Linear_Model.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Linear Regression Extension\n",
        "\n",
        "w207 section 3 - Ben Meier"
      ],
      "metadata": {
        "id": "ZKhIQwQSz4-J"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Import modules, data"
      ],
      "metadata": {
        "id": "S-FUM1JPz44I"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "rluWCdYq-AN4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4acbb65e-98ca-49c2-e762-3fc1ac6b6762"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'normalize': 'bool', 'sort': 'bool', 'ascending': 'bool', 'dropna': 'bool'}\n"
          ]
        }
      ],
      "source": [
        "import os\n",
        "import random\n",
        "\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "from google.colab import drive, files\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "\n",
        "# sklearn\n",
        "from sklearn import preprocessing\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "# tensorflow\n",
        "import tensorflow as tf\n",
        "from tensorflow import keras\n",
        "from tensorflow.keras import layers\n",
        "\n",
        "\n",
        "# Set options\n",
        "pd.set_option('display.max_columns', None)\n",
        "pd.set_option('display.max_rows', 1000)\n",
        "\n",
        "# Set value_counts(dropna=False)\n",
        "print(pd.Series.value_counts.__annotations__)\n",
        "pd.Series.value_counts.__defaults__ = (False, True, False, None, False)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "try:\n",
        "    import sweetviz\n",
        "except:\n",
        "    !pip install sweetviz\n",
        "    import sweetviz"
      ],
      "metadata": {
        "id": "G27DvSDVzgpS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Connect notebook to google drive W207 - Final Project Folder\n",
        "drive.mount('/content/drive')\n",
        "\n",
        "path = r'/content/drive/MyDrive/W207 - Final Project/'"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AwyZkXjvvhDQ",
        "outputId": "65528e69-c2e1-475d-c9eb-63da3162455d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "02NgmtjvzJO3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 565
        },
        "outputId": "369cb200-e8b2-40a2-8166-ebbe30a8f3e8"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   rand_num datasource      id    year                      climate  \\\n",
              "0  0.548814     austin  100012  2018.0  2A Hot - Humid (Houston-TX)   \n",
              "1  0.715189     austin  100012  2019.0  2A Hot - Humid (Houston-TX)   \n",
              "2  0.602763     austin  100030  2018.0  2A Hot - Humid (Houston-TX)   \n",
              "3  0.544883     austin  100030  2019.0  2A Hot - Humid (Houston-TX)   \n",
              "4  0.423655     austin  100138  2014.0  2A Hot - Humid (Houston-TX)   \n",
              "\n",
              "  building_class                facility_type  floor_area  year_built heating  \\\n",
              "0    Residential  Multifamily - Uncategorized    160356.0      2013.0     NaN   \n",
              "1    Residential  Multifamily - Uncategorized    160356.0      2013.0     NaN   \n",
              "2    Residential  Multifamily - Uncategorized     51195.0      1982.0     NaN   \n",
              "3    Residential  Multifamily - Uncategorized     51195.0      1982.0     NaN   \n",
              "4     Commercial                          NaN     62368.0         NaN     NaN   \n",
              "\n",
              "  cooling wall_type roof_ceiling window_glass_layers window_glass_type  \\\n",
              "0     NaN       NaN          NaN                 NaN               NaN   \n",
              "1     NaN       NaN          NaN                 NaN               NaN   \n",
              "2     NaN       NaN     Shingles         Single-pane               NaN   \n",
              "3     NaN       NaN     Shingles         Single-pane               NaN   \n",
              "4     NaN       NaN          NaN                 NaN               NaN   \n",
              "\n",
              "  energy_star_label  energy_star_rating  electric_eui  fuel_eui   site_eui  \\\n",
              "0               NaN                 NaN     28.656706       0.0  28.656706   \n",
              "1               NaN                 NaN     29.493681       0.0  29.493681   \n",
              "2               NaN                 NaN     37.971292       0.0  37.971292   \n",
              "3               NaN                 NaN     39.017660       0.0  39.017660   \n",
              "4               NaN                94.0     32.005873       NaN        NaN   \n",
              "\n",
              "   source_eui  ghg_emissions_int         city_line  clim_2A Hot - Humid  \\\n",
              "0   89.982058           3.565981  Austin, TX 78704                    1   \n",
              "1   92.610158           3.670133  Austin, TX 78704                    1   \n",
              "2  119.229858           4.725069  Austin, TX 78704                    1   \n",
              "3  122.515452           4.855277  Austin, TX 78704                    1   \n",
              "4         NaN                NaN  Austin, TX 78704                    1   \n",
              "\n",
              "   clim_3C Warm - Marine  clim_5A Cool - Humid  clim_3B Warm - Dry  \\\n",
              "0                      0                     0                   0   \n",
              "1                      0                     0                   0   \n",
              "2                      0                     0                   0   \n",
              "3                      0                     0                   0   \n",
              "4                      0                     0                   0   \n",
              "\n",
              "   clim_2B Hot - Dry  clim_4C Mixed - Marine  clim_6B Cold - Dry  \\\n",
              "0                  0                       0                   0   \n",
              "1                  0                       0                   0   \n",
              "2                  0                       0                   0   \n",
              "3                  0                       0                   0   \n",
              "4                  0                       0                   0   \n",
              "\n",
              "   clim_4B Mixed - Dry  clim_5B Cool - Dry  clim_4A Mixed - Humid  \\\n",
              "0                    0                   0                      0   \n",
              "1                    0                   0                      0   \n",
              "2                    0                   0                      0   \n",
              "3                    0                   0                      0   \n",
              "4                    0                   0                      0   \n",
              "\n",
              "   clim_6A Cold - Humid  clim_3A Warm - Humid  BC_Residential  BC_Commercial  \\\n",
              "0                     0                     0               0              1   \n",
              "1                     0                     0               0              1   \n",
              "2                     0                     0               0              1   \n",
              "3                     0                     0               0              1   \n",
              "4                     0                     0               1              0   \n",
              "\n",
              "   FT_Multifamily  FT_Industrial  FT_Office  FT_Retail  FT_Other  FT_Hotel  \\\n",
              "0               0              0          0          0         0         1   \n",
              "1               0              0          0          0         0         1   \n",
              "2               0              0          0          0         0         1   \n",
              "3               0              0          0          0         0         1   \n",
              "4               0              0          0          0         0         0   \n",
              "\n",
              "   FT_Restaurant  FT_Grocery  FT_Hospital  FT_Data Center  FT_Singlefamily  \\\n",
              "0              0           0            0               0                0   \n",
              "1              0           0            0               0                0   \n",
              "2              0           0            0               0                0   \n",
              "3              0           0            0               0                0   \n",
              "4              0           0            0               0                0   \n",
              "\n",
              "   WGL_Single-pane  WGL_Double-pane  WGT_Low-e  roof_Shingles  roof_Built-up  \\\n",
              "0                0                0          0              0              0   \n",
              "1                0                0          0              0              0   \n",
              "2                0                1          0              0              0   \n",
              "3                0                1          0              0              0   \n",
              "4                0                0          0              0              0   \n",
              "\n",
              "   roof_Slate or tile shingles  roof_Metal surfacing  \\\n",
              "0                            0                     0   \n",
              "1                            0                     0   \n",
              "2                            0                     0   \n",
              "3                            0                     0   \n",
              "4                            0                     0   \n",
              "\n",
              "   roof_Other Or Combination  roof_Asphalt/fiberglass/other shingles  \\\n",
              "0                          0                                       0   \n",
              "1                          0                                       0   \n",
              "2                          0                                       0   \n",
              "3                          0                                       0   \n",
              "4                          0                                       0   \n",
              "\n",
              "   roof_Wood shingles/shakes/other wood  \\\n",
              "0                                     0   \n",
              "1                                     0   \n",
              "2                                     1   \n",
              "3                                     1   \n",
              "4                                     0   \n",
              "\n",
              "   roof_Plastic/rubber/synthetic sheeting  roof_Green Roof  cool_Central AC  \\\n",
              "0                                       0                0                0   \n",
              "1                                       0                0                0   \n",
              "2                                       0                0                0   \n",
              "3                                       0                0                0   \n",
              "4                                       0                0                0   \n",
              "\n",
              "   cool_No cooling  cool_Other  cool_Cooling_Heat Pump  cool_Split AC  \\\n",
              "0                0           0                       0              0   \n",
              "1                0           0                       0              0   \n",
              "2                0           0                       0              0   \n",
              "3                0           0                       0              0   \n",
              "4                0           0                       0              0   \n",
              "\n",
              "   heat_Boiler  heat_Resistance Heating  heat_Heating_Heat pump  heat_Other  \\\n",
              "0            0                        0                       0           0   \n",
              "1            0                        0                       0           0   \n",
              "2            0                        0                       0           0   \n",
              "3            0                        0                       0           0   \n",
              "4            0                        0                       0           0   \n",
              "\n",
              "   heat_Heating_Furnace  wall_Other  wall_wall_Wood  wall_wall_Metal  \\\n",
              "0                     0           0               0                0   \n",
              "1                     0           0               0                0   \n",
              "2                     0           0               0                0   \n",
              "3                     0           0               0                0   \n",
              "4                     0           0               0                0   \n",
              "\n",
              "   wall_wall_Brick_stone  wall_wall_Concrete  \n",
              "0                      0                   0  \n",
              "1                      0                   0  \n",
              "2                      0                   0  \n",
              "3                      0                   0  \n",
              "4                      0                   0  "
            ],
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              "\n",
              "  <div id=\"df-67bd821e-6681-4efa-881f-001ce74da57d\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe thead th {\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>rand_num</th>\n",
              "      <th>datasource</th>\n",
              "      <th>id</th>\n",
              "      <th>year</th>\n",
              "      <th>climate</th>\n",
              "      <th>building_class</th>\n",
              "      <th>facility_type</th>\n",
              "      <th>floor_area</th>\n",
              "      <th>year_built</th>\n",
              "      <th>heating</th>\n",
              "      <th>cooling</th>\n",
              "      <th>wall_type</th>\n",
              "      <th>roof_ceiling</th>\n",
              "      <th>window_glass_layers</th>\n",
              "      <th>window_glass_type</th>\n",
              "      <th>energy_star_label</th>\n",
              "      <th>energy_star_rating</th>\n",
              "      <th>electric_eui</th>\n",
              "      <th>fuel_eui</th>\n",
              "      <th>site_eui</th>\n",
              "      <th>source_eui</th>\n",
              "      <th>ghg_emissions_int</th>\n",
              "      <th>city_line</th>\n",
              "      <th>clim_2A Hot - Humid</th>\n",
              "      <th>clim_3C Warm - Marine</th>\n",
              "      <th>clim_5A Cool - Humid</th>\n",
              "      <th>clim_3B Warm - Dry</th>\n",
              "      <th>clim_2B Hot - Dry</th>\n",
              "      <th>clim_4C Mixed - Marine</th>\n",
              "      <th>clim_6B Cold - Dry</th>\n",
              "      <th>clim_4B Mixed - Dry</th>\n",
              "      <th>clim_5B Cool - Dry</th>\n",
              "      <th>clim_4A Mixed - Humid</th>\n",
              "      <th>clim_6A Cold - Humid</th>\n",
              "      <th>clim_3A Warm - Humid</th>\n",
              "      <th>BC_Residential</th>\n",
              "      <th>BC_Commercial</th>\n",
              "      <th>FT_Multifamily</th>\n",
              "      <th>FT_Industrial</th>\n",
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              "      <th>FT_Hotel</th>\n",
              "      <th>FT_Restaurant</th>\n",
              "      <th>FT_Grocery</th>\n",
              "      <th>FT_Hospital</th>\n",
              "      <th>FT_Data Center</th>\n",
              "      <th>FT_Singlefamily</th>\n",
              "      <th>WGL_Single-pane</th>\n",
              "      <th>WGL_Double-pane</th>\n",
              "      <th>WGT_Low-e</th>\n",
              "      <th>roof_Shingles</th>\n",
              "      <th>roof_Built-up</th>\n",
              "      <th>roof_Slate or tile shingles</th>\n",
              "      <th>roof_Metal surfacing</th>\n",
              "      <th>roof_Other Or Combination</th>\n",
              "      <th>roof_Asphalt/fiberglass/other shingles</th>\n",
              "      <th>roof_Wood shingles/shakes/other wood</th>\n",
              "      <th>roof_Plastic/rubber/synthetic sheeting</th>\n",
              "      <th>roof_Green Roof</th>\n",
              "      <th>cool_Central AC</th>\n",
              "      <th>cool_No cooling</th>\n",
              "      <th>cool_Other</th>\n",
              "      <th>cool_Cooling_Heat Pump</th>\n",
              "      <th>cool_Split AC</th>\n",
              "      <th>heat_Boiler</th>\n",
              "      <th>heat_Resistance Heating</th>\n",
              "      <th>heat_Heating_Heat pump</th>\n",
              "      <th>heat_Other</th>\n",
              "      <th>heat_Heating_Furnace</th>\n",
              "      <th>wall_Other</th>\n",
              "      <th>wall_wall_Wood</th>\n",
              "      <th>wall_wall_Metal</th>\n",
              "      <th>wall_wall_Brick_stone</th>\n",
              "      <th>wall_wall_Concrete</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.548814</td>\n",
              "      <td>austin</td>\n",
              "      <td>100012</td>\n",
              "      <td>2018.0</td>\n",
              "      <td>2A Hot - Humid (Houston-TX)</td>\n",
              "      <td>Residential</td>\n",
              "      <td>Multifamily - Uncategorized</td>\n",
              "      <td>160356.0</td>\n",
              "      <td>2013.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>28.656706</td>\n",
              "      <td>0.0</td>\n",
              "      <td>28.656706</td>\n",
              "      <td>89.982058</td>\n",
              "      <td>3.565981</td>\n",
              "      <td>Austin, TX 78704</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
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              "      <th>1</th>\n",
              "      <td>0.715189</td>\n",
              "      <td>austin</td>\n",
              "      <td>100012</td>\n",
              "      <td>2019.0</td>\n",
              "      <td>2A Hot - Humid (Houston-TX)</td>\n",
              "      <td>Residential</td>\n",
              "      <td>Multifamily - Uncategorized</td>\n",
              "      <td>160356.0</td>\n",
              "      <td>2013.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>29.493681</td>\n",
              "      <td>0.0</td>\n",
              "      <td>29.493681</td>\n",
              "      <td>92.610158</td>\n",
              "      <td>3.670133</td>\n",
              "      <td>Austin, TX 78704</td>\n",
              "      <td>1</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.602763</td>\n",
              "      <td>austin</td>\n",
              "      <td>100030</td>\n",
              "      <td>2018.0</td>\n",
              "      <td>2A Hot - Humid (Houston-TX)</td>\n",
              "      <td>Residential</td>\n",
              "      <td>Multifamily - Uncategorized</td>\n",
              "      <td>51195.0</td>\n",
              "      <td>1982.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Shingles</td>\n",
              "      <td>Single-pane</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>37.971292</td>\n",
              "      <td>0.0</td>\n",
              "      <td>37.971292</td>\n",
              "      <td>119.229858</td>\n",
              "      <td>4.725069</td>\n",
              "      <td>Austin, TX 78704</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.544883</td>\n",
              "      <td>austin</td>\n",
              "      <td>100030</td>\n",
              "      <td>2019.0</td>\n",
              "      <td>2A Hot - Humid (Houston-TX)</td>\n",
              "      <td>Residential</td>\n",
              "      <td>Multifamily - Uncategorized</td>\n",
              "      <td>51195.0</td>\n",
              "      <td>1982.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Shingles</td>\n",
              "      <td>Single-pane</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>39.017660</td>\n",
              "      <td>0.0</td>\n",
              "      <td>39.017660</td>\n",
              "      <td>122.515452</td>\n",
              "      <td>4.855277</td>\n",
              "      <td>Austin, TX 78704</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.423655</td>\n",
              "      <td>austin</td>\n",
              "      <td>100138</td>\n",
              "      <td>2014.0</td>\n",
              "      <td>2A Hot - Humid (Houston-TX)</td>\n",
              "      <td>Commercial</td>\n",
              "      <td>NaN</td>\n",
              "      <td>62368.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>94.0</td>\n",
              "      <td>32.005873</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Austin, TX 78704</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-67bd821e-6681-4efa-881f-001ce74da57d')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-67bd821e-6681-4efa-881f-001ce74da57d button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-67bd821e-6681-4efa-881f-001ce74da57d');\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
        }
      ],
      "source": [
        "train = pd.read_pickle('/content/drive/MyDrive/W207 - Final Project/pickles/dffinal_multihot_train.pk1')\n",
        "test = pd.read_pickle('/content/drive/MyDrive/W207 - Final Project/pickles/dffinal_multihot_test.pk1')\n",
        "train.head()"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Data Preprocessing"
      ],
      "metadata": {
        "id": "Zn1am77Sz-K6"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Fix mixed column types"
      ],
      "metadata": {
        "id": "DFojBB_8-XL4"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "train.insert(0, 'df', 'train')\n",
        "test.insert(0, 'df', 'test')\n",
        "df = pd.concat([train, test])"
      ],
      "metadata": {
        "id": "As46dscRCQXU"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "bad_col_types = []\n",
        "for col in df.columns:\n",
        "    weird = (df[[col]].applymap(type) != df[[col]].iloc[0].apply(type)).any(axis=1)\n",
        "    if len(df[weird]) > 0:\n",
        "        bad_col_types.append(col)\n",
        "        print(col, \"Na values:\", df[col].isna().sum())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_M4VO7sn26GH",
        "outputId": "9e022141-0d7d-4db9-c4ff-55f17fa81e1d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "id Na values: 0\n",
            "climate Na values: 823\n",
            "facility_type Na values: 156941\n",
            "heating Na values: 295828\n",
            "cooling Na values: 145377\n",
            "wall_type Na values: 295626\n",
            "roof_ceiling Na values: 142155\n",
            "window_glass_layers Na values: 294400\n",
            "window_glass_type Na values: 296012\n",
            "energy_star_label Na values: 291654\n",
            "city_line Na values: 20484\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for col in bad_col_types:\n",
        "    df[col] = df[col].apply(lambda x: pd.NA if pd.isnull(x) else str(x))"
      ],
      "metadata": {
        "id": "5pUhO7v03txs"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MzpS-0SAHgS5",
        "outputId": "9262537e-547f-41a0-eb0e-bf2bd223b613"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "df                                             0\n",
              "rand_num                                       0\n",
              "datasource                                     0\n",
              "id                                             0\n",
              "year                                           0\n",
              "climate                                      823\n",
              "building_class                                 0\n",
              "facility_type                             156941\n",
              "floor_area                                     0\n",
              "year_built                                  4779\n",
              "heating                                   295828\n",
              "cooling                                   145377\n",
              "wall_type                                 295626\n",
              "roof_ceiling                              142155\n",
              "window_glass_layers                       294400\n",
              "window_glass_type                         296012\n",
              "energy_star_label                         291654\n",
              "energy_star_rating                        206522\n",
              "electric_eui                               95099\n",
              "fuel_eui                                  135265\n",
              "site_eui                                   91855\n",
              "source_eui                                 99129\n",
              "ghg_emissions_int                         152211\n",
              "city_line                                  20484\n",
              "clim_2A Hot - Humid                            0\n",
              "clim_3C Warm - Marine                          0\n",
              "clim_5A Cool - Humid                           0\n",
              "clim_3B Warm - Dry                             0\n",
              "clim_2B Hot - Dry                              0\n",
              "clim_4C Mixed - Marine                         0\n",
              "clim_6B Cold - Dry                             0\n",
              "clim_4B Mixed - Dry                            0\n",
              "clim_5B Cool - Dry                             0\n",
              "clim_4A Mixed - Humid                          0\n",
              "clim_6A Cold - Humid                           0\n",
              "clim_3A Warm - Humid                           0\n",
              "BC_Residential                                 0\n",
              "BC_Commercial                                  0\n",
              "FT_Multifamily                                 0\n",
              "FT_Industrial                                  0\n",
              "FT_Office                                      0\n",
              "FT_Retail                                      0\n",
              "FT_Other                                       0\n",
              "FT_Hotel                                       0\n",
              "FT_Restaurant                                  0\n",
              "FT_Grocery                                     0\n",
              "FT_Hospital                                    0\n",
              "FT_Data Center                                 0\n",
              "FT_Singlefamily                                0\n",
              "WGL_Single-pane                                0\n",
              "WGL_Double-pane                                0\n",
              "WGT_Low-e                                      0\n",
              "roof_Shingles                                  0\n",
              "roof_Built-up                                  0\n",
              "roof_Slate or tile shingles                    0\n",
              "roof_Metal surfacing                           0\n",
