bulldozer-price-prediction-project/end-to-end-bluebook-bulldozer-price-regression.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 🚜 Predicting the Sale Price of Bulldozers using Machine Learning\n",
    "\n",
    "In this notebook, we're going to go through an example machine learning project with the goal of predicting the sale price of bulldozers.\n",
    "\n",
    "## 1. Problem defition\n",
    "\n",
    "> How well can we predict the future sale price of a bulldozer, given its characteristics and previous examples of how much similar bulldozers have been sold for?\n",
    "\n",
    "## 2. Data\n",
    "\n",
    "The data is downloaded from the Kaggle Bluebook for Bulldozers competition: https://www.kaggle.com/c/bluebook-for-bulldozers/data\n",
    "\n",
    "There are 3 main datasets:\n",
    "\n",
    "* Train.csv is the training set, which contains data through the end of 2011.\n",
    "* Valid.csv is the validation set, which contains data from January 1, 2012 - April 30, 2012 You make predictions on this set throughout the majority of the competition. Your score on this set is used to create the public leaderboard.\n",
    "* Test.csv is the test set, which won't be released until the last week of the competition. It contains data from May 1, 2012 - November 2012. Your score on the test set determines your final rank for the competition.\n",
    "\n",
    "## 3. Evaluation\n",
    "\n",
    "The evaluation metric for this competition is the RMSLE (root mean squared log error) between the actual and predicted auction prices.\n",
    "\n",
    "For more on the evaluation of this project check: https://www.kaggle.com/c/bluebook-for-bulldozers/overview/evaluation\n",
    "\n",
    "**Note:** The goal for most regression evaluation metrics is to minimize the error. For example, our goal for this project will be to build a machine learning model which minimises RMSLE.\n",
    "\n",
    "## 4. Features\n",
    "\n",
    "Kaggle provides a data dictionary detailing all of the features of the dataset. You can view this data dictionary on Google Sheets: https://docs.google.com/spreadsheets/d/18ly-bLR8sbDJLITkWG7ozKm8l3RyieQ2Fpgix-beSYI/edit?usp=sharing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import sklearn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import training and validation sets\n",
    "df = pd.read_csv(\"data/TrainAndValid.csv\",\n",
    "                 low_memory=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 412698 entries, 0 to 412697\n",
      "Data columns (total 53 columns):\n",
      "SalesID                     412698 non-null int64\n",
      "SalePrice                   412698 non-null float64\n",
      "MachineID                   412698 non-null int64\n",
      "ModelID                     412698 non-null int64\n",
      "datasource                  412698 non-null int64\n",
      "auctioneerID                392562 non-null float64\n",
      "YearMade                    412698 non-null int64\n",
      "MachineHoursCurrentMeter    147504 non-null float64\n",
      "UsageBand                   73670 non-null object\n",
      "saledate                    412698 non-null object\n",
      "fiModelDesc                 412698 non-null object\n",
      "fiBaseModel                 412698 non-null object\n",
      "fiSecondaryDesc             271971 non-null object\n",
      "fiModelSeries               58667 non-null object\n",
      "fiModelDescriptor           74816 non-null object\n",
      "ProductSize                 196093 non-null object\n",
      "fiProductClassDesc          412698 non-null object\n",
      "state                       412698 non-null object\n",
      "ProductGroup                412698 non-null object\n",
      "ProductGroupDesc            412698 non-null object\n",
      "Drive_System                107087 non-null object\n",
      "Enclosure                   412364 non-null object\n",
      "Forks                       197715 non-null object\n",
      "Pad_Type                    81096 non-null object\n",
      "Ride_Control                152728 non-null object\n",
      "Stick                       81096 non-null object\n",
      "Transmission                188007 non-null object\n",
      "Turbocharged                81096 non-null object\n",
      "Blade_Extension             25983 non-null object\n",
      "Blade_Width                 25983 non-null object\n",
      "Enclosure_Type              25983 non-null object\n",
      "Engine_Horsepower           25983 non-null object\n",
      "Hydraulics                  330133 non-null object\n",
      "Pushblock                   25983 non-null object\n",
      "Ripper                      106945 non-null object\n",
      "Scarifier                   25994 non-null object\n",
      "Tip_Control                 25983 non-null object\n",
      "Tire_Size                   97638 non-null object\n",
      "Coupler                     220679 non-null object\n",
      "Coupler_System              44974 non-null object\n",
      "Grouser_Tracks              44875 non-null object\n",
      "Hydraulics_Flow             44875 non-null object\n",
      "Track_Type                  102193 non-null object\n",
      "Undercarriage_Pad_Width     102916 non-null object\n",
