BlueBook.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Copy of Copy of Project/Bulldozers.ipynb",
      "provenance": [],
      "collapsed_sections": [
        "Mu3kL6ZHYVp4"
      ]
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fZeB7imLthn8",
        "outputId": "3358f01e-2180-4554-99c3-bca05dde6706"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 2,
      "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",
      "metadata": {
        "id": "aFB-5v9f0__J"
      },
      "source": [
        "import pandas as pd\n",
        "import re, os\n",
        "import numpy as np\n",
        "from pathlib import Path\n",
        "from sklearn.ensemble import RandomForestRegressor, _forest\n",
        "from google.colab import data_table\n",
        "import matplotlib.pyplot as plt\n",
        "import plotly.express as px\n",
        "import plotly.graph_objects as go\n",
        "\n",
        "%matplotlib inline\n"
      ],
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NSHI1pirN2Dg"
      },
      "source": [
        "def flexible_display(df):\n",
        "  with pd.option_context(\"display.max_columns\", 500, \"display.max_rows\", 500):\n",
        "    display(df)"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WX0hCc_41Ecr"
      },
      "source": [
        "path = Path('/content/drive/MyDrive/DATA/bulldozers/Train.csv')"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xxb56wV906Iz",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "40e8cc3d-0a4e-4baf-ce87-1b921087bcd6"
      },
      "source": [
        "df_raw = pd.read_csv(f'{path}', low_memory=False, parse_dates=['saledate']);\n",
        "len(df_raw)"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "401125"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PQYoNwL33Apx",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4e2e689f-b9fa-40b0-d7dd-7a69373925a1"
      },
      "source": [
        "df_raw.info(memory_usage='deep', verbose=True)"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 401125 entries, 0 to 401124\n",
            "Data columns (total 53 columns):\n",
            " #   Column                    Non-Null Count   Dtype         \n",
            "---  ------                    --------------   -----         \n",
            " 0   SalesID                   401125 non-null  int64         \n",
            " 1   SalePrice                 401125 non-null  int64         \n",
            " 2   MachineID                 401125 non-null  int64         \n",
            " 3   ModelID                   401125 non-null  int64         \n",
            " 4   datasource                401125 non-null  int64         \n",
            " 5   auctioneerID              380989 non-null  float64       \n",
            " 6   YearMade                  401125 non-null  int64         \n",
            " 7   MachineHoursCurrentMeter  142765 non-null  float64       \n",
            " 8   UsageBand                 69639 non-null   object        \n",
            " 9   saledate                  401125 non-null  datetime64[ns]\n",
            " 10  fiModelDesc               401125 non-null  object        \n",
            " 11  fiBaseModel               401125 non-null  object        \n",
            " 12  fiSecondaryDesc           263934 non-null  object        \n",
            " 13  fiModelSeries             56908 non-null   object        \n",
            " 14  fiModelDescriptor         71919 non-null   object        \n",
            " 15  ProductSize               190350 non-null  object        \n",
            " 16  fiProductClassDesc        401125 non-null  object        \n",
            " 17  state                     401125 non-null  object        \n",
            " 18  ProductGroup              401125 non-null  object        \n",
            " 19  ProductGroupDesc          401125 non-null  object        \n",
            " 20  Drive_System              104361 non-null  object        \n",
            " 21  Enclosure                 400800 non-null  object        \n",
            " 22  Forks                     192077 non-null  object        \n",
            " 23  Pad_Type                  79134 non-null   object        \n",
            " 24  Ride_Control              148606 non-null  object        \n",
            " 25  Stick                     79134 non-null   object        \n",
            " 26  Transmission              183230 non-null  object        \n",
            " 27  Turbocharged              79134 non-null   object        \n",
            " 28  Blade_Extension           25219 non-null   object        \n",
            " 29  Blade_Width               25219 non-null   object        \n",
            " 30  Enclosure_Type            25219 non-null   object        \n",
            " 31  Engine_Horsepower         25219 non-null   object        \n",
            " 32  Hydraulics                320570 non-null  object        \n",
            " 33  Pushblock                 25219 non-null   object        \n",
            " 34  Ripper                    104137 non-null  object        \n",
            " 35  Scarifier                 25230 non-null   object        \n",
            " 36  Tip_Control               25219 non-null   object        \n",
            " 37  Tire_Size                 94718 non-null   object        \n",
            " 38  Coupler                   213952 non-null  object        \n",
            " 39  Coupler_System            43458 non-null   object        \n",
            " 40  Grouser_Tracks            43362 non-null   object        \n",
            " 41  Hydraulics_Flow           43362 non-null   object        \n",
            " 42  Track_Type                99153 non-null   object        \n",
            " 43  Undercarriage_Pad_Width   99872 non-null   object        \n",
            " 44  Stick_Length              99218 non-null   object        \n",
            " 45  Thumb                     99288 non-null   object        \n",
            " 46  Pattern_Changer           99218 non-null   object        \n",
            " 47  Grouser_Type              99153 non-null   object        \n",
            " 48  Backhoe_Mounting          78672 non-null   object        \n",
            " 49  Blade_Type                79833 non-null   object        \n",
            " 50  Travel_Controls           79834 non-null   object        \n",
            " 51  Differential_Type         69411 non-null   object        \n",
            " 52  Steering_Controls         69369 non-null   object        \n",
            "dtypes: datetime64[ns](1), float64(2), int64(6), object(44)\n",
            "memory usage: 789.7 MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2ie0gAjP4HnF",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "fcbb9624-0f65-47a2-83b7-3bb6b27eac79"
      },
      "source": [
        "df_raw.SalePrice = np.log(df_raw.SalePrice);\n",
        "df_raw.SalePrice"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0         11.097410\n",
              "1         10.950807\n",
              "2          9.210340\n",
              "3         10.558414\n",