              "roof_Other Or Combination                      0\n",
              "roof_Asphalt/fiberglass/other shingles         0\n",
              "roof_Wood shingles/shakes/other wood           0\n",
              "roof_Plastic/rubber/synthetic sheeting         0\n",
              "roof_Green Roof                                0\n",
              "cool_Central AC                                0\n",
              "cool_No cooling                                0\n",
              "cool_Other                                     0\n",
              "cool_Cooling_Heat Pump                         0\n",
              "cool_Split AC                                  0\n",
              "heat_Boiler                                    0\n",
              "heat_Resistance Heating                        0\n",
              "heat_Heating_Heat pump                         0\n",
              "heat_Other                                     0\n",
              "heat_Heating_Furnace                           0\n",
              "wall_Other                                     0\n",
              "wall_wall_Wood                                 0\n",
              "wall_wall_Metal                                0\n",
              "wall_wall_Brick_stone                          0\n",
              "wall_wall_Concrete                             0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Feature Engineering"
      ],
      "metadata": {
        "id": "Vqdzovjx_bjp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_engr = df.copy()\n",
        "df_engr.sample(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 565
        },
        "id": "Ppu5EbcYABBE",
        "outputId": "78452390-f6e0-4f0e-ac85-77c06a1164cf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           df  rand_num    datasource          id    year  \\\n",
              "29953   train  0.928333       chicago      159980  2019.0   \n",
              "214505  train  0.406801  nycOrdinance  1021360200  2013.0   \n",
              "122258  train  0.510924   gainesville      149224  2015.0   \n",
              "242397   test  0.982865  nycOrdinance  4050057502  2015.0   \n",
              "203061   test  0.080417  nycOrdinance  1011387501  2015.0   \n",
              "\n",
              "                                climate building_class  \\\n",
              "29953      5A Cool - Humid (Chicago-IL)    Residential   \n",
              "214505  4A Mixed - Humid (Baltimore-MD)    Residential   \n",
              "122258      2A Hot - Humid (Houston-TX)    Residential   \n",
              "242397  4A Mixed - Humid (Baltimore-MD)    Residential   \n",
              "203061  4A Mixed - Humid (Baltimore-MD)    Residential   \n",
              "\n",
              "                      facility_type  floor_area  year_built heating  \\\n",
              "29953   Multifamily - Uncategorized    106000.0      1967.0    <NA>   \n",
              "214505  Multifamily - Uncategorized     64214.0      1922.0    <NA>   \n",
              "122258                         <NA>      1554.0      1983.0    <NA>   \n",
              "242397  Multifamily - Uncategorized    111100.0      1924.0    <NA>   \n",
              "203061  Multifamily - Uncategorized    159018.0      1995.0    <NA>   \n",
              "\n",
              "                         cooling wall_type                       roof_ceiling  \\\n",
              "29953                       <NA>      <NA>                               <NA>   \n",
              "214505                      <NA>      <NA>                               <NA>   \n",
              "122258  Central Air Conditioning      <NA>  Asphalt/fiberglass/other shingles   \n",
              "242397                      <NA>      <NA>                               <NA>   \n",
              "203061                      <NA>      <NA>                               <NA>   \n",
              "\n",
              "       window_glass_layers window_glass_type energy_star_label  \\\n",
              "29953                 <NA>              <NA>              <NA>   \n",
              "214505                <NA>              <NA>              <NA>   \n",
              "122258                <NA>              <NA>              <NA>   \n",
              "242397                <NA>              <NA>              <NA>   \n",
              "203061                <NA>              <NA>              <NA>   \n",
              "\n",
              "        energy_star_rating  electric_eui   fuel_eui    site_eui  source_eui  \\\n",
              "29953                 55.0     10.191676  92.904301  103.095977  129.551380   \n",
              "214505                 NaN           NaN        NaN  119.435614  148.874963   \n",
              "122258                 NaN           NaN  15.251313         NaN         NaN   \n",
              "242397                89.0           NaN        NaN   76.605711  101.508803   \n",
              "203061                 1.0           NaN        NaN  241.277155  490.862991   \n",
              "\n",
              "        ghg_emissions_int              city_line  clim_2A Hot - Humid  \\\n",
              "29953            6.524756      Chicago, IL 60649                    0   \n",
              "214505                NaN     New York, NY 10032                    0   \n",
              "122258                NaN  Gainesville, FL 32606                    1   \n",
              "242397                NaN     Flushing, NY 11354                    0   \n",
              "203061                NaN     New York, NY 10023                    0   \n",
              "\n",
              "        clim_3C Warm - Marine  clim_5A Cool - Humid  clim_3B Warm - Dry  \\\n",
              "29953                       0                     0                   0   \n",
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              "122258                      0                     0                   0   \n",
              "242397                      0                     0                   0   \n",
              "203061                      0                     0                   0   \n",
              "\n",
              "        clim_2B Hot - Dry  clim_4C Mixed - Marine  clim_6B Cold - Dry  \\\n",
              "29953                   0                       0                   0   \n",
              "214505                  0                       1                   0   \n",
              "122258                  0                       0                   0   \n",
              "242397                  0                       1                   0   \n",
              "203061                  0                       1                   0   \n",
              "\n",
              "        clim_4B Mixed - Dry  clim_5B Cool - Dry  clim_4A Mixed - Humid  \\\n",
              "29953                     0                   1                      0   \n",
              "214505                    0                   0                      0   \n",
              "122258                    0                   0                      0   \n",
              "242397                    0                   0                      0   \n",
              "203061                    0                   0                      0   \n",
              "\n",
              "        clim_6A Cold - Humid  clim_3A Warm - Humid  BC_Residential  \\\n",
              "29953                      0                     0               0   \n",
              "214505                     0                     0               0   \n",
              "122258                     0                     0               0   \n",
              "242397                     0                     0               0   \n",
              "203061                     0                     0               0   \n",
              "\n",
              "        BC_Commercial  FT_Multifamily  FT_Industrial  FT_Office  FT_Retail  \\\n",
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              "\n",
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              "203061         0         1              0           0            0   \n",
              "\n",
              "        FT_Data Center  FT_Singlefamily  WGL_Single-pane  WGL_Double-pane  \\\n",
              "29953                0                0                0                0   \n",
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              "203061               0                0                0                0   \n",
              "\n",
              "        WGT_Low-e  roof_Shingles  roof_Built-up  roof_Slate or tile shingles  \\\n",
              "29953           0              0              0                            0   \n",
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              "122258          0              1              0                            0   \n",
              "242397          0              0              0                            0   \n",
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              "\n",
              "        roof_Metal surfacing  roof_Other Or Combination  \\\n",
              "29953                      0                          0   \n",
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              "122258                     0                          0   \n",
              "242397                     0                          0   \n",
              "203061                     0                          0   \n",
              "\n",
              "        roof_Asphalt/fiberglass/other shingles  \\\n",
              "29953                                        0   \n",
              "214505                                       0   \n",
              "122258                                       0   \n",
              "242397                                       0   \n",
              "203061                                       0   \n",
              "\n",
              "        roof_Wood shingles/shakes/other wood  \\\n",
              "29953                                      0   \n",
              "214505                                     0   \n",
              "122258                                     0   \n",
              "242397                                     0   \n",
              "203061                                     0   \n",
              "\n",
              "        roof_Plastic/rubber/synthetic sheeting  roof_Green Roof  \\\n",
              "29953                                        0                0   \n",
              "214505                                       0                0   \n",
              "122258                                       0                0   \n",
              "242397                                       0                0   \n",
              "203061                                       0                0   \n",
              "\n",
              "        cool_Central AC  cool_No cooling  cool_Other  cool_Cooling_Heat Pump  \\\n",
              "29953                 0                0           0                       0   \n",
              "214505                0                0           0                       0   \n",
              "122258                1                0           0                       0   \n",
              "242397                0                0           0                       0   \n",
              "203061                0                0           0                       0   \n",
              "\n",
              "        cool_Split AC  heat_Boiler  heat_Resistance Heating  \\\n",
              "29953               0            0                        0   \n",
              "214505              0            0                        0   \n",
              "122258              0            0                        0   \n",
              "242397              0            0                        0   \n",
              "203061              0            0                        0   \n",
              "\n",
              "        heat_Heating_Heat pump  heat_Other  heat_Heating_Furnace  wall_Other  \\\n",
              "29953                        0           0                     0           0   \n",
              "214505                       0           0                     0           0   \n",
              "122258                       0           0                     0           0   \n",
              "242397                       0           0                     0           0   \n",
              "203061                       0           0                     0           0   \n",
              "\n",
              "        wall_wall_Wood  wall_wall_Metal  wall_wall_Brick_stone  \\\n",
              "29953                0                0                      0   \n",
              "214505               0                0                      0   \n",
              "122258               0                0                      0   \n",
              "242397               0                0                      0   \n",
              "203061               0                0                      0   \n",
              "\n",
              "        wall_wall_Concrete  \n",
              "29953                    0  \n",
              "214505                   0  \n",
              "122258                   0  \n",
              "242397                   0  \n",
              "203061                   0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5a767314-4167-44a3-81b6-2f77627fc675\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>df</th>\n",
              "      <th>rand_num</th>\n",
              "      <th>datasource</th>\n",
              "      <th>id</th>\n",
              "      <th>year</th>\n",
              "      <th>climate</th>\n",
              "      <th>building_class</th>\n",
              "      <th>facility_type</th>\n",
              "      <th>floor_area</th>\n",
              "      <th>year_built</th>\n",
              "      <th>heating</th>\n",
              "      <th>cooling</th>\n",
              "      <th>wall_type</th>\n",
              "      <th>roof_ceiling</th>\n",
              "      <th>window_glass_layers</th>\n",
              "      <th>window_glass_type</th>\n",
              "      <th>energy_star_label</th>\n",
              "      <th>energy_star_rating</th>\n",
              "      <th>electric_eui</th>\n",
              "      <th>fuel_eui</th>\n",
              "      <th>site_eui</th>\n",
              "      <th>source_eui</th>\n",
              "      <th>ghg_emissions_int</th>\n",
              "      <th>city_line</th>\n",
              "      <th>clim_2A Hot - Humid</th>\n",
              "      <th>clim_3C Warm - Marine</th>\n",
              "      <th>clim_5A Cool - Humid</th>\n",
              "      <th>clim_3B Warm - Dry</th>\n",
              "      <th>clim_2B Hot - Dry</th>\n",
              "      <th>clim_4C Mixed - Marine</th>\n",
              "      <th>clim_6B Cold - Dry</th>\n",
              "      <th>clim_4B Mixed - Dry</th>\n",
              "      <th>clim_5B Cool - Dry</th>\n",
              "      <th>clim_4A Mixed - Humid</th>\n",
              "      <th>clim_6A Cold - Humid</th>\n",
              "      <th>clim_3A Warm - Humid</th>\n",
              "      <th>BC_Residential</th>\n",
              "      <th>BC_Commercial</th>\n",
              "      <th>FT_Multifamily</th>\n",
              "      <th>FT_Industrial</th>\n",
              "      <th>FT_Office</th>\n",
              "      <th>FT_Retail</th>\n",
              "      <th>FT_Other</th>\n",
              "      <th>FT_Hotel</th>\n",
              "      <th>FT_Restaurant</th>\n",
              "      <th>FT_Grocery</th>\n",
              "      <th>FT_Hospital</th>\n",
              "      <th>FT_Data Center</th>\n",
              "      <th>FT_Singlefamily</th>\n",
              "      <th>WGL_Single-pane</th>\n",
              "      <th>WGL_Double-pane</th>\n",
              "      <th>WGT_Low-e</th>\n",
              "      <th>roof_Shingles</th>\n",
              "      <th>roof_Built-up</th>\n",
              "      <th>roof_Slate or tile shingles</th>\n",
              "      <th>roof_Metal surfacing</th>\n",
              "      <th>roof_Other Or Combination</th>\n",
              "      <th>roof_Asphalt/fiberglass/other shingles</th>\n",
              "      <th>roof_Wood shingles/shakes/other wood</th>\n",
              "      <th>roof_Plastic/rubber/synthetic sheeting</th>\n",
              "      <th>roof_Green Roof</th>\n",
              "      <th>cool_Central AC</th>\n",
              "      <th>cool_No cooling</th>\n",
              "      <th>cool_Other</th>\n",
              "      <th>cool_Cooling_Heat Pump</th>\n",
              "      <th>cool_Split AC</th>\n",
              "      <th>heat_Boiler</th>\n",
              "      <th>heat_Resistance Heating</th>\n",
              "      <th>heat_Heating_Heat pump</th>\n",
              "      <th>heat_Other</th>\n",
              "      <th>heat_Heating_Furnace</th>\n",
              "      <th>wall_Other</th>\n",
              "      <th>wall_wall_Wood</th>\n",
              "      <th>wall_wall_Metal</th>\n",
              "      <th>wall_wall_Brick_stone</th>\n",
              "      <th>wall_wall_Concrete</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>29953</th>\n",
              "      <td>train</td>\n",
              "      <td>0.928333</td>\n",
              "      <td>chicago</td>\n",
              "      <td>159980</td>\n",
              "      <td>2019.0</td>\n",
              "      <td>5A Cool - Humid (Chicago-IL)</td>\n",
              "      <td>Residential</td>\n",
              "      <td>Multifamily - Uncategorized</td>\n",
              "      <td>106000.0</td>\n",
              "      <td>1967.0</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
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              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>55.0</td>\n",
              "      <td>10.191676</td>\n",
              "      <td>92.904301</td>\n",
              "      <td>103.095977</td>\n",
              "      <td>129.551380</td>\n",
              "      <td>6.524756</td>\n",
              "      <td>Chicago, IL 60649</td>\n",
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              "      <td>train</td>\n",
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              "      <td>2013.0</td>\n",
              "      <td>4A Mixed - Humid (Baltimore-MD)</td>\n",
              "      <td>Residential</td>\n",
              "      <td>Multifamily - Uncategorized</td>\n",
              "      <td>64214.0</td>\n",
              "      <td>1922.0</td>\n",
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              "      <td>&lt;NA&gt;</td>\n",
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              "      <td>119.435614</td>\n",
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              "      <th>122258</th>\n",
              "      <td>train</td>\n",
              "      <td>0.510924</td>\n",
              "      <td>gainesville</td>\n",
              "      <td>149224</td>\n",
              "      <td>2015.0</td>\n",
              "      <td>2A Hot - Humid (Houston-TX)</td>\n",
              "      <td>Residential</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>1554.0</td>\n",
              "      <td>1983.0</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>Central Air Conditioning</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>Asphalt/fiberglass/other shingles</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>15.251313</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Gainesville, FL 32606</td>\n",
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              "    <tr>\n",
              "      <th>242397</th>\n",
              "      <td>test</td>\n",
              "      <td>0.982865</td>\n",
              "      <td>nycOrdinance</td>\n",
              "      <td>4050057502</td>\n",
              "      <td>2015.0</td>\n",
              "      <td>4A Mixed - Humid (Baltimore-MD)</td>\n",
              "      <td>Residential</td>\n",
              "      <td>Multifamily - Uncategorized</td>\n",
              "      <td>111100.0</td>\n",
              "      <td>1924.0</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
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              "      <td>&lt;NA&gt;</td>\n",
              "      <td>89.0</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>76.605711</td>\n",
              "      <td>101.508803</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Flushing, NY 11354</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>203061</th>\n",
              "      <td>test</td>\n",
              "      <td>0.080417</td>\n",
              "      <td>nycOrdinance</td>\n",
              "      <td>1011387501</td>\n",
              "      <td>2015.0</td>\n",
              "      <td>4A Mixed - Humid (Baltimore-MD)</td>\n",
              "      <td>Residential</td>\n",
              "      <td>Multifamily - Uncategorized</td>\n",
              "      <td>159018.0</td>\n",
              "      <td>1995.0</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>1.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>241.277155</td>\n",
              "      <td>490.862991</td>\n",
              "      <td>NaN</td>\n",
              "      <td>New York, NY 10023</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5a767314-4167-44a3-81b6-2f77627fc675')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "        \n",
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              "\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Binarize building_class"
      ],
      "metadata": {
        "id": "jHb6zz5QALah"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_engr.building_class.drop_duplicates()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "z5CwBmGoAK7K",
        "outputId": "afe3d34d-8dc9-439b-8467-950a45aa0553"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    Residential\n",
              "4     Commercial\n",
              "Name: building_class, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "repl = {'Residential': 1.0,\n",
        "        'Commercial': 0.0}\n",
        "df_engr['is_residential'] = df_engr.building_class.replace(repl)\n",
        "df_engr['is_residential'] = df_engr.is_residential.astype('uint8')\n",
        "df_engr[['is_residential', 'building_class']].drop_duplicates()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "id": "Va2UPuSHAPYN",
        "outputId": "53cda71a-4d63-4933-91ad-c2b2f814dc2c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   is_residential building_class\n",
              "0               1    Residential\n",
              "4               0     Commercial"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-104e417b-8d4a-40ef-a134-4ecd00d931f9\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>is_residential</th>\n",
              "      <th>building_class</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Residential</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0</td>\n",
              "      <td>Commercial</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-104e417b-8d4a-40ef-a134-4ecd00d931f9')\"\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
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              "      background-color: #434B5C;\n",
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              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
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              "        const buttonEl =\n",
              "          document.querySelector('#df-104e417b-8d4a-40ef-a134-4ecd00d931f9 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-104e417b-8d4a-40ef-a134-4ecd00d931f9');\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",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Has Energy Star Label"
      ],
      "metadata": {
        "id": "JRJD-sMafANB"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_engr['energy_star_label'].drop_duplicates()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5T5tCuypfIRm",
        "outputId": "a5539e28-b2e5-4f83-fca9-63f181b98f4e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0               <NA>\n",
              "8892         Labeled\n",
              "15641    Not Labeled\n",
              "Name: energy_star_label, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "repl = {'Labeled': 1.0,\n",
        "        'Not Labeled': 0.0}\n",
        "df_engr['has_energy_star_label'] = df_engr.energy_star_label.replace(repl)\n",
        "df_engr[['has_energy_star_label', 'energy_star_label']].drop_duplicates()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "cnZg0cGzfnFg",
        "outputId": "ac74ed87-aac7-46cb-b883-40a1eb1caaaf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      has_energy_star_label energy_star_label\n",
              "0                      <NA>              <NA>\n",
              "8892                    1.0           Labeled\n",
              "15641                   0.0       Not Labeled"
            ],
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              "\n",
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              "      <td>0.0</td>\n",
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              "    .colab-df-container {\n",
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              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-542ec03e-6f48-4ad7-96a5-e1d6abf7f0d8 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-542ec03e-6f48-4ad7-96a5-e1d6abf7f0d8');\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": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Humidity, Temp"
      ],
      "metadata": {
        "id": "EjbfTtTX_sMT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def split_climate(dfin):\n",
        "        \n",
        "    fn = lambda x: pd.NA if isinstance(x,  type(pd.NA)) else x.split(\" - \")[1].split(\" \")[0] if isinstance(x, str) else pd.NA\n",
        "    dfin['dryness'] = dfin.climate.apply(fn)\n",
        "\n",
        "    fn = lambda x: pd.NA if isinstance(x,  type(pd.NA)) else x.split(\" - \")[0].split(\" \")[1] if isinstance(x, str) else pd.NA\n",
        "    dfin['temp'] = dfin.climate.apply(fn)\n",
        "\n",
        "    return dfin"
      ],
      "metadata": {
        "id": "YXiMGkq2_r_H"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_engr = split_climate(df_engr)"
      ],
      "metadata": {
        "id": "5rPWRG8jJ5kh"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_engr = pd.concat([df_engr.drop(columns=['dryness', 'temp']),\n",
        "                     pd.get_dummies(df_engr.temp, prefix='temp', dummy_na=True),\n",
        "                     pd.get_dummies(df_engr.dryness, prefix='dryness', dummy_na=True)\n",
        "                    ], axis=1)"
      ],
      "metadata": {
        "id": "wvexgefuDhDv"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Building Age"
      ],
      "metadata": {
        "id": "ZBzwAx4JUKdY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_engr['age'] = df_engr.year - df_engr.year_built\n"
      ],
      "metadata": {
        "id": "Vn81OyH8Tl0H"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_engr.sample(7)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 732
