data_processing.ipynb

{
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      "cell_type": "markdown",
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        "id": "view-in-github",
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      "source": [
        "<a href=\"https://colab.research.google.com/github/JohnnyBravo10/NBA-salary-prediction-/blob/main/data_processing.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#importing libraries\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "from random import random\n",
        "from random import randint\n",
        "from random import seed\n",
        "from numpy import mean\n",
        "from numpy import std\n",
        "from numpy import absolute\n",
        "from sklearn.datasets import make_regression\n",
        "from sklearn.model_selection import cross_val_score\n",
        "from sklearn.model_selection import RepeatedKFold\n",
        "from sklearn.linear_model import LinearRegression\n",
        "from sklearn.linear_model import HuberRegressor\n",
        "from sklearn.linear_model import RANSACRegressor\n",
        "from sklearn.linear_model import TheilSenRegressor, GammaRegressor, PoissonRegressor, TweedieRegressor, Ridge, Lasso\n",
        "from matplotlib import pyplot\n",
        "from sklearn.ensemble import RandomForestRegressor, BaggingRegressor\n",
        "from sklearn.metrics import mean_absolute_percentage_error\n",
        "from sklearn.feature_selection import SelectKBest, f_regression\n",
        "from sklearn import preprocessing\n",
        "import numpy as np\n",
        "from sklearn.neighbors import KNeighborsRegressor\n",
        "from sklearn.dummy import DummyRegressor\n"
      ],
      "metadata": {
        "id": "APoW8cI9w6F4"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "##loading dataset\n",
        "dataframe = pd.read_csv(\"/nba_contracts_history.csv\")\n",
        "print(dataframe.shape)\n",
        "dataframe\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "XyfXXDiHk7XY",
        "outputId": "fa92c1b6-c8ee-4504-e658-c24895a3208d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 679
        }
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(199, 28)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                NAME  CONTRACT_START  CONTRACT_END    AVG_SALARY   AGE    GP  \\\n",
              "0    Wesley Matthews            2019          2020  2.564753e+06  32.0  69.0   \n",
              "1        Brook Lopez            2015          2017  2.116568e+07  27.0  72.0   \n",
              "2     DeAndre Jordan            2011          2014  1.075976e+07  22.0  80.0   \n",
              "3    Markieff Morris            2015          2018  8.143324e+06  25.0  82.0   \n",
              "4      Dwight Howard            2018          2019  1.341074e+07  32.0  81.0   \n",
              "..               ...             ...           ...           ...   ...   ...   \n",
              "194      Brook Lopez            2012          2014  1.469367e+07  24.0   5.0   \n",
              "195   Nikola Vucevic            2015          2018  1.200000e+07  24.0  74.0   \n",
              "196      Aron Baynes            2015          2017  5.766667e+06  28.0  70.0   \n",
              "197   Andre Iguodala            2013          2016  1.200000e+07  29.0  80.0   \n",
              "198   Draymond Green            2015          2019  1.640000e+07  25.0  79.0   \n",
              "\n",
              "        W     L     MIN     PTS  ...   FT%   OREB   DREB     REB    AST  \\\n",
              "0    27.0  42.0  2091.0   840.0  ...  81.0   32.0  138.0   170.0  160.0   \n",
              "1    34.0  38.0  2100.0  1236.0  ...  81.4  214.0  321.0   535.0   50.0   \n",
              "2    31.0  49.0  2047.0   566.0  ...  45.2  207.0  368.0   575.0   42.0   \n",
              "3    39.0  43.0  2581.0  1258.0  ...  76.3  110.0  396.0   506.0  192.0   \n",
              "4    35.0  46.0  2463.0  1347.0  ...  57.4  255.0  757.0  1012.0  105.0   \n",
              "..    ...   ...     ...     ...  ...   ...    ...    ...     ...    ...   \n",
              "194   2.0   3.0   136.0    96.0  ...  62.5    8.0   10.0    18.0    6.0   \n",
              "195  21.0  53.0  2529.0  1428.0  ...  75.2  238.0  572.0   810.0  147.0   \n",
              "196  49.0  21.0  1122.0   461.0  ...  86.5  109.0  209.0   318.0   35.0   \n",
              "197  57.0  23.0  2779.0  1038.0  ...  57.4   82.0  341.0   423.0  433.0   \n",
              "198  64.0  15.0  2490.0   921.0  ...  66.0  114.0  533.0   647.0  291.0   \n",
              "\n",
              "       TOV    STL    BLK     PF    +/-  \n",
              "0     91.0   54.0   17.0  160.0  -90.0  \n",
              "1    104.0   43.0  126.0  206.0 -104.0  \n",
              "2    101.0   41.0  142.0  255.0 -100.0  \n",
              "3    170.0  101.0   39.0  245.0  105.0  \n",
              "4    208.0   48.0  131.0  249.0   89.0  \n",
              "..     ...    ...    ...    ...    ...  \n",
              "194    6.0    1.0    4.0    8.0  -27.0  \n",
              "195  148.0   54.0   54.0  220.0 -302.0  \n",
              "196   65.0   16.0   22.0  162.0  136.0  \n",
              "197  206.0  139.0   52.0  127.0  380.0  \n",
              "198  133.0  123.0   99.0  253.0  839.0  \n",
              "\n",
              "[199 rows x 28 columns]"
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>NAME</th>\n",
              "      <th>CONTRACT_START</th>\n",
              "      <th>CONTRACT_END</th>\n",
              "      <th>AVG_SALARY</th>\n",
              "      <th>AGE</th>\n",
              "      <th>GP</th>\n",
              "      <th>W</th>\n",
              "      <th>L</th>\n",
              "      <th>MIN</th>\n",
              "      <th>PTS</th>\n",
              "      <th>...</th>\n",
              "      <th>FT%</th>\n",
              "      <th>OREB</th>\n",
              "      <th>DREB</th>\n",
              "      <th>REB</th>\n",
              "      <th>AST</th>\n",
              "      <th>TOV</th>\n",
              "      <th>STL</th>\n",
              "      <th>BLK</th>\n",
              "      <th>PF</th>\n",
              "      <th>+/-</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Wesley Matthews</td>\n",
              "      <td>2019</td>\n",
              "      <td>2020</td>\n",
              "      <td>2.564753e+06</td>\n",
              "      <td>32.0</td>\n",
              "      <td>69.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>42.0</td>\n",
              "      <td>2091.0</td>\n",
              "      <td>840.0</td>\n",
              "      <td>...</td>\n",
              "      <td>81.0</td>\n",
              "      <td>32.0</td>\n",
              "      <td>138.0</td>\n",
              "      <td>170.0</td>\n",
              "      <td>160.0</td>\n",
              "      <td>91.0</td>\n",
              "      <td>54.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>160.0</td>\n",
              "      <td>-90.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Brook Lopez</td>\n",
              "      <td>2015</td>\n",
              "      <td>2017</td>\n",
              "      <td>2.116568e+07</td>\n",
              "      <td>27.0</td>\n",
              "      <td>72.0</td>\n",
              "      <td>34.0</td>\n",
              "      <td>38.0</td>\n",
              "      <td>2100.0</td>\n",
              "      <td>1236.0</td>\n",
              "      <td>...</td>\n",
              "      <td>81.4</td>\n",
              "      <td>214.0</td>\n",
              "      <td>321.0</td>\n",
              "      <td>535.0</td>\n",
              "      <td>50.0</td>\n",
              "      <td>104.0</td>\n",
              "      <td>43.0</td>\n",
              "      <td>126.0</td>\n",
              "      <td>206.0</td>\n",
              "      <td>-104.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>DeAndre Jordan</td>\n",
              "      <td>2011</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.075976e+07</td>\n",
              "      <td>22.0</td>\n",
              "      <td>80.0</td>\n",
              "      <td>31.0</td>\n",
              "      <td>49.0</td>\n",
              "      <td>2047.0</td>\n",
              "      <td>566.0</td>\n",
              "      <td>...</td>\n",
              "      <td>45.2</td>\n",
              "      <td>207.0</td>\n",
              "      <td>368.0</td>\n",
              "      <td>575.0</td>\n",
              "      <td>42.0</td>\n",
              "      <td>101.0</td>\n",
              "      <td>41.0</td>\n",
              "      <td>142.0</td>\n",
              "      <td>255.0</td>\n",
              "      <td>-100.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Markieff Morris</td>\n",
              "      <td>2015</td>\n",
              "      <td>2018</td>\n",
              "      <td>8.143324e+06</td>\n",
              "      <td>25.0</td>\n",
              "      <td>82.0</td>\n",
              "      <td>39.0</td>\n",
              "      <td>43.0</td>\n",
              "      <td>2581.0</td>\n",
              "      <td>1258.0</td>\n",
              "      <td>...</td>\n",
              "      <td>76.3</td>\n",
              "      <td>110.0</td>\n",
              "      <td>396.0</td>\n",
              "      <td>506.0</td>\n",
              "      <td>192.0</td>\n",
              "      <td>170.0</td>\n",
              "      <td>101.0</td>\n",
              "      <td>39.0</td>\n",
              "      <td>245.0</td>\n",
              "      <td>105.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Dwight Howard</td>\n",
              "      <td>2018</td>\n",
              "      <td>2019</td>\n",
              "      <td>1.341074e+07</td>\n",