              "4          9.305651\n",
              "            ...    \n",
              "401120     9.259131\n",
              "401121     9.305651\n",
              "401122     9.350102\n",
              "401123     9.104980\n",
              "401124     8.955448\n",
              "Name: SalePrice, Length: 401125, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9ljuEbtBLpfj",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "418cebe5-0d82-433b-f525-e1b76e625c75"
      },
      "source": [
        "last_date = df_raw.saledate.max()\n",
        "first_date = df_raw.saledate.min()\n",
        "days_of_week = df_raw.saledate.dt.day_name().unique()\n",
        "number_of_days = last_date - first_date\n",
        "\n",
        "last_date, first_date, days_of_week, number_of_days"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(Timestamp('2011-12-30 00:00:00'),\n",
              " Timestamp('1989-01-17 00:00:00'),\n",
              " array(['Thursday', 'Friday', 'Tuesday', 'Wednesday', 'Monday', 'Sunday',\n",
              "        'Saturday'], dtype=object),\n",
              " Timedelta('8382 days 00:00:00'))"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nvNVj_xqJ4aI"
      },
      "source": [
        "## Convert Objects to Category Data Type"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ssT7xRcKKEJ-"
      },
      "source": [
        "def categorify(df):\n",
        "  for cols in df.columns:\n",
        "    if pd.api.types.is_string_dtype(df[cols]):\n",
        "      df[cols] = pd.Categorical(df[cols], ordered=True)\n",
        "\n",
        "categorify(df_raw)"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hLSBFjYiUVXT",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3ab21d87-c7da-4c0f-8063-b0f12034c335"
      },
      "source": [
        "df_raw.UsageBand.cat.set_categories([\"Low\", \"Medium\", \"High\"], ordered=True, inplace=True);\n",
        "# df_raw.ProductSize.cat.set_categories(['Small', 'Mini', 'Medium', 'Large / Medium', 'Large', 'Compact'], ordered=True, inplace=True)\n",
        "df_raw.UsageBand'\n",
        "# df_raw.ProductSize"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0            Low\n",
              "1            Low\n",
              "2           High\n",
              "3           High\n",
              "4         Medium\n",
              "           ...  \n",
              "401120       NaN\n",
              "401121       NaN\n",
              "401122       NaN\n",
              "401123       NaN\n",
              "401124       NaN\n",
              "Name: UsageBand, Length: 401125, dtype: category\n",
              "Categories (3, object): ['Low' < 'Medium' < 'High']"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AMmq-OnUUVPP",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 954
        },
        "outputId": "31462231-c048-489e-b9d7-90e5a83d789c"
      },
      "source": [
        "flexible_display(df_raw.isnull().sum().sort_values(ascending=False) / len(df_raw))"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Tip_Control                 0.937129\n",
              "Blade_Extension             0.937129\n",
              "Blade_Width                 0.937129\n",
              "Enclosure_Type              0.937129\n",
              "Engine_Horsepower           0.937129\n",
              "Pushblock                   0.937129\n",
              "Scarifier                   0.937102\n",
              "Hydraulics_Flow             0.891899\n",
              "Grouser_Tracks              0.891899\n",
              "Coupler_System              0.891660\n",
              "fiModelSeries               0.858129\n",
              "Steering_Controls           0.827064\n",
              "Differential_Type           0.826959\n",
              "UsageBand                   0.826391\n",
              "fiModelDescriptor           0.820707\n",
              "Backhoe_Mounting            0.803872\n",
              "Pad_Type                    0.802720\n",
              "Stick                       0.802720\n",
              "Turbocharged                0.802720\n",
              "Blade_Type                  0.800977\n",
              "Travel_Controls             0.800975\n",
              "Tire_Size                   0.763869\n",
              "Track_Type                  0.752813\n",
              "Grouser_Type                0.752813\n",
              "Pattern_Changer             0.752651\n",
              "Stick_Length                0.752651\n",
              "Thumb                       0.752476\n",
              "Undercarriage_Pad_Width     0.751020\n",
              "Ripper                      0.740388\n",
              "Drive_System                0.739829\n",
              "MachineHoursCurrentMeter    0.644089\n",
              "Ride_Control                0.629527\n",
              "Transmission                0.543210\n",
              "ProductSize                 0.525460\n",
              "Forks                       0.521154\n",
              "Coupler                     0.466620\n",
              "fiSecondaryDesc             0.342016\n",
              "Hydraulics                  0.200823\n",
              "auctioneerID                0.050199\n",
              "Enclosure                   0.000810\n",
              "ProductGroupDesc            0.000000\n",
              "YearMade                    0.000000\n",
              "SalePrice                   0.000000\n",
              "MachineID                   0.000000\n",
              "ModelID                     0.000000\n",
              "datasource                  0.000000\n",
              "saledate                    0.000000\n",
              "ProductGroup                0.000000\n",
              "fiModelDesc                 0.000000\n",
              "fiBaseModel                 0.000000\n",
              "fiProductClassDesc          0.000000\n",
              "state                       0.000000\n",
              "SalesID                     0.000000\n",
              "dtype: float64"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GBQJNxO2o7Be"
      },
      "source": [
        "raw = df_raw.copy()"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2-3RHAVNp_BV"
      },
      "source": [
        "raw.info()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IUMt7fOsPmbd"
      },
      "source": [
        "def insert_code_cat(df):\n",
        "  for cols in df.columns:\n",
        "    if pd.api.types.is_categorical_dtype(df[cols]):\n",
        "      df[cols] = df[cols].cat.codes + 1\n",
        "\n",
        "insert_code_cat(df_raw)"
      ],
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sLg2ohAbQ2Bd",
        "outputId": "63b2adbc-369e-43b1-818d-72b9b35123b6"
      },
      "source": [
        "def fill_missing_numerical(df):\n",
        "  nan_dict = {}\n",
        "  for colname, series in df.items():\n",
        "    if pd.api.types.is_numeric_dtype(series):\n",
        "      if pd.isna(series).sum():\n",
        "        df[colname + '_is_missing'] = pd.isnull(series)\n",