        },
        "id": "AtnuG8XPULBQ",
        "outputId": "9b1e00c3-1840-4eb7-92be-fafa51c6b403"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           df  rand_num    datasource          id    year  \\\n",
              "266664  train  0.608428       seattle       21338  2019.0   \n",
              "222332  train  0.282614  nycOrdinance  2033190107  2017.0   \n",
              "144956   test  0.399884   gainesville      154554  2011.0   \n",
              "116614  train  0.473474   gainesville      147731  2012.0   \n",
              "80749    test  0.453825   gainesville      138535  2011.0   \n",
              "169121  train  0.701932   gainesville      161527  2012.0   \n",
              "214251   test  0.716063  nycOrdinance  1021190036  2014.0   \n",
              "\n",
              "                                climate building_class  \\\n",
              "266664     4C Mixed - Marine (Salem-OR)    Residential   \n",
              "222332  4A Mixed - Humid (Baltimore-MD)    Residential   \n",
              "144956      2A Hot - Humid (Houston-TX)    Residential   \n",
              "116614      2A Hot - Humid (Houston-TX)    Residential   \n",
              "80749       2A Hot - Humid (Houston-TX)    Residential   \n",
              "169121      2A Hot - Humid (Houston-TX)    Residential   \n",
              "214251  4A Mixed - Humid (Baltimore-MD)    Residential   \n",
              "\n",
              "                      facility_type  floor_area  year_built heating  \\\n",
              "266664            2-4 Unit Building     24840.0      1905.0    <NA>   \n",
              "222332  Multifamily - Uncategorized     60366.0      1926.0    <NA>   \n",
              "144956                         <NA>      1718.0      2000.0    <NA>   \n",
              "116614                         <NA>      1291.0      1968.0    <NA>   \n",
              "80749                          <NA>      1180.0      1984.0    <NA>   \n",
              "169121                         <NA>      1131.0      1979.0    <NA>   \n",
              "214251  Multifamily - Uncategorized    135070.0      1983.0    <NA>   \n",
              "\n",
              "                         cooling wall_type                       roof_ceiling  \\\n",
              "266664                      <NA>      <NA>                               <NA>   \n",
              "222332                      <NA>      <NA>                               <NA>   \n",
              "144956  Central Air Conditioning      <NA>  Asphalt/fiberglass/other shingles   \n",
              "116614  Central Air Conditioning      <NA>                           Built-up   \n",
              "80749   Central Air Conditioning      <NA>  Asphalt/fiberglass/other shingles   \n",
              "169121  Central Air Conditioning      <NA>  Asphalt/fiberglass/other shingles   \n",
              "214251                      <NA>      <NA>                               <NA>   \n",
              "\n",
              "       window_glass_layers window_glass_type energy_star_label  \\\n",
              "266664                <NA>              <NA>              <NA>   \n",
              "222332                <NA>              <NA>              <NA>   \n",
              "144956                <NA>              <NA>              <NA>   \n",
              "116614                <NA>              <NA>              <NA>   \n",
              "80749                 <NA>              <NA>              <NA>   \n",
              "169121                <NA>              <NA>              <NA>   \n",
              "214251                <NA>              <NA>              <NA>   \n",
              "\n",
              "        energy_star_rating  electric_eui   fuel_eui    site_eui  source_eui  \\\n",
              "266664                90.0     16.672507  12.718478   29.390986   65.706075   \n",
              "222332                47.0           NaN        NaN  122.000000  160.800000   \n",
              "144956                 NaN           NaN  14.435720         NaN         NaN   \n",
              "116614                 NaN     20.098159  25.467209   45.565369   89.848791   \n",
              "80749                  NaN      9.478839   8.556784   17.229151   37.901382   \n",
              "169121                 NaN     44.526574        NaN         NaN         NaN   \n",
              "214251                45.0           NaN        NaN   85.348952  126.714952   \n",
              "\n",
              "        ghg_emissions_int              city_line  clim_2A Hot - Humid  \\\n",
              "266664           2.101401      Seattle, WA 98104                    0   \n",
              "222332                NaN        Bronx, NY 10468                    0   \n",
              "144956                NaN  Gainesville, FL 32608                    1   \n",
              "116614           4.377304  Gainesville, FL 32609                    1   \n",
              "80749            1.880522  Gainesville, FL 32606                    1   \n",
              "169121                NaN                   <NA>                    1   \n",
              "214251                NaN     New York, NY 10032                    0   \n",
              "\n",
              "        clim_3C Warm - Marine  clim_5A Cool - Humid  clim_3B Warm - Dry  \\\n",
              "266664                      0                     0                   0   \n",
              "222332                      0                     0                   0   \n",
              "144956                      0                     0                   0   \n",
              "116614                      0                     0                   0   \n",
              "80749                       0                     0                   0   \n",
              "169121                      0                     0                   0   \n",
              "214251                      0                     0                   0   \n",
              "\n",
              "        clim_2B Hot - Dry  clim_4C Mixed - Marine  clim_6B Cold - Dry  \\\n",
              "266664                  0                       0                   0   \n",
              "222332                  0                       1                   0   \n",
              "144956                  0                       0                   0   \n",
              "116614                  0                       0                   0   \n",
              "80749                   0                       0                   0   \n",
              "169121                  0                       0                   0   \n",
              "214251                  0                       1                   0   \n",
              "\n",
              "        clim_4B Mixed - Dry  clim_5B Cool - Dry  clim_4A Mixed - Humid  \\\n",
              "266664                    1                   0                      0   \n",
              "222332                    0                   0                      0   \n",
              "144956                    0                   0                      0   \n",
              "116614                    0                   0                      0   \n",
              "80749                     0                   0                      0   \n",
              "169121                    0                   0                      0   \n",
              "214251                    0                   0                      0   \n",
              "\n",
              "        clim_6A Cold - Humid  clim_3A Warm - Humid  BC_Residential  \\\n",
              "266664                     0                     0               0   \n",
              "222332                     0                     0               0   \n",
              "144956                     0                     0               0   \n",
              "116614                     0                     0               0   \n",
              "80749                      0                     0               0   \n",
              "169121                     0                     0               0   \n",
              "214251                     0                     0               0   \n",
              "\n",
              "        BC_Commercial  FT_Multifamily  FT_Industrial  FT_Office  FT_Retail  \\\n",
              "266664              1               0              0          0          0   \n",
              "222332              1               0              0          0          0   \n",
              "144956              1               0              0          0          0   \n",
              "116614              1               0              0          0          0   \n",
              "80749               1               0              0          0          0   \n",
              "169121              1               0              0          0          0   \n",
              "214251              1               0              0          0          0   \n",
              "\n",
              "        FT_Other  FT_Hotel  FT_Restaurant  FT_Grocery  FT_Hospital  \\\n",
              "266664         0         1              0           0            0   \n",
              "222332         0         1              0           0            0   \n",
              "144956         0         0              0           0            0   \n",
              "116614         0         0              0           0            0   \n",
              "80749          0         0              0           0            0   \n",
              "169121         0         0              0           0            0   \n",
              "214251         0         1              0           0            0   \n",
              "\n",
              "        FT_Data Center  FT_Singlefamily  WGL_Single-pane  WGL_Double-pane  \\\n",
              "266664               0                0                0                0   \n",
              "222332               0                0                0                0   \n",
              "144956               0                0                0                0   \n",
              "116614               0                0                0                0   \n",
              "80749                0                0                0                0   \n",
              "169121               0                0                0                0   \n",
              "214251               0                0                0                0   \n",
              "\n",
              "        WGT_Low-e  roof_Shingles  roof_Built-up  roof_Slate or tile shingles  \\\n",
              "266664          0              0              0                            0   \n",
              "222332          0              0              0                            0   \n",
              "144956          0              1              0                            0   \n",
              "116614          0              0              1                            0   \n",
              "80749           0              1              0                            0   \n",
              "169121          0              1              0                            0   \n",
              "214251          0              0              0                            0   \n",
              "\n",
              "        roof_Metal surfacing  roof_Other Or Combination  \\\n",
              "266664                     0                          0   \n",
              "222332                     0                          0   \n",
              "144956                     0                          0   \n",
              "116614                     0                          0   \n",
              "80749                      0                          0   \n",
              "169121                     0                          0   \n",
              "214251                     0                          0   \n",
              "\n",
              "        roof_Asphalt/fiberglass/other shingles  \\\n",
              "266664                                       0   \n",
              "222332                                       0   \n",
              "144956                                       0   \n",
              "116614                                       0   \n",
              "80749                                        0   \n",
              "169121                                       0   \n",
              "214251                                       0   \n",
              "\n",
              "        roof_Wood shingles/shakes/other wood  \\\n",
              "266664                                     0   \n",
              "222332                                     0   \n",
              "144956                                     0   \n",
              "116614                                     0   \n",
              "80749                                      0   \n",
              "169121                                     0   \n",
              "214251                                     0   \n",
              "\n",
              "        roof_Plastic/rubber/synthetic sheeting  roof_Green Roof  \\\n",
              "266664                                       0                0   \n",
              "222332                                       0                0   \n",
              "144956                                       0                0   \n",
              "116614                                       0                0   \n",
              "80749                                        0                0   \n",
              "169121                                       0                0   \n",
              "214251                                       0                0   \n",
              "\n",
              "        cool_Central AC  cool_No cooling  cool_Other  cool_Cooling_Heat Pump  \\\n",
              "266664                0                0           0                       0   \n",
              "222332                0                0           0                       0   \n",
              "144956                1                0           0                       0   \n",
              "116614                1                0           0                       0   \n",
              "80749                 1                0           0                       0   \n",
              "169121                1                0           0                       0   \n",
              "214251                0                0           0                       0   \n",
              "\n",
              "        cool_Split AC  heat_Boiler  heat_Resistance Heating  \\\n",
              "266664              0            0                        0   \n",
              "222332              0            0                        0   \n",
              "144956              0            0                        0   \n",
              "116614              0            0                        0   \n",
              "80749               0            0                        0   \n",
              "169121              0            0                        0   \n",
              "214251              0            0                        0   \n",
              "\n",
              "        heat_Heating_Heat pump  heat_Other  heat_Heating_Furnace  wall_Other  \\\n",
              "266664                       0           0                     0           0   \n",
              "222332                       0           0                     0           0   \n",
              "144956                       0           0                     0           0   \n",
              "116614                       0           0                     0           0   \n",
              "80749                        0           0                     0           0   \n",
              "169121                       0           0                     0           0   \n",
              "214251                       0           0                     0           0   \n",
              "\n",
              "        wall_wall_Wood  wall_wall_Metal  wall_wall_Brick_stone  \\\n",
              "266664               0                0                      0   \n",
              "222332               0                0                      0   \n",
              "144956               0                0                      0   \n",
              "116614               0                0                      0   \n",
              "80749                0                0                      0   \n",
              "169121               0                0                      0   \n",
              "214251               0                0                      0   \n",
              "\n",
              "        wall_wall_Concrete  is_residential has_energy_star_label  temp_Cold  \\\n",
              "266664                   0               1                  <NA>          0   \n",
              "222332                   0               1                  <NA>          0   \n",
              "144956                   0               1                  <NA>          0   \n",
              "116614                   0               1                  <NA>          0   \n",
              "80749                    0               1                  <NA>          0   \n",
              "169121                   0               1                  <NA>          0   \n",
              "214251                   0               1                  <NA>          0   \n",
              "\n",
              "        temp_Cool  temp_Hot  temp_Mixed  temp_Warm  temp_nan  dryness_Dry  \\\n",
              "266664          0         0           1          0         0            0   \n",
              "222332          0         0           1          0         0            0   \n",
              "144956          0         1           0          0         0            0   \n",
              "116614          0         1           0          0         0            0   \n",
              "80749           0         1           0          0         0            0   \n",
              "169121          0         1           0          0         0            0   \n",
              "214251          0         0           1          0         0            0   \n",
              "\n",
              "        dryness_Humid  dryness_Marine  dryness_nan    age  \n",
              "266664              0               1            0  114.0  \n",
              "222332              1               0            0   91.0  \n",
              "144956              1               0            0   11.0  \n",
              "116614              1               0            0   44.0  \n",
              "80749               1               0            0   27.0  \n",
              "169121              1               0            0   33.0  \n",
              "214251              1               0            0   31.0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-4e8f6b69-04f2-45d9-a3dc-f95734346ffe\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>df</th>\n",
              "      <th>rand_num</th>\n",
              "      <th>datasource</th>\n",
              "      <th>id</th>\n",
              "      <th>year</th>\n",
              "      <th>climate</th>\n",
              "      <th>building_class</th>\n",
              "      <th>facility_type</th>\n",
              "      <th>floor_area</th>\n",
              "      <th>year_built</th>\n",
              "      <th>heating</th>\n",
              "      <th>cooling</th>\n",
              "      <th>wall_type</th>\n",
              "      <th>roof_ceiling</th>\n",
              "      <th>window_glass_layers</th>\n",
              "      <th>window_glass_type</th>\n",
              "      <th>energy_star_label</th>\n",
              "      <th>energy_star_rating</th>\n",
              "      <th>electric_eui</th>\n",
              "      <th>fuel_eui</th>\n",
              "      <th>site_eui</th>\n",
              "      <th>source_eui</th>\n",
              "      <th>ghg_emissions_int</th>\n",
              "      <th>city_line</th>\n",
              "      <th>clim_2A Hot - Humid</th>\n",
              "      <th>clim_3C Warm - Marine</th>\n",
              "      <th>clim_5A Cool - Humid</th>\n",
              "      <th>clim_3B Warm - Dry</th>\n",
              "      <th>clim_2B Hot - Dry</th>\n",
              "      <th>clim_4C Mixed - Marine</th>\n",
              "      <th>clim_6B Cold - Dry</th>\n",
              "      <th>clim_4B Mixed - Dry</th>\n",
              "      <th>clim_5B Cool - Dry</th>\n",
              "      <th>clim_4A Mixed - Humid</th>\n",
              "      <th>clim_6A Cold - Humid</th>\n",
              "      <th>clim_3A Warm - Humid</th>\n",
              "      <th>BC_Residential</th>\n",
              "      <th>BC_Commercial</th>\n",
              "      <th>FT_Multifamily</th>\n",
              "      <th>FT_Industrial</th>\n",
              "      <th>FT_Office</th>\n",
              "      <th>FT_Retail</th>\n",
              "      <th>FT_Other</th>\n",
              "      <th>FT_Hotel</th>\n",
              "      <th>FT_Restaurant</th>\n",
              "      <th>FT_Grocery</th>\n",
              "      <th>FT_Hospital</th>\n",
              "      <th>FT_Data Center</th>\n",
              "      <th>FT_Singlefamily</th>\n",
              "      <th>WGL_Single-pane</th>\n",
              "      <th>WGL_Double-pane</th>\n",
              "      <th>WGT_Low-e</th>\n",
              "      <th>roof_Shingles</th>\n",
              "      <th>roof_Built-up</th>\n",
              "      <th>roof_Slate or tile shingles</th>\n",
              "      <th>roof_Metal surfacing</th>\n",
              "      <th>roof_Other Or Combination</th>\n",
              "      <th>roof_Asphalt/fiberglass/other shingles</th>\n",
              "      <th>roof_Wood shingles/shakes/other wood</th>\n",
              "      <th>roof_Plastic/rubber/synthetic sheeting</th>\n",
              "      <th>roof_Green Roof</th>\n",
              "      <th>cool_Central AC</th>\n",
              "      <th>cool_No cooling</th>\n",
              "      <th>cool_Other</th>\n",
              "      <th>cool_Cooling_Heat Pump</th>\n",
              "      <th>cool_Split AC</th>\n",
              "      <th>heat_Boiler</th>\n",
              "      <th>heat_Resistance Heating</th>\n",
              "      <th>heat_Heating_Heat pump</th>\n",
              "      <th>heat_Other</th>\n",
              "      <th>heat_Heating_Furnace</th>\n",
              "      <th>wall_Other</th>\n",
              "      <th>wall_wall_Wood</th>\n",
              "      <th>wall_wall_Metal</th>\n",
              "      <th>wall_wall_Brick_stone</th>\n",
              "      <th>wall_wall_Concrete</th>\n",
              "      <th>is_residential</th>\n",
              "      <th>has_energy_star_label</th>\n",
              "      <th>temp_Cold</th>\n",
              "      <th>temp_Cool</th>\n",
              "      <th>temp_Hot</th>\n",
              "      <th>temp_Mixed</th>\n",
              "      <th>temp_Warm</th>\n",
              "      <th>temp_nan</th>\n",
              "      <th>dryness_Dry</th>\n",
              "      <th>dryness_Humid</th>\n",
              "      <th>dryness_Marine</th>\n",
              "      <th>dryness_nan</th>\n",
              "      <th>age</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>266664</th>\n",
              "      <td>train</td>\n",
              "      <td>0.608428</td>\n",
              "      <td>seattle</td>\n",
              "      <td>21338</td>\n",
              "      <td>2019.0</td>\n",
              "      <td>4C Mixed - Marine (Salem-OR)</td>\n",
              "      <td>Residential</td>\n",
              "      <td>2-4 Unit Building</td>\n",
              "      <td>24840.0</td>\n",
              "      <td>1905.0</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>90.0</td>\n",
              "      <td>16.672507</td>\n",
              "      <td>12.718478</td>\n",
              "      <td>29.390986</td>\n",
              "      <td>65.706075</td>\n",
              "      <td>2.101401</td>\n",
              "      <td>Seattle, WA 98104</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>114.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>222332</th>\n",
              "      <td>train</td>\n",
              "      <td>0.282614</td>\n",
              "      <td>nycOrdinance</td>\n",
              "      <td>2033190107</td>\n",
              "      <td>2017.0</td>\n",
              "      <td>4A Mixed - Humid (Baltimore-MD)</td>\n",
              "      <td>Residential</td>\n",
              "      <td>Multifamily - Uncategorized</td>\n",
              "      <td>60366.0</td>\n",
              "      <td>1926.0</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>47.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>122.000000</td>\n",
              "      <td>160.800000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Bronx, NY 10468</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>91.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>144956</th>\n",
              "      <td>test</td>\n",
              "      <td>0.399884</td>\n",
              "      <td>gainesville</td>\n",
              "      <td>154554</td>\n",
              "      <td>2011.0</td>\n",
              "      <td>2A Hot - Humid (Houston-TX)</td>\n",
              "      <td>Residential</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>1718.0</td>\n",
              "      <td>2000.0</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>Central Air Conditioning</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>Asphalt/fiberglass/other shingles</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>14.435720</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Gainesville, FL 32608</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>11.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>116614</th>\n",
              "      <td>train</td>\n",
              "      <td>0.473474</td>\n",
              "      <td>gainesville</td>\n",
              "      <td>147731</td>\n",
              "      <td>2012.0</td>\n",
              "      <td>2A Hot - Humid (Houston-TX)</td>\n",
              "      <td>Residential</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>1291.0</td>\n",
              "      <td>1968.0</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>Central Air Conditioning</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>Built-up</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>NaN</td>\n",
              "      <td>20.098159</td>\n",
              "      <td>25.467209</td>\n",
              "      <td>45.565369</td>\n",
              "      <td>89.848791</td>\n",
              "      <td>4.377304</td>\n",
              "      <td>Gainesville, FL 32609</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>44.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>80749</th>\n",
              "      <td>test</td>\n",
              "      <td>0.453825</td>\n",
              "      <td>gainesville</td>\n",
              "      <td>138535</td>\n",
              "      <td>2011.0</td>\n",
              "      <td>2A Hot - Humid (Houston-TX)</td>\n",
