Pump_It_Up_Feature_Selection.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Pump It Up - Feature Selection",
      "provenance": [],
      "mount_file_id": "1hgmcS_-PUpWj6uGkgnoTxs5udSQXpJSR",
      "authorship_tag": "ABX9TyMlv38qfmGJfGSaYmX9+FSi",
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Yoshani/Pump-It-Up/blob/master/Pump_It_Up_Feature_Selection.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Cjfh2OV4hmJR"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "from sklearn import preprocessing\n",
        "\n",
        "# plotting\n",
        "import matplotlib.pyplot as plt\n",
        "from matplotlib import pyplot\n",
        "import seaborn as sns\n",
        "\n",
        "# feature selection\n",
        "from sklearn.feature_selection import mutual_info_classif\n",
        "from sklearn.datasets import make_classification\n",
        "from sklearn.feature_selection import SelectKBest\n",
        "from sklearn.feature_selection import chi2\n",
        "from sklearn.feature_selection import f_classif"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Gwtwrm5miJGo"
      },
      "source": [
        "def make_mi_scores(X, y):\n",
        "    X_mi = X.copy()\n",
        "    y_mi = y.copy()\n",
        "    for colname in X_mi.select_dtypes([\"object\", \"category\"]):\n",
        "        X_mi[colname], _ = X_mi[colname].factorize()\n",
        "    # All discrete features should now have integer dtypes\n",
        "    discrete_features = [pd.api.types.is_integer_dtype(t) for t in X_mi.dtypes]\n",
        "    mi_scores = mutual_info_classif(X_mi, y_mi.values.ravel(), discrete_features=discrete_features, random_state=0)\n",
        "    mi_scores = pd.Series(mi_scores, name=\"MI Scores\", index=X_mi.columns)\n",
        "    mi_scores = mi_scores.sort_values(ascending=False)\n",
        "    return mi_scores\n",
        "\n",
        "def plot_mi_scores(scores):\n",
        "    scores = scores.sort_values(ascending=True)\n",
        "    width = np.arange(len(scores))\n",
        "    ticks = list(scores.index)\n",
        "    plt.barh(width, scores)\n",
        "    plt.yticks(width, ticks)\n",
        "    plt.title(\"Mutual Information Scores\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6IOeoPKMhvMr"
      },
      "source": [
        "# Get datasets"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xOecdt-fhtkY"
      },
      "source": [
        "features_df = pd.read_csv(\n",
        "    \"/content/drive/MyDrive/PumpItUp/TrainingSet.csv\", \n",
        "    index_col=\"id\",\n",
        "    low_memory=False\n",
        ")\n",
        "labels_df = pd.read_csv(\n",
        "    \"/content/drive/MyDrive/PumpItUp/TrainingLabels.csv\", \n",
        "    index_col=\"id\"\n",
        ")\n",
        "test_df = pd.read_csv(\n",
        "    \"/content/drive/MyDrive/PumpItUp/TestSet.csv\", \n",
        "    index_col=\"id\",\n",
        "    low_memory=False\n",
        ")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lfhhS37Th8Yi"
      },
      "source": [
        "X = features_df.copy()\n",
        "y = labels_df.copy()\n",
        "X_test = test_df.copy()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rfumfgu4h_JX"
      },
      "source": [
        "# Feature Selection"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 838
        },
        "id": "PentegkyiBk9",
        "outputId": "dfece75c-1556-41e7-8103-1f31a99c20e2"
      },
      "source": [
        "mi_scores = make_mi_scores(features_df, labels_df)\n",
        "plt.figure(dpi=100, figsize=(15, 10))\n",
        "plot_mi_scores(mi_scores.head(40))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "data": {
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\n",
            "text/plain": [
              "<Figure size 1500x1000 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "k7C3JYFliSgk"
      },
      "source": [
        "Numerical attributes"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "background_save": true,
          "base_uri": "https://localhost:8080/",
          "height": 142
        },
        "id": "8TipNAaoiTGU",
        "outputId": "eb6ce28e-f4b0-4892-dea0-0a78635ebf14"
      },
      "source": [
        "numerical_df = features_df.select_dtypes([\"int\", \"float\"])\n",
        "numerical_df.head(2)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>amount_tsh</th>\n",
              "      <th>gps_height</th>\n",
              "      <th>longitude</th>\n",
              "      <th>latitude</th>\n",