      "Stick_Length                102261 non-null object\n",
      "Thumb                       102332 non-null object\n",
      "Pattern_Changer             102261 non-null object\n",
      "Grouser_Type                102193 non-null object\n",
      "Backhoe_Mounting            80712 non-null object\n",
      "Blade_Type                  81875 non-null object\n",
      "Travel_Controls             81877 non-null object\n",
      "Differential_Type           71564 non-null object\n",
      "Steering_Controls           71522 non-null object\n",
      "dtypes: float64(3), int64(5), object(45)\n",
      "memory usage: 166.9+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SalesID                          0\n",
       "SalePrice                        0\n",
       "MachineID                        0\n",
       "ModelID                          0\n",
       "datasource                       0\n",
       "auctioneerID                 20136\n",
       "YearMade                         0\n",
       "MachineHoursCurrentMeter    265194\n",
       "UsageBand                   339028\n",
       "saledate                         0\n",
       "fiModelDesc                      0\n",
       "fiBaseModel                      0\n",
       "fiSecondaryDesc             140727\n",
       "fiModelSeries               354031\n",
       "fiModelDescriptor           337882\n",
       "ProductSize                 216605\n",
       "fiProductClassDesc               0\n",
       "state                            0\n",
       "ProductGroup                     0\n",
       "ProductGroupDesc                 0\n",
       "Drive_System                305611\n",
       "Enclosure                      334\n",
       "Forks                       214983\n",
       "Pad_Type                    331602\n",
       "Ride_Control                259970\n",
       "Stick                       331602\n",
       "Transmission                224691\n",
       "Turbocharged                331602\n",
       "Blade_Extension             386715\n",
       "Blade_Width                 386715\n",
       "Enclosure_Type              386715\n",
       "Engine_Horsepower           386715\n",
       "Hydraulics                   82565\n",
       "Pushblock                   386715\n",
       "Ripper                      305753\n",
       "Scarifier                   386704\n",
       "Tip_Control                 386715\n",
       "Tire_Size                   315060\n",
       "Coupler                     192019\n",
       "Coupler_System              367724\n",
       "Grouser_Tracks              367823\n",
       "Hydraulics_Flow             367823\n",
       "Track_Type                  310505\n",
       "Undercarriage_Pad_Width     309782\n",
       "Stick_Length                310437\n",
       "Thumb                       310366\n",
       "Pattern_Changer             310437\n",
       "Grouser_Type                310505\n",
       "Backhoe_Mounting            331986\n",
       "Blade_Type                  330823\n",
       "Travel_Controls             330821\n",
       "Differential_Type           341134\n",
       "Steering_Controls           341176\n",
       "dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['SalesID', 'SalePrice', 'MachineID', 'ModelID', 'datasource',\n",
       "       'auctioneerID', 'YearMade', 'MachineHoursCurrentMeter', 'UsageBand',\n",
       "       'saledate', 'fiModelDesc', 'fiBaseModel', 'fiSecondaryDesc',\n",
       "       'fiModelSeries', 'fiModelDescriptor', 'ProductSize',\n",
       "       'fiProductClassDesc', 'state', 'ProductGroup', 'ProductGroupDesc',\n",
       "       'Drive_System', 'Enclosure', 'Forks', 'Pad_Type', 'Ride_Control',\n",
       "       'Stick', 'Transmission', 'Turbocharged', 'Blade_Extension',\n",
       "       'Blade_Width', 'Enclosure_Type', 'Engine_Horsepower', 'Hydraulics',\n",
       "       'Pushblock', 'Ripper', 'Scarifier', 'Tip_Control', 'Tire_Size',\n",
       "       'Coupler', 'Coupler_System', 'Grouser_Tracks', 'Hydraulics_Flow',\n",
       "       'Track_Type', 'Undercarriage_Pad_Width', 'Stick_Length', 'Thumb',\n",
       "       'Pattern_Changer', 'Grouser_Type', 'Backhoe_Mounting', 'Blade_Type',\n",
       "       'Travel_Controls', 'Differential_Type', 'Steering_Controls'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x11c946250>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.scatter(df[\"saledate\"][:1000], df[\"SalePrice\"][:1000])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      11/16/2006 0:00\n",
       "1       3/26/2004 0:00\n",
       "2       2/26/2004 0:00\n",
       "3       5/19/2011 0:00\n",
       "4       7/23/2009 0:00\n",
       "            ...       \n",
       "995     7/16/2009 0:00\n",
       "996     6/14/2007 0:00\n",
       "997     9/22/2005 0:00\n",
       "998     7/28/2005 0:00\n",
       "999     6/16/2011 0:00\n",
       "Name: saledate, Length: 1000, dtype: object"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.saledate[:1000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('O')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.saledate.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11cc2f810>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.SalePrice.plot.hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Parsing dates\n",