              "      <td>32.0</td>\n",
              "      <td>81.0</td>\n",
              "      <td>35.0</td>\n",
              "      <td>46.0</td>\n",
              "      <td>2463.0</td>\n",
              "      <td>1347.0</td>\n",
              "      <td>...</td>\n",
              "      <td>57.4</td>\n",
              "      <td>255.0</td>\n",
              "      <td>757.0</td>\n",
              "      <td>1012.0</td>\n",
              "      <td>105.0</td>\n",
              "      <td>208.0</td>\n",
              "      <td>48.0</td>\n",
              "      <td>131.0</td>\n",
              "      <td>249.0</td>\n",
              "      <td>89.0</td>\n",
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              "    <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",
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              "    <tr>\n",
              "      <th>194</th>\n",
              "      <td>Brook Lopez</td>\n",
              "      <td>2012</td>\n",
              "      <td>2014</td>\n",
              "      <td>1.469367e+07</td>\n",
              "      <td>24.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>136.0</td>\n",
              "      <td>96.0</td>\n",
              "      <td>...</td>\n",
              "      <td>62.5</td>\n",
              "      <td>8.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>18.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>-27.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>195</th>\n",
              "      <td>Nikola Vucevic</td>\n",
              "      <td>2015</td>\n",
              "      <td>2018</td>\n",
              "      <td>1.200000e+07</td>\n",
              "      <td>24.0</td>\n",
              "      <td>74.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>53.0</td>\n",
              "      <td>2529.0</td>\n",
              "      <td>1428.0</td>\n",
              "      <td>...</td>\n",
              "      <td>75.2</td>\n",
              "      <td>238.0</td>\n",
              "      <td>572.0</td>\n",
              "      <td>810.0</td>\n",
              "      <td>147.0</td>\n",
              "      <td>148.0</td>\n",
              "      <td>54.0</td>\n",
              "      <td>54.0</td>\n",
              "      <td>220.0</td>\n",
              "      <td>-302.0</td>\n",
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              "    <tr>\n",
              "      <th>196</th>\n",
              "      <td>Aron Baynes</td>\n",
              "      <td>2015</td>\n",
              "      <td>2017</td>\n",
              "      <td>5.766667e+06</td>\n",
              "      <td>28.0</td>\n",
              "      <td>70.0</td>\n",
              "      <td>49.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>1122.0</td>\n",
              "      <td>461.0</td>\n",
              "      <td>...</td>\n",
              "      <td>86.5</td>\n",
              "      <td>109.0</td>\n",
              "      <td>209.0</td>\n",
              "      <td>318.0</td>\n",
              "      <td>35.0</td>\n",
              "      <td>65.0</td>\n",
              "      <td>16.0</td>\n",
              "      <td>22.0</td>\n",
              "      <td>162.0</td>\n",
              "      <td>136.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>197</th>\n",
              "      <td>Andre Iguodala</td>\n",
              "      <td>2013</td>\n",
              "      <td>2016</td>\n",
              "      <td>1.200000e+07</td>\n",
              "      <td>29.0</td>\n",
              "      <td>80.0</td>\n",
              "      <td>57.0</td>\n",
              "      <td>23.0</td>\n",
              "      <td>2779.0</td>\n",
              "      <td>1038.0</td>\n",
              "      <td>...</td>\n",
              "      <td>57.4</td>\n",
              "      <td>82.0</td>\n",
              "      <td>341.0</td>\n",
              "      <td>423.0</td>\n",
              "      <td>433.0</td>\n",
              "      <td>206.0</td>\n",
              "      <td>139.0</td>\n",
              "      <td>52.0</td>\n",
              "      <td>127.0</td>\n",
              "      <td>380.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>198</th>\n",
              "      <td>Draymond Green</td>\n",
              "      <td>2015</td>\n",
              "      <td>2019</td>\n",
              "      <td>1.640000e+07</td>\n",
              "      <td>25.0</td>\n",
              "      <td>79.0</td>\n",
              "      <td>64.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>2490.0</td>\n",
              "      <td>921.0</td>\n",
              "      <td>...</td>\n",
              "      <td>66.0</td>\n",
              "      <td>114.0</td>\n",
              "      <td>533.0</td>\n",
              "      <td>647.0</td>\n",
              "      <td>291.0</td>\n",
              "      <td>133.0</td>\n",
              "      <td>123.0</td>\n",
              "      <td>99.0</td>\n",
              "      <td>253.0</td>\n",
              "      <td>839.0</td>\n",
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              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-8ddd3105-3bd2-4cee-a222-b69423f1f014');\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": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "EazaXwHb2XIZ"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "##stathistical exploration\n",
        "dataframe.describe(percentiles=[]).T.apply(lambda s: s.apply('{0:.2f}'.format))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 896
        },
        "id": "HAKXtezgwYER",
        "outputId": "5a940382-d7e1-4d87-df2d-c6d0a1ad74e7"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                 count         mean         std        min         50%  \\\n",
              "CONTRACT_START  199.00      2015.24        2.07    2011.00     2015.00   \n",
              "CONTRACT_END    199.00      2017.51        1.71    2013.00     2018.00   \n",
              "AVG_SALARY      199.00  11073609.12  7897819.67  823244.00  9500000.00   \n",
              "AGE             199.00        25.93        2.84      20.00       25.00   \n",
              "GP              199.00        64.17       19.57       1.00       72.00   \n",
              "W               199.00        34.22       14.49       0.00       35.00   \n",
              "L               199.00        29.95       13.02       0.00       31.00   \n",
              "MIN             199.00      1746.98      782.41       2.00     1867.00   \n",
              "PTS             199.00       813.45      499.93       0.00      734.00   \n",
              "FGM             199.00       300.40      178.63       0.00      277.00   \n",
              "FGA             199.00       638.76      374.61       1.00      572.00   \n",
              "FG%             199.00        46.74        8.09       0.00       45.50   \n",
              "3PM             199.00        63.61       58.40       0.00       57.00   \n",
              "3PA             199.00       173.95      148.65       0.00      170.00   \n",
              "3P%             199.00        29.72       13.24       0.00       34.80   \n",
              "FTM             199.00       149.05      128.38       0.00      107.00   \n",
              "FTA             199.00       195.52      162.24       0.00      145.00   \n",
              "FT%             199.00        74.03       14.98       0.00       76.80   \n",
              "OREB            199.00        79.35       72.71       0.00       51.00   \n",
              "DREB            199.00       248.98      164.02       1.00      209.00   \n",
              "REB             199.00       328.33      226.11       1.00      286.00   \n",
              "AST             199.00       171.67      163.87       0.00      110.00   \n",
              "TOV             199.00       103.39       70.89       0.00       85.00   \n",
              "STL             199.00        58.19       37.31       0.00       48.00   \n",
              "BLK             199.00        39.63       43.35       0.00       23.00   \n",
              "PF              199.00       137.67       64.28       1.00      137.00   \n",
              "+/-             199.00        62.87      227.68    -628.00       44.00   \n",
              "\n",
              "                        max  \n",
              "CONTRACT_START      2019.00  \n",
              "CONTRACT_END        2020.00  \n",
              "AVG_SALARY      33599500.00  \n",
              "AGE                   36.00  \n",
              "GP                    82.00  \n",
              "W                     64.00  \n",
              "L                     62.00  \n",
              "MIN                 3125.00  \n",
              "PTS                 2376.00  \n",
              "FGM                  743.00  \n",
              "FGA                 1643.00  \n",
              "FG%                  100.00  \n",
              "3PM                  272.00  \n",
              "3PA                  657.00  \n",
              "3P%                   50.00  \n",
              "FTM                  720.00  \n",
              "FTA                  837.00  \n",
              "FT%                  100.00  \n",
              "OREB                 397.00  \n",
              "DREB                 829.00  \n",
              "REB                 1226.00  \n",
              "AST                  839.00  \n",
              "TOV                  374.00  \n",
              "STL                  169.00  \n",
              "BLK                  269.00  \n",
              "PF                   291.00  \n",
              "+/-                  839.00  "
            ],
            "text/html": [
              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>count</th>\n",