              "      <td>Residential</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>1180.0</td>\n",
              "      <td>1984.0</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>Central Air Conditioning</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>Asphalt/fiberglass/other shingles</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>NaN</td>\n",
              "      <td>9.478839</td>\n",
              "      <td>8.556784</td>\n",
              "      <td>17.229151</td>\n",
              "      <td>37.901382</td>\n",
              "      <td>1.880522</td>\n",
              "      <td>Gainesville, FL 32606</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>27.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169121</th>\n",
              "      <td>train</td>\n",
              "      <td>0.701932</td>\n",
              "      <td>gainesville</td>\n",
              "      <td>161527</td>\n",
              "      <td>2012.0</td>\n",
              "      <td>2A Hot - Humid (Houston-TX)</td>\n",
              "      <td>Residential</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>1131.0</td>\n",
              "      <td>1979.0</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>Central Air Conditioning</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>Asphalt/fiberglass/other shingles</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>NaN</td>\n",
              "      <td>44.526574</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>33.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>214251</th>\n",
              "      <td>test</td>\n",
              "      <td>0.716063</td>\n",
              "      <td>nycOrdinance</td>\n",
              "      <td>1021190036</td>\n",
              "      <td>2014.0</td>\n",
              "      <td>4A Mixed - Humid (Baltimore-MD)</td>\n",
              "      <td>Residential</td>\n",
              "      <td>Multifamily - Uncategorized</td>\n",
              "      <td>135070.0</td>\n",
              "      <td>1983.0</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>45.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>85.348952</td>\n",
              "      <td>126.714952</td>\n",
              "      <td>NaN</td>\n",
              "      <td>New York, NY 10032</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>31.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4e8f6b69-04f2-45d9-a3dc-f95734346ffe')\"\n",
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              "      gap: 12px;\n",
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              "\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-4e8f6b69-04f2-45d9-a3dc-f95734346ffe');\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",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Drop NA Site_EUI"
      ],
      "metadata": {
        "id": "cHuUqj5T29L0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Split back into train/test\n",
        "df_engr_train = df_engr.loc[df_engr.df == 'train', :].copy()\n",
        "df_engr_test = df_engr.loc[df_engr.df == 'test', :].copy()"
      ],
      "metadata": {
        "id": "eB__-n1I_nEk"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"Shape of train:\", df_engr_train.shape, \"test:\", df_engr_test.shape)\n",
        "print(\"Missing site_eui from train:\", df_engr_train.site_eui.isna().sum(), \"from test:\", df_engr_test.site_eui.isna().sum())\n",
        "\n",
        "print(\"Drop Site_EUI NAN:\")\n",
        "train_dropna = df_engr_train.loc[df_engr_train.site_eui.isna() != 1, :]\n",
        "test_dropna = df_engr_test.loc[df_engr_test.site_eui.isna() != 1, :]\n",
        "\n",
        "print(\"Shape of train:\", train_dropna.shape, \"test:\", test_dropna.shape)\n",
        "print(\"Missing site_eui from train:\", train_dropna.site_eui.isna().sum(), \"from test:\", test_dropna.site_eui.isna().sum())\n",
        "train_dropna.sample(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 639
        },
        "id": "1n1IhbVf0jd6",
        "outputId": "8e7102e8-f022-4ad2-abcb-9d8e53ca5776"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Shape of train: (187002, 89) test: (109063, 89)\n",
            "Missing site_eui from train: 59407 from test: 32448\n",
            "Drop Site_EUI NAN:\n",
            "Shape of train: (127595, 89) test: (76615, 89)\n",
            "Missing site_eui from train: 0 from test: 0\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           df  rand_num    datasource              id    year  \\\n",
              "163795  train  0.206336   gainesville          160125  2013.0   \n",
              "19891   train  0.239773       calProp  19644856013015  2012.0   \n",
              "226776  train  0.409079  nycOrdinance      3010280056  2016.0   \n",
              "94408   train  0.497278   gainesville          142054  2014.0   \n",
              "207542  train  0.777345  nycOrdinance      1013860064  2015.0   \n",
              "\n",
              "                                climate building_class  \\\n",
              "163795      2A Hot - Humid (Houston-TX)    Residential   \n",
              "19891        3B Warm - Dry (El Paso-TX)     Commercial   \n",
              "226776  4A Mixed - Humid (Baltimore-MD)    Residential   \n",
              "94408       2A Hot - Humid (Houston-TX)    Residential   \n",
              "207542  4A Mixed - Humid (Baltimore-MD)    Residential   \n",
              "\n",
              "                                  facility_type  floor_area  year_built  \\\n",
              "163795                                     <NA>      1530.0      1965.0   \n",
              "19891   Education - Elementary or middle school     87940.0         NaN   \n",
              "226776              Multifamily - Uncategorized     18000.0      1914.0   \n",
              "94408                                      <NA>      2645.0      1991.0   \n",
              "207542              Multifamily - Uncategorized    113068.0      1929.0   \n",
              "\n",
              "       heating                   cooling wall_type  \\\n",
              "163795    <NA>  Central Air Conditioning      <NA>   \n",
              "19891     <NA>                      <NA>      <NA>   \n",
              "226776    <NA>                      <NA>      <NA>   \n",
              "94408     <NA>  Central Air Conditioning      <NA>   \n",
              "207542    <NA>                      <NA>      <NA>   \n",
              "\n",
              "                             roof_ceiling window_glass_layers  \\\n",
              "163795  Asphalt/fiberglass/other shingles                <NA>   \n",
              "19891                                <NA>                <NA>   \n",
              "226776                               <NA>                <NA>   \n",
              "94408   Asphalt/fiberglass/other shingles                <NA>   \n",
              "207542                               <NA>                <NA>   \n",
              "\n",
              "       window_glass_type energy_star_label  energy_star_rating  electric_eui  \\\n",
              "163795              <NA>              <NA>                 NaN     27.957885   \n",
              "19891               <NA>              <NA>                 NaN     16.991673   \n",
              "226776              <NA>              <NA>                28.0           NaN   \n",
              "94408               <NA>              <NA>                 NaN     30.789945   \n",
              "207542              <NA>              <NA>                 NaN           NaN   \n",
              "\n",
              "         fuel_eui    site_eui  source_eui  ghg_emissions_int  \\\n",
              "163795  22.810978   49.984531  110.915737           5.277820   \n",
              "19891    1.116670   18.108344   54.526359           1.533661   \n",
              "226776        NaN  149.191257  178.411202                NaN   \n",
              "94408   23.365373   57.633658  124.866326           5.849315   \n",
              "207542        NaN   87.167926  134.550632                NaN   \n",
              "\n",
              "                    city_line  clim_2A Hot - Humid  clim_3C Warm - Marine  \\\n",
              "163795  Gainesville, FL 32603                    1                      0   \n",
              "19891      Whittier, CA 90604                    0                      0   \n",
              "226776     Brooklyn, NY 11215                    0                      0   \n",
              "94408   Gainesville, FL 32608                    1                      0   \n",
              "207542     New York, NY 10021                    0                      0   \n",
              "\n",
              "        clim_5A Cool - Humid  clim_3B Warm - Dry  clim_2B Hot - Dry  \\\n",
              "163795                     0                   0                  0   \n",
              "19891                      0                   1                  0   \n",
              "226776                     0                   0                  0   \n",
              "94408                      0                   0                  0   \n",
              "207542                     0                   0                  0   \n",
              "\n",
              "        clim_4C Mixed - Marine  clim_6B Cold - Dry  clim_4B Mixed - Dry  \\\n",
              "163795                       0                   0                    0   \n",
              "19891                        0                   0                    0   \n",
              "226776                       1                   0                    0   \n",
              "94408                        0                   0                    0   \n",
              "207542                       1                   0                    0   \n",
              "\n",
              "        clim_5B Cool - Dry  clim_4A Mixed - Humid  clim_6A Cold - Humid  \\\n",
              "163795                   0                      0                     0   \n",
              "19891                    0                      0                     0   \n",
              "226776                   0                      0                     0   \n",
              "94408                    0                      0                     0   \n",
              "207542                   0                      0                     0   \n",
              "\n",
              "        clim_3A Warm - Humid  BC_Residential  BC_Commercial  FT_Multifamily  \\\n",
              "163795                     0               0              1               0   \n",
              "19891                      0               1              0               0   \n",
              "226776                     0               0              1               0   \n",
              "94408                      0               0              1               0   \n",
              "207542                     0               0              1               0   \n",
              "\n",
              "        FT_Industrial  FT_Office  FT_Retail  FT_Other  FT_Hotel  \\\n",
              "163795              0          0          0         0         0   \n",
              "19891               0          0          0         0         0   \n",
              "226776              0          0          0         0         1   \n",
              "94408               0          0          0         0         0   \n",
              "207542              0          0          0         0         1   \n",
              "\n",
              "        FT_Restaurant  FT_Grocery  FT_Hospital  FT_Data Center  \\\n",
              "163795              0           0            0               0   \n",
              "19891               1           0            0               0   \n",
              "226776              0           0            0               0   \n",
              "94408               0           0            0               0   \n",
              "207542              0           0            0               0   \n",
              "\n",
              "        FT_Singlefamily  WGL_Single-pane  WGL_Double-pane  WGT_Low-e  \\\n",
              "163795                0                0                0          0   \n",
              "19891                 0                0                0          0   \n",
              "226776                0                0                0          0   \n",
              "94408                 0                0                0          0   \n",
              "207542                0                0                0          0   \n",
              "\n",
              "        roof_Shingles  roof_Built-up  roof_Slate or tile shingles  \\\n",
              "163795              1              0                            0   \n",
              "19891               0              0                            0   \n",
              "226776              0              0                            0   \n",
              "94408               1              0                            0   \n",
              "207542              0              0                            0   \n",
              "\n",
              "        roof_Metal surfacing  roof_Other Or Combination  \\\n",
              "163795                     0                          0   \n",
              "19891                      0                          0   \n",
              "226776                     0                          0   \n",
              "94408                      0                          0   \n",
              "207542                     0                          0   \n",
              "\n",
              "        roof_Asphalt/fiberglass/other shingles  \\\n",
              "163795                                       0   \n",
              "19891                                        0   \n",
              "226776                                       0   \n",
              "94408                                        0   \n",
              "207542                                       0   \n",
              "\n",
              "        roof_Wood shingles/shakes/other wood  \\\n",
              "163795                                     0   \n",
              "19891                                      0   \n",
              "226776                                     0   \n",
              "94408                                      0   \n",
              "207542                                     0   \n",
              "\n",
              "        roof_Plastic/rubber/synthetic sheeting  roof_Green Roof  \\\n",
              "163795                                       0                0   \n",
              "19891                                        0                0   \n",
              "226776                                       0                0   \n",
              "94408                                        0                0   \n",
              "207542                                       0                0   \n",
              "\n",
              "        cool_Central AC  cool_No cooling  cool_Other  cool_Cooling_Heat Pump  \\\n",
              "163795                1                0           0                       0   \n",
              "19891                 0                0           0                       0   \n",
              "226776                0                0           0                       0   \n",
              "94408                 1                0           0                       0   \n",
              "207542                0                0           0                       0   \n",
              "\n",
              "        cool_Split AC  heat_Boiler  heat_Resistance Heating  \\\n",
              "163795              0            0                        0   \n",
              "19891               0            0                        0   \n",
              "226776              0            0                        0   \n",
              "94408               0            0                        0   \n",
              "207542              0            0                        0   \n",
              "\n",
              "        heat_Heating_Heat pump  heat_Other  heat_Heating_Furnace  wall_Other  \\\n",
              "163795                       0           0                     0           0   \n",
              "19891                        0           0                     0           0   \n",
              "226776                       0           0                     0           0   \n",
              "94408                        0           0                     0           0   \n",
              "207542                       0           0                     0           0   \n",
              "\n",
              "        wall_wall_Wood  wall_wall_Metal  wall_wall_Brick_stone  \\\n",
              "163795               0                0                      0   \n",
              "19891                0                0                      0   \n",
              "226776               0                0                      0   \n",
              "94408                0                0                      0   \n",
              "207542               0                0                      0   \n",
              "\n",
              "        wall_wall_Concrete  is_residential has_energy_star_label  temp_Cold  \\\n",
              "163795                   0               1                  <NA>          0   \n",
              "19891                    0               0                  <NA>          0   \n",
              "226776                   0               1                  <NA>          0   \n",
              "94408                    0               1                  <NA>          0   \n",
              "207542                   0               1                  <NA>          0   \n",
              "\n",
              "        temp_Cool  temp_Hot  temp_Mixed  temp_Warm  temp_nan  dryness_Dry  \\\n",
              "163795          0         1           0          0         0            0   \n",
              "19891           0         0           0          1         0            1   \n",
              "226776          0         0           1          0         0            0   \n",
              "94408           0         1           0          0         0            0   \n",
              "207542          0         0           1          0         0            0   \n",
              "\n",
              "        dryness_Humid  dryness_Marine  dryness_nan    age  \n",
              "163795              1               0            0   48.0  \n",
              "19891               0               0            0    NaN  \n",
              "226776              1               0            0  102.0  \n",
              "94408               1               0            0   23.0  \n",
              "207542              1               0            0   86.0  "
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>df</th>\n",
              "      <th>rand_num</th>\n",
              "      <th>datasource</th>\n",
              "      <th>id</th>\n",
              "      <th>year</th>\n",
              "      <th>climate</th>\n",
              "      <th>building_class</th>\n",
              "      <th>facility_type</th>\n",
              "      <th>floor_area</th>\n",
              "      <th>year_built</th>\n",
              "      <th>heating</th>\n",
              "      <th>cooling</th>\n",
              "      <th>wall_type</th>\n",
              "      <th>roof_ceiling</th>\n",
              "      <th>window_glass_layers</th>\n",
              "      <th>window_glass_type</th>\n",
              "      <th>energy_star_label</th>\n",
              "      <th>energy_star_rating</th>\n",
              "      <th>electric_eui</th>\n",
              "      <th>fuel_eui</th>\n",
              "      <th>site_eui</th>\n",
              "      <th>source_eui</th>\n",
              "      <th>ghg_emissions_int</th>\n",
              "      <th>city_line</th>\n",
              "      <th>clim_2A Hot - Humid</th>\n",
              "      <th>clim_3C Warm - Marine</th>\n",
              "      <th>clim_5A Cool - Humid</th>\n",
              "      <th>clim_3B Warm - Dry</th>\n",
              "      <th>clim_2B Hot - Dry</th>\n",
              "      <th>clim_4C Mixed - Marine</th>\n",
              "      <th>clim_6B Cold - Dry</th>\n",
              "      <th>clim_4B Mixed - Dry</th>\n",
              "      <th>clim_5B Cool - Dry</th>\n",
              "      <th>clim_4A Mixed - Humid</th>\n",
              "      <th>clim_6A Cold - Humid</th>\n",
              "      <th>clim_3A Warm - Humid</th>\n",
              "      <th>BC_Residential</th>\n",
              "      <th>BC_Commercial</th>\n",
              "      <th>FT_Multifamily</th>\n",
              "      <th>FT_Industrial</th>\n",
              "      <th>FT_Office</th>\n",
              "      <th>FT_Retail</th>\n",
              "      <th>FT_Other</th>\n",
              "      <th>FT_Hotel</th>\n",
              "      <th>FT_Restaurant</th>\n",
              "      <th>FT_Grocery</th>\n",
              "      <th>FT_Hospital</th>\n",
              "      <th>FT_Data Center</th>\n",
              "      <th>FT_Singlefamily</th>\n",
              "      <th>WGL_Single-pane</th>\n",
              "      <th>WGL_Double-pane</th>\n",
              "      <th>WGT_Low-e</th>\n",
              "      <th>roof_Shingles</th>\n",
              "      <th>roof_Built-up</th>\n",
              "      <th>roof_Slate or tile shingles</th>\n",
              "      <th>roof_Metal surfacing</th>\n",
              "      <th>roof_Other Or Combination</th>\n",
              "      <th>roof_Asphalt/fiberglass/other shingles</th>\n",
              "      <th>roof_Wood shingles/shakes/other wood</th>\n",
              "      <th>roof_Plastic/rubber/synthetic sheeting</th>\n",
              "      <th>roof_Green Roof</th>\n",
              "      <th>cool_Central AC</th>\n",
              "      <th>cool_No cooling</th>\n",
              "      <th>cool_Other</th>\n",
              "      <th>cool_Cooling_Heat Pump</th>\n",
              "      <th>cool_Split AC</th>\n",
              "      <th>heat_Boiler</th>\n",
              "      <th>heat_Resistance Heating</th>\n",
              "      <th>heat_Heating_Heat pump</th>\n",
              "      <th>heat_Other</th>\n",
              "      <th>heat_Heating_Furnace</th>\n",
              "      <th>wall_Other</th>\n",
              "      <th>wall_wall_Wood</th>\n",
              "      <th>wall_wall_Metal</th>\n",
              "      <th>wall_wall_Brick_stone</th>\n",
              "      <th>wall_wall_Concrete</th>\n",
              "      <th>is_residential</th>\n",
              "      <th>has_energy_star_label</th>\n",
              "      <th>temp_Cold</th>\n",
              "      <th>temp_Cool</th>\n",
              "      <th>temp_Hot</th>\n",
              "      <th>temp_Mixed</th>\n",
              "      <th>temp_Warm</th>\n",
              "      <th>temp_nan</th>\n",
              "      <th>dryness_Dry</th>\n",
              "      <th>dryness_Humid</th>\n",
              "      <th>dryness_Marine</th>\n",
              "      <th>dryness_nan</th>\n",
              "      <th>age</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>163795</th>\n",
              "      <td>train</td>\n",
              "      <td>0.206336</td>\n",
              "      <td>gainesville</td>\n",
              "      <td>160125</td>\n",
              "      <td>2013.0</td>\n",
              "      <td>2A Hot - Humid (Houston-TX)</td>\n",
              "      <td>Residential</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>1530.0</td>\n",
              "      <td>1965.0</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>Central Air Conditioning</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>Asphalt/fiberglass/other shingles</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>NaN</td>\n",
              "      <td>27.957885</td>\n",
              "      <td>22.810978</td>\n",
              "      <td>49.984531</td>\n",
              "      <td>110.915737</td>\n",
              "      <td>5.277820</td>\n",
              "      <td>Gainesville, FL 32603</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>48.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19891</th>\n",
              "      <td>train</td>\n",
              "      <td>0.239773</td>\n",
              "      <td>calProp</td>\n",
              "      <td>19644856013015</td>\n",
              "      <td>2012.0</td>\n",
              "      <td>3B Warm - Dry (El Paso-TX)</td>\n",
              "      <td>Commercial</td>\n",
              "      <td>Education - Elementary or middle school</td>\n",
              "      <td>87940.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>NaN</td>\n",
              "      <td>16.991673</td>\n",
              "      <td>1.116670</td>\n",
              "      <td>18.108344</td>\n",
              "      <td>54.526359</td>\n",
              "      <td>1.533661</td>\n",
              "      <td>Whittier, CA 90604</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>226776</th>\n",
              "      <td>train</td>\n",
              "      <td>0.409079</td>\n",
              "      <td>nycOrdinance</td>\n",
              "      <td>3010280056</td>\n",
              "      <td>2016.0</td>\n",
              "      <td>4A Mixed - Humid (Baltimore-MD)</td>\n",
              "      <td>Residential</td>\n",
              "      <td>Multifamily - Uncategorized</td>\n",
              "      <td>18000.0</td>\n",
              "      <td>1914.0</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>28.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>149.191257</td>\n",
              "      <td>178.411202</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Brooklyn, NY 11215</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>102.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>94408</th>\n",
              "      <td>train</td>\n",
              "      <td>0.497278</td>\n",
              "      <td>gainesville</td>\n",
              "      <td>142054</td>\n",
              "      <td>2014.0</td>\n",
              "      <td>2A Hot - Humid (Houston-TX)</td>\n",
              "      <td>Residential</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>2645.0</td>\n",
              "      <td>1991.0</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>Central Air Conditioning</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>Asphalt/fiberglass/other shingles</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>NaN</td>\n",
              "      <td>30.789945</td>\n",
              "      <td>23.365373</td>\n",
              "      <td>57.633658</td>\n",
              "      <td>124.866326</td>\n",
              "      <td>5.849315</td>\n",
              "      <td>Gainesville, FL 32608</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>23.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>207542</th>\n",
              "      <td>train</td>\n",
              "      <td>0.777345</td>\n",
              "      <td>nycOrdinance</td>\n",
              "      <td>1013860064</td>\n",
              "      <td>2015.0</td>\n",
              "      <td>4A Mixed - Humid (Baltimore-MD)</td>\n",