              "      <th>num_private</th>\n",
              "      <th>region_code</th>\n",
              "      <th>district_code</th>\n",
              "      <th>population</th>\n",
              "      <th>construction_year</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>id</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>69572</th>\n",
              "      <td>6000.0</td>\n",
              "      <td>1390</td>\n",
              "      <td>34.938093</td>\n",
              "      <td>-9.856322</td>\n",
              "      <td>0</td>\n",
              "      <td>11</td>\n",
              "      <td>5</td>\n",
              "      <td>109</td>\n",
              "      <td>1999</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8776</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1399</td>\n",
              "      <td>34.698766</td>\n",
              "      <td>-2.147466</td>\n",
              "      <td>0</td>\n",
              "      <td>20</td>\n",
              "      <td>2</td>\n",
              "      <td>280</td>\n",
              "      <td>2010</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       amount_tsh  gps_height  ...  population  construction_year\n",
              "id                             ...                               \n",
              "69572      6000.0        1390  ...         109               1999\n",
              "8776          0.0        1399  ...         280               2010\n",
              "\n",
              "[2 rows x 9 columns]"
            ]
          },
          "execution_count": null,
          "metadata": {},
          "output_type": "execute_result"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "background_save": true
        },
        "id": "REeC5XGpiUwL"
      },
      "source": [
        "fs = SelectKBest(score_func=f_classif, k='all')\n",
        "fs.fit_transform(X=numerical_df, y=labels_df.values.ravel())\n",
        "cols = numerical_df.columns[fs.get_support(indices=True)].tolist()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "background_save": true,
          "base_uri": "https://localhost:8080/",
          "height": 399
        },
        "id": "yAkSGJJziWai",
        "outputId": "80eb2fec-2ac9-44ff-9cf5-c81b472328bf"
      },
      "source": [
        "# plot the scores\n",
        "plt.subplots(figsize=(10, 5))\n",
        "pyplot.bar(cols, fs.scores_, color=['red', 'black'])\n",
        "plt.xticks(rotation = 90)\n",
        "pyplot.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Q-cdiNcSiaj6"
      },
      "source": [
        "Categorical attributes"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "background_save": true,
          "base_uri": "https://localhost:8080/",
          "height": 229
        },
        "id": "c8kQjhV5ibJX",
        "outputId": "a8454751-4855-41f3-c9bb-d58aefec29ce"
      },
      "source": [
        "categorical_df = features_df.select_dtypes([\"object\", \"category\"])\n",
        "categorical_df.head(2)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>date_recorded</th>\n",
              "      <th>funder</th>\n",
              "      <th>installer</th>\n",
              "      <th>wpt_name</th>\n",
              "      <th>basin</th>\n",
              "      <th>subvillage</th>\n",
              "      <th>region</th>\n",
              "      <th>lga</th>\n",
              "      <th>ward</th>\n",
              "      <th>public_meeting</th>\n",
              "      <th>recorded_by</th>\n",
              "      <th>scheme_management</th>\n",
              "      <th>scheme_name</th>\n",
              "      <th>permit</th>\n",
              "      <th>extraction_type</th>\n",
              "      <th>extraction_type_group</th>\n",
              "      <th>extraction_type_class</th>\n",
              "      <th>management</th>\n",
              "      <th>management_group</th>\n",
              "      <th>payment</th>\n",
              "      <th>payment_type</th>\n",
              "      <th>water_quality</th>\n",
              "      <th>quality_group</th>\n",
              "      <th>quantity</th>\n",
              "      <th>quantity_group</th>\n",
              "      <th>source</th>\n",
              "      <th>source_type</th>\n",
              "      <th>source_class</th>\n",
              "      <th>waterpoint_type</th>\n",
              "      <th>waterpoint_type_group</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>id</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>69572</th>\n",