              "      <th>mean</th>\n",
              "      <th>std</th>\n",
              "      <th>min</th>\n",
              "      <th>50%</th>\n",
              "      <th>max</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>CONTRACT_START</th>\n",
              "      <td>199.00</td>\n",
              "      <td>2015.24</td>\n",
              "      <td>2.07</td>\n",
              "      <td>2011.00</td>\n",
              "      <td>2015.00</td>\n",
              "      <td>2019.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CONTRACT_END</th>\n",
              "      <td>199.00</td>\n",
              "      <td>2017.51</td>\n",
              "      <td>1.71</td>\n",
              "      <td>2013.00</td>\n",
              "      <td>2018.00</td>\n",
              "      <td>2020.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>AVG_SALARY</th>\n",
              "      <td>199.00</td>\n",
              "      <td>11073609.12</td>\n",
              "      <td>7897819.67</td>\n",
              "      <td>823244.00</td>\n",
              "      <td>9500000.00</td>\n",
              "      <td>33599500.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>AGE</th>\n",
              "      <td>199.00</td>\n",
              "      <td>25.93</td>\n",
              "      <td>2.84</td>\n",
              "      <td>20.00</td>\n",
              "      <td>25.00</td>\n",
              "      <td>36.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>GP</th>\n",
              "      <td>199.00</td>\n",
              "      <td>64.17</td>\n",
              "      <td>19.57</td>\n",
              "      <td>1.00</td>\n",
              "      <td>72.00</td>\n",
              "      <td>82.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>W</th>\n",
              "      <td>199.00</td>\n",
              "      <td>34.22</td>\n",
              "      <td>14.49</td>\n",
              "      <td>0.00</td>\n",
              "      <td>35.00</td>\n",
              "      <td>64.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L</th>\n",
              "      <td>199.00</td>\n",
              "      <td>29.95</td>\n",
              "      <td>13.02</td>\n",
              "      <td>0.00</td>\n",
              "      <td>31.00</td>\n",
              "      <td>62.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MIN</th>\n",
              "      <td>199.00</td>\n",
              "      <td>1746.98</td>\n",
              "      <td>782.41</td>\n",
              "      <td>2.00</td>\n",
              "      <td>1867.00</td>\n",
              "      <td>3125.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>PTS</th>\n",
              "      <td>199.00</td>\n",
              "      <td>813.45</td>\n",
              "      <td>499.93</td>\n",
              "      <td>0.00</td>\n",
              "      <td>734.00</td>\n",
              "      <td>2376.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>FGM</th>\n",
              "      <td>199.00</td>\n",
              "      <td>300.40</td>\n",
              "      <td>178.63</td>\n",
              "      <td>0.00</td>\n",
              "      <td>277.00</td>\n",
              "      <td>743.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>FGA</th>\n",
              "      <td>199.00</td>\n",
              "      <td>638.76</td>\n",
              "      <td>374.61</td>\n",
              "      <td>1.00</td>\n",
              "      <td>572.00</td>\n",
              "      <td>1643.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>FG%</th>\n",
              "      <td>199.00</td>\n",
              "      <td>46.74</td>\n",
              "      <td>8.09</td>\n",
              "      <td>0.00</td>\n",
              "      <td>45.50</td>\n",
              "      <td>100.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3PM</th>\n",
              "      <td>199.00</td>\n",
              "      <td>63.61</td>\n",
              "      <td>58.40</td>\n",
              "      <td>0.00</td>\n",
              "      <td>57.00</td>\n",
              "      <td>272.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3PA</th>\n",
              "      <td>199.00</td>\n",
              "      <td>173.95</td>\n",
              "      <td>148.65</td>\n",
              "      <td>0.00</td>\n",
              "      <td>170.00</td>\n",
              "      <td>657.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3P%</th>\n",
              "      <td>199.00</td>\n",
              "      <td>29.72</td>\n",
              "      <td>13.24</td>\n",
              "      <td>0.00</td>\n",
              "      <td>34.80</td>\n",
              "      <td>50.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>FTM</th>\n",
              "      <td>199.00</td>\n",
              "      <td>149.05</td>\n",
              "      <td>128.38</td>\n",
              "      <td>0.00</td>\n",
              "      <td>107.00</td>\n",
              "      <td>720.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>FTA</th>\n",
              "      <td>199.00</td>\n",
              "      <td>195.52</td>\n",
              "      <td>162.24</td>\n",
              "      <td>0.00</td>\n",
              "      <td>145.00</td>\n",
              "      <td>837.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>FT%</th>\n",
              "      <td>199.00</td>\n",
              "      <td>74.03</td>\n",
              "      <td>14.98</td>\n",
              "      <td>0.00</td>\n",
              "      <td>76.80</td>\n",
              "      <td>100.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>OREB</th>\n",
              "      <td>199.00</td>\n",
              "      <td>79.35</td>\n",
              "      <td>72.71</td>\n",
              "      <td>0.00</td>\n",
              "      <td>51.00</td>\n",
              "      <td>397.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DREB</th>\n",
              "      <td>199.00</td>\n",
              "      <td>248.98</td>\n",
              "      <td>164.02</td>\n",
              "      <td>1.00</td>\n",
              "      <td>209.00</td>\n",
              "      <td>829.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>REB</th>\n",
              "      <td>199.00</td>\n",
              "      <td>328.33</td>\n",
              "      <td>226.11</td>\n",
              "      <td>1.00</td>\n",
              "      <td>286.00</td>\n",
              "      <td>1226.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>AST</th>\n",
              "      <td>199.00</td>\n",
              "      <td>171.67</td>\n",
              "      <td>163.87</td>\n",
              "      <td>0.00</td>\n",
              "      <td>110.00</td>\n",
              "      <td>839.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>TOV</th>\n",
              "      <td>199.00</td>\n",
              "      <td>103.39</td>\n",
              "      <td>70.89</td>\n",
              "      <td>0.00</td>\n",
              "      <td>85.00</td>\n",
              "      <td>374.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>STL</th>\n",
              "      <td>199.00</td>\n",
              "      <td>58.19</td>\n",
              "      <td>37.31</td>\n",
              "      <td>0.00</td>\n",
              "      <td>48.00</td>\n",
              "      <td>169.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>BLK</th>\n",
              "      <td>199.00</td>\n",
              "      <td>39.63</td>\n",
              "      <td>43.35</td>\n",
              "      <td>0.00</td>\n",
              "      <td>23.00</td>\n",
              "      <td>269.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>PF</th>\n",
              "      <td>199.00</td>\n",
              "      <td>137.67</td>\n",
              "      <td>64.28</td>\n",
              "      <td>1.00</td>\n",
              "      <td>137.00</td>\n",
              "      <td>291.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>+/-</th>\n",
              "      <td>199.00</td>\n",
              "      <td>62.87</td>\n",
              "      <td>227.68</td>\n",
              "      <td>-628.00</td>\n",
              "      <td>44.00</td>\n",
              "      <td>839.00</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dataframe.hist(bins=30, figsize=(15, 16), )\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 934
        },
        "id": "RxqZLOFmrl6N",
        "outputId": "8021df8d-4dbd-4a9b-8415-2f765066d30b"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x1152 with 30 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#checking for duplicates\n",
        "dups=dataframe.duplicated()\n",
        "print(dups.any())\n",
        "\n",
        "print(dataframe[dups])\n",
        "#turns out there's a duplicate\n",
        "#delete duplicate rows\n",
        "dataframe.drop_duplicates(inplace=True)\n",
        "print(dataframe.shape)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3R-WDOfka8jJ",
        "outputId": "23d07a9e-32ca-404f-ae7b-b74ff6cf5090"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "True\n",
            "           NAME  CONTRACT_START  CONTRACT_END  AVG_SALARY   AGE    GP    W  \\\n",
            "144  Quinn Cook            2017          2018    867391.5  24.0  14.0  9.0   \n",
            "\n",
            "       L    MIN   PTS  ...   FT%  OREB  DREB  REB   AST   TOV  STL  BLK    PF  \\\n",
            "144  5.0  187.0  79.0  ...  40.0   1.0   6.0  7.0  26.0  13.0  4.0  0.0  13.0   \n",
            "\n",
            "      +/-  \n",
            "144 -41.0  \n",
            "\n",
            "[1 rows x 28 columns]\n",
            "(198, 28)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "##learningset construction\n",
