a.queueChild(h,a(f)),this._stringText&&a.queueChild(h,a(l.createTextNode(this._stringText))),a.queueChild(h,a(p)),u.precacheNode(this,f),this._closingComment=p,h}var d=c(this._stringText);return t.renderToStaticMarkup?d:\"<!--\"+o+\"-->\"+d+\"<!--\"+s+\"-->\"},receiveComponent:function(t,e){if(t!==this._currentElement){this._currentElement=t;var n=\"\"+t;if(n!==this._stringText){this._stringText=n;var r=this.getHostNode();o.replaceDelimitedText(r[0],r[1],n)}}},getHostNode:function(){var t=this._commentNodes;if(t)return t;if(!this._closingComment)for(var e=u.getNodeFromInstance(this),n=e.nextSibling;;){if(null==n?r(\"67\",this._domID):void 0,8===n.nodeType&&\" /react-text \"===n.nodeValue){this._closingComment=n;break}n=n.nextSibling}return t=[this._hostNode,this._closingComment],this._commentNodes=t,t},unmountComponent:function(){this._closingComment=null,this._commentNodes=null,u.uncacheNode(this)}}),t.exports=s},function(t,e,n){\"use strict\";function r(){this._rootNodeID&&l.updateWrapper(this)}function i(t){var e=this._currentElement.props,n=u.executeOnChange(e,t);return s.asap(r,this),n}var o=n(2),a=n(3),u=n(85),c=n(4),s=n(11),l=(n(0),n(1),{getHostProps:function(t,e){null!=e.dangerouslySetInnerHTML?o(\"91\"):void 0;var n=a({},e,{value:void 0,defaultValue:void 0,children:\"\"+t._wrapperState.initialValue,onChange:t._wrapperState.onChange});return n},mountWrapper:function(t,e){var n=u.getValue(e),r=n;if(null==n){var a=e.defaultValue,c=e.children;null!=c&&(null!=a?o(\"92\"):void 0,Array.isArray(c)&&(c.length<=1?void 0:o(\"93\"),c=c[0]),a=\"\"+c),null==a&&(a=\"\"),r=a}t._wrapperState={initialValue:\"\"+r,listeners:null,onChange:i.bind(t)}},updateWrapper:function(t){var e=t._currentElement.props,n=c.getNodeFromInstance(t),r=u.getValue(e);if(null!=r){var i=\"\"+r;i!==n.value&&(n.value=i),null==e.defaultValue&&(n.defaultValue=i)}null!=e.defaultValue&&(n.defaultValue=e.defaultValue)},postMountWrapper:function(t){var e=c.getNodeFromInstance(t),n=e.textContent;\n",
              "n===t._wrapperState.initialValue&&(e.value=n)}});t.exports=l},function(t,e,n){\"use strict\";function r(t,e){\"_hostNode\"in t?void 0:c(\"33\"),\"_hostNode\"in e?void 0:c(\"33\");for(var n=0,r=t;r;r=r._hostParent)n++;for(var i=0,o=e;o;o=o._hostParent)i++;for(;n-i>0;)t=t._hostParent,n--;for(;i-n>0;)e=e._hostParent,i--;for(var a=n;a--;){if(t===e)return t;t=t._hostParent,e=e._hostParent}return null}function i(t,e){\"_hostNode\"in t?void 0:c(\"35\"),\"_hostNode\"in e?void 0:c(\"35\");for(;e;){if(e===t)return!0;e=e._hostParent}return!1}function o(t){return\"_hostNode\"in t?void 0:c(\"36\"),t._hostParent}function a(t,e,n){for(var r=[];t;)r.push(t),t=t._hostParent;var i;for(i=r.length;i-- >0;)e(r[i],\"captured\",n);for(i=0;i<r.length;i++)e(r[i],\"bubbled\",n)}function u(t,e,n,i,o){for(var a=t&&e?r(t,e):null,u=[];t&&t!==a;)u.push(t),t=t._hostParent;for(var c=[];e&&e!==a;)c.push(e),e=e._hostParent;var s;for(s=0;s<u.length;s++)n(u[s],\"bubbled\",i);for(s=c.length;s-- 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r(){C||(C=!0,y.EventEmitter.injectReactEventListener(m),y.EventPluginHub.injectEventPluginOrder(u),y.EventPluginUtils.injectComponentTree(p),y.EventPluginUtils.injectTreeTraversal(d),y.EventPluginHub.injectEventPluginsByName({SimpleEventPlugin:w,EnterLeaveEventPlugin:c,ChangeEventPlugin:a,SelectEventPlugin:x,BeforeInputEventPlugin:o}),y.HostComponent.injectGenericComponentClass(f),y.HostComponent.injectTextComponentClass(v),y.DOMProperty.injectDOMPropertyConfig(i),y.DOMProperty.injectDOMPropertyConfig(s),y.DOMProperty.injectDOMPropertyConfig(b),y.EmptyComponent.injectEmptyComponentFactory(function(t){return new h(t)}),y.Updates.injectReconcileTransaction(_),y.Updates.injectBatchingStrategy(g),y.Component.injectEnvironment(l))}var