    "\n",
    "When we work with time series data, we want to enrich the time & date component as much as possible.\n",
    "\n",
    "We can do that by telling pandas which of our columns has dates in it using the `parse_dates` parameter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import data again but this time parse dates\n",
    "df = pd.read_csv(\"data/TrainAndValid.csv\",\n",
    "                 low_memory=False,\n",
    "                 parse_dates=[\"saledate\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('<M8[ns]')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.saledate.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     2006-11-16\n",
       "1     2004-03-26\n",
       "2     2004-02-26\n",
       "3     2011-05-19\n",
       "4     2009-07-23\n",
       "         ...    \n",
       "995   2009-07-16\n",
       "996   2007-06-14\n",
       "997   2005-09-22\n",
       "998   2005-07-28\n",
       "999   2011-06-16\n",
       "Name: saledate, Length: 1000, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.saledate[:1000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x109d81390>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.scatter(df[\"saledate\"][:1000], df[\"SalePrice\"][:1000])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>...</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1139246</td>\n",
       "      <td>66000.0</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>Low</td>\n",
       "      <td>2006-11-16</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Conventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1139248</td>\n",
       "      <td>57000.0</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>Low</td>\n",
       "      <td>2004-03-26</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Conventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1139249</td>\n",
       "      <td>10000.0</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>High</td>\n",
       "      <td>2004-02-26</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1139251</td>\n",
       "      <td>38500.0</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>High</td>\n",
       "      <td>2011-05-19</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1139253</td>\n",
       "      <td>11000.0</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>Medium</td>\n",
       "      <td>2009-07-23</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 53 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   SalesID  SalePrice  MachineID  ModelID  datasource  auctioneerID  YearMade  \\\n",
       "0  1139246    66000.0     999089     3157         121           3.0      2004   \n",
       "1  1139248    57000.0     117657       77         121           3.0      1996   \n",
       "2  1139249    10000.0     434808     7009         121           3.0      2001   \n",
       "3  1139251    38500.0    1026470      332         121           3.0      2001   \n",
       "4  1139253    11000.0    1057373    17311         121           3.0      2007   \n",
       "\n",
       "   MachineHoursCurrentMeter UsageBand   saledate  ... Undercarriage_Pad_Width  \\\n",
       "0                      68.0       Low 2006-11-16  ...                     NaN   \n",
       "1                    4640.0       Low 2004-03-26  ...                     NaN   \n",
       "2                    2838.0      High 2004-02-26  ...                     NaN   \n",
       "3                    3486.0      High 2011-05-19  ...                     NaN   \n",
       "4                     722.0    Medium 2009-07-23  ...                     NaN   \n",
       "\n",
       "  Stick_Length Thumb Pattern_Changer Grouser_Type Backhoe_Mounting Blade_Type  \\\n",
       "0          NaN   NaN             NaN          NaN              NaN        NaN   \n",
       "1          NaN   NaN             NaN          NaN              NaN        NaN   \n",
       "2          NaN   NaN             NaN          NaN              NaN        NaN   \n",
       "3          NaN   NaN             NaN          NaN              NaN        NaN   \n",
       "4          NaN   NaN             NaN          NaN              NaN        NaN   \n",
       "\n",
       "  Travel_Controls Differential_Type Steering_Controls  \n",
       "0             NaN          Standard      Conventional  \n",
       "1             NaN          Standard      Conventional  \n",
       "2             NaN               NaN               NaN  \n",
       "3             NaN               NaN               NaN  \n",
       "4             NaN               NaN               NaN  \n",
       "\n",
       "[5 rows x 53 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>SalesID</th>\n",
       "      <td>1139246</td>\n",
       "      <td>1139248</td>\n",
       "      <td>1139249</td>\n",
       "      <td>1139251</td>\n",
       "      <td>1139253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SalePrice</th>\n",
       "      <td>66000</td>\n",
       "      <td>57000</td>\n",
       "      <td>10000</td>\n",
       "      <td>38500</td>\n",
       "      <td>11000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MachineID</th>\n",
       "      <td>999089</td>\n",
       "      <td>117657</td>\n",
       "      <td>434808</td>\n",