        "        df[colname] = df[colname].fillna(series.median())\n",
        "        nan_dict[colname] = series.median()\n",
        "  return nan_dict\n",
        "\n",
        "fill_missing_numerical(df_raw)"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'MachineHoursCurrentMeter': 0.0, 'auctioneerID': 2.0}"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fVNbmPR8MFXb"
      },
      "source": [
        "def add_date_element(df, time_field):\n",
        "  time_field_dtype = df[time_field].dtype\n",
        "  if isinstance(time_field_dtype, pd.core.dtypes.dtypes.DatetimeTZDtype):\n",
        "    df[time_field] = np.datetime64\n",
        "  if not np.issubdtype(df[time_field], np.datetime64):\n",
        "    df[time_field] = pd.to_datetime(df[time_field], infer_datetime_format = True)\n",
        "  col = df[time_field]\n",
        "  substitute_name = re.sub('[Dd]ate$', '', time_field)\n",
        "  list_of_attr = ['Year', 'Month', 'Week', 'Day', 'Dayofweek', 'Dayofyear', 'Weekofyear', 'Is_month_end', 'Is_month_start', \n",
        "            'Is_quarter_end', 'Is_quarter_start', 'Is_year_end', 'Is_year_start']\n",
        "  for attr in list_of_attr:\n",
        "    df[substitute_name + attr] = getattr(col.dt, attr.lower())\n",
        "\n",
        "  return df\n"
      ],
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 652
        },
        "id": "vN55018fTiqB",
        "outputId": "c418188e-2a92-491e-a8b8-a79e0db4e488"
      },
      "source": [
        "add_date_element(df_raw, 'saledate')"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:12: FutureWarning: Series.dt.weekofyear and Series.dt.week have been deprecated.  Please use Series.dt.isocalendar().week instead.\n",
            "  if sys.path[0] == '':\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>SalesID</th>\n",
              "      <th>SalePrice</th>\n",
              "      <th>MachineID</th>\n",
              "      <th>ModelID</th>\n",
              "      <th>datasource</th>\n",
              "      <th>auctioneerID</th>\n",
              "      <th>YearMade</th>\n",
              "      <th>MachineHoursCurrentMeter</th>\n",
              "      <th>UsageBand</th>\n",
              "      <th>saledate</th>\n",
              "      <th>fiModelDesc</th>\n",
              "      <th>fiBaseModel</th>\n",
              "      <th>fiSecondaryDesc</th>\n",
              "      <th>fiModelSeries</th>\n",
              "      <th>fiModelDescriptor</th>\n",
              "      <th>ProductSize</th>\n",
              "      <th>fiProductClassDesc</th>\n",
              "      <th>state</th>\n",
              "      <th>ProductGroup</th>\n",
              "      <th>ProductGroupDesc</th>\n",
              "      <th>Drive_System</th>\n",
              "      <th>Enclosure</th>\n",
              "      <th>Forks</th>\n",
              "      <th>Pad_Type</th>\n",
              "      <th>Ride_Control</th>\n",
              "      <th>Stick</th>\n",
              "      <th>Transmission</th>\n",
              "      <th>Turbocharged</th>\n",
              "      <th>Blade_Extension</th>\n",
              "      <th>Blade_Width</th>\n",
              "      <th>Enclosure_Type</th>\n",
              "      <th>Engine_Horsepower</th>\n",
              "      <th>Hydraulics</th>\n",
              "      <th>Pushblock</th>\n",
              "      <th>Ripper</th>\n",
              "      <th>Scarifier</th>\n",
              "      <th>Tip_Control</th>\n",
              "      <th>Tire_Size</th>\n",
              "      <th>Coupler</th>\n",
              "      <th>Coupler_System</th>\n",
              "      <th>Grouser_Tracks</th>\n",
              "      <th>Hydraulics_Flow</th>\n",
              "      <th>Track_Type</th>\n",
              "      <th>Undercarriage_Pad_Width</th>\n",
              "      <th>Stick_Length</th>\n",
              "      <th>Thumb</th>\n",
              "      <th>Pattern_Changer</th>\n",
              "      <th>Grouser_Type</th>\n",
              "      <th>Backhoe_Mounting</th>\n",
              "      <th>Blade_Type</th>\n",
              "      <th>Travel_Controls</th>\n",
              "      <th>Differential_Type</th>\n",
              "      <th>Steering_Controls</th>\n",
              "      <th>auctioneerID_is_missing</th>\n",
              "      <th>MachineHoursCurrentMeter_is_missing</th>\n",
              "      <th>saleYear</th>\n",
              "      <th>saleMonth</th>\n",
              "      <th>saleWeek</th>\n",
              "      <th>saleDay</th>\n",
              "      <th>saleDayofweek</th>\n",
              "      <th>saleDayofyear</th>\n",
              "      <th>saleWeekofyear</th>\n",
              "      <th>saleIs_month_end</th>\n",
              "      <th>saleIs_month_start</th>\n",
              "      <th>saleIs_quarter_end</th>\n",
              "      <th>saleIs_quarter_start</th>\n",
              "      <th>saleIs_year_end</th>\n",
              "      <th>saleIs_year_start</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1139246</td>\n",
              "      <td>11.097410</td>\n",
              "      <td>999089</td>\n",
              "      <td>3157</td>\n",
              "      <td>121</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2004</td>\n",
              "      <td>68.0</td>\n",
              "      <td>1</td>\n",
              "      <td>2006-11-16</td>\n",
              "      <td>950</td>\n",
              "      <td>296</td>\n",
              "      <td>41</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>59</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>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>17</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>2006</td>\n",
              "      <td>11</td>\n",
              "      <td>46</td>\n",
              "      <td>16</td>\n",
              "      <td>3</td>\n",
              "      <td>320</td>\n",
              "      <td>46</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1139248</td>\n",
              "      <td>10.950807</td>\n",
              "      <td>117657</td>\n",
              "      <td>77</td>\n",
              "      <td>121</td>\n",
              "      <td>3.0</td>\n",
              "      <td>1996</td>\n",
              "      <td>4640.0</td>\n",
              "      <td>1</td>\n",
              "      <td>2004-03-26</td>\n",
              "      <td>1725</td>\n",
              "      <td>527</td>\n",
              "      <td>55</td>\n",
              "      <td>98</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>62</td>\n",
              "      <td>33</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>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>12</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>2004</td>\n",
              "      <td>3</td>\n",
              "      <td>13</td>\n",
              "      <td>26</td>\n",
              "      <td>4</td>\n",
              "      <td>86</td>\n",
              "      <td>13</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1139249</td>\n",