i=n(331),o=n(333),a=n(335),u=n(337),c=n(338),s=n(341),l=n(343),f=n(346),p=n(4),h=n(348),d=n(356),v=n(354),g=n(357),m=n(361),y=n(362),_=n(367),b=n(372),x=n(373),w=n(374),C=!1;t.exports={inject:r}},function(t,e,n){\"use strict\";var r=\"function\"==typeof 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v={_enabled:!0,_handleTopLevel:null,WINDOW_HANDLE:s.canUseDOM?window:null,setHandleTopLevel:function(t){v._handleTopLevel=t},setEnabled:function(t){v._enabled=!!t},isEnabled:function(){return v._enabled},trapBubbledEvent:function(t,e,n){return n?c.listen(n,e,v.dispatchEvent.bind(null,t)):null},trapCapturedEvent:function(t,e,n){return n?c.capture(n,e,v.dispatchEvent.bind(null,t)):null},monitorScrollValue:function(t){var e=a.bind(null,t);c.listen(window,\"scroll\",e)},dispatchEvent:function(t,e){if(v._enabled){var n=i.getPooled(t,e);try{p.batchedUpdates(o,n)}finally{i.release(n)}}}};t.exports=v},function(t,e,n){\"use strict\";var r=n(21),i=n(22),o=n(50),a=n(86),u=n(159),c=n(51),s=n(161),l=n(11),f={Component:a.injection,DOMProperty:r.injection,EmptyComponent:u.injection,EventPluginHub:i.injection,EventPluginUtils:o.injection,EventEmitter:c.injection,HostComponent:s.injection,Updates:l.injection};t.exports=f},function(t,e,n){\"use strict\";var r=n(385),i=/\\/?>/,o=/^<\\!\\-\\-/,a={CHECKSUM_ATTR_NAME:\"data-react-checksum\",addChecksumToMarkup:function(t){var e=r(t);return o.test(t)?t:t.replace(i,\" \"+a.CHECKSUM_ATTR_NAME+'=\"'+e+'\"$&')},canReuseMarkup:function(t,e){var n=e.getAttribute(a.CHECKSUM_ATTR_NAME);n=n&&parseInt(n,10);var i=r(t);return i===n}};t.exports=a},function(t,e,n){\"use strict\";function r(t,e,n){return{type:\"INSERT_MARKUP\",content:t,fromIndex:null,fromNode:null,toIndex:n,afterNode:e}}function i(t,e,n){return{type:\"MOVE_EXISTING\",content:null,fromIndex:t._mountIndex,fromNode:p.getHostNode(t),toIndex:n,afterNode:e}}function o(t,e){return{type:\"REMOVE_NODE\",content:null,fromIndex:t._mountIndex,fromNode:e,toIndex:null,afterNode:null}}function a(t){return{type:\"SET_MARKUP\",content:t,fromIndex:null,fromNode:null,toIndex:null,afterNode:null}}function u(t){return{type:\"TEXT_CONTENT\",content:t,fromIndex:null,fromNode:null,toIndex:null,afterNode:null}}function c(t,e){return e&&(t=t||[],t.push(e)),t}function s(t,e){f.processChildrenUpdates(t,e)}var l=n(2),f=n(86),p=(n(40),n(9),n(15),n(24)),h=n(342),d=(n(8),n(388)),v=(n(0),{Mixin:{_reconcilerInstantiateChildren:function(t,e,n){return h.instantiateChildren(t,e,n)},_reconcilerUpdateChildren:function(t,e,n,r,i,o){var a,u=0;return a=d(e,u),h.updateChildren(t,a,n,r,i,this,this._hostContainerInfo,o,u),a},mountChildren:function(t,e,n){var r=this._reconcilerInstantiateChildren(t,e,n);this._renderedChildren=r;var i=[],o=0;for(var a in r)if(r.hasOwnProperty(a)){var u=r[a],c=0,s=p.mountComponent(u,e,this,this._hostContainerInfo,n,c);u._mountIndex=o++,i.push(s)}return i},updateTextContent:function(t){var e=this._renderedChildren;h.unmountChildren(e,!1);for(var n in e)e.hasOwnProperty(n)&&l(\"118\");var r=[u(t)];s(this,r)},updateMarkup:function(t){var e=this._renderedChildren;h.unmountChildren(e,!1);for(var n in e)e.hasOwnProperty(n)&&l(\"118\");var r=[a(t)];s(this,r)},updateChildren:function(t,e,n){this._updateChildren(t,e,n)},_updateChildren:function(t,e,n){var r=this._renderedChildren,i={},o=[],a=this._reconcilerUpdateChildren(r,t,o,i,e,n);if(a||r){var u,l=null,f=0,h=0,d=0,v=null;for(u in a)if(a.hasOwnProperty(u)){var g=r&&r[u],m=a[u];g===m?