       "      <td>1026470</td>\n",
       "      <td>1057373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ModelID</th>\n",
       "      <td>3157</td>\n",
       "      <td>77</td>\n",
       "      <td>7009</td>\n",
       "      <td>332</td>\n",
       "      <td>17311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>datasource</th>\n",
       "      <td>121</td>\n",
       "      <td>121</td>\n",
       "      <td>121</td>\n",
       "      <td>121</td>\n",
       "      <td>121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>auctioneerID</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YearMade</th>\n",
       "      <td>2004</td>\n",
       "      <td>1996</td>\n",
       "      <td>2001</td>\n",
       "      <td>2001</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MachineHoursCurrentMeter</th>\n",
       "      <td>68</td>\n",
       "      <td>4640</td>\n",
       "      <td>2838</td>\n",
       "      <td>3486</td>\n",
       "      <td>722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UsageBand</th>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "      <td>Medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saledate</th>\n",
       "      <td>2006-11-16 00:00:00</td>\n",
       "      <td>2004-03-26 00:00:00</td>\n",
       "      <td>2004-02-26 00:00:00</td>\n",
       "      <td>2011-05-19 00:00:00</td>\n",
       "      <td>2009-07-23 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fiModelDesc</th>\n",
       "      <td>521D</td>\n",
       "      <td>950FII</td>\n",
       "      <td>226</td>\n",
       "      <td>PC120-6E</td>\n",
       "      <td>S175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fiBaseModel</th>\n",
       "      <td>521</td>\n",
       "      <td>950</td>\n",
       "      <td>226</td>\n",
       "      <td>PC120</td>\n",
       "      <td>S175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fiSecondaryDesc</th>\n",
       "      <td>D</td>\n",
       "      <td>F</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fiModelSeries</th>\n",
       "      <td>NaN</td>\n",
       "      <td>II</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-6E</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fiModelDescriptor</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ProductSize</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Medium</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Small</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fiProductClassDesc</th>\n",
       "      <td>Wheel Loader - 110.0 to 120.0 Horsepower</td>\n",
       "      <td>Wheel Loader - 150.0 to 175.0 Horsepower</td>\n",
       "      <td>Skid Steer Loader - 1351.0 to 1601.0 Lb Operat...</td>\n",
       "      <td>Hydraulic Excavator, Track - 12.0 to 14.0 Metr...</td>\n",
       "      <td>Skid Steer Loader - 1601.0 to 1751.0 Lb Operat...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>North Carolina</td>\n",
       "      <td>New York</td>\n",
       "      <td>Texas</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ProductGroup</th>\n",
       "      <td>WL</td>\n",
       "      <td>WL</td>\n",
       "      <td>SSL</td>\n",
       "      <td>TEX</td>\n",
       "      <td>SSL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ProductGroupDesc</th>\n",
       "      <td>Wheel Loader</td>\n",
       "      <td>Wheel Loader</td>\n",
       "      <td>Skid Steer Loaders</td>\n",
       "      <td>Track Excavators</td>\n",
       "      <td>Skid Steer Loaders</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Drive_System</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Enclosure</th>\n",
       "      <td>EROPS w AC</td>\n",
       "      <td>EROPS w AC</td>\n",
       "      <td>OROPS</td>\n",
       "      <td>EROPS w AC</td>\n",
       "      <td>EROPS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Forks</th>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pad_Type</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ride_Control</th>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Stick</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Transmission</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Turbocharged</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Blade_Extension</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Blade_Width</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Enclosure_Type</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Engine_Horsepower</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hydraulics</th>\n",
       "      <td>2 Valve</td>\n",
       "      <td>2 Valve</td>\n",
       "      <td>Auxiliary</td>\n",
       "      <td>2 Valve</td>\n",