              "      <td>9.210340</td>\n",
              "      <td>434808</td>\n",
              "      <td>7009</td>\n",
              "      <td>121</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2001</td>\n",
              "      <td>2838.0</td>\n",
              "      <td>3</td>\n",
              "      <td>2004-02-26</td>\n",
              "      <td>331</td>\n",
              "      <td>110</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>39</td>\n",
              "      <td>32</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>6</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>4</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>2004</td>\n",
              "      <td>2</td>\n",
              "      <td>9</td>\n",
              "      <td>26</td>\n",
              "      <td>3</td>\n",
              "      <td>57</td>\n",
              "      <td>9</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1139251</td>\n",
              "      <td>10.558414</td>\n",
              "      <td>1026470</td>\n",
              "      <td>332</td>\n",
              "      <td>121</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2001</td>\n",
              "      <td>3486.0</td>\n",
              "      <td>3</td>\n",
              "      <td>2011-05-19</td>\n",
              "      <td>3674</td>\n",
              "      <td>1375</td>\n",
              "      <td>0</td>\n",
              "      <td>45</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>8</td>\n",
              "      <td>44</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>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>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>2011</td>\n",
              "      <td>5</td>\n",
              "      <td>20</td>\n",
              "      <td>19</td>\n",
              "      <td>3</td>\n",
              "      <td>139</td>\n",
              "      <td>20</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1139253</td>\n",
              "      <td>9.305651</td>\n",
              "      <td>1057373</td>\n",
              "      <td>17311</td>\n",
              "      <td>121</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2007</td>\n",
              "      <td>722.0</td>\n",
              "      <td>2</td>\n",
              "      <td>2009-07-23</td>\n",
              "      <td>4208</td>\n",
              "      <td>1529</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>40</td>\n",
              "      <td>32</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>1</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>4</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>2009</td>\n",
              "      <td>7</td>\n",
              "      <td>30</td>\n",
              "      <td>23</td>\n",
              "      <td>3</td>\n",
              "      <td>204</td>\n",
              "      <td>30</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>401120</th>\n",
              "      <td>6333336</td>\n",
              "      <td>9.259131</td>\n",
              "      <td>1840702</td>\n",
              "      <td>21439</td>\n",
              "      <td>149</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2005</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>2011-11-02</td>\n",
              "      <td>657</td>\n",
              "      <td>207</td>\n",
              "      <td>106</td>\n",
              "      <td>63</td>\n",
              "      <td>0</td>\n",
              "      <td>5</td>\n",
              "      <td>17</td>\n",
              "      <td>20</td>\n",
              "      <td>4</td>\n",
              "      <td>4</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>4</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>19</td>\n",
              "      <td>29</td>\n",
              "      <td>3</td>\n",
              "      <td>2</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>False</td>\n",
              "      <td>True</td>\n",
              "      <td>2011</td>\n",
              "      <td>11</td>\n",
              "      <td>44</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>306</td>\n",
              "      <td>44</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>401121</th>\n",
              "      <td>6333337</td>\n",
              "      <td>9.305651</td>\n",
              "      <td>1830472</td>\n",
              "      <td>21439</td>\n",
              "      <td>149</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2005</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>2011-11-02</td>\n",
              "      <td>657</td>\n",
              "      <td>207</td>\n",
              "      <td>106</td>\n",
              "      <td>63</td>\n",
              "      <td>0</td>\n",
              "      <td>5</td>\n",
              "      <td>17</td>\n",
              "      <td>20</td>\n",
              "      <td>4</td>\n",
              "      <td>4</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>12</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>19</td>\n",
              "      <td>29</td>\n",
              "      <td>3</td>\n",
              "      <td>2</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>False</td>\n",
              "      <td>True</td>\n",
              "      <td>2011</td>\n",
              "      <td>11</td>\n",
              "      <td>44</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>306</td>\n",
              "      <td>44</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>401122</th>\n",
              "      <td>6333338</td>\n",
              "      <td>9.350102</td>\n",
              "      <td>1887659</td>\n",
              "      <td>21439</td>\n",
              "      <td>149</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2005</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>2011-11-02</td>\n",
              "      <td>657</td>\n",
              "      <td>207</td>\n",
              "      <td>106</td>\n",
              "      <td>63</td>\n",
              "      <td>0</td>\n",
              "      <td>5</td>\n",
              "      <td>17</td>\n",
              "      <td>20</td>\n",
              "      <td>4</td>\n",
              "      <td>4</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>4</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>19</td>\n",
              "      <td>29</td>\n",
              "      <td>3</td>\n",
              "      <td>2</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>False</td>\n",
              "      <td>True</td>\n",
              "      <td>2011</td>\n",
              "      <td>11</td>\n",
              "      <td>44</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>306</td>\n",
              "      <td>44</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>401123</th>\n",
              "      <td>6333341</td>\n",
              "      <td>9.104980</td>\n",
              "      <td>1903570</td>\n",
              "      <td>21435</td>\n",