        "\n",
        "learningSet= pd.DataFrame(dataframe.iloc[:,3:])\n",
        "learningSet['Duration']=dataframe['CONTRACT_END']-dataframe['CONTRACT_START']\n",
        "print(learningSet.shape)\n",
        "learningSet\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 506
        },
        "id": "V99_cI_nJL5K",
        "outputId": "2f413a8d-7b8e-41b2-df06-b95acf4e806e"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(198, 26)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       AVG_SALARY   AGE    GP     W     L     MIN     PTS    FGM     FGA  \\\n",
              "0    2.564753e+06  32.0  69.0  27.0  42.0  2091.0   840.0  279.0   698.0   \n",
              "1    2.116568e+07  27.0  72.0  34.0  38.0  2100.0  1236.0  506.0   987.0   \n",
              "2    1.075976e+07  22.0  80.0  31.0  49.0  2047.0   566.0  234.0   341.0   \n",
              "3    8.143324e+06  25.0  82.0  39.0  43.0  2581.0  1258.0  512.0  1100.0   \n",
              "4    1.341074e+07  32.0  81.0  35.0  46.0  2463.0  1347.0  506.0   911.0   \n",
              "..            ...   ...   ...   ...   ...     ...     ...    ...     ...   \n",
              "194  1.469367e+07  24.0   5.0   2.0   3.0   136.0    96.0   38.0    77.0   \n",
              "195  1.200000e+07  24.0  74.0  21.0  53.0  2529.0  1428.0  631.0  1206.0   \n",
              "196  5.766667e+06  28.0  70.0  49.0  21.0  1122.0   461.0  185.0   327.0   \n",
              "197  1.200000e+07  29.0  80.0  57.0  23.0  2779.0  1038.0  396.0   879.0   \n",
              "198  1.640000e+07  25.0  79.0  64.0  15.0  2490.0   921.0  339.0   765.0   \n",
              "\n",
              "      FG%  ...   OREB   DREB     REB    AST    TOV    STL    BLK     PF  \\\n",
              "0    40.0  ...   32.0  138.0   170.0  160.0   91.0   54.0   17.0  160.0   \n",
              "1    51.3  ...  214.0  321.0   535.0   50.0  104.0   43.0  126.0  206.0   \n",
              "2    68.6  ...  207.0  368.0   575.0   42.0  101.0   41.0  142.0  255.0   \n",
              "3    46.5  ...  110.0  396.0   506.0  192.0  170.0  101.0   39.0  245.0   \n",
              "4    55.5  ...  255.0  757.0  1012.0  105.0  208.0   48.0  131.0  249.0   \n",
              "..    ...  ...    ...    ...     ...    ...    ...    ...    ...    ...   \n",
              "194  49.4  ...    8.0   10.0    18.0    6.0    6.0    1.0    4.0    8.0   \n",
              "195  52.3  ...  238.0  572.0   810.0  147.0  148.0   54.0   54.0  220.0   \n",
              "196  56.6  ...  109.0  209.0   318.0   35.0   65.0   16.0   22.0  162.0   \n",
              "197  45.1  ...   82.0  341.0   423.0  433.0  206.0  139.0   52.0  127.0   \n",
              "198  44.3  ...  114.0  533.0   647.0  291.0  133.0  123.0   99.0  253.0   \n",
              "\n",
              "       +/-  Duration  \n",
              "0    -90.0         1  \n",
              "1   -104.0         2  \n",
              "2   -100.0         3  \n",
              "3    105.0         3  \n",
              "4     89.0         1  \n",
              "..     ...       ...  \n",
              "194  -27.0         2  \n",
              "195 -302.0         3  \n",
              "196  136.0         2  \n",
              "197  380.0         3  \n",
              "198  839.0         4  \n",
              "\n",
              "[198 rows x 26 columns]"
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              "      <th></th>\n",
              "      <th>AVG_SALARY</th>\n",
              "      <th>AGE</th>\n",
              "      <th>GP</th>\n",
              "      <th>W</th>\n",
              "      <th>L</th>\n",
              "      <th>MIN</th>\n",
              "      <th>PTS</th>\n",
              "      <th>FGM</th>\n",
              "      <th>FGA</th>\n",
              "      <th>FG%</th>\n",
              "      <th>...</th>\n",
              "      <th>OREB</th>\n",
              "      <th>DREB</th>\n",
              "      <th>REB</th>\n",
              "      <th>AST</th>\n",
              "      <th>TOV</th>\n",
              "      <th>STL</th>\n",
              "      <th>BLK</th>\n",
              "      <th>PF</th>\n",
              "      <th>+/-</th>\n",
              "      <th>Duration</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2.564753e+06</td>\n",
              "      <td>32.0</td>\n",
              "      <td>69.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>42.0</td>\n",
              "      <td>2091.0</td>\n",
              "      <td>840.0</td>\n",
              "      <td>279.0</td>\n",
              "      <td>698.0</td>\n",
              "      <td>40.0</td>\n",
              "      <td>...</td>\n",
              "      <td>32.0</td>\n",
              "      <td>138.0</td>\n",
              "      <td>170.0</td>\n",
              "      <td>160.0</td>\n",
              "      <td>91.0</td>\n",
              "      <td>54.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>160.0</td>\n",
              "      <td>-90.0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2.116568e+07</td>\n",
              "      <td>27.0</td>\n",
              "      <td>72.0</td>\n",
              "      <td>34.0</td>\n",
              "      <td>38.0</td>\n",
              "      <td>2100.0</td>\n",
              "      <td>1236.0</td>\n",
              "      <td>506.0</td>\n",
              "      <td>987.0</td>\n",
              "      <td>51.3</td>\n",
              "      <td>...</td>\n",
              "      <td>214.0</td>\n",
              "      <td>321.0</td>\n",
              "      <td>535.0</td>\n",
              "      <td>50.0</td>\n",
              "      <td>104.0</td>\n",
              "      <td>43.0</td>\n",
              "      <td>126.0</td>\n",
              "      <td>206.0</td>\n",
              "      <td>-104.0</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1.075976e+07</td>\n",
              "      <td>22.0</td>\n",
              "      <td>80.0</td>\n",
              "      <td>31.0</td>\n",
              "      <td>49.0</td>\n",
              "      <td>2047.0</td>\n",
              "      <td>566.0</td>\n",
              "      <td>234.0</td>\n",
              "      <td>341.0</td>\n",
              "      <td>68.6</td>\n",
              "      <td>...</td>\n",
              "      <td>207.0</td>\n",
              "      <td>368.0</td>\n",
              "      <td>575.0</td>\n",
              "      <td>42.0</td>\n",
              "      <td>101.0</td>\n",
              "      <td>41.0</td>\n",
              "      <td>142.0</td>\n",
              "      <td>255.0</td>\n",
              "      <td>-100.0</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>8.143324e+06</td>\n",
              "      <td>25.0</td>\n",
              "      <td>82.0</td>\n",
              "      <td>39.0</td>\n",
              "      <td>43.0</td>\n",
              "      <td>2581.0</td>\n",
              "      <td>1258.0</td>\n",
              "      <td>512.0</td>\n",
              "      <td>1100.0</td>\n",
              "      <td>46.5</td>\n",
              "      <td>...</td>\n",
              "      <td>110.0</td>\n",
              "      <td>396.0</td>\n",
              "      <td>506.0</td>\n",
              "      <td>192.0</td>\n",
              "      <td>170.0</td>\n",
              "      <td>101.0</td>\n",
              "      <td>39.0</td>\n",
              "      <td>245.0</td>\n",
              "      <td>105.0</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1.341074e+07</td>\n",
              "      <td>32.0</td>\n",
              "      <td>81.0</td>\n",
              "      <td>35.0</td>\n",
              "      <td>46.0</td>\n",
              "      <td>2463.0</td>\n",
              "      <td>1347.0</td>\n",
              "      <td>506.0</td>\n",
              "      <td>911.0</td>\n",
              "      <td>55.5</td>\n",
              "      <td>...</td>\n",
              "      <td>255.0</td>\n",
              "      <td>757.0</td>\n",
              "      <td>1012.0</td>\n",
              "      <td>105.0</td>\n",
              "      <td>208.0</td>\n",
              "      <td>48.0</td>\n",
              "      <td>131.0</td>\n",
              "      <td>249.0</td>\n",
              "      <td>89.0</td>\n",
              "      <td>1</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",
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              "    <tr>\n",
              "      <th>194</th>\n",
              "      <td>1.469367e+07</td>\n",
              "      <td>24.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>136.0</td>\n",
              "      <td>96.0</td>\n",
              "      <td>38.0</td>\n",
              "      <td>77.0</td>\n",
              "      <td>49.4</td>\n",
              "      <td>...</td>\n",
              "      <td>8.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>18.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>-27.0</td>\n",
              "      <td>2</td>\n",
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              "    <tr>\n",
              "      <th>195</th>\n",
              "      <td>1.200000e+07</td>\n",
              "      <td>24.0</td>\n",
              "      <td>74.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>53.0</td>\n",
              "      <td>2529.0</td>\n",
              "      <td>1428.0</td>\n",
              "      <td>631.0</td>\n",
              "      <td>1206.0</td>\n",
              "      <td>52.3</td>\n",
              "      <td>...</td>\n",
              "      <td>238.0</td>\n",
              "      <td>572.0</td>\n",
              "      <td>810.0</td>\n",
              "      <td>147.0</td>\n",
              "      <td>148.0</td>\n",
              "      <td>54.0</td>\n",