(l=c(l,this.moveChild(g,v,f,h)),h=Math.max(g._mountIndex,h),g._mountIndex=f):(g&&(h=Math.max(g._mountIndex,h)),l=c(l,this._mountChildAtIndex(m,o[d],v,f,e,n)),d++),f++,v=p.getHostNode(m)}for(u in i)i.hasOwnProperty(u)&&(l=c(l,this._unmountChild(r[u],i[u])));l&&s(this,l),this._renderedChildren=a}},unmountChildren:function(t){var e=this._renderedChildren;h.unmountChildren(e,t),this._renderedChildren=null},moveChild:function(t,e,n,r){if(t._mountIndex<r)return i(t,e,n)},createChild:function(t,e,n){return r(n,e,t._mountIndex)},removeChild:function(t,e){return o(t,e)},_mountChildAtIndex:function(t,e,n,r,i,o){return t._mountIndex=r,this.createChild(t,n,e)},_unmountChild:function(t,e){var n=this.removeChild(t,e);return t._mountIndex=null,n}}});t.exports=v},function(t,e,n){\"use strict\";function r(t){return!(!t||\"function\"!=typeof t.attachRef||\"function\"!=typeof t.detachRef)}var i=n(2),o=(n(0),{addComponentAsRefTo:function(t,e,n){r(n)?void 0:i(\"119\"),n.attachRef(e,t)},removeComponentAsRefFrom:function(t,e,n){r(n)?void 0:i(\"120\");var o=n.getPublicInstance();o&&o.refs[e]===t.getPublicInstance()&&n.detachRef(e)}});t.exports=o},function(t,e,n){\"use strict\";var r=\"SECRET_DO_NOT_PASS_THIS_OR_YOU_WILL_BE_FIRED\";t.exports=r},function(t,e,n){\"use strict\";function r(t){this.reinitializeTransaction(),this.renderToStaticMarkup=!1,this.reactMountReady=o.getPooled(null),this.useCreateElement=t}var i=n(3),o=n(155),a=n(17),u=n(51),c=n(162),s=(n(9),n(53)),l=n(88),f={initialize:c.getSelectionInformation,close:c.restoreSelection},p={initialize:function(){var t=u.isEnabled();return u.setEnabled(!1),t},close:function(t){u.setEnabled(t)}},h={initialize:function(){this.reactMountReady.reset()},close:function(){this.reactMountReady.notifyAll()}},d=[f,p,h],v={getTransactionWrappers:function(){return d},getReactMountReady:function(){return this.reactMountReady},getUpdateQueue:function(){return l},checkpoint:function(){return this.reactMountReady.checkpoint()},rollback:function(t){this.reactMountReady.rollback(t)},destructor:function(){o.release(this.reactMountReady),this.reactMountReady=null}};i(r.prototype,s,v),a.addPoolingTo(r),t.exports=r},function(t,e,n){\"use strict\";function r(t,e,n){\"function\"==typeof t?t(e.getPublicInstance()):o.addComponentAsRefTo(e,t,n)}function i(t,e,n){\"function\"==typeof t?t(null):o.removeComponentAsRefFrom(e,t,n)}var o=n(365),a={};a.attachRefs=function(t,e){if(null!==e&&\"object\"==typeof e){var n=e.ref;null!=n&&r(n,t,e._owner)}},a.shouldUpdateRefs=function(t,e){var n=null,r=null;null!==t&&\"object\"==typeof 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              " <script>\n",
              "   if (window.SHAP) SHAP.ReactDom.render(\n",
              "    SHAP.React.createElement(SHAP.AdditiveForceVisualizer, {\"outNames\": [\"f(x)\"], \"baseValue\": 0.4933333333333332, \"outValue\": 0.52, \"link\": \"identity\", \"featureNames\": [\"Goal Scored\", \"Ball Possession %\", \"Attempts\", \"On-Target\", \"Off-Target\", \"Blocked\", \"Corners\", \"Offsides\", \"Free Kicks\", \"Saves\", \"Pass Accuracy %\", \"Passes\", \"Distance Covered (Kms)\", \"Fouls Committed\", \"Yellow Card\", \"Yellow & Red\", \"Red\", \"Goals in PSO\"], \"features\": {\"0\": {\"effect\": 0.07631664425523205, \"value\": 3.0}, \"1\": {\"effect\": 0.017082196603667013, \"value\": 56.0}, \"2\": {\"effect\": -0.042474266233413355, \"value\": 24.0}, \"3\": {\"effect\": 0.029715828728578975, \"value\": 8.0}, \"4\": {\"effect\": -0.04146371496684343, \"value\": 10.0}, \"5\": {\"effect\": 0.007079420488682486, \"value\": 6.0}, \"6\": {\"effect\": -0.0013043244392677705, \"value\": 10.0}, \"7\": {\"effect\": 0.0008979633346299538, \"value\": 1.0}, \"8\": {\"effect\": -0.04781617597156596, \"value\": 10.0}, \"9\": {\"effect\": 0.002840887308742504, \"value\": 3.0}, \"10\": {\"effect\": 0.003555173709970192, \"value\": 87.0}, \"11\": {\"effect\": 0.023536801162783755, \"value\": 621.0}, \"12\": {\"effect\": 0.00908527501062293, \"value\": 108.0}, \"13\": {\"effect\": -0.011187407983633928, \"value\": 13.0}, \"14\": {\"effect\": 0.0009597191843076884, \"value\": 0.0}, \"15\": {\"effect\": 0.00039319007929300084, \"value\": 0.0}, \"16\": {\"effect\": -0.0005505436051192608, \"value\": 0.0}}, \"plot_cmap\": \"RdBu\", \"labelMargin\": 20}),\n",