              "      <td>149</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2005</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>2011-10-25</td>\n",
              "      <td>483</td>\n",
              "      <td>159</td>\n",
              "      <td>106</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>5</td>\n",
              "      <td>13</td>\n",
              "      <td>9</td>\n",
              "      <td>4</td>\n",
              "      <td>4</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>12</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>19</td>\n",
              "      <td>29</td>\n",
              "      <td>3</td>\n",
              "      <td>2</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>False</td>\n",
              "      <td>True</td>\n",
              "      <td>2011</td>\n",
              "      <td>10</td>\n",
              "      <td>43</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>298</td>\n",
              "      <td>43</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>401124</th>\n",
              "      <td>6333342</td>\n",
              "      <td>8.955448</td>\n",
              "      <td>1926965</td>\n",
              "      <td>21435</td>\n",
              "      <td>149</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2005</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>2011-10-25</td>\n",
              "      <td>483</td>\n",
              "      <td>159</td>\n",
              "      <td>106</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>5</td>\n",
              "      <td>13</td>\n",
              "      <td>9</td>\n",
              "      <td>4</td>\n",
              "      <td>4</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>12</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>19</td>\n",
              "      <td>29</td>\n",
              "      <td>3</td>\n",
              "      <td>2</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>False</td>\n",
              "      <td>True</td>\n",
              "      <td>2011</td>\n",
              "      <td>10</td>\n",
              "      <td>43</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>298</td>\n",
              "      <td>43</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>401125 rows × 68 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "        SalesID  SalePrice  ...  saleIs_year_end  saleIs_year_start\n",
              "0       1139246  11.097410  ...            False              False\n",
              "1       1139248  10.950807  ...            False              False\n",
              "2       1139249   9.210340  ...            False              False\n",
              "3       1139251  10.558414  ...            False              False\n",
              "4       1139253   9.305651  ...            False              False\n",
              "...         ...        ...  ...              ...                ...\n",
              "401120  6333336   9.259131  ...            False              False\n",
              "401121  6333337   9.305651  ...            False              False\n",
              "401122  6333338   9.350102  ...            False              False\n",
              "401123  6333341   9.104980  ...            False              False\n",
              "401124  6333342   8.955448  ...            False              False\n",
              "\n",
              "[401125 rows x 68 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mtLI520mmcfs"
      },
      "source": [
        "def split_train_valid(df, num):\n",
        "  return df[:num].copy(), df[num:].copy()\n",
        "\n",
        "def RMSE(a, b):\n",
        "  return np.sqrt(((a-b)**2).mean())\n",
        "\n",
        "\n",
        "def display_metrics(model):\n",
        "\n",
        "    dict_metrics = {\n",
        "        'R^2 for training :': model.score(x_train, y_train),\n",
        "        'R^2 for validating :': model.score(x_valid, y_valid),\n",
        "        'RMSE for training :' : RMSE(model.predict(x_train), y_train),\n",
        "        'RMSE for validating :' : RMSE(model.predict(x_valid), y_valid)\n",
        "    }\n",
        "    if hasattr(model, 'oob_score_'):\n",
        "      dict_metrics['Out Of Bag Score'] = model.oob_score_\n",
        "    print(dict_metrics)\n",
        "\n"
      ],
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iXjIf1eVeJv7"
      },
      "source": [
        "df_raw.drop('saledate', axis = 'columns', inplace=True)"
      ],
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Lk80-CJgaFGN"
      },
      "source": [
        "def split_dependent(df, y_field):\n",
        "  global dataframe, y\n",
        "  y = df[y_field]\n",
        "  dataframe = df.copy()\n",
        "  dataframe.drop(y_field, inplace=True, axis = 1)"
      ],
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fWL14UiDbZQP"
      },
      "source": [
        "split_dependent(df_raw, \"SalePrice\")"
      ],
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2tbQbvSFhK3L"
      },
      "source": [
        "dataframe.to_feather(\"/content/drive/MyDrive/DATA/bulldozers/tmp-bulldozers\")"
      ],
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "L9ltDM-omgO4"
      },
      "source": [
        "n_valid = 12000\n",
        "n_train = len(dataframe) - n_valid\n",
        "\n",
        "x_train, x_valid = split_train_valid(dataframe, n_train)\n",
        "y_train, y_valid = split_train_valid(y, n_train)\n",
        "raw_train, raw_valid = split_train_valid(raw, n_train)"
      ],
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tJ3flT4Dkvlr"
      },
      "source": [
        "assert x_train.shape[0] == y_train.shape[0], \"Wrong Dimensions of Train\"\n",
        "assert x_valid.shape[0] == y_valid.shape[0], \"Wrong Dimensions of Valid\""
      ],
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UzFKjrfFmcPG",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "60c08e34-0a56-4e2b-c379-848fd1f6630b"
      },
      "source": [
        "RF_Model = RandomForestRegressor(n_estimators=80, n_jobs=-1, min_samples_leaf=5, max_features=0.5, max_samples=50000)\n",
        "%time RF_Model.fit(x_train, y_train)\n",
        "display_metrics(RF_Model)"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "CPU times: user 55.4 s, sys: 242 ms, total: 55.6 s\n",
            "Wall time: 29 s\n",
            "{'R^2 for training :': 0.901121374338367, 'R^2 for validating :': 0.886317818673251, 'RMSE for training :': 0.21751228846494292, 'RMSE for validating :': 0.25230288241730264}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "f_oT0aBjhnJ5",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "23a2e665-6405-478d-b035-c370bce62695"
      },
      "source": [
        "estimators_preds = np.stack([t.predict(x_valid.values) for t in RF_Model.estimators_]);\n",
        "estimators_preds.shape"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(80, 12000)"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mYOUC2bqjOQU",
        "outputId": "cd1a96b0-a44c-4458-ee11-2231fd20e2b6"
      },
      "source": [