              "      <td>54.0</td>\n",
              "      <td>220.0</td>\n",
              "      <td>-302.0</td>\n",
              "      <td>3</td>\n",
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              "    <tr>\n",
              "      <th>196</th>\n",
              "      <td>5.766667e+06</td>\n",
              "      <td>28.0</td>\n",
              "      <td>70.0</td>\n",
              "      <td>49.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>1122.0</td>\n",
              "      <td>461.0</td>\n",
              "      <td>185.0</td>\n",
              "      <td>327.0</td>\n",
              "      <td>56.6</td>\n",
              "      <td>...</td>\n",
              "      <td>109.0</td>\n",
              "      <td>209.0</td>\n",
              "      <td>318.0</td>\n",
              "      <td>35.0</td>\n",
              "      <td>65.0</td>\n",
              "      <td>16.0</td>\n",
              "      <td>22.0</td>\n",
              "      <td>162.0</td>\n",
              "      <td>136.0</td>\n",
              "      <td>2</td>\n",
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              "    <tr>\n",
              "      <th>197</th>\n",
              "      <td>1.200000e+07</td>\n",
              "      <td>29.0</td>\n",
              "      <td>80.0</td>\n",
              "      <td>57.0</td>\n",
              "      <td>23.0</td>\n",
              "      <td>2779.0</td>\n",
              "      <td>1038.0</td>\n",
              "      <td>396.0</td>\n",
              "      <td>879.0</td>\n",
              "      <td>45.1</td>\n",
              "      <td>...</td>\n",
              "      <td>82.0</td>\n",
              "      <td>341.0</td>\n",
              "      <td>423.0</td>\n",
              "      <td>433.0</td>\n",
              "      <td>206.0</td>\n",
              "      <td>139.0</td>\n",
              "      <td>52.0</td>\n",
              "      <td>127.0</td>\n",
              "      <td>380.0</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>198</th>\n",
              "      <td>1.640000e+07</td>\n",
              "      <td>25.0</td>\n",
              "      <td>79.0</td>\n",
              "      <td>64.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>2490.0</td>\n",
              "      <td>921.0</td>\n",
              "      <td>339.0</td>\n",
              "      <td>765.0</td>\n",
              "      <td>44.3</td>\n",
              "      <td>...</td>\n",
              "      <td>114.0</td>\n",
              "      <td>533.0</td>\n",
              "      <td>647.0</td>\n",
              "      <td>291.0</td>\n",
              "      <td>133.0</td>\n",
              "      <td>123.0</td>\n",
              "      <td>99.0</td>\n",
              "      <td>253.0</td>\n",
              "      <td>839.0</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>198 rows × 26 columns</p>\n",
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              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "##checking if there are missing values\n",
        "\n",
        "print(learningSet.isna().any().any())\n",
        "\n",
        "##there aren't any missing values"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qSCRmhErYc-7",
        "outputId": "bd073704-7fbc-4483-b7df-a5715acb5129"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "False\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "##min max normalizatio (also standardization was tryied)\n",
        "\n",
        "'''\n",
        "scaler = preprocessing.StandardScaler().fit(learningSet.iloc[:,1:])\n",
        "'''\n",
        "#normalizing learningSet (min-max)\n",
        "normalizedLearningSet= learningSet.copy()\n",
        "'''\n",
        "normalizedLearningSet.iloc[:,1:] = scaler.transform(normalizedLearningSet.iloc[:,1:])\n",
        "'''\n",
        "for feature_name in normalizedLearningSet.iloc[:,1:].columns:\n",
        "    max_value = learningSet[feature_name].max()\n",
        "    min_value = learningSet[feature_name].min()\n",
        "    normalizedLearningSet[feature_name] = (normalizedLearningSet[feature_name] - min_value) / (max_value - min_value)\n",
        "\n",
        "normalizedLearningSet"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "wrp_zEn1pP0Z",
        "outputId": "59ae4a38-d29d-4deb-e60a-f4a252ccf53c"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       AVG_SALARY     AGE        GP         W         L       MIN       PTS  \\\n",
              "0    2.564753e+06  0.7500  0.839506  0.421875  0.677419  0.668908  0.353535   \n",
              "1    2.116568e+07  0.4375  0.876543  0.531250  0.612903  0.671790  0.520202   \n",
              "2    1.075976e+07  0.1250  0.975309  0.484375  0.790323  0.654819  0.238215   \n",
              "3    8.143324e+06  0.3125  1.000000  0.609375  0.693548  0.825809  0.529461   \n",
              "4    1.341074e+07  0.7500  0.987654  0.546875  0.741935  0.788024  0.566919   \n",
              "..            ...     ...       ...       ...       ...       ...       ...   \n",
              "194  1.469367e+07  0.2500  0.049383  0.031250  0.048387  0.042907  0.040404   \n",
              "195  1.200000e+07  0.2500  0.901235  0.328125  0.854839  0.809158  0.601010   \n",
              "196  5.766667e+06  0.5000  0.851852  0.765625  0.338710  0.358630  0.194024   \n",
              "197  1.200000e+07  0.5625  0.975309  0.890625  0.370968  0.889209  0.436869   \n",
              "198  1.640000e+07  0.3125  0.962963  1.000000  0.241935  0.796670  0.387626   \n",
              "\n",
              "          FGM       FGA    FG%  ...      OREB      DREB       REB       AST  \\\n",
              "0    0.375505  0.424482  0.400  ...  0.080605  0.165459  0.137959  0.190703   \n",
              "1    0.681023  0.600487  0.513  ...  0.539043  0.386473  0.435918  0.059595   \n",
              "2    0.314939  0.207065  0.686  ...  0.521411  0.443237  0.468571  0.050060   \n",
              "3    0.689098  0.669306  0.465  ...  0.277078  0.477053  0.412245  0.228844   \n",
              "4    0.681023  0.554202  0.555  ...  0.642317  0.913043  0.825306  0.125149   \n",
              "..        ...       ...    ...  ...       ...       ...       ...       ...   \n",
              "194  0.051144  0.046285  0.494  ...  0.020151  0.010870  0.013878  0.007151   \n",
              "195  0.849260  0.733861  0.523  ...  0.599496  0.689614  0.660408  0.175209   \n",
              "196  0.248991  0.198538  0.566  ...  0.274559  0.251208  0.258776  0.041716   \n",
              "197  0.532974  0.534714  0.451  ...  0.206549  0.410628  0.344490  0.516091   \n",
              "198  0.456258  0.465286  0.443  ...  0.287154  0.642512  0.527347  0.346841   \n",
              "\n",
              "          TOV       STL       BLK        PF       +/-  Duration  \n",
              "0    0.243316  0.319527  0.063197  0.548276  0.366735  0.000000  \n",
              "1    0.278075  0.254438  0.468401  0.706897  0.357192  0.333333  \n",
              "2    0.270053  0.242604  0.527881  0.875862  0.359918  0.666667  \n",
              "3    0.454545  0.597633  0.144981  0.841379  0.499659  0.666667  \n",
              "4    0.556150  0.284024  0.486989  0.855172  0.488753  0.000000  \n",
              "..        ...       ...       ...       ...       ...       ...  \n",
              "194  0.016043  0.005917  0.014870  0.024138  0.409680  0.333333  \n",
              "195  0.395722  0.319527  0.200743  0.755172  0.222222  0.666667  \n",
              "196  0.173797  0.094675  0.081784  0.555172  0.520791  0.333333  \n",
              "197  0.550802  0.822485  0.193309  0.434483  0.687117  0.666667  \n",
              "198  0.355615  0.727811  0.368030  0.868966  1.000000  1.000000  \n",
              "\n",
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              "      <th></th>\n",
              "      <th>AVG_SALARY</th>\n",
              "      <th>AGE</th>\n",
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              "      <th>W</th>\n",
              "      <th>L</th>\n",
              "      <th>MIN</th>\n",
              "      <th>PTS</th>\n",
              "      <th>FGM</th>\n",
              "      <th>FGA</th>\n",
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              "      <th>OREB</th>\n",
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              "      <th>0</th>\n",
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              "      <td>0.353535</td>\n",
              "      <td>0.375505</td>\n",
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              "      <td>0.165459</td>\n",
              "      <td>0.137959</td>\n",
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              "      <td>0.319527</td>\n",
              "      <td>0.063197</td>\n",
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              "      <th>1</th>\n",
              "      <td>2.116568e+07</td>\n",
              "      <td>0.4375</td>\n",
              "      <td>0.876543</td>\n",
              "      <td>0.531250</td>\n",
              "      <td>0.612903</td>\n",
              "      <td>0.671790</td>\n",
              "      <td>0.520202</td>\n",
              "      <td>0.681023</td>\n",
              "      <td>0.600487</td>\n",
              "      <td>0.513</td>\n",
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              "      <td>0.539043</td>\n",
              "      <td>0.386473</td>\n",
              "      <td>0.435918</td>\n",
              "      <td>0.059595</td>\n",
              "      <td>0.278075</td>\n",
              "      <td>0.254438</td>\n",
              "      <td>0.468401</td>\n",
              "      <td>0.706897</td>\n",