              "    document.getElementById('iP7CNL0K5F7KEKE3V9XQD')\n",
              "  );\n",
              "</script>"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "SHAP diagram that shows how the features impact on the match Uruguay-Russia. A\n",
        "force diagram representing how much the features change the final value. For example we see that\n",
        "“Goal Scored = 3” has the most impact for it pushes the final value to the right with the biggest\n",
        "interval.\n",
        "\n",
        "Features on the left are the\n",
        "ones that increase the predictions, and their relative length is an indication of the\n",
        "importance of the features in determining the prediction.\n",
        "Features on the right, same logic, are the ones that are expected to decrease the\n",
        "prediction value. For this specific match, we predicted a probability of 0.52 for\n",
        "Uruguay to have “Player of the Match” that is not so high considering that they\n",
        "scored three goals (remember that goal scored was identified as the most important\n",
        "feature).\n",
        "The value 0.52 has to be compared with the baseline value of 0.50, which is the\n",
        "average of all the outputs and, in this case, represents the maximal uncertainty. We\n",
        "see the explanation of this result: albeit the red driving features, we have the free\n",
        "kicks, attempts, and off-target features that depress the overall probability. The shift\n",
        "from the baseline is the difference in length between the sum of red bars and the\n",
        "blue bars."
      ],
      "metadata": {
        "id": "kRgBRq-W6zBD"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "SHAP allows getting a summary plot in which we see the\n",
        "impact of each feature on each prediction."
      ],
      "metadata": {
        "id": "nwmgVRns1VaA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "shap_values = k_explainer.shap_values(val_X) #A\n",
        "shap.summary_plot(shap_values[1], val_X)\n",
        "#A We call the summary plot"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 926,
          "referenced_widgets": [
            "f882167446644d97b2b99297d291168b",
            "6d51e47ecd064c76a94cde6f812620f0",
            "d194088e84e74c44be81c52c6dd804be",
            "5b11d004299741448a800716e2dc3e8e",
            "70656072e4be425ea08d69159808ae70",
            "b542f6cb3b7c4cf98aea257df0fcc790",
            "08e443b1dc9644cc83c9e7df2253c355",
            "4ffd045b26b9406aa71429d7f5ae0c23",
            "4ab7bbbabe3f4214b49d8780f60c9cb1",
            "649fe5df834c434795c0a918ae215d33",
            "257b215314e8441ea3903d06578055a4"
          ]
        },
        "id": "DVgvwfvN1Wdy",
        "outputId": "08b3c9f0-8f2d-4bca-b83f-e0048988b92f"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/32 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "f882167446644d97b2b99297d291168b"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "No data for colormapping provided via 'c'. Parameters 'vmin', 'vmax' will be ignored\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x870 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "SHAP allows getting a summary plot in which we see the\n",
        "impact of each feature on each prediction."
      ],
      "metadata": {
        "id": "mbSKZq6h3fKN"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Recap\n",
        "\n",
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      "metadata": {
        "id": "ShIK-ABL5a9K"
      }
    }
  ]
}