        "np.mean(estimators_preds[:, 0]), np.std(estimators_preds[:, 0]), "
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(9.26099574892273, 0.24524027971635615)"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WIUBb3d-rb4U"
      },
      "source": [
        "## EDA"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g4UP5UuLlZ8s"
      },
      "source": [
        "df_tmp = raw_valid.copy()\n",
        "df_tmp[\"pred\"]  = np.mean(estimators_preds, axis=0)\n",
        "df_tmp[\"pred_std\"] = np.std(estimators_preds, axis=0);\n",
        "df_tmp"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IO9cfXynlZtp",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 517
        },
        "outputId": "68214254-1e11-4aaf-87c5-32abebb53a58"
      },
      "source": [
        "fig = px.bar(orientation='h', y=df_tmp.Enclosure.cat.categories, x=df_tmp.Enclosure.value_counts());\n",
        "fig.update_layout(plot_bgcolor='rgb(115,115,115)', height=500, width=900)\n",
        "fig.show()"
      ],
      "execution_count": 82,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<html>\n",
              "<head><meta charset=\"utf-8\" /></head>\n",
              "<body>\n",
              "    <div>\n",
              "            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>\n",
              "                <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
              "        <script src=\"https://cdn.plot.ly/plotly-latest.min.js\"></script>    \n",
              "            <div id=\"6e165177-fcaf-49aa-b1a0-3ac15832d95d\" class=\"plotly-graph-div\" style=\"height:500px; width:900px;\"></div>\n",
              "            <script type=\"text/javascript\">\n",
              "                \n",
              "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
              "                    \n",
              "                if (document.getElementById(\"6e165177-fcaf-49aa-b1a0-3ac15832d95d\")) {\n",
              "                    Plotly.newPlot(\n",
              "                        '6e165177-fcaf-49aa-b1a0-3ac15832d95d',\n",
              "                        [{\"alignmentgroup\": \"True\", \"hoverlabel\": {\"namelength\": 0}, \"hovertemplate\": \"x=%{x}<br>y=%{y}\", \"legendgroup\": \"\", \"marker\": {\"color\": \"#636efa\"}, \"name\": \"\", \"offsetgroup\": \"\", \"orientation\": \"h\", \"showlegend\": false, \"textposition\": \"auto\", \"type\": \"bar\", \"x\": [4913, 3777, 3308, 0, 0, 0], \"xaxis\": \"x\", \"y\": [\"EROPS\", \"EROPS AC\", \"EROPS w AC\", \"NO ROPS\", \"None or Unspecified\", \"OROPS\"], \"yaxis\": \"y\"}],\n",
              "                        {\"barmode\": \"relative\", \"height\": 500, \"legend\": {\"tracegroupgap\": 0}, \"margin\": {\"t\": 60}, \"plot_bgcolor\": \"rgb(115,115,115)\", \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"width\": 900, \"xaxis\": {\"anchor\": \"y\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"x\"}}, \"yaxis\": {\"anchor\": \"x\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"y\"}}},\n",
              "                        {\"responsive\": true}\n",
              "                    ).then(function(){\n",
              "                            \n",
              "var gd = document.getElementById('6e165177-fcaf-49aa-b1a0-3ac15832d95d');\n",
              "var x = new MutationObserver(function (mutations, observer) {{\n",
              "        var display = window.getComputedStyle(gd).display;\n",
              "        if (!display || display === 'none') {{\n",
              "            console.log([gd, 'removed!']);\n",
              "            Plotly.purge(gd);\n",
              "            observer.disconnect();\n",
              "        }}\n",
              "}});\n",
              "\n",
              "// Listen for the removal of the full notebook cells\n",
              "var notebookContainer = gd.closest('#notebook-container');\n",
              "if (notebookContainer) {{\n",
              "    x.observe(notebookContainer, {childList: true});\n",
              "}}\n",
              "\n",
              "// Listen for the clearing of the current output cell\n",
              "var outputEl = gd.closest('.output');\n",
              "if (outputEl) {{\n",
              "    x.observe(outputEl, {childList: true});\n",
              "}}\n",
              "\n",
              "                        })\n",
              "                };\n",
              "                \n",
              "            </script>\n",
              "        </div>\n",
              "</body>\n",
              "</html>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CS1-eBZGlZnb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 517
        },
        "outputId": "227342ea-9ffc-4d19-d05a-445d63aee597"
      },
      "source": [
        "a = df_tmp.groupby(\"ProductSize\", as_index=False).size().rename(columns={'size':'counts'})\n",
        "fig = px.bar(orientation=\"h\", y= a.ProductSize, x=a.counts);\n",
        "fig.update_layout(plot_bgcolor='rgb(115,115,115)', height=500, width=900)\n",
        "fig.show()\n"
      ],
      "execution_count": 128,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<html>\n",
              "<head><meta charset=\"utf-8\" /></head>\n",
              "<body>\n",
              "    <div>\n",
              "            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>\n",
              "                <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
              "        <script src=\"https://cdn.plot.ly/plotly-latest.min.js\"></script>    \n",
              "            <div id=\"0f3bf850-8779-411c-aad0-92f719a77893\" class=\"plotly-graph-div\" style=\"height:500px; width:900px;\"></div>\n",
              "            <script type=\"text/javascript\">\n",
              "                \n",
              "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
              "                    \n",
              "                if (document.getElementById(\"0f3bf850-8779-411c-aad0-92f719a77893\")) {\n",
              "                    Plotly.newPlot(\n",
              "                        '0f3bf850-8779-411c-aad0-92f719a77893',\n",
              "                        [{\"alignmentgroup\": \"True\", \"hoverlabel\": {\"namelength\": 0}, \"hovertemplate\": \"x=%{x}<br>y=%{y}\", \"legendgroup\": \"\", \"marker\": {\"color\": \"#636efa\"}, \"name\": \"\", \"offsetgroup\": \"\", \"orientation\": \"h\", \"showlegend\": false, \"textposition\": \"auto\", \"type\": \"bar\", \"x\": [143, 297, 1706, 1549, 1369, 624], \"xaxis\": \"x\", \"y\": [\"Compact\", \"Large\", \"Large / Medium\", \"Medium\", \"Mini\", \"Small\"], \"yaxis\": \"y\"}],\n",
              "                        {\"barmode\": \"relative\", \"height\": 500, \"legend\": {\"tracegroupgap\": 0}, \"margin\": {\"t\": 60}, \"plot_bgcolor\": \"rgb(115,115,115)\", \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"width\": 900, \"xaxis\": {\"anchor\": \"y\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"x\"}}, \"yaxis\": {\"anchor\": \"x\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"y\"}}},\n",