              "      <td>0.357192</td>\n",
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              "      <th>2</th>\n",
              "      <td>1.075976e+07</td>\n",
              "      <td>0.1250</td>\n",
              "      <td>0.975309</td>\n",
              "      <td>0.484375</td>\n",
              "      <td>0.790323</td>\n",
              "      <td>0.654819</td>\n",
              "      <td>0.238215</td>\n",
              "      <td>0.314939</td>\n",
              "      <td>0.207065</td>\n",
              "      <td>0.686</td>\n",
              "      <td>...</td>\n",
              "      <td>0.521411</td>\n",
              "      <td>0.443237</td>\n",
              "      <td>0.468571</td>\n",
              "      <td>0.050060</td>\n",
              "      <td>0.270053</td>\n",
              "      <td>0.242604</td>\n",
              "      <td>0.527881</td>\n",
              "      <td>0.875862</td>\n",
              "      <td>0.359918</td>\n",
              "      <td>0.666667</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>8.143324e+06</td>\n",
              "      <td>0.3125</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.609375</td>\n",
              "      <td>0.693548</td>\n",
              "      <td>0.825809</td>\n",
              "      <td>0.529461</td>\n",
              "      <td>0.689098</td>\n",
              "      <td>0.669306</td>\n",
              "      <td>0.465</td>\n",
              "      <td>...</td>\n",
              "      <td>0.277078</td>\n",
              "      <td>0.477053</td>\n",
              "      <td>0.412245</td>\n",
              "      <td>0.228844</td>\n",
              "      <td>0.454545</td>\n",
              "      <td>0.597633</td>\n",
              "      <td>0.144981</td>\n",
              "      <td>0.841379</td>\n",
              "      <td>0.499659</td>\n",
              "      <td>0.666667</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1.341074e+07</td>\n",
              "      <td>0.7500</td>\n",
              "      <td>0.987654</td>\n",
              "      <td>0.546875</td>\n",
              "      <td>0.741935</td>\n",
              "      <td>0.788024</td>\n",
              "      <td>0.566919</td>\n",
              "      <td>0.681023</td>\n",
              "      <td>0.554202</td>\n",
              "      <td>0.555</td>\n",
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              "      <td>0.642317</td>\n",
              "      <td>0.913043</td>\n",
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              "      <td>0.284024</td>\n",
              "      <td>0.486989</td>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "      <td>0.031250</td>\n",
              "      <td>0.048387</td>\n",
              "      <td>0.042907</td>\n",
              "      <td>0.040404</td>\n",
              "      <td>0.051144</td>\n",
              "      <td>0.046285</td>\n",
              "      <td>0.494</td>\n",
              "      <td>...</td>\n",
              "      <td>0.020151</td>\n",
              "      <td>0.010870</td>\n",
              "      <td>0.013878</td>\n",
              "      <td>0.007151</td>\n",
              "      <td>0.016043</td>\n",
              "      <td>0.005917</td>\n",
              "      <td>0.014870</td>\n",
              "      <td>0.024138</td>\n",
              "      <td>0.409680</td>\n",
              "      <td>0.333333</td>\n",
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              "    <tr>\n",
              "      <th>195</th>\n",
              "      <td>1.200000e+07</td>\n",
              "      <td>0.2500</td>\n",
              "      <td>0.901235</td>\n",
              "      <td>0.328125</td>\n",
              "      <td>0.854839</td>\n",
              "      <td>0.809158</td>\n",
              "      <td>0.601010</td>\n",
              "      <td>0.849260</td>\n",
              "      <td>0.733861</td>\n",
              "      <td>0.523</td>\n",
              "      <td>...</td>\n",
              "      <td>0.599496</td>\n",
              "      <td>0.689614</td>\n",
              "      <td>0.660408</td>\n",
              "      <td>0.175209</td>\n",
              "      <td>0.395722</td>\n",
              "      <td>0.319527</td>\n",
              "      <td>0.200743</td>\n",
              "      <td>0.755172</td>\n",
              "      <td>0.222222</td>\n",
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              "      <th>196</th>\n",
              "      <td>5.766667e+06</td>\n",
              "      <td>0.5000</td>\n",
              "      <td>0.851852</td>\n",
              "      <td>0.765625</td>\n",
              "      <td>0.338710</td>\n",
              "      <td>0.358630</td>\n",
              "      <td>0.194024</td>\n",
              "      <td>0.248991</td>\n",
              "      <td>0.198538</td>\n",
              "      <td>0.566</td>\n",
              "      <td>...</td>\n",
              "      <td>0.274559</td>\n",
              "      <td>0.251208</td>\n",
              "      <td>0.258776</td>\n",
              "      <td>0.041716</td>\n",
              "      <td>0.173797</td>\n",
              "      <td>0.094675</td>\n",
              "      <td>0.081784</td>\n",
              "      <td>0.555172</td>\n",
              "      <td>0.520791</td>\n",
              "      <td>0.333333</td>\n",
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              "    <tr>\n",
              "      <th>197</th>\n",
              "      <td>1.200000e+07</td>\n",
              "      <td>0.5625</td>\n",
              "      <td>0.975309</td>\n",
              "      <td>0.890625</td>\n",
              "      <td>0.370968</td>\n",
              "      <td>0.889209</td>\n",
              "      <td>0.436869</td>\n",
              "      <td>0.532974</td>\n",
              "      <td>0.534714</td>\n",
              "      <td>0.451</td>\n",
              "      <td>...</td>\n",
              "      <td>0.206549</td>\n",
              "      <td>0.410628</td>\n",
              "      <td>0.344490</td>\n",
              "      <td>0.516091</td>\n",
              "      <td>0.550802</td>\n",
              "      <td>0.822485</td>\n",
              "      <td>0.193309</td>\n",
              "      <td>0.434483</td>\n",
              "      <td>0.687117</td>\n",
              "      <td>0.666667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>198</th>\n",
              "      <td>1.640000e+07</td>\n",
              "      <td>0.3125</td>\n",
              "      <td>0.962963</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.241935</td>\n",
              "      <td>0.796670</td>\n",
              "      <td>0.387626</td>\n",
              "      <td>0.456258</td>\n",
              "      <td>0.465286</td>\n",
              "      <td>0.443</td>\n",
              "      <td>...</td>\n",
              "      <td>0.287154</td>\n",
              "      <td>0.642512</td>\n",
              "      <td>0.527347</td>\n",
              "      <td>0.346841</td>\n",
              "      <td>0.355615</td>\n",
              "      <td>0.727811</td>\n",
              "      <td>0.368030</td>\n",
              "      <td>0.868966</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "<p>198 rows × 26 columns</p>\n",
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          "metadata": {},
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#correlations\n",
        "plt.figure(figsize=(12, 12))\n",
        "sns.heatmap(learningSet.corr(), annot=True, cbar=False)\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
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          "height": 754
        },
        "id": "idDiVPL6g41E",
        "outputId": "b1b0b83a-a139-43ff-d92a-32fec0ad9f92"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 864x864 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#first model developing\n",
        "x= normalizedLearningSet.iloc[:,1:]\n",
        "y= normalizedLearningSet.iloc[:,0]\n",
        "\n",
        "# dictionary of model names and model objects\n",
        "def get_models():\n",
        " models = dict()\n",
        " models['Linear'] = LinearRegression()\n",
        " models['TheilSen'] = TheilSenRegressor()\n",
        " #models['Tweedie'] = TweedieRegressor()  \n",
        " #models['Gamma'] = GammaRegressor()\n",
        " #models['Poisson'] = PoissonRegressor()\n",
        " #models['Ransac'] = RANSACRegressor()\n",
        " #models['Huber'] = HuberRegressor()\n",
        " models['RandomForest']= RandomForestRegressor(n_estimators=500)\n",
        " #models['Ridge']=Ridge()\n",
        " #models['Lasso']=Lasso()\n",
        " models['KNN']=KNeighborsRegressor(n_neighbors=4)\n",
        " models['Bagging']=BaggingRegressor(n_estimators=500)\n",
        " models ['dummy']=DummyRegressor()\n",
        "\n",
        " return models\n",
        "\n",
        "# evaluate a model\n",
        "def evalute_model(X, y, model, name):\n",
        " # define model evaluation method\n",
        " cv = RepeatedKFold(n_splits=10, n_repeats=3, random_state=1)\n",
        " # evaluate model\n",
        " scores = cross_val_score(model, X, y, scoring='neg_mean_absolute_percentage_error', cv=10, n_jobs=-1)\n",
        " # force scores to be positive\n",
        " scores = absolute(scores)\n",
        " return scores\n",
        "\n",
        "# retrieve models\n",
        "models = get_models()\n",
        "results = dict()\n",
        "for name, model in models.items():\n",
        " # evaluate the model\n",
        " results[name] = evalute_model(x, y, model, name)\n",
        " # summarize progress\n",
        " print('>%s %.3f (%.3f)' % (name, mean(results[name]), std(results[name])))"
      ],
      "metadata": {