              "      <td>Residential</td>\n",
              "      <td>Multifamily - Uncategorized</td>\n",
              "      <td>113068.0</td>\n",
              "      <td>1929.0</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>87.167926</td>\n",
              "      <td>134.550632</td>\n",
              "      <td>NaN</td>\n",
              "      <td>New York, NY 10021</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>86.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-91d25e8a-5065-4ca4-81e7-aafcfeef08f0')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-91d25e8a-5065-4ca4-81e7-aafcfeef08f0 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-91d25e8a-5065-4ca4-81e7-aafcfeef08f0');\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": 20
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### SweetViz"
      ],
      "metadata": {
        "id": "hP4ZUKpi_gVj"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "train_dropna.site_eui.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gZt8jglKVJwn",
        "outputId": "78f93f3a-70c3-48f2-cf3c-a095cf04a407"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count    127595.000000\n",
              "mean         64.742619\n",
              "std          56.407862\n",
              "min           1.002456\n",
              "25%          32.305466\n",
              "50%          51.446028\n",
              "75%          80.975918\n",
              "max         997.866120\n",
              "Name: site_eui, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "train_dropna.isna().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "I5cWSrqetk4c",
        "outputId": "aae594ee-28d2-45e2-dd81-ff300c3c6a0e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "df                                             0\n",
              "rand_num                                       0\n",
              "datasource                                     0\n",
              "id                                             0\n",
              "year                                           0\n",
              "climate                                      479\n",
              "building_class                                 0\n",
              "facility_type                              43727\n",
              "floor_area                                     0\n",
              "year_built                                  2727\n",
              "heating                                   127563\n",
              "cooling                                    85046\n",
              "wall_type                                 127253\n",
              "roof_ceiling                               83464\n",
              "window_glass_layers                       126732\n",
              "window_glass_type                         127571\n",
              "energy_star_label                         124212\n",
              "energy_star_rating                         71970\n",
              "electric_eui                               40778\n",
              "fuel_eui                                   43037\n",
              "site_eui                                       0\n",
              "source_eui                                  6035\n",
              "ghg_emissions_int                          40257\n",
              "city_line                                   6243\n",
              "clim_2A Hot - Humid                            0\n",
              "clim_3C Warm - Marine                          0\n",
              "clim_5A Cool - Humid                           0\n",
              "clim_3B Warm - Dry                             0\n",
              "clim_2B Hot - Dry                              0\n",
              "clim_4C Mixed - Marine                         0\n",
              "clim_6B Cold - Dry                             0\n",
              "clim_4B Mixed - Dry                            0\n",
              "clim_5B Cool - Dry                             0\n",
              "clim_4A Mixed - Humid                          0\n",
              "clim_6A Cold - Humid                           0\n",
              "clim_3A Warm - Humid                           0\n",
              "BC_Residential                                 0\n",
              "BC_Commercial                                  0\n",
              "FT_Multifamily                                 0\n",
              "FT_Industrial                                  0\n",
              "FT_Office                                      0\n",
              "FT_Retail                                      0\n",
              "FT_Other                                       0\n",
              "FT_Hotel                                       0\n",
              "FT_Restaurant                                  0\n",
              "FT_Grocery                                     0\n",
              "FT_Hospital                                    0\n",
              "FT_Data Center                                 0\n",
              "FT_Singlefamily                                0\n",
              "WGL_Single-pane                                0\n",
              "WGL_Double-pane                                0\n",
              "WGT_Low-e                                      0\n",
              "roof_Shingles                                  0\n",
              "roof_Built-up                                  0\n",
              "roof_Slate or tile shingles                    0\n",
              "roof_Metal surfacing                           0\n",
              "roof_Other Or Combination                      0\n",
              "roof_Asphalt/fiberglass/other shingles         0\n",
              "roof_Wood shingles/shakes/other wood           0\n",
              "roof_Plastic/rubber/synthetic sheeting         0\n",
              "roof_Green Roof                                0\n",
              "cool_Central AC                                0\n",
              "cool_No cooling                                0\n",
              "cool_Other                                     0\n",
              "cool_Cooling_Heat Pump                         0\n",
              "cool_Split AC                                  0\n",
              "heat_Boiler                                    0\n",
              "heat_Resistance Heating                        0\n",
              "heat_Heating_Heat pump                         0\n",
              "heat_Other                                     0\n",
              "heat_Heating_Furnace                           0\n",
              "wall_Other                                     0\n",
              "wall_wall_Wood                                 0\n",
              "wall_wall_Metal                                0\n",
              "wall_wall_Brick_stone                          0\n",
              "wall_wall_Concrete                             0\n",
              "is_residential                                 0\n",
              "has_energy_star_label                     124212\n",
              "temp_Cold                                      0\n",
              "temp_Cool                                      0\n",
              "temp_Hot                                       0\n",
              "temp_Mixed                                     0\n",
              "temp_Warm                                      0\n",
              "temp_nan                                       0\n",
              "dryness_Dry                                    0\n",
              "dryness_Humid                                  0\n",
              "dryness_Marine                                 0\n",
              "dryness_nan                                    0\n",
              "age                                         2727\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Create SweetViz\n",
        "target = 'site_eui'\n",
        "cols = [col for col in train_dropna.columns \n",
        "        if col not in ['electric_eui', 'fuel_eui', 'source_eui', 'ghg_emissions_int']]\n",
        "\n",
        "path_rpt = path + 'output_ben/LR Raw Report.html'\n",
        "rpt  = sweetviz.compare(\n",
        "    [train_dropna[cols], \"Training\"],\n",
        "    [test_dropna[cols], \"Test\"],\n",
        "    target_feat=target)\n",
        "rpt.show_html(path_rpt)\n",
        "\n",
        "files.download(path_rpt)"
      ],
      "metadata": {
        "id": "aqBhgS7i0CMm"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Check for duplicates:"
      ],
      "metadata": {
        "id": "tghSEzwA0C_v"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "pks = ['datasource', 'id', 'year']\n",
        "train_dropna.value_counts(pks, dropna=False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bfIbKQWyyIRP",
        "outputId": "2babf064-d599-4625-8822-99b1fe471088"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "datasource    id          year  \n",
              "austin        100012      2018.0    1\n",
              "nycOrdinance  1019760013  2017.0    1\n",
              "              1019770041  2016.0    1\n",
              "              1019770034  2016.0    1\n",
              "              1019770033  2016.0    1\n",
              "                                   ..\n",
              "gainesville   139092      2013.0    1\n",
              "                          2012.0    1\n",
              "                          2011.0    1\n",
              "              139091      2014.0    1\n",
              "syracuse      99          2017.0    1\n",
              "Length: 127595, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "test_dropna.value_counts(pks, dropna=False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4iHX6KYMylQ8",
        "outputId": "c5bddb4f-0b81-4d62-8131-81928df79e38"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "datasource    id          year  \n",
              "austin        100409      2018.0    1\n",
              "nycOrdinance  1012900056  2011.0    1\n",
              "              1012900044  2016.0    1\n",
              "                          2015.0    1\n",
              "                          2014.0    1\n",
              "                                   ..\n",
              "gainesville   141433      2011.0    1\n",
              "              141431      2014.0    1\n",
              "                          2013.0    1\n",
              "                          2012.0    1\n",
              "syracuse      83          2017.0    1\n",
              "Length: 76615, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### DFs Ready for Models"
      ],
      "metadata": {
        "id": "Iu3kP9r1yrb_"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "xBdhFJx7_9RC",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 565
        },
        "outputId": "ebdc6f50-38e6-4f3c-f920-03fae61af481"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        rand_num    datasource          id    year  \\\n",
              "165405  0.184726   gainesville      160557  2010.0   \n",
              "145188  0.169489   gainesville      154625  2012.0   \n",
              "271993  0.805354       seattle       25149  2017.0   \n",
              "217856  0.885759  nycOrdinance  2025510065  2017.0   \n",
              "208679  0.295285  nycOrdinance  1014457501  2017.0   \n",
              "\n",
              "                                climate building_class  \\\n",
              "165405      2A Hot - Humid (Houston-TX)    Residential   \n",
              "145188      2A Hot - Humid (Houston-TX)    Residential   \n",
              "271993     4C Mixed - Marine (Salem-OR)    Residential   \n",
              "217856  4A Mixed - Humid (Baltimore-MD)    Residential   \n",
              "208679  4A Mixed - Humid (Baltimore-MD)    Residential   \n",
              "\n",
              "                      facility_type  floor_area  year_built heating  \\\n",
              "165405                         <NA>      1478.0      1995.0    <NA>   \n",
              "145188                         <NA>      2991.0      2001.0    <NA>   \n",
              "271993             5+ Unit Building     36765.0      1967.0    <NA>   \n",
              "217856  Multifamily - Uncategorized     32034.0      1920.0    <NA>   \n",
              "208679  Multifamily - Uncategorized    340286.0      1961.0    <NA>   \n",
              "\n",
              "                         cooling wall_type                       roof_ceiling  \\\n",
              "165405  Central Air Conditioning      <NA>  Asphalt/fiberglass/other shingles   \n",
              "145188  Central Air Conditioning      <NA>  Asphalt/fiberglass/other shingles   \n",
              "271993                      <NA>      <NA>                               <NA>   \n",
              "217856                      <NA>      <NA>                               <NA>   \n",
              "208679                      <NA>      <NA>                               <NA>   \n",
              "\n",
              "       window_glass_layers window_glass_type energy_star_label  \\\n",
              "165405                <NA>              <NA>              <NA>   \n",
              "145188                <NA>              <NA>              <NA>   \n",
              "271993                <NA>              <NA>              <NA>   \n",
              "217856                <NA>              <NA>              <NA>   \n",
              "208679                <NA>              <NA>              <NA>   \n",
              "\n",
              "        energy_star_rating  electric_eui   fuel_eui  source_eui  \\\n",
              "165405                 NaN           NaN  14.276375  104.394966   \n",
              "145188                 NaN     13.358843  15.361487   57.635800   \n",
              "271993                31.0     38.242503   0.000000  120.081459   \n",
              "217856                14.0           NaN        NaN  189.800000   \n",
              "208679                46.0           NaN        NaN  109.100000   \n",
              "\n",
              "        ghg_emissions_int              city_line  clim_2A Hot - Humid  \\\n",
              "165405           5.287179  Gainesville, FL 32605                    1   \n",
              "145188           2.800035  Gainesville, FL 32606                    1   \n",
              "271993           3.301319      Seattle, WA 98118                    0   \n",
              "217856                NaN        Bronx, NY 10454                    0   \n",
              "208679                NaN     New York, NY 10021                    0   \n",
              "\n",
              "        clim_3C Warm - Marine  clim_5A Cool - Humid  clim_3B Warm - Dry  \\\n",
              "165405                      0                     0                   0   \n",
              "145188                      0                     0                   0   \n",
              "271993                      0                     0                   0   \n",
              "217856                      0                     0                   0   \n",
              "208679                      0                     0                   0   \n",
              "\n",
              "        clim_2B Hot - Dry  clim_4C Mixed - Marine  clim_6B Cold - Dry  \\\n",
              "165405                  0                       0                   0   \n",
              "145188                  0                       0                   0   \n",
              "271993                  0                       0                   0   \n",
              "217856                  0                       1                   0   \n",
              "208679                  0                       1                   0   \n",
              "\n",
              "        clim_4B Mixed - Dry  clim_5B Cool - Dry  clim_4A Mixed - Humid  \\\n",
              "165405                    0                   0                      0   \n",
              "145188                    0                   0                      0   \n",
              "271993                    1                   0                      0   \n",
              "217856                    0                   0                      0   \n",
              "208679                    0                   0                      0   \n",
              "\n",
              "        clim_6A Cold - Humid  clim_3A Warm - Humid  BC_Residential  \\\n",
              "165405                     0                     0               0   \n",
              "145188                     0                     0               0   \n",
              "271993                     0                     0               0   \n",
              "217856                     0                     0               0   \n",
              "208679                     0                     0               0   \n",
              "\n",
              "        BC_Commercial  FT_Multifamily  FT_Industrial  FT_Office  FT_Retail  \\\n",
              "165405              1               0              0          0          0   \n",
              "145188              1               0              0          0          0   \n",
              "271993              1               0              0          0          0   \n",
              "217856              1               0              0          0          0   \n",
              "208679              1               0              0          0          0   \n",
              "\n",
              "        FT_Other  FT_Hotel  FT_Restaurant  FT_Grocery  FT_Hospital  \\\n",
              "165405         0         0              0           0            0   \n",
              "145188         0         0              0           0            0   \n",
              "271993         0         1              0           0            0   \n",
              "217856         0         1              0           0            0   \n",
              "208679         0         1              0           0            0   \n",
              "\n",
              "        FT_Data Center  FT_Singlefamily  WGL_Single-pane  WGL_Double-pane  \\\n",
              "165405               0                0                0                0   \n",
              "145188               0                0                0                0   \n",
              "271993               0                0                0                0   \n",
              "217856               0                0                0                0   \n",
              "208679               0                0                0                0   \n",
              "\n",
              "        WGT_Low-e  roof_Shingles  roof_Built-up  roof_Slate or tile shingles  \\\n",
              "165405          0              1              0                            0   \n",
              "145188          0              1              0                            0   \n",
              "271993          0              0              0                            0   \n",
              "217856          0              0              0                            0   \n",
              "208679          0              0              0                            0   \n",
              "\n",
              "        roof_Metal surfacing  roof_Other Or Combination  \\\n",
              "165405                     0                          0   \n",
              "145188                     0                          0   \n",
              "271993                     0                          0   \n",
              "217856                     0                          0   \n",
              "208679                     0                          0   \n",
              "\n",
              "        roof_Asphalt/fiberglass/other shingles  \\\n",
              "165405                                       0   \n",
              "145188                                       0   \n",
              "271993                                       0   \n",
              "217856                                       0   \n",
              "208679                                       0   \n",
              "\n",
              "        roof_Wood shingles/shakes/other wood  \\\n",
              "165405                                     0   \n",
              "145188                                     0   \n",
              "271993                                     0   \n",
              "217856                                     0   \n",
              "208679                                     0   \n",
              "\n",
              "        roof_Plastic/rubber/synthetic sheeting  roof_Green Roof  \\\n",
              "165405                                       0                0   \n",
              "145188                                       0                0   \n",
              "271993                                       0                0   \n",
              "217856                                       0                0   \n",
              "208679                                       0                0   \n",
              "\n",
              "        cool_Central AC  cool_No cooling  cool_Other  cool_Cooling_Heat Pump  \\\n",
              "165405                1                0           0                       0   \n",
              "145188                1                0           0                       0   \n",
              "271993                0                0           0                       0   \n",
              "217856                0                0           0                       0   \n",
              "208679                0                0           0                       0   \n",
              "\n",
              "        cool_Split AC  heat_Boiler  heat_Resistance Heating  \\\n",
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              "\n",
              "        wall_wall_Wood  wall_wall_Metal  wall_wall_Brick_stone  \\\n",
              "165405               0                0                      0   \n",
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              "217856                   0               1                  <NA>          0   \n",
              "208679                   0               1                  <NA>          0   \n",
              "\n",
              "        temp_Cool  temp_Hot  temp_Mixed  temp_Warm  temp_nan  dryness_Dry  \\\n",
              "165405          0         1           0          0         0            0   \n",
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              "\n",
              "        dryness_Humid  dryness_Marine  dryness_nan   age  \n",
              "165405              1               0            0  15.0  \n",
              "145188              1               0            0  11.0  \n",
              "271993              0               1            0  50.0  \n",
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              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>rand_num</th>\n",
              "      <th>datasource</th>\n",
              "      <th>id</th>\n",
              "      <th>year</th>\n",
              "      <th>climate</th>\n",
              "      <th>building_class</th>\n",
              "      <th>facility_type</th>\n",
              "      <th>floor_area</th>\n",
              "      <th>year_built</th>\n",
              "      <th>heating</th>\n",
              "      <th>cooling</th>\n",
              "      <th>wall_type</th>\n",
              "      <th>roof_ceiling</th>\n",
              "      <th>window_glass_layers</th>\n",
              "      <th>window_glass_type</th>\n",
              "      <th>energy_star_label</th>\n",
              "      <th>energy_star_rating</th>\n",
              "      <th>electric_eui</th>\n",
              "      <th>fuel_eui</th>\n",
              "      <th>source_eui</th>\n",
              "      <th>ghg_emissions_int</th>\n",
              "      <th>city_line</th>\n",
              "      <th>clim_2A Hot - Humid</th>\n",
              "      <th>clim_3C Warm - Marine</th>\n",
              "      <th>clim_5A Cool - Humid</th>\n",
              "      <th>clim_3B Warm - Dry</th>\n",
              "      <th>clim_2B Hot - Dry</th>\n",
              "      <th>clim_4C Mixed - Marine</th>\n",
              "      <th>clim_6B Cold - Dry</th>\n",
              "      <th>clim_4B Mixed - Dry</th>\n",
              "      <th>clim_5B Cool - Dry</th>\n",
              "      <th>clim_4A Mixed - Humid</th>\n",
              "      <th>clim_6A Cold - Humid</th>\n",
              "      <th>clim_3A Warm - Humid</th>\n",
              "      <th>BC_Residential</th>\n",
              "      <th>BC_Commercial</th>\n",
              "      <th>FT_Multifamily</th>\n",
              "      <th>FT_Industrial</th>\n",
              "      <th>FT_Office</th>\n",
              "      <th>FT_Retail</th>\n",
              "      <th>FT_Other</th>\n",
              "      <th>FT_Hotel</th>\n",
              "      <th>FT_Restaurant</th>\n",
              "      <th>FT_Grocery</th>\n",
              "      <th>FT_Hospital</th>\n",
              "      <th>FT_Data Center</th>\n",
              "      <th>FT_Singlefamily</th>\n",
              "      <th>WGL_Single-pane</th>\n",
              "      <th>WGL_Double-pane</th>\n",
              "      <th>WGT_Low-e</th>\n",
              "      <th>roof_Shingles</th>\n",
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              "      <th>roof_Slate or tile shingles</th>\n",
              "      <th>roof_Metal surfacing</th>\n",
              "      <th>roof_Other Or Combination</th>\n",
              "      <th>roof_Asphalt/fiberglass/other shingles</th>\n",
              "      <th>roof_Wood shingles/shakes/other wood</th>\n",
              "      <th>roof_Plastic/rubber/synthetic sheeting</th>\n",
              "      <th>roof_Green Roof</th>\n",
              "      <th>cool_Central AC</th>\n",
              "      <th>cool_No cooling</th>\n",
              "      <th>cool_Other</th>\n",
              "      <th>cool_Cooling_Heat Pump</th>\n",
              "      <th>cool_Split AC</th>\n",
              "      <th>heat_Boiler</th>\n",
              "      <th>heat_Resistance Heating</th>\n",
              "      <th>heat_Heating_Heat pump</th>\n",
              "      <th>heat_Other</th>\n",
              "      <th>heat_Heating_Furnace</th>\n",
              "      <th>wall_Other</th>\n",
              "      <th>wall_wall_Wood</th>\n",
              "      <th>wall_wall_Metal</th>\n",
              "      <th>wall_wall_Brick_stone</th>\n",
              "      <th>wall_wall_Concrete</th>\n",
              "      <th>is_residential</th>\n",
              "      <th>has_energy_star_label</th>\n",
              "      <th>temp_Cold</th>\n",
              "      <th>temp_Cool</th>\n",
              "      <th>temp_Hot</th>\n",
              "      <th>temp_Mixed</th>\n",
              "      <th>temp_Warm</th>\n",
              "      <th>temp_nan</th>\n",
              "      <th>dryness_Dry</th>\n",
              "      <th>dryness_Humid</th>\n",
              "      <th>dryness_Marine</th>\n",
              "      <th>dryness_nan</th>\n",
              "      <th>age</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>165405</th>\n",
              "      <td>0.184726</td>\n",
              "      <td>gainesville</td>\n",