              "                        {\"responsive\": true}\n",
              "                    ).then(function(){\n",
              "                            \n",
              "var gd = document.getElementById('0f3bf850-8779-411c-aad0-92f719a77893');\n",
              "var x = new MutationObserver(function (mutations, observer) {{\n",
              "        var display = window.getComputedStyle(gd).display;\n",
              "        if (!display || display === 'none') {{\n",
              "            console.log([gd, 'removed!']);\n",
              "            Plotly.purge(gd);\n",
              "            observer.disconnect();\n",
              "        }}\n",
              "}});\n",
              "\n",
              "// Listen for the removal of the full notebook cells\n",
              "var notebookContainer = gd.closest('#notebook-container');\n",
              "if (notebookContainer) {{\n",
              "    x.observe(notebookContainer, {childList: true});\n",
              "}}\n",
              "\n",
              "// Listen for the clearing of the current output cell\n",
              "var outputEl = gd.closest('.output');\n",
              "if (outputEl) {{\n",
              "    x.observe(outputEl, {childList: true});\n",
              "}}\n",
              "\n",
              "                        })\n",
              "                };\n",
              "                \n",
              "            </script>\n",
              "        </div>\n",
              "</body>\n",
              "</html>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "id": "QHBFD0ZRMdAi",
        "outputId": "6606b7f4-4037-4605-91c3-5a3688d82f30"
      },
      "source": [
        "fields = [\"Enclosure\", \"pred\", \"pred_std\", \"SalePrice\"]\n",
        "Enclosure_agg = df_tmp[fields].groupby(\"Enclosure\", as_index=False).mean();\n",
        "Enclosure_agg"
      ],
      "execution_count": 104,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Enclosure</th>\n",
              "      <th>pred</th>\n",
              "      <th>pred_std</th>\n",
              "      <th>SalePrice</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>EROPS</td>\n",
              "      <td>9.839758</td>\n",
              "      <td>0.248333</td>\n",
              "      <td>9.849178</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>EROPS AC</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>EROPS w AC</td>\n",
              "      <td>10.566917</td>\n",
              "      <td>0.244723</td>\n",
              "      <td>10.623971</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>NO ROPS</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>None or Unspecified</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>OROPS</td>\n",
              "      <td>9.689200</td>\n",
              "      <td>0.201239</td>\n",
              "      <td>9.682064</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             Enclosure       pred  pred_std  SalePrice\n",
              "0                EROPS   9.839758  0.248333   9.849178\n",
              "1             EROPS AC        NaN       NaN        NaN\n",
              "2           EROPS w AC  10.566917  0.244723  10.623971\n",
              "3              NO ROPS        NaN       NaN        NaN\n",
              "4  None or Unspecified        NaN       NaN        NaN\n",
              "5                OROPS   9.689200  0.201239   9.682064"
            ]
          },
          "metadata": {},
          "execution_count": 104
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "id": "P1baA2f5Mc97",
        "outputId": "ea86ea8e-f152-4335-f80e-05bea8e69b52"
      },
      "source": [
        "fields = [\"ProductSize\", \"pred\", \"pred_std\", \"SalePrice\"]\n",
        "Size_agg = df_tmp[fields].groupby(\"ProductSize\", as_index=False).mean();\n",
        "Size_agg"
      ],
      "execution_count": 107,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>ProductSize</th>\n",
              "      <th>pred</th>\n",
              "      <th>pred_std</th>\n",
              "      <th>SalePrice</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Compact</td>\n",
              "      <td>9.862501</td>\n",
              "      <td>0.304415</td>\n",
              "      <td>9.735093</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Large</td>\n",
              "      <td>10.381497</td>\n",
              "      <td>0.334016</td>\n",
              "      <td>10.470589</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Large / Medium</td>\n",
              "      <td>10.635872</td>\n",
              "      <td>0.272664</td>\n",
              "      <td>10.691871</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Medium</td>\n",
              "      <td>10.622059</td>\n",
              "      <td>0.267110</td>\n",
              "      <td>10.681511</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Mini</td>\n",
              "      <td>9.562280</td>\n",
              "      <td>0.226924</td>\n",
              "      <td>9.535147</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Small</td>\n",
              "      <td>10.321464</td>\n",
              "      <td>0.279179</td>\n",
              "      <td>10.324448</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      ProductSize       pred  pred_std  SalePrice\n",
              "0         Compact   9.862501  0.304415   9.735093\n",
              "1           Large  10.381497  0.334016  10.470589\n",
              "2  Large / Medium  10.635872  0.272664  10.691871\n",
              "3          Medium  10.622059  0.267110  10.681511\n",
              "4            Mini   9.562280  0.226924   9.535147\n",
              "5           Small  10.321464  0.279179  10.324448"
            ]
          },
          "metadata": {},
          "execution_count": 107
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 517
        },
        "id": "mq_4QgMRMc4Z",
        "outputId": "a4e47385-db6f-465a-eea8-03217bd39157"
      },
      "source": [
        "fig = px.bar(orientation=\"h\", x= Enclosure_agg.SalePrice, y= Enclosure_agg.Enclosure);\n",
        "fig.update_layout(plot_bgcolor='rgb(115,115,115)', height=500, width=900)\n",
        "fig.show()"
      ],
      "execution_count": 110,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<html>\n",
              "<head><meta charset=\"utf-8\" /></head>\n",
              "<body>\n",
              "    <div>\n",
              "            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>\n",
              "                <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
              "        <script src=\"https://cdn.plot.ly/plotly-latest.min.js\"></script>    \n",
              "            <div id=\"17ee9e86-2d32-4e47-9d3f-3eb28cd872cc\" class=\"plotly-graph-div\" style=\"height:500px; width:900px;\"></div>\n",
              "            <script type=\"text/javascript\">\n",
              "                \n",