        "id": "L5CVJm8QpOUs",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "11cf86dd-1344-4cfb-bf0e-f8c93d161768"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            ">Linear 0.551 (0.137)\n",
            ">TheilSen 0.549 (0.127)\n",
            ">RandomForest 0.504 (0.124)\n",
            ">KNN 0.496 (0.108)\n",
            ">Bagging 0.539 (0.147)\n",
            ">dummy 1.552 (0.559)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#tentativo di prendere in considerazione anche anno inizio contratto\n",
        "withContractBeginyear= normalizedLearningSet.copy()\n",
        "withContractBeginyear['beginYear']=dataframe['CONTRACT_START']\n",
        "print(withContractBeginyear.shape)\n",
        "\n",
        "#second model developing\n",
        "x2= withContractBeginyear.iloc[:,1:]\n",
        "y2= withContractBeginyear.iloc[:,0]\n",
        "\n",
        "# retrieve models\n",
        "models = get_models()\n",
        "results = dict()\n",
        "for name, model in models.items():\n",
        " # evaluate the model\n",
        " results[name] = evalute_model(x2, y2, model, name)\n",
        " # summarize progress\n",
        " print('>%s %.3f (%.3f)' % (name, mean(results[name]), std(results[name])))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WTSxnZYyvJvZ",
        "outputId": "bee0889d-8895-47ce-a2ac-958b511e947d"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(198, 27)\n",
            ">Linear 0.577 (0.152)\n",
            ">TheilSen 0.565 (0.146)\n",
            ">RandomForest 0.497 (0.116)\n",
            ">KNN 0.555 (0.215)\n",
            ">Bagging 0.477 (0.068)\n",
            ">dummy 1.552 (0.559)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "LE PRESTAZIONI NON MIGLIORANO CONSIDERANDO L'ANNO DI INIZIO DEL CONTRATTTO"
      ],
      "metadata": {
        "id": "x2kW7NJpwJbZ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#tentativo rimuovendo dal learning set le variabili dipendenti da altre (esempio: REB=OREB+DREB)\n",
        "\n",
        "withoutDependents= normalizedLearningSet.iloc[:,[0,1,3,4,5,7,8,10,11,13,14,16,17,19,20,21,22,23,24,25]].copy() \n",
        "\n",
        "print(withoutDependents)\n",
        "\n",
        "#third model developing\n",
        "x3= withoutDependents.iloc[:,1:]\n",
        "y3= withoutDependents.iloc[:,0]\n",
        "\n",
        "# retrieve models\n",
        "models = get_models()\n",
        "results = dict()\n",
        "for name, model in models.items():\n",
        " # evaluate the model\n",
        " results[name] = evalute_model(x3, y3, model, name)\n",
        " # summarize progress\n",
        " print('>%s %.3f (%.3f)' % (name, mean(results[name]), std(results[name])))\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ml9GVOUjwtPU",
        "outputId": "54e60d74-4f06-450d-8694-7eaf7e9ac578"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "       AVG_SALARY     AGE         W         L       MIN       FGM       FGA  \\\n",
            "0    2.564753e+06  0.7500  0.421875  0.677419  0.668908  0.375505  0.424482   \n",
            "1    2.116568e+07  0.4375  0.531250  0.612903  0.671790  0.681023  0.600487   \n",
            "2    1.075976e+07  0.1250  0.484375  0.790323  0.654819  0.314939  0.207065   \n",
            "3    8.143324e+06  0.3125  0.609375  0.693548  0.825809  0.689098  0.669306   \n",
            "4    1.341074e+07  0.7500  0.546875  0.741935  0.788024  0.681023  0.554202   \n",
            "..            ...     ...       ...       ...       ...       ...       ...   \n",
            "194  1.469367e+07  0.2500  0.031250  0.048387  0.042907  0.051144  0.046285   \n",
            "195  1.200000e+07  0.2500  0.328125  0.854839  0.809158  0.849260  0.733861   \n",
            "196  5.766667e+06  0.5000  0.765625  0.338710  0.358630  0.248991  0.198538   \n",
            "197  1.200000e+07  0.5625  0.890625  0.370968  0.889209  0.532974  0.534714   \n",
            "198  1.640000e+07  0.3125  1.000000  0.241935  0.796670  0.456258  0.465286   \n",
            "\n",
            "          3PM       3PA       FTM       FTA      OREB      DREB       AST  \\\n",
            "0    0.551471  0.613394  0.183333  0.194743  0.080605  0.165459  0.190703   \n",
            "1    0.003676  0.015221  0.309722  0.327360  0.539043  0.386473  0.059595   \n",
            "2    0.000000  0.001522  0.136111  0.259259  0.521411  0.443237  0.050060   \n",
            "3    0.209559  0.272451  0.245833  0.277180  0.277078  0.477053  0.228844   \n",
            "4    0.003676  0.010654  0.463889  0.695341  0.642317  0.913043  0.125149   \n",
            "..        ...       ...       ...       ...       ...       ...       ...   \n",
            "194  0.000000  0.000000  0.027778  0.038232  0.020151  0.010870  0.007151   \n",
            "195  0.007353  0.009132  0.227778  0.260454  0.599496  0.689614  0.175209   \n",
            "196  0.003676  0.006088  0.125000  0.124253  0.274559  0.251208  0.041716   \n",
            "197  0.334559  0.436834  0.215278  0.322581  0.206549  0.410628  0.516091   \n",
            "198  0.408088  0.500761  0.183333  0.238949  0.287154  0.642512  0.346841   \n",
            "\n",
            "          TOV       STL       BLK        PF       +/-  Duration  \n",
            "0    0.243316  0.319527  0.063197  0.548276  0.366735  0.000000  \n",
            "1    0.278075  0.254438  0.468401  0.706897  0.357192  0.333333  \n",
            "2    0.270053  0.242604  0.527881  0.875862  0.359918  0.666667  \n",
            "3    0.454545  0.597633  0.144981  0.841379  0.499659  0.666667  \n",
            "4    0.556150  0.284024  0.486989  0.855172  0.488753  0.000000  \n",
            "..        ...       ...       ...       ...       ...       ...  \n",
            "194  0.016043  0.005917  0.014870  0.024138  0.409680  0.333333  \n",
            "195  0.395722  0.319527  0.200743  0.755172  0.222222  0.666667  \n",
            "196  0.173797  0.094675  0.081784  0.555172  0.520791  0.333333  \n",
            "197  0.550802  0.822485  0.193309  0.434483  0.687117  0.666667  \n",
            "198  0.355615  0.727811  0.368030  0.868966  1.000000  1.000000  \n",
            "\n",
            "[198 rows x 20 columns]\n",
            ">Linear 0.550 (0.116)\n",
            ">TheilSen 0.490 (0.106)\n",
            ">RandomForest 0.506 (0.140)\n",
            ">KNN 0.453 (0.094)\n",
            ">Bagging 0.520 (0.159)\n",
            ">dummy 1.552 (0.559)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "RESULTS HAVE IMPROVED! (A LITTLE BIT)"
      ],
      "metadata": {
        "id": "YHhWKgid7783"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#tentativo considerando solo le feature più importanti (avendo già rimosso quelle dipendenti)\n",
        "\n",
        "#fourth model delevlopment\n",
        "x4= withoutDependents.iloc[:,1:].copy()\n",
        "y4= withoutDependents.iloc[:,0].copy()\n",
        "\n",
        "# define feature selection\n",
        "fs = SelectKBest(k=15)\n",
        "\n",
        "\n",
        "# apply feature selection\n",
        "print(x4.shape)\n",
        "fs.fit_transform(x4,y4)\n",
        "print(fs.get_feature_names_out())\n",
        "x4_selected = pd.DataFrame(x4[['AGE','W','MIN','FGM','FGA','FTM','FTA','OREB','DREB','AST','TOV','STL','BLK','PF','Duration']])\n",
        "##x4_selected.rename(columns={0:'AGE',1:'W',2:'MIN',3:'FGM',4:'FGA',5:'FTM',6:'FTA',7:'OREB',8:'DREB',9:'AST',10:'TOV',11:'STL',12:'BLK',13:'PF',14:'Duration'})\n",
        "print(x4_selected)\n",
        "\n",
        "\n",
        "# retrieve models\n",
        "models = get_models()\n",
        "results = dict()\n",
        "for name, model in models.items():\n",
        " # evaluate the model\n",
        " results[name] = evalute_model(x4_selected, y4, model, name)\n",
        " # summarize progress\n",
        " print('>%s %.3f (%.3f)' % (name, mean(results[name]), std(results[name])))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rw91UEua8lCH",
        "outputId": "4ea2e9f1-0a0c-48ff-832d-df7ffd602bba"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(198, 19)\n",
            "['AGE' 'W' 'MIN' 'FGM' 'FGA' 'FTM' 'FTA' 'OREB' 'DREB' 'AST' 'TOV' 'STL'\n",
            " 'BLK' 'PF' 'Duration']\n",
            "        AGE         W       MIN       FGM       FGA       FTM       FTA  \\\n",
            "0    0.7500  0.421875  0.668908  0.375505  0.424482  0.183333  0.194743   \n",
            "1    0.4375  0.531250  0.671790  0.681023  0.600487  0.309722  0.327360   \n",
            "2    0.1250  0.484375  0.654819  0.314939  0.207065  0.136111  0.259259   \n",
            "3    0.3125  0.609375  0.825809  0.689098  0.669306  0.245833  0.277180   \n",
            "4    0.7500  0.546875  0.788024  0.681023  0.554202  0.463889  0.695341   \n",
            "..      ...       ...       ...       ...       ...       ...       ...   \n",
            "194  0.2500  0.031250  0.042907  0.051144  0.046285  0.027778  0.038232   \n",
            "195  0.2500  0.328125  0.809158  0.849260  0.733861  0.227778  0.260454   \n",
            "196  0.5000  0.765625  0.358630  0.248991  0.198538  0.125000  0.124253   \n",
            "197  0.5625  0.890625  0.889209  0.532974  0.534714  0.215278  0.322581   \n",
            "198  0.3125  1.000000  0.796670  0.456258  0.465286  0.183333  0.238949   \n",
            "\n",
            "         OREB      DREB       AST       TOV       STL       BLK        PF  \\\n",
            "0    0.080605  0.165459  0.190703  0.243316  0.319527  0.063197  0.548276   \n",
            "1    0.539043  0.386473  0.059595  0.278075  0.254438  0.468401  0.706897   \n",
            "2    0.521411  0.443237  0.050060  0.270053  0.242604  0.527881  0.875862   \n",