              "      <td>160557</td>\n",
              "      <td>2010.0</td>\n",
              "      <td>2A Hot - Humid (Houston-TX)</td>\n",
              "      <td>Residential</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>1478.0</td>\n",
              "      <td>1995.0</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>Central Air Conditioning</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>Asphalt/fiberglass/other shingles</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>14.276375</td>\n",
              "      <td>104.394966</td>\n",
              "      <td>5.287179</td>\n",
              "      <td>Gainesville, FL 32605</td>\n",
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              "      <td>&lt;NA&gt;</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>15.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>145188</th>\n",
              "      <td>0.169489</td>\n",
              "      <td>gainesville</td>\n",
              "      <td>154625</td>\n",
              "      <td>2012.0</td>\n",
              "      <td>2A Hot - Humid (Houston-TX)</td>\n",
              "      <td>Residential</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>2991.0</td>\n",
              "      <td>2001.0</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>Central Air Conditioning</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>Asphalt/fiberglass/other shingles</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
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              "      <td>13.358843</td>\n",
              "      <td>15.361487</td>\n",
              "      <td>57.635800</td>\n",
              "      <td>2.800035</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
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              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>11.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>271993</th>\n",
              "      <td>0.805354</td>\n",
              "      <td>seattle</td>\n",
              "      <td>25149</td>\n",
              "      <td>2017.0</td>\n",
              "      <td>4C Mixed - Marine (Salem-OR)</td>\n",
              "      <td>Residential</td>\n",
              "      <td>5+ Unit Building</td>\n",
              "      <td>36765.0</td>\n",
              "      <td>1967.0</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>31.0</td>\n",
              "      <td>38.242503</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>120.081459</td>\n",
              "      <td>3.301319</td>\n",
              "      <td>Seattle, WA 98118</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>Residential</td>\n",
              "      <td>Multifamily - Uncategorized</td>\n",
              "      <td>32034.0</td>\n",
              "      <td>1920.0</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
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              "      <td>14.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>189.800000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Bronx, NY 10454</td>\n",
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              "      <td>0</td>\n",
              "      <td>97.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>208679</th>\n",
              "      <td>0.295285</td>\n",
              "      <td>nycOrdinance</td>\n",
              "      <td>1014457501</td>\n",
              "      <td>2017.0</td>\n",
              "      <td>4A Mixed - Humid (Baltimore-MD)</td>\n",
              "      <td>Residential</td>\n",
              "      <td>Multifamily - Uncategorized</td>\n",
              "      <td>340286.0</td>\n",
              "      <td>1961.0</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>46.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>109.100000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>New York, NY 10021</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>56.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-515baf7e-dfa5-4d8e-b74f-035c4d5e4e65')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-515baf7e-dfa5-4d8e-b74f-035c4d5e4e65 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-515baf7e-dfa5-4d8e-b74f-035c4d5e4e65');\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": 27
        }
      ],
      "source": [
        "y = train_dropna[['site_eui']].copy()\n",
        "y_test = test_dropna[['site_eui']].copy()\n",
        "\n",
        "X = train_dropna.drop(columns=['site_eui', 'df']).copy()\n",
        "X_test = test_dropna.drop(columns=['site_eui', 'df']).copy()\n",
        "X.sample(5)"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Model Functions"
      ],
      "metadata": {
        "id": "19IRp3rsXaQw"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def linear_model(X, y, num_features, \n",
        "                 normalize=False,\n",
        "                 learning_rate=0.001, batch=32, epochs=15):\n",
        "    \"\"\"Build a TF linear regression model using Keras.\n",
        "    \"\"\"\n",
        "\n",
        "    tf.keras.backend.clear_session()\n",
        "    tf.random.set_seed(0)\n",
        "\n",
        "    # single layer sequential for linear reg\n",
        "    model = tf.keras.Sequential()\n",
        "\n",
        "    if normalize:\n",
        "        norm = tf.keras.layers.Normalization()\n",
        "        norm.adapt(X)\n",
        "        norm_mean = norm.mean.numpy()\n",
        "        norm_var = norm.variance.numpy()\n",
        "\n",
        "        model.add(norm)\n",
        "\n",
        "    model.add(tf.keras.layers.Dense(\n",
        "        units=1,                     # output dim\n",
        "        input_shape=[num_features],  # input dim\n",
        "        use_bias=True,               # use a bias (intercept) param\n",
        "    ))\n",
        "\n",
        "    # Compile, specify MSE as loss \n",
        "    model.compile(loss='mse', \n",
        "                  optimizer=tf.keras.optimizers.Adam(learning_rate=learning_rate), \n",
        "                  metrics = ['MAE', 'MAPE'])\n",
        "    \n",
        "    print(model.summary())\n",
        "\n",
        "    history = model.fit(x=X, y=y, \n",
        "                        validation_split=0.1, \n",
        "                        batch_size=12, \n",
        "                        epochs=epochs)\n",
        "    \n",
        "    return model, history"
      ],
      "metadata": {
        "id": "G2FKDETMXZg-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def linear_plot(X, model, history, \n",
        "                loss_ylim=200_000, mae_ylim=200, mape_ylim=200):\n",
        "    \"\"\"Plots emtrics for linear regression\"\"\"\n",
        "    hist = history.history\n",
        "    x_arr = np.arange(len(hist['loss'])) + 1\n",
        "\n",
        "    fig = plt.figure(figsize=(12, 4))\n",
        "    ax = fig.add_subplot(1, 3, 1)\n",
        "    ax.plot(x_arr, hist['loss'], '-o', label='Train loss')\n",
        "    ax.plot(x_arr, hist['val_loss'], '--<', label='Validation loss')\n",
        "    ax.legend(fontsize=15)\n",
        "    ax.set_xlabel('Epoch', size=15)\n",
        "    ax.set_ylabel('Loss', size=15)\n",
        "    ax.set_ylim(0,loss_ylim)\n",
        "\n",
        "    ax = fig.add_subplot(1, 3, 2)\n",
        "    ax.plot(x_arr, hist['MAE'], '-o', label='Train MAE')\n",
        "    ax.plot(x_arr, hist['val_MAE'], '--<', label='Validation MAE')\n",
        "    ax.legend(fontsize=15)\n",
        "    ax.set_xlabel('Epoch', size=15)\n",
        "    ax.set_ylabel('MeanAbsoluteError', size=15)\n",
        "    ax.set_ylim(0,mae_ylim)\n",
        "\n",
        "    ax = fig.add_subplot(1, 3, 3)\n",
        "    ax.plot(x_arr, hist['MAPE'], '-o', label='Train MAPE')\n",
        "    ax.plot(x_arr, hist['val_MAPE'], '--<', label='Validation MAPE')\n",
        "    ax.legend(fontsize=15)\n",
        "    ax.set_xlabel('Epoch', size=15)\n",
        "    ax.set_ylabel('MeanAbsolutePercentageError', size=15)\n",
        "    ax.set_ylim(0,mape_ylim)\n",
        "\n",
        "    plt.show()\n",
        "        \n",
        "    # Show the final train loss value and the learned model weights.\n",
        "    print('Final val loss:', round(list(history.history['val_loss'])[-1], 2))\n",
        "    print('Final val mean absolute error:', round(list(history.history['val_MAE'])[-1], 2))\n",
        "    print('Final val mean absolute percentage error:', round(list(history.history['val_MAPE'])[-1], 2))\n",
        "    print('Final bias:', round(model.layers[0].get_weights()[1].flatten()[0], 2))\n",
        "    for col, val in zip(X.columns, model.layers[0].get_weights()[0].flatten().tolist()):\n",
        "        print(col, round(val, 4))\n",
        "    return None\n"
      ],
      "metadata": {
        "id": "tvxQxSfS8sLC"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nAtwKVa4Av-A"
      },
      "source": [
        "## Baseline Model\n",
        "Features: age, floor_area, energy_star_rating, is_residential\n",
        "\n",
        "Baseline model with just one row for each building (most recent)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 318
        },
        "id": "d8uYKo5XBqK_",
        "outputId": "de8d64b2-ac75-4b71-f052-d0558bd72fa4"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "shape: (127595, 4)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                 age    floor_area  energy_star_rating  is_residential\n",
              "count  124868.000000  1.275950e+05        55625.000000   127595.000000\n",
              "mean       47.665166  1.022971e+05           61.404422        0.675489\n",
              "std        32.447077  1.993315e+05           29.074337        0.468194\n",
              "min         0.000000  5.000000e+02            1.000000        0.000000\n",
              "25%        21.000000  2.110000e+03           40.000000        0.000000\n",
              "50%        41.000000  5.294400e+04           68.000000        1.000000\n",
              "75%        72.000000  1.114765e+05           86.000000        1.000000\n",
              "max       367.000000  6.385382e+06          100.000000        1.000000"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-abb87d2a-1f33-4692-8cfc-ba7d7ac7af14\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>floor_area</th>\n",
              "      <th>energy_star_rating</th>\n",
              "      <th>is_residential</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>124868.000000</td>\n",
              "      <td>1.275950e+05</td>\n",
              "      <td>55625.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>47.665166</td>\n",
              "      <td>1.022971e+05</td>\n",
              "      <td>61.404422</td>\n",
              "      <td>0.675489</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>32.447077</td>\n",
              "      <td>1.993315e+05</td>\n",
              "      <td>29.074337</td>\n",
              "      <td>0.468194</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>5.000000e+02</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>21.000000</td>\n",
              "      <td>2.110000e+03</td>\n",
              "      <td>40.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>41.000000</td>\n",
              "      <td>5.294400e+04</td>\n",
              "      <td>68.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>72.000000</td>\n",
              "      <td>1.114765e+05</td>\n",
              "      <td>86.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>367.000000</td>\n",
              "      <td>6.385382e+06</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-abb87d2a-1f33-4692-8cfc-ba7d7ac7af14')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-abb87d2a-1f33-4692-8cfc-ba7d7ac7af14 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-abb87d2a-1f33-4692-8cfc-ba7d7ac7af14');\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": 30
        }
      ],
      "source": [
        "# Identify continuous variables\n",
        "cols = ['age', 'floor_area', 'energy_star_rating', 'is_residential']\n",
        "baseline = X[cols].copy()\n",
        "print(\"shape:\", baseline.shape)\n",
        "baseline.describe()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Deal with NANs\n",
        "missing = baseline.isna().any(axis=1)\n",
        "print(\"Rows with missing values:\", missing.sum())\n",
        "\n",
        "baseline = baseline[~missing]\n",
        "baseline_y = y[~missing]\n",
        "pd.concat([baseline, baseline_y]).sample(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 224
        },
        "id": "Ovr7lxzc7Njt",
        "outputId": "da9377fa-c310-40e1-d426-5d5fa660a144"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Rows with missing values: 72695\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          age  floor_area  energy_star_rating  is_residential   site_eui\n",
              "266012    NaN         NaN                 NaN             NaN  34.497987\n",
              "255797  107.0     67460.0                12.0             0.0        NaN\n",
              "25847     NaN         NaN                 NaN             NaN  60.005214\n",
              "224065   76.0     69734.0                75.0             1.0        NaN\n",
              "246536   12.0     78894.0                57.0             0.0        NaN"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5d49a734-2759-408c-b732-7b266989b459\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>floor_area</th>\n",
              "      <th>energy_star_rating</th>\n",
              "      <th>is_residential</th>\n",
              "      <th>site_eui</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>266012</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>34.497987</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>255797</th>\n",
              "      <td>107.0</td>\n",
              "      <td>67460.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25847</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>60.005214</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>224065</th>\n",
              "      <td>76.0</td>\n",
              "      <td>69734.0</td>\n",
              "      <td>75.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>246536</th>\n",
              "      <td>12.0</td>\n",
              "      <td>78894.0</td>\n",
              "      <td>57.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5d49a734-2759-408c-b732-7b266989b459')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-5d49a734-2759-408c-b732-7b266989b459 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-5d49a734-2759-408c-b732-7b266989b459');\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": 31
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Fit model"
      ],
      "metadata": {
        "id": "b7eZ1c_pZBKJ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "baseline_model, baseline_history = linear_model(\n",
        "    baseline, baseline_y, \n",
        "    num_features=baseline.shape[1],\n",
        "    epochs=15)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HYwg7E3M82tG",
        "outputId": "4cbb509d-e5c1-4192-946b-43d508a0d089"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " dense (Dense)               (None, 1)                 5         \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 5\n",
            "Trainable params: 5\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "Epoch 1/25\n",
            "4118/4118 [==============================] - 7s 2ms/step - loss: 4147452160.0000 - MAE: 20997.5156 - MAPE: 40209.7695 - val_loss: 5533.7080 - val_MAE: 56.1455 - val_MAPE: 131.0619\n",
            "Epoch 2/25\n",
            "4118/4118 [==============================] - 8s 2ms/step - loss: 7529.5649 - MAE: 67.6204 - MAPE: 186.0019 - val_loss: 5053.9146 - val_MAE: 52.7149 - val_MAPE: 122.0158\n",
            "Epoch 3/25\n",
            "4118/4118 [==============================] - 7s 2ms/step - loss: 6287.1719 - MAE: 59.5684 - MAPE: 159.6319 - val_loss: 3663.8054 - val_MAE: 43.3602 - val_MAPE: 96.2381\n",
            "Epoch 4/25\n",
            "4118/4118 [==============================] - 6s 2ms/step - loss: 13852.0791 - MAE: 53.8428 - MAPE: 119.1228 - val_loss: 5464.6104 - val_MAE: 51.3970 - val_MAPE: 108.5111\n",
            "Epoch 5/25\n",
            "4118/4118 [==============================] - 6s 2ms/step - loss: 21177.8867 - MAE: 59.8403 - MAPE: 118.9203 - val_loss: 3474.6504 - val_MAE: 39.6438 - val_MAPE: 62.8142\n",
            "Epoch 6/25\n",
            "4118/4118 [==============================] - 6s 1ms/step - loss: 28678.1504 - MAE: 64.7019 - MAPE: 127.1543 - val_loss: 4822.1367 - val_MAE: 50.0441 - val_MAPE: 78.4152\n",
            "Epoch 7/25\n",
            "4118/4118 [==============================] - 6s 2ms/step - loss: 21613.8730 - MAE: 66.7529 - MAPE: 131.1654 - val_loss: 2784.4138 - val_MAE: 33.9978 - val_MAPE: 65.2045\n",
            "Epoch 8/25\n",
            "4118/4118 [==============================] - 6s 2ms/step - loss: 38605.5625 - MAE: 60.7765 - MAPE: 118.6418 - val_loss: 3501.4924 - val_MAE: 39.3678 - val_MAPE: 78.5193\n",
            "Epoch 9/25\n",
            "4118/4118 [==============================] - 6s 2ms/step - loss: 19296.4609 - MAE: 59.4078 - MAPE: 113.0713 - val_loss: 275801.3438 - val_MAE: 365.0661 - val_MAPE: 689.9648\n",
            "Epoch 10/25\n",
            "4118/4118 [==============================] - 6s 2ms/step - loss: 38434.4336 - MAE: 65.9562 - MAPE: 127.0057 - val_loss: 2592.7974 - val_MAE: 31.9415 - val_MAPE: 57.0991\n",
            "Epoch 11/25\n",
            "4118/4118 [==============================] - 8s 2ms/step - loss: 35488.1055 - MAE: 65.9204 - MAPE: 126.0335 - val_loss: 2778.2371 - val_MAE: 33.6888 - val_MAPE: 55.8112\n",
            "Epoch 12/25\n",
            "4118/4118 [==============================] - 6s 2ms/step - loss: 13770.1787 - MAE: 52.1201 - MAPE: 105.8877 - val_loss: 2589.4392 - val_MAE: 32.0131 - val_MAPE: 58.6851\n",
            "Epoch 13/25\n",
            "4118/4118 [==============================] - 6s 2ms/step - loss: 26656.6152 - MAE: 63.4233 - MAPE: 122.7721 - val_loss: 3038.1484 - val_MAE: 36.4730 - val_MAPE: 59.2863\n",
            "Epoch 14/25\n",
            "4118/4118 [==============================] - 6s 2ms/step - loss: 21543.2051 - MAE: 60.3924 - MAPE: 118.1640 - val_loss: 3629.8921 - val_MAE: 39.6476 - val_MAPE: 78.4787\n",
            "Epoch 15/25\n",
            "4118/4118 [==============================] - 6s 2ms/step - loss: 28425.2207 - MAE: 62.9840 - MAPE: 125.6910 - val_loss: 2532.8633 - val_MAE: 31.1160 - val_MAPE: 53.1263\n",
            "Epoch 16/25\n",
            "4118/4118 [==============================] - 6s 1ms/step - loss: 28539.2227 - MAE: 61.3451 - MAPE: 116.4859 - val_loss: 15054.4658 - val_MAE: 83.0205 - val_MAPE: 167.5537\n",
            "Epoch 17/25\n",
            "4118/4118 [==============================] - 6s 1ms/step - loss: 20110.1797 - MAE: 62.6192 - MAPE: 119.8616 - val_loss: 2551.9023 - val_MAE: 31.5656 - val_MAPE: 57.3779\n",
            "Epoch 18/25\n",
            "4118/4118 [==============================] - 6s 2ms/step - loss: 40291.6406 - MAE: 62.4603 - MAPE: 124.9258 - val_loss: 2864.8840 - val_MAE: 34.4551 - val_MAPE: 56.7336\n",
            "Epoch 19/25\n",
            "4118/4118 [==============================] - 6s 1ms/step - loss: 18819.5918 - MAE: 55.7078 - MAPE: 110.1784 - val_loss: 44952.6172 - val_MAE: 155.2664 - val_MAPE: 256.7364\n",
            "Epoch 20/25\n",
            "4118/4118 [==============================] - 6s 2ms/step - loss: 18583.8438 - MAE: 56.4141 - MAPE: 109.5499 - val_loss: 2574.0073 - val_MAE: 31.3387 - val_MAPE: 52.7644\n",
            "Epoch 21/25\n",
            "4118/4118 [==============================] - 7s 2ms/step - loss: 20958.6973 - MAE: 58.8337 - MAPE: 115.2833 - val_loss: 36717.1172 - val_MAE: 131.0354 - val_MAPE: 259.5819\n",
            "Epoch 22/25\n",
            "4118/4118 [==============================] - 6s 1ms/step - loss: 27165.5820 - MAE: 62.7083 - MAPE: 127.9639 - val_loss: 3427.8022 - val_MAE: 39.9922 - val_MAPE: 62.6804\n",
            "Epoch 23/25\n",
            "4118/4118 [==============================] - 11s 3ms/step - loss: 13686.3291 - MAE: 54.8500 - MAPE: 107.0183 - val_loss: 34939.4844 - val_MAE: 127.0880 - val_MAPE: 251.4756\n",
            "Epoch 24/25\n",
            "4118/4118 [==============================] - 9s 2ms/step - loss: 42447.9766 - MAE: 66.4484 - MAPE: 127.3015 - val_loss: 19312.2793 - val_MAE: 101.9076 - val_MAPE: 164.5419\n",
            "Epoch 25/25\n",
            "4118/4118 [==============================] - 12s 3ms/step - loss: 20305.3809 - MAE: 60.9292 - MAPE: 125.1622 - val_loss: 5731.9443 - val_MAE: 55.0277 - val_MAPE: 85.8319\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "linear_plot(baseline, baseline_model, baseline_history)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 438
        },
        "id": "63yVHV8yRVGZ",
        "outputId": "fab80489-c6b1-4599-f5c9-93c83de73074"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x400 with 3 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final val loss: 5731.94\n",
            "Final val mean absolute error: 55.03\n",
            "Final val mean absolute percentage error: 85.83\n",
            "Final bias: 15.2\n",
            "age 0.69\n",
            "floor_area -0.0\n",
            "energy_star_rating -0.13\n",
            "is_residential 11.63\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5M8F_gvAMgR3"
      },
      "source": [
        "## Linear Model - multihot\n",
        "\n",
        "- Idenfity MH columns\n",
        "- Drop 'other' columns for multicollinearity\n",
        "- Dropped columns with excessive NAs:\n",
        "    - 'has_energy_star_label', 'energy_star_rating'"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Identify columns of interest\n",
        "cols = ['is_residential', 'floor_area', 'age', \n",
        "    # Dropped due to excessive NAs: 'has_energy_star_label', 'energy_star_rating',\n",
        "    'FT_Multifamily', 'FT_Industrial', 'FT_Office', 'FT_Retail', 'FT_Hotel', 'FT_Restaurant', \n",
        "    'FT_Grocery', 'FT_Hospital', 'FT_Data Center', 'FT_Singlefamily', # 'FT_Other', \n",
        "    'WGL_Single-pane', 'WGL_Double-pane', 'WGT_Low-e',  # There are ton's of 'missing' for this column\n",
        "    'roof_Shingles', 'roof_Built-up', 'roof_Slate or tile shingles', 'roof_Metal surfacing', \n",
        "    'roof_Asphalt/fiberglass/other shingles', 'roof_Wood shingles/shakes/other wood', \n",
        "    'roof_Plastic/rubber/synthetic sheeting', 'roof_Green Roof', # 'roof_Other Or Combination', \n",
        "    'cool_Central AC', 'cool_No cooling', 'cool_Cooling_Heat Pump', 'cool_Split AC',  # 'cool_Other',\n",
        "    'heat_Boiler', 'heat_Resistance Heating', 'heat_Heating_Heat pump', 'heat_Heating_Furnace',  # 'heat_Other', \n",
        "    'wall_wall_Metal', 'wall_wall_Brick_stone', 'wall_wall_Concrete', 'wall_wall_Wood', # 'wall_Other', \n",
        "    'temp_Cold', 'temp_Cool', 'temp_Hot', 'temp_Mixed', 'temp_Warm', #'temp_nan', \n",
        "    'dryness_Dry', 'dryness_Humid', 'dryness_Marine', #'dryness_nan'\n",
        "    ]"
      ],
      "metadata": {
        "id": "OYIBCqNYY2X_"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "lm_mh = X[cols].copy()\n",
        "print(\"shape:\", lm_mh.shape)\n",
        "lm_mh.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417
        },
        "id": "meR_yRSGa-rD",
        "outputId": "56bcb681-ac06-4320-9b63-cbe58b9f1ef2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "shape: (127595, 44)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       is_residential    floor_area            age  FT_Multifamily  \\\n",
              "count   127595.000000  1.275950e+05  124868.000000   127595.000000   \n",
              "mean         0.675489  1.022971e+05      47.665166        0.000259   \n",
              "std          0.468194  1.993315e+05      32.447077        0.016080   \n",
              "min          0.000000  5.000000e+02       0.000000        0.000000   \n",
              "25%          0.000000  2.110000e+03      21.000000        0.000000   \n",
              "50%          1.000000  5.294400e+04      41.000000        0.000000   \n",
              "75%          1.000000  1.114765e+05      72.000000        0.000000   \n",
              "max          1.000000  6.385382e+06     367.000000        1.000000   \n",
              "\n",
              "       FT_Industrial      FT_Office      FT_Retail       FT_Hotel  \\\n",
              "count  127595.000000  127595.000000  127595.000000  127595.000000   \n",
              "mean        0.007257       0.005713       0.044242       0.320091   \n",
              "std         0.084881       0.075371       0.205632       0.466513   \n",
              "min         0.000000       0.000000       0.000000       0.000000   \n",
              "25%         0.000000       0.000000       0.000000       0.000000   \n",
              "50%         0.000000       0.000000       0.000000       0.000000   \n",
              "75%         0.000000       0.000000       0.000000       1.000000   \n",
              "max         1.000000       1.000000       1.000000       1.000000   \n",
              "\n",
              "       FT_Restaurant     FT_Grocery    FT_Hospital  FT_Data Center  \\\n",
              "count  127595.000000  127595.000000  127595.000000   127595.000000   \n",
              "mean        0.190015       0.011450       0.002359        0.037204   \n",
              "std         0.392315       0.106392       0.048513        0.189261   \n",
              "min         0.000000       0.000000       0.000000        0.000000   \n",
              "25%         0.000000       0.000000       0.000000        0.000000   \n",
              "50%         0.000000       0.000000       0.000000        0.000000   \n",
              "75%         0.000000       0.000000       0.000000        0.000000   \n",
              "max         1.000000       1.000000       1.000000        1.000000   \n",
              "\n",
              "       FT_Singlefamily  WGL_Single-pane  WGL_Double-pane      WGT_Low-e  \\\n",
              "count    127595.000000    127595.000000    127595.000000  127595.000000   \n",
              "mean          0.002680         0.001136         0.005627       0.000188   \n",
              "std           0.051703         0.033692         0.074803       0.013714   \n",
              "min           0.000000         0.000000         0.000000       0.000000   \n",
              "25%           0.000000         0.000000         0.000000       0.000000   \n",
              "50%           0.000000         0.000000         0.000000       0.000000   \n",
              "75%           0.000000         0.000000         0.000000       0.000000   \n",
              "max           1.000000         1.000000         1.000000       1.000000   \n",
              "\n",
              "       roof_Shingles  roof_Built-up  roof_Slate or tile shingles  \\\n",
              "count  127595.000000  127595.000000                     127595.0   \n",
              "mean        0.316384       0.016403                          0.0   \n",
              "std         0.465066       0.127022                          0.0   \n",