       "      <td>Auxiliary</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pushblock</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ripper</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Scarifier</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tip_Control</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tire_Size</th>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>23.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Coupler</th>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>None or Unspecified</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Coupler_System</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Grouser_Tracks</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hydraulics_Flow</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Standard</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Standard</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Track_Type</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Undercarriage_Pad_Width</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Stick_Length</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thumb</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pattern_Changer</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Grouser_Type</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Backhoe_Mounting</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Blade_Type</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Travel_Controls</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Differential_Type</th>\n",
       "      <td>Standard</td>\n",
       "      <td>Standard</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Steering_Controls</th>\n",
       "      <td>Conventional</td>\n",
       "      <td>Conventional</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                 0  \\\n",
       "SalesID                                                    1139246   \n",
       "SalePrice                                                    66000   \n",
       "MachineID                                                   999089   \n",
       "ModelID                                                       3157   \n",
       "datasource                                                     121   \n",
       "auctioneerID                                                     3   \n",
       "YearMade                                                      2004   \n",
       "MachineHoursCurrentMeter                                        68   \n",
       "UsageBand                                                      Low   \n",
       "saledate                                       2006-11-16 00:00:00   \n",
       "fiModelDesc                                                   521D   \n",
       "fiBaseModel                                                    521   \n",
       "fiSecondaryDesc                                                  D   \n",
       "fiModelSeries                                                  NaN   \n",
       "fiModelDescriptor                                              NaN   \n",
       "ProductSize                                                    NaN   \n",
       "fiProductClassDesc        Wheel Loader - 110.0 to 120.0 Horsepower   \n",
       "state                                                      Alabama   \n",
       "ProductGroup                                                    WL   \n",
       "ProductGroupDesc                                      Wheel Loader   \n",
       "Drive_System                                                   NaN   \n",
       "Enclosure                                               EROPS w AC   \n",
       "Forks                                          None or Unspecified   \n",
       "Pad_Type                                                       NaN   \n",
       "Ride_Control                                   None or Unspecified   \n",
       "Stick                                                          NaN   \n",
       "Transmission                                                   NaN   \n",
       "Turbocharged                                                   NaN   \n",
       "Blade_Extension                                                NaN   \n",
       "Blade_Width                                                    NaN   \n",
       "Enclosure_Type                                                 NaN   \n",
       "Engine_Horsepower                                              NaN   \n",
       "Hydraulics                                                 2 Valve   \n",
       "Pushblock                                                      NaN   \n",
       "Ripper                                                         NaN   \n",
       "Scarifier                                                      NaN   \n",
       "Tip_Control                                                    NaN   \n",
       "Tire_Size                                      None or Unspecified   \n",
       "Coupler                                        None or Unspecified   \n",
       "Coupler_System                                                 NaN   \n",
       "Grouser_Tracks                                                 NaN   \n",
       "Hydraulics_Flow                                                NaN   \n",
       "Track_Type                                                     NaN   \n",
       "Undercarriage_Pad_Width                                        NaN   \n",
       "Stick_Length                                                   NaN   \n",
       "Thumb                                                          NaN   \n",
       "Pattern_Changer                                                NaN   \n",
       "Grouser_Type                                                   NaN   \n",
       "Backhoe_Mounting                                               NaN   \n",