              "      <td>2011-03-14</td>\n",
              "      <td>Roman</td>\n",
              "      <td>Roman</td>\n",
              "      <td>none</td>\n",
              "      <td>Lake Nyasa</td>\n",
              "      <td>Mnyusi B</td>\n",
              "      <td>Iringa</td>\n",
              "      <td>Ludewa</td>\n",
              "      <td>Mundindi</td>\n",
              "      <td>True</td>\n",
              "      <td>GeoData Consultants Ltd</td>\n",
              "      <td>VWC</td>\n",
              "      <td>Roman</td>\n",
              "      <td>False</td>\n",
              "      <td>gravity</td>\n",
              "      <td>gravity</td>\n",
              "      <td>gravity</td>\n",
              "      <td>vwc</td>\n",
              "      <td>user-group</td>\n",
              "      <td>pay annually</td>\n",
              "      <td>annually</td>\n",
              "      <td>soft</td>\n",
              "      <td>good</td>\n",
              "      <td>enough</td>\n",
              "      <td>enough</td>\n",
              "      <td>spring</td>\n",
              "      <td>spring</td>\n",
              "      <td>groundwater</td>\n",
              "      <td>communal standpipe</td>\n",
              "      <td>communal standpipe</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8776</th>\n",
              "      <td>2013-03-06</td>\n",
              "      <td>Grumeti</td>\n",
              "      <td>GRUMETI</td>\n",
              "      <td>Zahanati</td>\n",
              "      <td>Lake Victoria</td>\n",
              "      <td>Nyamara</td>\n",
              "      <td>Mara</td>\n",
              "      <td>Serengeti</td>\n",
              "      <td>Natta</td>\n",
              "      <td>NaN</td>\n",
              "      <td>GeoData Consultants Ltd</td>\n",
              "      <td>Other</td>\n",
              "      <td>NaN</td>\n",
              "      <td>True</td>\n",
              "      <td>gravity</td>\n",
              "      <td>gravity</td>\n",
              "      <td>gravity</td>\n",
              "      <td>wug</td>\n",
              "      <td>user-group</td>\n",
              "      <td>never pay</td>\n",
              "      <td>never pay</td>\n",
              "      <td>soft</td>\n",
              "      <td>good</td>\n",
              "      <td>insufficient</td>\n",
              "      <td>insufficient</td>\n",
              "      <td>rainwater harvesting</td>\n",
              "      <td>rainwater harvesting</td>\n",
              "      <td>surface</td>\n",
              "      <td>communal standpipe</td>\n",
              "      <td>communal standpipe</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      date_recorded   funder  ...     waterpoint_type waterpoint_type_group\n",
              "id                            ...                                          \n",
              "69572    2011-03-14    Roman  ...  communal standpipe    communal standpipe\n",
              "8776     2013-03-06  Grumeti  ...  communal standpipe    communal standpipe\n",
              "\n",
              "[2 rows x 30 columns]"
            ]
          },
          "execution_count": null,
          "metadata": {},
          "output_type": "execute_result"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wYbMtlZJicnZ"
      },
      "source": [
        "for colname in categorical_df:\n",
        "    categorical_df[colname], _ = categorical_df[colname].factorize()\n",
        "\n",
        "label = labels_df.copy()\n",
        "label['status_group'], _ = label['status_group'].factorize()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZwUuW09vieaE"
      },
      "source": [
        "fs = SelectKBest(score_func=chi2, k='all')\n",
        "fs.fit(categorical_df, label)\n",
        "categorical_df_fs = fs.transform(categorical_df)\n",
        "cols = categorical_df.columns[fs.get_support(indices=True)].tolist()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 533
        },
        "id": "8wTXEGndihf0",
        "outputId": "cac4daab-b6c0-4880-a4a3-e204d05c2f97"
      },
      "source": [
        "# scores for the features\n",
        "# for i in range(len(fs.scores_)):\n",
        "# \tprint(cols[i],': %f' % (fs.scores_[i]))\n",
        "\n",
        "# plot the scores\n",
        "plt.subplots(figsize=(20, 7))\n",
        "pyplot.bar(cols, fs.scores_, color=['red', 'black'])\n",
        "plt.xticks(rotation = 90)\n",
        "pyplot.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}