              "min         0.000000       0.000000                          0.0   \n",
              "25%         0.000000       0.000000                          0.0   \n",
              "50%         0.000000       0.000000                          0.0   \n",
              "75%         1.000000       0.000000                          0.0   \n",
              "max         1.000000       1.000000                          0.0   \n",
              "\n",
              "       roof_Metal surfacing  roof_Asphalt/fiberglass/other shingles  \\\n",
              "count         127595.000000                           127595.000000   \n",
              "mean               0.002273                                0.000149   \n",
              "std                0.047620                                0.012202   \n",
              "min                0.000000                                0.000000   \n",
              "25%                0.000000                                0.000000   \n",
              "50%                0.000000                                0.000000   \n",
              "75%                0.000000                                0.000000   \n",
              "max                1.000000                                1.000000   \n",
              "\n",
              "       roof_Wood shingles/shakes/other wood  \\\n",
              "count                         127595.000000   \n",
              "mean                               0.006999   \n",
              "std                                0.083365   \n",
              "min                                0.000000   \n",
              "25%                                0.000000   \n",
              "50%                                0.000000   \n",
              "75%                                0.000000   \n",
              "max                                1.000000   \n",
              "\n",
              "       roof_Plastic/rubber/synthetic sheeting  roof_Green Roof  \\\n",
              "count                           127595.000000    127595.000000   \n",
              "mean                                 0.000627         0.000031   \n",
              "std                                  0.025032         0.005599   \n",
              "min                                  0.000000         0.000000   \n",
              "25%                                  0.000000         0.000000   \n",
              "50%                                  0.000000         0.000000   \n",
              "75%                                  0.000000         0.000000   \n",
              "max                                  1.000000         1.000000   \n",
              "\n",
              "       cool_Central AC  cool_No cooling  cool_Cooling_Heat Pump  \\\n",
              "count    127595.000000    127595.000000           127595.000000   \n",
              "mean          0.323469         0.000031                0.000008   \n",
              "std           0.467802         0.005599                0.002800   \n",
              "min           0.000000         0.000000                0.000000   \n",
              "25%           0.000000         0.000000                0.000000   \n",
              "50%           0.000000         0.000000                0.000000   \n",
              "75%           1.000000         0.000000                0.000000   \n",
              "max           1.000000         1.000000                1.000000   \n",
              "\n",
              "       cool_Split AC    heat_Boiler  heat_Resistance Heating  \\\n",
              "count  127595.000000  127595.000000            127595.000000   \n",
              "mean        0.000016       0.000165                 0.000024   \n",
              "std         0.003959       0.012828                 0.004849   \n",
              "min         0.000000       0.000000                 0.000000   \n",
              "25%         0.000000       0.000000                 0.000000   \n",
              "50%         0.000000       0.000000                 0.000000   \n",
              "75%         0.000000       0.000000                 0.000000   \n",
              "max         1.000000       1.000000                 1.000000   \n",
              "\n",
              "       heat_Heating_Heat pump  heat_Heating_Furnace  wall_wall_Metal  \\\n",
              "count           127595.000000         127595.000000    127595.000000   \n",
              "mean                 0.000031              0.000024         0.000047   \n",
              "std                  0.005599              0.004849         0.006857   \n",
              "min                  0.000000              0.000000         0.000000   \n",
              "25%                  0.000000              0.000000         0.000000   \n",
              "50%                  0.000000              0.000000         0.000000   \n",
              "75%                  0.000000              0.000000         0.000000   \n",
              "max                  1.000000              1.000000         1.000000   \n",
              "\n",
              "       wall_wall_Brick_stone  wall_wall_Concrete  wall_wall_Wood  \\\n",
              "count          127595.000000       127595.000000   127595.000000   \n",
              "mean                0.000259            0.000674        0.000415   \n",
              "std                 0.016080            0.025953        0.020377   \n",
              "min                 0.000000            0.000000        0.000000   \n",
              "25%                 0.000000            0.000000        0.000000   \n",
              "50%                 0.000000            0.000000        0.000000   \n",
              "75%                 0.000000            0.000000        0.000000   \n",
              "max                 1.000000            1.000000        1.000000   \n",
              "\n",
              "           temp_Cold      temp_Cool       temp_Hot     temp_Mixed  \\\n",
              "count  127595.000000  127595.000000  127595.000000  127595.000000   \n",
              "mean        0.001121       0.122011       0.354363       0.446742   \n",
              "std         0.033459       0.327300       0.478322       0.497157   \n",
              "min         0.000000       0.000000       0.000000       0.000000   \n",
              "25%         0.000000       0.000000       0.000000       0.000000   \n",
              "50%         0.000000       0.000000       0.000000       0.000000   \n",
              "75%         0.000000       0.000000       1.000000       1.000000   \n",
              "max         1.000000       1.000000       1.000000       1.000000   \n",
              "\n",
              "           temp_Warm    dryness_Dry  dryness_Humid  dryness_Marine  \n",
              "count  127595.000000  127595.000000  127595.000000   127595.000000  \n",
              "mean        0.072009       0.025808       0.835197        0.135240  \n",
              "std         0.258504       0.158563       0.371004        0.341982  \n",
              "min         0.000000       0.000000       0.000000        0.000000  \n",
              "25%         0.000000       0.000000       1.000000        0.000000  \n",
              "50%         0.000000       0.000000       1.000000        0.000000  \n",
              "75%         0.000000       0.000000       1.000000        0.000000  \n",
              "max         1.000000       1.000000       1.000000        1.000000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-83054e90-b076-41aa-9657-e382ab892f23\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>is_residential</th>\n",
              "      <th>floor_area</th>\n",
              "      <th>age</th>\n",
              "      <th>FT_Multifamily</th>\n",
              "      <th>FT_Industrial</th>\n",
              "      <th>FT_Office</th>\n",
              "      <th>FT_Retail</th>\n",
              "      <th>FT_Hotel</th>\n",
              "      <th>FT_Restaurant</th>\n",
              "      <th>FT_Grocery</th>\n",
              "      <th>FT_Hospital</th>\n",
              "      <th>FT_Data Center</th>\n",
              "      <th>FT_Singlefamily</th>\n",
              "      <th>WGL_Single-pane</th>\n",
              "      <th>WGL_Double-pane</th>\n",
              "      <th>WGT_Low-e</th>\n",
              "      <th>roof_Shingles</th>\n",
              "      <th>roof_Built-up</th>\n",
              "      <th>roof_Slate or tile shingles</th>\n",
              "      <th>roof_Metal surfacing</th>\n",
              "      <th>roof_Asphalt/fiberglass/other shingles</th>\n",
              "      <th>roof_Wood shingles/shakes/other wood</th>\n",
              "      <th>roof_Plastic/rubber/synthetic sheeting</th>\n",
              "      <th>roof_Green Roof</th>\n",
              "      <th>cool_Central AC</th>\n",
              "      <th>cool_No cooling</th>\n",
              "      <th>cool_Cooling_Heat Pump</th>\n",
              "      <th>cool_Split AC</th>\n",
              "      <th>heat_Boiler</th>\n",
              "      <th>heat_Resistance Heating</th>\n",
              "      <th>heat_Heating_Heat pump</th>\n",
              "      <th>heat_Heating_Furnace</th>\n",
              "      <th>wall_wall_Metal</th>\n",
              "      <th>wall_wall_Brick_stone</th>\n",
              "      <th>wall_wall_Concrete</th>\n",
              "      <th>wall_wall_Wood</th>\n",
              "      <th>temp_Cold</th>\n",
              "      <th>temp_Cool</th>\n",
              "      <th>temp_Hot</th>\n",
              "      <th>temp_Mixed</th>\n",
              "      <th>temp_Warm</th>\n",
              "      <th>dryness_Dry</th>\n",
              "      <th>dryness_Humid</th>\n",
              "      <th>dryness_Marine</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>127595.000000</td>\n",
              "      <td>1.275950e+05</td>\n",
              "      <td>124868.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.0</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "      <td>127595.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>0.675489</td>\n",
              "      <td>1.022971e+05</td>\n",
              "      <td>47.665166</td>\n",
              "      <td>0.000259</td>\n",
              "      <td>0.007257</td>\n",
              "      <td>0.005713</td>\n",
              "      <td>0.044242</td>\n",
              "      <td>0.320091</td>\n",
              "      <td>0.190015</td>\n",
              "      <td>0.011450</td>\n",
              "      <td>0.002359</td>\n",
              "      <td>0.037204</td>\n",
              "      <td>0.002680</td>\n",
              "      <td>0.001136</td>\n",
              "      <td>0.005627</td>\n",
              "      <td>0.000188</td>\n",
              "      <td>0.316384</td>\n",
              "      <td>0.016403</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.002273</td>\n",
              "      <td>0.000149</td>\n",
              "      <td>0.006999</td>\n",
              "      <td>0.000627</td>\n",
              "      <td>0.000031</td>\n",
              "      <td>0.323469</td>\n",
              "      <td>0.000031</td>\n",
              "      <td>0.000008</td>\n",
              "      <td>0.000016</td>\n",
              "      <td>0.000165</td>\n",
              "      <td>0.000024</td>\n",
              "      <td>0.000031</td>\n",
              "      <td>0.000024</td>\n",
              "      <td>0.000047</td>\n",
              "      <td>0.000259</td>\n",
              "      <td>0.000674</td>\n",
              "      <td>0.000415</td>\n",
              "      <td>0.001121</td>\n",
              "      <td>0.122011</td>\n",
              "      <td>0.354363</td>\n",
              "      <td>0.446742</td>\n",
              "      <td>0.072009</td>\n",
              "      <td>0.025808</td>\n",
              "      <td>0.835197</td>\n",
              "      <td>0.135240</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>0.468194</td>\n",
              "      <td>1.993315e+05</td>\n",
              "      <td>32.447077</td>\n",
              "      <td>0.016080</td>\n",
              "      <td>0.084881</td>\n",
              "      <td>0.075371</td>\n",
              "      <td>0.205632</td>\n",
              "      <td>0.466513</td>\n",
              "      <td>0.392315</td>\n",
              "      <td>0.106392</td>\n",
              "      <td>0.048513</td>\n",
              "      <td>0.189261</td>\n",
              "      <td>0.051703</td>\n",
              "      <td>0.033692</td>\n",
              "      <td>0.074803</td>\n",
              "      <td>0.013714</td>\n",
              "      <td>0.465066</td>\n",
              "      <td>0.127022</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.047620</td>\n",
              "      <td>0.012202</td>\n",
              "      <td>0.083365</td>\n",
              "      <td>0.025032</td>\n",
              "      <td>0.005599</td>\n",
              "      <td>0.467802</td>\n",
              "      <td>0.005599</td>\n",
              "      <td>0.002800</td>\n",
              "      <td>0.003959</td>\n",
              "      <td>0.012828</td>\n",
              "      <td>0.004849</td>\n",
              "      <td>0.005599</td>\n",
              "      <td>0.004849</td>\n",
              "      <td>0.006857</td>\n",
              "      <td>0.016080</td>\n",
              "      <td>0.025953</td>\n",
              "      <td>0.020377</td>\n",
              "      <td>0.033459</td>\n",
              "      <td>0.327300</td>\n",
              "      <td>0.478322</td>\n",
              "      <td>0.497157</td>\n",
              "      <td>0.258504</td>\n",
              "      <td>0.158563</td>\n",
              "      <td>0.371004</td>\n",
              "      <td>0.341982</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>5.000000e+02</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>2.110000e+03</td>\n",
              "      <td>21.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>5.294400e+04</td>\n",
              "      <td>41.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.114765e+05</td>\n",
              "      <td>72.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>6.385382e+06</td>\n",
              "      <td>367.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-83054e90-b076-41aa-9657-e382ab892f23')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-83054e90-b076-41aa-9657-e382ab892f23 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-83054e90-b076-41aa-9657-e382ab892f23');\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",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "lm_mh.isna().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fOOahxuhnXw5",
        "outputId": "ceba8bd2-c02b-4ce5-90e2-dd915126025c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "is_residential                               0\n",
              "floor_area                                   0\n",
              "age                                       2727\n",
              "FT_Multifamily                               0\n",
              "FT_Industrial                                0\n",
              "FT_Office                                    0\n",
              "FT_Retail                                    0\n",
              "FT_Hotel                                     0\n",
              "FT_Restaurant                                0\n",
              "FT_Grocery                                   0\n",
              "FT_Hospital                                  0\n",
              "FT_Data Center                               0\n",
              "FT_Singlefamily                              0\n",
              "WGL_Single-pane                              0\n",
              "WGL_Double-pane                              0\n",
              "WGT_Low-e                                    0\n",
              "roof_Shingles                                0\n",
              "roof_Built-up                                0\n",
              "roof_Slate or tile shingles                  0\n",
              "roof_Metal surfacing                         0\n",
              "roof_Asphalt/fiberglass/other shingles       0\n",
              "roof_Wood shingles/shakes/other wood         0\n",
              "roof_Plastic/rubber/synthetic sheeting       0\n",
              "roof_Green Roof                              0\n",
              "cool_Central AC                              0\n",
              "cool_No cooling                              0\n",
              "cool_Cooling_Heat Pump                       0\n",
              "cool_Split AC                                0\n",
              "heat_Boiler                                  0\n",
              "heat_Resistance Heating                      0\n",
              "heat_Heating_Heat pump                       0\n",
              "heat_Heating_Furnace                         0\n",
              "wall_wall_Metal                              0\n",
              "wall_wall_Brick_stone                        0\n",
              "wall_wall_Concrete                           0\n",
              "wall_wall_Wood                               0\n",
              "temp_Cold                                    0\n",
              "temp_Cool                                    0\n",
              "temp_Hot                                     0\n",
              "temp_Mixed                                   0\n",
              "temp_Warm                                    0\n",
              "dryness_Dry                                  0\n",
              "dryness_Humid                                0\n",
              "dryness_Marine                               0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "lm_mh"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 522
        },
        "id": "OJBCg4gMnl4Z",
        "outputId": "d5b7de9d-41d9-4aa6-db9c-1cec6e21248c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        is_residential  floor_area   age  FT_Multifamily  FT_Industrial  \\\n",
              "0                    1    160356.0   5.0               0              0   \n",
              "1                    1    160356.0   6.0               0              0   \n",
              "2                    1     51195.0  36.0               0              0   \n",
              "3                    1     51195.0  37.0               0              0   \n",
              "6                    1      5158.0  22.0               0              0   \n",
              "...                ...         ...   ...             ...            ...   \n",
              "296060               0     69230.0  57.0               0              0   \n",
              "296061               0     69230.0  58.0               0              0   \n",
              "296062               0     69230.0  59.0               0              0   \n",
              "296063               0     50163.0  56.0               0              0   \n",
              "296064               0     50163.0  57.0               0              0   \n",
              "\n",
              "        FT_Office  FT_Retail  FT_Hotel  FT_Restaurant  FT_Grocery  \\\n",
              "0               0          0         1              0           0   \n",
              "1               0          0         1              0           0   \n",
              "2               0          0         1              0           0   \n",
              "3               0          0         1              0           0   \n",
              "6               0          0         1              0           0   \n",
              "...           ...        ...       ...            ...         ...   \n",
              "296060          0          0         0              1           0   \n",
              "296061          0          0         0              1           0   \n",
              "296062          0          0         0              1           0   \n",
              "296063          0          0         0              1           0   \n",
              "296064          0          0         0              1           0   \n",
              "\n",
              "        FT_Hospital  FT_Data Center  FT_Singlefamily  WGL_Single-pane  \\\n",
              "0                 0               0                0                0   \n",
              "1                 0               0                0                0   \n",
              "2                 0               0                0                0   \n",
              "3                 0               0                0                0   \n",
              "6                 0               0                0                1   \n",
              "...             ...             ...              ...              ...   \n",
              "296060            0               0                0                0   \n",
              "296061            0               0                0                0   \n",
              "296062            0               0                0                0   \n",
              "296063            0               0                0                0   \n",
              "296064            0               0                0                0   \n",
              "\n",
              "        WGL_Double-pane  WGT_Low-e  roof_Shingles  roof_Built-up  \\\n",
              "0                     0          0              0              0   \n",
              "1                     0          0              0              0   \n",
              "2                     1          0              0              0   \n",
              "3                     1          0              0              0   \n",
              "6                     0          0              0              0   \n",
              "...                 ...        ...            ...            ...   \n",
              "296060                0          0              0              0   \n",
              "296061                0          0              0              0   \n",
              "296062                0          0              0              0   \n",
              "296063                0          0              0              0   \n",
              "296064                0          0              0              0   \n",
              "\n",
              "        roof_Slate or tile shingles  roof_Metal surfacing  \\\n",
              "0                                 0                     0   \n",
              "1                                 0                     0   \n",
              "2                                 0                     0   \n",
              "3                                 0                     0   \n",
              "6                                 0                     0   \n",
              "...                             ...                   ...   \n",
              "296060                            0                     0   \n",
              "296061                            0                     0   \n",
              "296062                            0                     0   \n",
              "296063                            0                     0   \n",
              "296064                            0                     0   \n",
              "\n",
              "        roof_Asphalt/fiberglass/other shingles  \\\n",
              "0                                            0   \n",
              "1                                            0   \n",
              "2                                            0   \n",
              "3                                            0   \n",
              "6                                            0   \n",
              "...                                        ...   \n",
              "296060                                       0   \n",
              "296061                                       0   \n",
              "296062                                       0   \n",
              "296063                                       0   \n",
              "296064                                       0   \n",
              "\n",
              "        roof_Wood shingles/shakes/other wood  \\\n",
              "0                                          0   \n",
              "1                                          0   \n",
              "2                                          1   \n",
              "3                                          1   \n",
              "6                                          1   \n",
              "...                                      ...   \n",
              "296060                                     0   \n",
              "296061                                     0   \n",
              "296062                                     0   \n",
              "296063                                     0   \n",
              "296064                                     0   \n",
              "\n",
              "        roof_Plastic/rubber/synthetic sheeting  roof_Green Roof  \\\n",
              "0                                            0                0   \n",
              "1                                            0                0   \n",
              "2                                            0                0   \n",
              "3                                            0                0   \n",
              "6                                            0                0   \n",
              "...                                        ...              ...   \n",
              "296060                                       0                0   \n",
              "296061                                       0                0   \n",
              "296062                                       0                0   \n",
              "296063                                       0                0   \n",
              "296064                                       0                0   \n",
              "\n",
              "        cool_Central AC  cool_No cooling  cool_Cooling_Heat Pump  \\\n",
              "0                     0                0                       0   \n",
              "1                     0                0                       0   \n",
              "2                     0                0                       0   \n",
              "3                     0                0                       0   \n",
              "6                     0                0                       0   \n",
              "...                 ...              ...                     ...   \n",
              "296060                0                0                       0   \n",
              "296061                0                0                       0   \n",
              "296062                0                0                       0   \n",
              "296063                0                0                       0   \n",
              "296064                0                0                       0   \n",
              "\n",
              "        cool_Split AC  heat_Boiler  heat_Resistance Heating  \\\n",
              "0                   0            0                        0   \n",
              "1                   0            0                        0   \n",
              "2                   0            0                        0   \n",