            "3    0.277078  0.477053  0.228844  0.454545  0.597633  0.144981  0.841379   \n",
            "4    0.642317  0.913043  0.125149  0.556150  0.284024  0.486989  0.855172   \n",
            "..        ...       ...       ...       ...       ...       ...       ...   \n",
            "194  0.020151  0.010870  0.007151  0.016043  0.005917  0.014870  0.024138   \n",
            "195  0.599496  0.689614  0.175209  0.395722  0.319527  0.200743  0.755172   \n",
            "196  0.274559  0.251208  0.041716  0.173797  0.094675  0.081784  0.555172   \n",
            "197  0.206549  0.410628  0.516091  0.550802  0.822485  0.193309  0.434483   \n",
            "198  0.287154  0.642512  0.346841  0.355615  0.727811  0.368030  0.868966   \n",
            "\n",
            "     Duration  \n",
            "0    0.000000  \n",
            "1    0.333333  \n",
            "2    0.666667  \n",
            "3    0.666667  \n",
            "4    0.000000  \n",
            "..        ...  \n",
            "194  0.333333  \n",
            "195  0.666667  \n",
            "196  0.333333  \n",
            "197  0.666667  \n",
            "198  1.000000  \n",
            "\n",
            "[198 rows x 15 columns]\n",
            ">Linear 0.534 (0.161)\n",
            ">TheilSen 0.475 (0.115)\n",
            ">RandomForest 0.512 (0.148)\n",
            ">KNN 0.494 (0.120)\n",
            ">Bagging 0.518 (0.137)\n",
            ">dummy 1.552 (0.559)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "RESULTS don't IMPROVE\n",
        "\n",
        "FEATURES ESCLUSE: L, 3PM, 3PA, +/-"
      ],
      "metadata": {
        "id": "nXT0oB3CDS_k"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "TENTATIVO DI NORMALIZZAZIONE ANCHE/ SOLO CON IL PARAMETRO normalize=True nel metodo LinearRegression() NON HA MIGLIORATO I RISULTATI"
      ],
      "metadata": {
        "id": "4weq9j67So4d"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "A6xpEd-2Ax_L"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#tentativo considerando solo le feature più importanti sull'intero dataset normalizzato\n",
        "\n",
        "#fourth model delevlopment\n",
        "x5= normalizedLearningSet.iloc[:,1:].copy()\n",
        "y5= normalizedLearningSet.iloc[:,0].copy()\n",
        "\n",
        "# define feature selection\n",
        "fs = SelectKBest(f_regression,k=13)\n",
        "\n",
        "\n",
        "# apply feature selection\n",
        "print(x5.shape)\n",
        "x5_selected=pd.DataFrame(fs.fit_transform(x5, y5), columns=fs.get_feature_names_out())\n",
        "print(fs.get_feature_names_out())\n",
        "#print(x5_selected)\n",
        "\n",
        "\n",
        "# retrieve models\n",
        "models = get_models()\n",
        "results = dict()\n",
        "for name, model in models.items():\n",
        " # evaluate the model\n",
        " results[name] = evalute_model(x5_selected, y5, model, name)\n",
        " # summarize progress\n",
        " print('>%s %.3f (%.3f)' % (name, mean(results[name]), std(results[name])))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a21e4f3b-b93f-4085-d1e8-0237b1a18923",
        "id": "d-_glt6NAz4h"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(198, 25)\n",
            "['W' 'MIN' 'PTS' 'FGM' 'FGA' 'FTM' 'FTA' 'DREB' 'REB' 'AST' 'TOV' 'STL'\n",
            " '+/-']\n",
            ">Linear 0.588 (0.109)\n",
            ">TheilSen 0.547 (0.109)\n",
            ">RandomForest 0.623 (0.176)\n",
            ">KNN 0.650 (0.172)\n",
            ">Bagging 0.624 (0.171)\n",
            ">dummy 1.552 (0.559)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "RESULTS DON'T IMPROVE"
      ],
      "metadata": {
        "id": "d3R4VHSEIKly"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "##def della prediction function\n",
        "\n",
        "def firstPrediction(data):\n",
        "  d=data.copy()\n",
        "  for feature_name in d.columns:\n",
        "    max_value = learningSet[feature_name].max()\n",
        "    min_value = learningSet[feature_name].min()\n",
        "    d[feature_name] = (data[feature_name] - min_value) / (max_value - min_value)\n",
        "  return TheilSenRegressor().fit(x4_selected, y4).predict(d)\n",
        "\n",
        "\n",
        "##consiglio per creare il dataframe di input\n",
        "a=pd.DataFrame(np.array([[27, 34, 2100, 506, 987, 223, 274, 214,321,50,104,43,126,206,2]]),columns=x4_selected.columns)\n",
        "\n",
        "print (firstPrediction(a))\n"
      ],
      "metadata": {
        "id": "43UO9kXye9ha",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5a2af20e-b8f0-4c30-8d70-e269393c0f65"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[14595571.72326288]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "CRUL9R_0OijS"
      },
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "##def della seconda prediction function\n",
        "\n",
        "def secondPrediction(data):\n",
        "  d=data.copy()\n",
        "  for feature_name in d.columns:\n",
        "    max_value = learningSet[feature_name].max()\n",
        "    min_value = learningSet[feature_name].min()\n",
        "    d[feature_name] = (data[feature_name] - min_value) / (max_value - min_value)\n",
        "  return KNeighborsRegressor(n_neighbors=4).fit(x3, y3).predict(d)\n",
        "\n",
        "\n",
        "##consiglio per creare il dataframe di input\n",
        "b=pd.DataFrame(np.array([[27, 34, 38, 2100, 506, 987, 1,10,223, 274, 214,321,50,104,43,126,206,-104,2]]),columns=x3.columns)\n",
        "c=pd.DataFrame(np.array([[40, 0, 0, 0, 20, 0, 0,0,0, 0, 0,0,0,0,0,0,0,0,1]]),columns=x3.columns)\n",
        "e=pd.DataFrame(np.array([[20, 80, 0, 3200, 500, 500, 300,300,200, 200, 200,200,200,0,200,200,0,800,1]]),columns=x3.columns)\n",
        "f=pd.DataFrame(np.array([[20, 80, 0, 0, 0, 500, 0,300,0, 200, 200,200,200,0,200,200,0,800,1]]),columns=x3.columns)\n",
        "print (secondPrediction(b))\n",
        "print (secondPrediction(c))\n",
        "print (secondPrediction(e))\n",
        "print (secondPrediction(f))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "91dfa264-191c-4d99-81e3-c97a2d31c94a",
        "id": "x7RBDT-1OjRu"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[16181756.47916667]\n",
            "[2304027.]\n",
            "[19478959.20833333]\n",
            "[5310996.5]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#trying to normalize stats with minutes played\n",
        "x6=learningSet.iloc[:,1:].copy()\n",
        "y6=learningSet.iloc[:,0].copy()\n",
        "\n",
        "x6\n",
        "for column in ['PTS', 'FGM', 'FGA', '3PM', '3PA', 'FTM', 'FTA', 'OREB', 'DREB', 'REB', 'AST', 'TOV', 'STL', 'BLK', 'PF', '+/-']:\n",
        "  x6[column]=x6[column]/x6['MIN']\n",
        "\n",
        "x6\n",
        "\n",
        "# retrieve models\n",
        "models = get_models()\n",
        "results = dict()\n",
        "for name, model in models.items():\n",
        " # evaluate the model\n",
        " results[name] = evalute_model(x6, y6, model, name)\n",
        " # summarize progress\n",
        " print('>%s %.3f (%.3f)' % (name, mean(results[name]), std(results[name])))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2nSc_J_IhmdZ",
        "outputId": "3c3711c2-2b12-48d6-d239-96e773231cbc"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            ">Linear 0.568 (0.145)\n",
            ">TheilSen 0.763 (0.366)\n",
            ">RandomForest 0.565 (0.125)\n",
            ">KNN 0.787 (0.179)\n",
            ">Bagging 0.581 (0.115)\n",
            ">dummy 1.552 (0.559)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "RESULTS DON'T IMPROVE"
      ],
      "metadata": {
        "id": "d_uKxHX_5Dyj"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#trying to discretize the normalized learning without dependents set\n",
        "x7=withoutDependents.iloc[:,1:].copy()\n",
        "y7=withoutDependents.iloc[:,0].copy()\n",
        "\n",
        "est = preprocessing.KBinsDiscretizer(n_bins=10,  encode='ordinal').fit(x7)\n",
        "x7=(est.transform(x7))\n",
        "x7\n",
        "\n",
        "# retrieve models\n",
        "models = get_models()\n",
        "results = dict()\n",
        "for name, model in models.items():\n",
        " # evaluate the model\n",
        " results[name] = evalute_model(x7, y7, model, name)\n",
        " # summarize progress\n",
        " print('>%s %.3f (%.3f)' % (name, mean(results[name]), std(results[name])))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Yn_Ozag7lhy8",
        "outputId": "9fcd54c4-3464-42fd-f18b-5f2239775f43"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            ">Linear 0.513 (0.123)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/sklearn/preprocessing/_discretization.py:230: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 0 are removed. Consider decreasing the number of bins.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.8/dist-packages/sklearn/preprocessing/_discretization.py:230: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 6 are removed. Consider decreasing the number of bins.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.8/dist-packages/sklearn/preprocessing/_discretization.py:230: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 18 are removed. Consider decreasing the number of bins.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            ">TheilSen 0.501 (0.120)\n",
            ">RandomForest 0.477 (0.120)\n",
            ">KNN 0.584 (0.152)\n",
            ">Bagging 0.484 (0.112)\n",
            ">dummy 1.552 (0.559)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "RESULTS DON'T IMPROVE"
      ],
      "metadata": {
        "id": "KQ5RaxU65LH2"
      }
    }
  ],
  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}