              "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
              "                    \n",
              "                if (document.getElementById(\"17ee9e86-2d32-4e47-9d3f-3eb28cd872cc\")) {\n",
              "                    Plotly.newPlot(\n",
              "                        '17ee9e86-2d32-4e47-9d3f-3eb28cd872cc',\n",
              "                        [{\"alignmentgroup\": \"True\", \"hoverlabel\": {\"namelength\": 0}, \"hovertemplate\": \"x=%{x}<br>y=%{y}\", \"legendgroup\": \"\", \"marker\": {\"color\": \"#636efa\"}, \"name\": \"\", \"offsetgroup\": \"\", \"orientation\": \"h\", \"showlegend\": false, \"textposition\": \"auto\", \"type\": \"bar\", \"x\": [9.849178243059285, null, 10.623970821787893, null, null, 9.682064481019257], \"xaxis\": \"x\", \"y\": [\"EROPS\", \"EROPS AC\", \"EROPS w AC\", \"NO ROPS\", \"None or Unspecified\", \"OROPS\"], \"yaxis\": \"y\"}],\n",
              "                        {\"barmode\": \"relative\", \"height\": 500, \"legend\": {\"tracegroupgap\": 0}, \"margin\": {\"t\": 60}, \"plot_bgcolor\": \"rgb(115,115,115)\", \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"width\": 900, \"xaxis\": {\"anchor\": \"y\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"x\"}}, \"yaxis\": {\"anchor\": \"x\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"y\"}}},\n",
              "                        {\"responsive\": true}\n",
              "                    ).then(function(){\n",
              "                            \n",
              "var gd = document.getElementById('17ee9e86-2d32-4e47-9d3f-3eb28cd872cc');\n",
              "var x = new MutationObserver(function (mutations, observer) {{\n",
              "        var display = window.getComputedStyle(gd).display;\n",
              "        if (!display || display === 'none') {{\n",
              "            console.log([gd, 'removed!']);\n",
              "            Plotly.purge(gd);\n",
              "            observer.disconnect();\n",
              "        }}\n",
              "}});\n",
              "\n",
              "// Listen for the removal of the full notebook cells\n",
              "var notebookContainer = gd.closest('#notebook-container');\n",
              "if (notebookContainer) {{\n",
              "    x.observe(notebookContainer, {childList: true});\n",
              "}}\n",
              "\n",
              "// Listen for the clearing of the current output cell\n",
              "var outputEl = gd.closest('.output');\n",
              "if (outputEl) {{\n",
              "    x.observe(outputEl, {childList: true});\n",
              "}}\n",
              "\n",
              "                        })\n",
              "                };\n",
              "                \n",
              "            </script>\n",
              "        </div>\n",
              "</body>\n",
              "</html>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 517
        },
        "id": "RloQiXkMMc1d",
        "outputId": "98288fcd-5697-4a6e-e543-d030cf08f397"
      },
      "source": [
        "fig = px.bar(orientation=\"h\", x= Size_agg.SalePrice, y= Size_agg.ProductSize);\n",
        "fig.update_layout(plot_bgcolor='rgb(115,115,115)', height=500, width=900)\n",
        "fig.show()"
      ],
      "execution_count": 111,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<html>\n",
              "<head><meta charset=\"utf-8\" /></head>\n",
              "<body>\n",
              "    <div>\n",
              "            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>\n",
              "                <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
              "        <script src=\"https://cdn.plot.ly/plotly-latest.min.js\"></script>    \n",
              "            <div id=\"ad114cce-a22d-4d8e-b6fe-6c1cd377a071\" class=\"plotly-graph-div\" style=\"height:500px; width:900px;\"></div>\n",
              "            <script type=\"text/javascript\">\n",
              "                \n",
              "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
              "                    \n",
              "                if (document.getElementById(\"ad114cce-a22d-4d8e-b6fe-6c1cd377a071\")) {\n",
              "                    Plotly.newPlot(\n",
              "                        'ad114cce-a22d-4d8e-b6fe-6c1cd377a071',\n",
              "                        [{\"alignmentgroup\": \"True\", \"hoverlabel\": {\"namelength\": 0}, \"hovertemplate\": \"x=%{x}<br>y=%{y}\", \"legendgroup\": \"\", \"marker\": {\"color\": \"#636efa\"}, \"name\": \"\", \"offsetgroup\": \"\", \"orientation\": \"h\", \"showlegend\": false, \"textposition\": \"auto\", \"type\": \"bar\", \"x\": [9.73509272940156, 10.470589195279276, 10.691871092787256, 10.681511269791987, 9.535146895225376, 10.324447895122388], \"xaxis\": \"x\", \"y\": [\"Compact\", \"Large\", \"Large / Medium\", \"Medium\", \"Mini\", \"Small\"], \"yaxis\": \"y\"}],\n",
              "                        {\"barmode\": \"relative\", \"height\": 500, \"legend\": {\"tracegroupgap\": 0}, \"margin\": {\"t\": 60}, \"plot_bgcolor\": \"rgb(115,115,115)\", \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"width\": 900, \"xaxis\": {\"anchor\": \"y\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"x\"}}, \"yaxis\": {\"anchor\": \"x\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"y\"}}},\n",
              "                        {\"responsive\": true}\n",
              "                    ).then(function(){\n",
              "                            \n",
              "var gd = document.getElementById('ad114cce-a22d-4d8e-b6fe-6c1cd377a071');\n",
              "var x = new MutationObserver(function (mutations, observer) {{\n",
              "        var display = window.getComputedStyle(gd).display;\n",
              "        if (!display || display === 'none') {{\n",
              "            console.log([gd, 'removed!']);\n",
              "            Plotly.purge(gd);\n",
              "            observer.disconnect();\n",
              "        }}\n",
              "}});\n",
              "\n",
              "// Listen for the removal of the full notebook cells\n",
              "var notebookContainer = gd.closest('#notebook-container');\n",
              "if (notebookContainer) {{\n",
              "    x.observe(notebookContainer, {childList: true});\n",
              "}}\n",
              "\n",
              "// Listen for the clearing of the current output cell\n",
              "var outputEl = gd.closest('.output');\n",
              "if (outputEl) {{\n",
              "    x.observe(outputEl, {childList: true});\n",
              "}}\n",
              "\n",
              "                        })\n",
              "                };\n",
              "                \n",
              "            </script>\n",
              "        </div>\n",
              "</body>\n",
              "</html>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AcTZLpS-OEgW"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}