              "3                   0            0                        0   \n",
              "6                   0            0                        0   \n",
              "...               ...          ...                      ...   \n",
              "296060              0            0                        0   \n",
              "296061              0            0                        0   \n",
              "296062              0            0                        0   \n",
              "296063              0            0                        0   \n",
              "296064              0            0                        0   \n",
              "\n",
              "        heat_Heating_Heat pump  heat_Heating_Furnace  wall_wall_Metal  \\\n",
              "0                            0                     0                0   \n",
              "1                            0                     0                0   \n",
              "2                            0                     0                0   \n",
              "3                            0                     0                0   \n",
              "6                            0                     0                0   \n",
              "...                        ...                   ...              ...   \n",
              "296060                       0                     0                0   \n",
              "296061                       0                     0                0   \n",
              "296062                       0                     0                0   \n",
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              "[127595 rows x 44 columns]"
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>296064</th>\n",
              "      <td>0</td>\n",
              "      <td>50163.0</td>\n",
              "      <td>57.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>127595 rows × 44 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5080a48a-25fa-4961-99d2-4f8807a1c91e')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-5080a48a-25fa-4961-99d2-4f8807a1c91e button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-5080a48a-25fa-4961-99d2-4f8807a1c91e');\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": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Deal with NANs\n",
        "print(\"Rows:\", lm_mh.shape[0])\n",
        "missing = lm_mh.isna().any(axis=1)\n",
        "print(\"Rows with missing values:\", missing.sum())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hqwIgulGa-o0",
        "outputId": "1a412dea-1bfd-4048-d79e-6f590f6a36e4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Rows: 127595\n",
            "Rows with missing values: 2727\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"Missing values by column:\")\n",
        "for col in lm_mh.columns:\n",
        "    nas = lm_mh[col].isnull().sum()\n",
        "    if nas != 0:\n",
        "        print(col, nas)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "W6oMDONajYfP",
        "outputId": "21662a70-6871-43d3-e994-4b5475303e51"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Missing values by column:\n",
            "age 2727\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "lm_mh = lm_mh[~missing]\n",
        "lm_mh_y = y[~missing]\n",
        "print(\"Final size:\", lm_mh.shape[0])\n",
        "pd.concat([lm_mh, lm_mh_y], axis=1).sample(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 323
        },
        "id": "3dQeMULvjH91",
        "outputId": "1311d855-0b6d-495a-b6b3-9df709b5f39b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final size: 124868\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        is_residential  floor_area   age  FT_Multifamily  FT_Industrial  \\\n",
              "123874               1      2312.0  36.0               0              0   \n",
              "174961               1      1392.0  35.0               0              0   \n",
              "84783                1      2256.0  42.0               0              0   \n",
              "85829                1      1052.0  33.0               0              0   \n",
              "234922               1    128160.0  60.0               0              0   \n",
              "\n",
              "        FT_Office  FT_Retail  FT_Hotel  FT_Restaurant  FT_Grocery  \\\n",
              "123874          0          0         0              0           0   \n",
              "174961          0          0         0              0           0   \n",
              "84783           0          0         0              0           0   \n",
              "85829           0          0         0              0           0   \n",
              "234922          0          0         1              0           0   \n",
              "\n",
              "        FT_Hospital  FT_Data Center  FT_Singlefamily  WGL_Single-pane  \\\n",
              "123874            0               0                0                0   \n",
              "174961            0               0                0                0   \n",
              "84783             0               0                0                0   \n",
              "85829             0               0                0                0   \n",
              "234922            0               0                0                0   \n",
              "\n",
              "        WGL_Double-pane  WGT_Low-e  roof_Shingles  roof_Built-up  \\\n",
              "123874                0          0              1              0   \n",
              "174961                0          0              1              0   \n",
              "84783                 0          0              0              1   \n",
              "85829                 0          0              1              0   \n",
              "234922                0          0              0              0   \n",
              "\n",
              "        roof_Slate or tile shingles  roof_Metal surfacing  \\\n",
              "123874                            0                     0   \n",
              "174961                            0                     0   \n",
              "84783                             0                     0   \n",
              "85829                             0                     0   \n",
              "234922                            0                     0   \n",
              "\n",
              "        roof_Asphalt/fiberglass/other shingles  \\\n",
              "123874                                       0   \n",
              "174961                                       0   \n",
              "84783                                        0   \n",
              "85829                                        0   \n",
              "234922                                       0   \n",
              "\n",
              "        roof_Wood shingles/shakes/other wood  \\\n",
              "123874                                     0   \n",
              "174961                                     0   \n",
              "84783                                      0   \n",
              "85829                                      0   \n",
              "234922                                     0   \n",
              "\n",
              "        roof_Plastic/rubber/synthetic sheeting  roof_Green Roof  \\\n",
              "123874                                       0                0   \n",
              "174961                                       0                0   \n",
              "84783                                        0                0   \n",
              "85829                                        0                0   \n",
              "234922                                       0                0   \n",
              "\n",
              "        cool_Central AC  cool_No cooling  cool_Cooling_Heat Pump  \\\n",
              "123874                1                0                       0   \n",
              "174961                1                0                       0   \n",
              "84783                 1                0                       0   \n",
              "85829                 1                0                       0   \n",
              "234922                0                0                       0   \n",
              "\n",
              "        cool_Split AC  heat_Boiler  heat_Resistance Heating  \\\n",
              "123874              0            0                        0   \n",
              "174961              0            0                        0   \n",
              "84783               0            0                        0   \n",
              "85829               0            0                        0   \n",
              "234922              0            0                        0   \n",
              "\n",
              "        heat_Heating_Heat pump  heat_Heating_Furnace  wall_wall_Metal  \\\n",
              "123874                       0                     0                0   \n",
              "174961                       0                     0                0   \n",
              "84783                        0                     0                0   \n",
              "85829                        0                     0                0   \n",
              "234922                       0                     0                0   \n",
              "\n",
              "        wall_wall_Brick_stone  wall_wall_Concrete  wall_wall_Wood  temp_Cold  \\\n",
              "123874                      0                   0               0          0   \n",
              "174961                      0                   0               0          0   \n",
              "84783                       0                   0               0          0   \n",
              "85829                       0                   0               0          0   \n",
              "234922                      0                   0               0          0   \n",
              "\n",
              "        temp_Cool  temp_Hot  temp_Mixed  temp_Warm  dryness_Dry  \\\n",
              "123874          0         1           0          0            0   \n",
              "174961          0         1           0          0            0   \n",
              "84783           0         1           0          0            0   \n",
              "85829           0         1           0          0            0   \n",
              "234922          0         0           1          0            0   \n",
              "\n",
              "        dryness_Humid  dryness_Marine   site_eui  \n",
              "123874              1               0  34.452903  \n",
              "174961              1               0  26.732995  \n",
              "84783               1               0  46.032024  \n",
              "85829               1               0  54.073972  \n",
              "234922              1               0  75.991803  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5c88f07f-22a5-4697-8aa1-4bc3b8efbf02\">\n",
              "    <div class=\"colab-df-container\">\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "    }\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>is_residential</th>\n",
              "      <th>floor_area</th>\n",
              "      <th>age</th>\n",
              "      <th>FT_Multifamily</th>\n",
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              "      <th>FT_Singlefamily</th>\n",
              "      <th>WGL_Single-pane</th>\n",
              "      <th>WGL_Double-pane</th>\n",
              "      <th>WGT_Low-e</th>\n",
              "      <th>roof_Shingles</th>\n",
              "      <th>roof_Built-up</th>\n",
              "      <th>roof_Slate or tile shingles</th>\n",
              "      <th>roof_Metal surfacing</th>\n",
              "      <th>roof_Asphalt/fiberglass/other shingles</th>\n",
              "      <th>roof_Wood shingles/shakes/other wood</th>\n",
              "      <th>roof_Plastic/rubber/synthetic sheeting</th>\n",
              "      <th>roof_Green Roof</th>\n",
              "      <th>cool_Central AC</th>\n",
              "      <th>cool_No cooling</th>\n",
              "      <th>cool_Cooling_Heat Pump</th>\n",
              "      <th>cool_Split AC</th>\n",
              "      <th>heat_Boiler</th>\n",
              "      <th>heat_Resistance Heating</th>\n",
              "      <th>heat_Heating_Heat pump</th>\n",
              "      <th>heat_Heating_Furnace</th>\n",
              "      <th>wall_wall_Metal</th>\n",
              "      <th>wall_wall_Brick_stone</th>\n",
              "      <th>wall_wall_Concrete</th>\n",
              "      <th>wall_wall_Wood</th>\n",
              "      <th>temp_Cold</th>\n",
              "      <th>temp_Cool</th>\n",
              "      <th>temp_Hot</th>\n",
              "      <th>temp_Mixed</th>\n",
              "      <th>temp_Warm</th>\n",
              "      <th>dryness_Dry</th>\n",
              "      <th>dryness_Humid</th>\n",
              "      <th>dryness_Marine</th>\n",
              "      <th>site_eui</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>46.032024</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>85829</th>\n",
              "      <td>1</td>\n",
              "      <td>1052.0</td>\n",
              "      <td>33.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>54.073972</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>234922</th>\n",
              "      <td>1</td>\n",
              "      <td>128160.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>75.991803</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5c88f07f-22a5-4697-8aa1-4bc3b8efbf02')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-5c88f07f-22a5-4697-8aa1-4bc3b8efbf02 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-5c88f07f-22a5-4697-8aa1-4bc3b8efbf02');\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": 40
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Fit model"
      ],
      "metadata": {
        "id": "D_dTbXWGbPy6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "mh_model, mh_history = linear_model(\n",
        "    lm_mh, lm_mh_y, \n",
        "    num_features=lm_mh.shape[1],\n",
        "    batch=10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5DpXN4I3a-lX",
        "outputId": "ff404265-09cb-48cd-bbe5-46780b11bf18"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " dense (Dense)               (None, 1)                 45        \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 45\n",
            "Trainable params: 45\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "Epoch 1/15\n",
            "9366/9366 [==============================] - 16s 2ms/step - loss: 23775828.0000 - MAE: 500.1418 - MAPE: 1088.3533 - val_loss: 4832.8667 - val_MAE: 40.5390 - val_MAPE: 72.5917\n",
            "Epoch 2/15\n",
            "9366/9366 [==============================] - 18s 2ms/step - loss: 34841.4727 - MAE: 54.5358 - MAPE: 126.4630 - val_loss: 5203.0532 - val_MAE: 44.8090 - val_MAPE: 83.9225\n",
            "Epoch 3/15\n",
            "9366/9366 [==============================] - 15s 2ms/step - loss: 22129.8398 - MAE: 47.9527 - MAPE: 118.1991 - val_loss: 5107.5991 - val_MAE: 43.2429 - val_MAPE: 98.1967\n",
            "Epoch 4/15\n",
            "9366/9366 [==============================] - 15s 2ms/step - loss: 27224.2598 - MAE: 51.0509 - MAPE: 124.7097 - val_loss: 6003.6538 - val_MAE: 47.9021 - val_MAPE: 114.2218\n",
            "Epoch 5/15\n",
            "9366/9366 [==============================] - 15s 2ms/step - loss: 39896.2148 - MAE: 47.3132 - MAPE: 116.5407 - val_loss: 4326.9229 - val_MAE: 37.6663 - val_MAPE: 80.0940\n",
            "Epoch 6/15\n",
            "9366/9366 [==============================] - 17s 2ms/step - loss: 28156.6934 - MAE: 45.3846 - MAPE: 111.2304 - val_loss: 5033.6016 - val_MAE: 43.8657 - val_MAPE: 105.1975\n",
            "Epoch 7/15\n",
            "9366/9366 [==============================] - 15s 2ms/step - loss: 18513.6465 - MAE: 46.8192 - MAPE: 113.1816 - val_loss: 4250.9297 - val_MAE: 38.0973 - val_MAPE: 87.1321\n",
            "Epoch 8/15\n",
            "9366/9366 [==============================] - 15s 2ms/step - loss: 19717.8594 - MAE: 48.6446 - MAPE: 120.1200 - val_loss: 4183.6484 - val_MAE: 35.4854 - val_MAPE: 71.5085\n",
            "Epoch 9/15\n",
            "9366/9366 [==============================] - 15s 2ms/step - loss: 33906.8789 - MAE: 49.6001 - MAPE: 120.9685 - val_loss: 4060.9385 - val_MAE: 36.6600 - val_MAPE: 84.7028\n",
            "Epoch 10/15\n",
            "9366/9366 [==============================] - 24s 3ms/step - loss: 21250.2344 - MAE: 43.8924 - MAPE: 109.8904 - val_loss: 5847.7910 - val_MAE: 48.1673 - val_MAPE: 119.7234\n",
            "Epoch 11/15\n",
            "9366/9366 [==============================] - 17s 2ms/step - loss: 23340.0039 - MAE: 45.7508 - MAPE: 114.3525 - val_loss: 5401.2754 - val_MAE: 43.5998 - val_MAPE: 80.3660\n",
            "Epoch 12/15\n",
            "9366/9366 [==============================] - 15s 2ms/step - loss: 21028.6074 - MAE: 43.0703 - MAPE: 110.2841 - val_loss: 4070.4006 - val_MAE: 37.3614 - val_MAPE: 88.9455\n",
            "Epoch 13/15\n",
            "9366/9366 [==============================] - 15s 2ms/step - loss: 35664.5742 - MAE: 45.4681 - MAPE: 112.8294 - val_loss: 246555.5000 - val_MAE: 304.0724 - val_MAPE: 607.6373\n",
            "Epoch 14/15\n",
            "9366/9366 [==============================] - 15s 2ms/step - loss: 36513.0469 - MAE: 42.6581 - MAPE: 111.3856 - val_loss: 3884.8879 - val_MAE: 33.0557 - val_MAPE: 69.2596\n",
            "Epoch 15/15\n",
            "9366/9366 [==============================] - 15s 2ms/step - loss: 35010.1406 - MAE: 47.0854 - MAPE: 117.1740 - val_loss: 3766.3481 - val_MAE: 34.7889 - val_MAPE: 83.5004\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "linear_plot(lm_mh, mh_model, mh_history)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "KtMShATga-iX",
        "outputId": "a5b587dc-a623-4bb5-c99c-87aafc0ed470"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x400 with 3 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final val loss: 3766.35\n",
            "Final val mean absolute error: 34.79\n",
            "Final val mean absolute percentage error: 83.5\n",
            "Final bias: 13.3\n",
            "is_residential 5.24\n",
            "floor_area 0.0\n",
            "age 0.42\n",
            "FT_Multifamily 4.88\n",
            "FT_Industrial 27.16\n",
            "FT_Office 11.72\n",
            "FT_Retail 14.07\n",
            "FT_Hotel 5.97\n",
            "FT_Restaurant 5.23\n",
            "FT_Grocery 16.91\n",
            "FT_Hospital 12.92\n",
            "FT_Data Center 9.59\n",
            "FT_Singlefamily 5.29\n",
            "WGL_Single-pane -1.64\n",
            "WGL_Double-pane -6.6\n",
            "WGT_Low-e -2.02\n",
            "roof_Shingles 0.33\n",
            "roof_Built-up -5.14\n",
            "roof_Slate or tile shingles 0.24\n",
            "roof_Metal surfacing -0.58\n",
            "roof_Asphalt/fiberglass/other shingles 1.2\n",
            "roof_Wood shingles/shakes/other wood -2.08\n",
            "roof_Plastic/rubber/synthetic sheeting -1.89\n",
            "roof_Green Roof -1.27\n",
            "cool_Central AC -0.88\n",
            "cool_No cooling 0.21\n",
            "cool_Cooling_Heat Pump 0.29\n",
            "cool_Split AC -0.15\n",
            "heat_Boiler 0.23\n",
            "heat_Resistance Heating 0.73\n",
            "heat_Heating_Heat pump 0.1\n",
            "heat_Heating_Furnace 0.87\n",
            "wall_wall_Metal -0.78\n",
            "wall_wall_Brick_stone 2.6\n",
            "wall_wall_Concrete -0.01\n",
            "wall_wall_Wood -0.11\n",
            "temp_Cold 3.89\n",
            "temp_Cool 14.92\n",
            "temp_Hot -4.97\n",
            "temp_Mixed 10.56\n",
            "temp_Warm 3.03\n",
            "dryness_Dry 6.08\n",
            "dryness_Humid 13.97\n",
            "dryness_Marine -0.72\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Linear Model - normalized"
      ],
      "metadata": {
        "id": "DsyQgVnkbSfg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "lm_mh.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6euMXZIVu3LH",
        "outputId": "709ceec8-3f6c-4cea-c327-0b3f411db31e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(124868, 44)"
            ]
          },
          "metadata": {},
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Fit model\n",
        "learning_rate=0.001"
      ],
      "metadata": {
        "id": "gbYII6vJxIBB"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "mh_norm_model, mh_norm_history = linear_model(\n",
        "    lm_mh, lm_mh_y, \n",
        "    num_features=lm_mh.shape[1],\n",
        "    normalize=True,\n",
        "    batch=10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qqrlLcjTvAYW",
        "outputId": "8a17149e-9910-4b4e-d09c-e7108c439b30"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " normalization (Normalizatio  (None, 44)               89        \n",
            " n)                                                              \n",
            "                                                                 \n",
            " dense (Dense)               (None, 1)                 45        \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 134\n",
            "Trainable params: 45\n",
            "Non-trainable params: 89\n",
            "_________________________________________________________________\n",
            "None\n",
            "Epoch 1/15\n",
            "9366/9366 [==============================] - 17s 2ms/step - loss: 6375.0869 - MAE: 60.4408 - MAPE: 100.3607 - val_loss: 6634.2314 - val_MAE: 56.4846 - val_MAPE: 81.3593\n",
            "Epoch 2/15\n",
            "9366/9366 [==============================] - 17s 2ms/step - loss: 5091.8149 - MAE: 52.5786 - MAPE: 96.9700 - val_loss: 5904.9458 - val_MAE: 50.7050 - val_MAPE: 77.6413\n",
            "Epoch 3/15\n",
            "9366/9366 [==============================] - 17s 2ms/step - loss: 4169.0928 - MAE: 45.0469 - MAPE: 88.3266 - val_loss: 5206.0864 - val_MAE: 44.7807 - val_MAPE: 71.8708\n",
            "Epoch 4/15\n",
            "9366/9366 [==============================] - 16s 2ms/step - loss: 3462.6387 - MAE: 38.3785 - MAPE: 80.5620 - val_loss: 4552.4570 - val_MAE: 39.2605 - val_MAPE: 67.1055\n",
            "Epoch 5/15\n",
            "9366/9366 [==============================] - 17s 2ms/step - loss: 2938.5298 - MAE: 32.7543 - MAPE: 74.8623 - val_loss: 3992.8369 - val_MAE: 34.7558 - val_MAPE: 65.0312\n",
            "Epoch 6/15\n",
            "9366/9366 [==============================] - 16s 2ms/step - loss: 2582.3091 - MAE: 28.5119 - MAPE: 72.4597 - val_loss: 3603.3452 - val_MAE: 31.8588 - val_MAPE: 65.6885\n",
            "Epoch 7/15\n",
            "9366/9366 [==============================] - 16s 2ms/step - loss: 2366.0945 - MAE: 25.8887 - MAPE: 73.3071 - val_loss: 3377.4661 - val_MAE: 30.6952 - val_MAPE: 69.5322\n",
            "Epoch 8/15\n",
            "9366/9366 [==============================] - 16s 2ms/step - loss: 2258.3855 - MAE: 24.8503 - MAPE: 76.4201 - val_loss: 3268.8184 - val_MAE: 30.8576 - val_MAPE: 75.1121\n",
            "Epoch 9/15\n",
            "9366/9366 [==============================] - 16s 2ms/step - loss: 2213.0835 - MAE: 24.6644 - MAPE: 79.6550 - val_loss: 3228.9905 - val_MAE: 31.4508 - val_MAPE: 79.7067\n",
            "Epoch 10/15\n",
            "9366/9366 [==============================] - 16s 2ms/step - loss: 2193.9910 - MAE: 24.7255 - MAPE: 81.7194 - val_loss: 3211.5752 - val_MAE: 31.9034 - val_MAPE: 82.5763\n",
            "Epoch 11/15\n",
            "9366/9366 [==============================] - 16s 2ms/step - loss: 2184.2820 - MAE: 24.7786 - MAPE: 82.7436 - val_loss: 3204.1331 - val_MAE: 32.2642 - val_MAPE: 84.5228\n",
            "Epoch 12/15\n",
            "9366/9366 [==============================] - 16s 2ms/step - loss: 2178.2327 - MAE: 24.8302 - MAPE: 83.3034 - val_loss: 3195.3083 - val_MAE: 32.3976 - val_MAPE: 85.3447\n",
            "Epoch 13/15\n",
            "9366/9366 [==============================] - 16s 2ms/step - loss: 2173.4021 - MAE: 24.8236 - MAPE: 83.3698 - val_loss: 3193.0042 - val_MAE: 32.5426 - val_MAPE: 85.9687\n",
            "Epoch 14/15\n",
            "9366/9366 [==============================] - 16s 2ms/step - loss: 2169.5300 - MAE: 24.8275 - MAPE: 83.4029 - val_loss: 3191.3162 - val_MAE: 32.6466 - val_MAPE: 86.3691\n",
            "Epoch 15/15\n",
            "9366/9366 [==============================] - 16s 2ms/step - loss: 2166.0935 - MAE: 24.8289 - MAPE: 83.3850 - val_loss: 3186.9941 - val_MAE: 32.6250 - val_MAPE: 86.2118\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "linear_plot(lm_mh, mh_norm_model, mh_norm_history,\n",
        "            loss_ylim=10_000, mae_ylim=100, mape_ylim=125)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "mOl2zi-Jw31H",
        "outputId": "19beebbf-2772-437b-a328-962975b6f02b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x400 with 3 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final val loss: 3186.99\n",
            "Final val mean absolute error: 32.62\n",
            "Final val mean absolute percentage error: 86.21\n",
            "Final bias: 0.22\n",
            "is_residential 0.686\n",
            "floor_area 101674.2656\n",
            "age 47.6652\n",
            "FT_Multifamily 0.0003\n",
            "FT_Industrial 0.0073\n",
            "FT_Office 0.0056\n",
            "FT_Retail 0.0442\n",
            "FT_Hotel 0.3233\n",
            "FT_Restaurant 0.1804\n",
            "FT_Grocery 0.0113\n",
            "FT_Hospital 0.0024\n",
            "FT_Data Center 0.037\n",
            "FT_Singlefamily 0.0027\n",
            "WGL_Single-pane 0.0012\n",
            "WGL_Double-pane 0.0058\n",
            "WGT_Low-e 0.0002\n",
            "roof_Shingles 0.3233\n",
            "roof_Built-up 0.0168\n",
            "roof_Slate or tile shingles 0.0\n",
            "roof_Metal surfacing 0.0023\n",
            "roof_Asphalt/fiberglass/other shingles 0.0002\n",
            "roof_Wood shingles/shakes/other wood 0.0071\n",
            "roof_Plastic/rubber/synthetic sheeting 0.0006\n",
            "roof_Green Roof 0.0\n",
            "cool_Central AC 0.3305\n",
            "cool_No cooling 0.0\n",
            "cool_Cooling_Heat Pump 0.0\n",
            "cool_Split AC 0.0\n",
            "heat_Boiler 0.0002\n",
            "heat_Resistance Heating 0.0\n",
            "heat_Heating_Heat pump 0.0\n",
            "heat_Heating_Furnace 0.0\n",
            "wall_wall_Metal 0.0\n",
            "wall_wall_Brick_stone 0.0003\n",
            "wall_wall_Concrete 0.0007\n",
            "wall_wall_Wood 0.0004\n",
            "temp_Cold 0.0011\n",
            "temp_Cool 0.1233\n",
            "temp_Hot 0.3618\n",
            "temp_Mixed 0.4504\n",
            "temp_Warm 0.0599\n",
            "dryness_Dry 0.0187\n",
            "dryness_Humid 0.8471\n",
            "dryness_Marine 0.1308\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "-XjezAUJxDFQ"
      },
      "execution_count": null,
      "outputs": []
    }
  ],
  "metadata": {
    "colab": {
      "name": "Ben_linear_model.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    },
    "gpuClass": "standard"
  },
  "nbformat": 4,
  "nbformat_minor": 0
}