       "Blade_Type                                                     NaN   \n",
       "Travel_Controls                                                NaN   \n",
       "Differential_Type                                         Standard   \n",
       "Steering_Controls                                     Conventional   \n",
       "\n",
       "                                                                 1  \\\n",
       "SalesID                                                    1139248   \n",
       "SalePrice                                                    57000   \n",
       "MachineID                                                   117657   \n",
       "ModelID                                                         77   \n",
       "datasource                                                     121   \n",
       "auctioneerID                                                     3   \n",
       "YearMade                                                      1996   \n",
       "MachineHoursCurrentMeter                                      4640   \n",
       "UsageBand                                                      Low   \n",
       "saledate                                       2004-03-26 00:00:00   \n",
       "fiModelDesc                                                 950FII   \n",
       "fiBaseModel                                                    950   \n",
       "fiSecondaryDesc                                                  F   \n",
       "fiModelSeries                                                   II   \n",
       "fiModelDescriptor                                              NaN   \n",
       "ProductSize                                                 Medium   \n",
       "fiProductClassDesc        Wheel Loader - 150.0 to 175.0 Horsepower   \n",
       "state                                               North Carolina   \n",
       "ProductGroup                                                    WL   \n",
       "ProductGroupDesc                                      Wheel Loader   \n",
       "Drive_System                                                   NaN   \n",
       "Enclosure                                               EROPS w AC   \n",
       "Forks                                          None or Unspecified   \n",
       "Pad_Type                                                       NaN   \n",
       "Ride_Control                                   None or Unspecified   \n",
       "Stick                                                          NaN   \n",
       "Transmission                                                   NaN   \n",
       "Turbocharged                                                   NaN   \n",
       "Blade_Extension                                                NaN   \n",
       "Blade_Width                                                    NaN   \n",
       "Enclosure_Type                                                 NaN   \n",
       "Engine_Horsepower                                              NaN   \n",
       "Hydraulics                                                 2 Valve   \n",
       "Pushblock                                                      NaN   \n",
       "Ripper                                                         NaN   \n",
       "Scarifier                                                      NaN   \n",
       "Tip_Control                                                    NaN   \n",
       "Tire_Size                                                     23.5   \n",
       "Coupler                                        None or Unspecified   \n",
       "Coupler_System                                                 NaN   \n",
       "Grouser_Tracks                                                 NaN   \n",
       "Hydraulics_Flow                                                NaN   \n",
       "Track_Type                                                     NaN   \n",
       "Undercarriage_Pad_Width                                        NaN   \n",
       "Stick_Length                                                   NaN   \n",
       "Thumb                                                          NaN   \n",
       "Pattern_Changer                                                NaN   \n",
       "Grouser_Type                                                   NaN   \n",
       "Backhoe_Mounting                                               NaN   \n",
       "Blade_Type                                                     NaN   \n",
       "Travel_Controls                                                NaN   \n",
       "Differential_Type                                         Standard   \n",
       "Steering_Controls                                     Conventional   \n",
       "\n",
       "                                                                          2  \\\n",
       "SalesID                                                             1139249   \n",
       "SalePrice                                                             10000   \n",
       "MachineID                                                            434808   \n",
       "ModelID                                                                7009   \n",
       "datasource                                                              121   \n",
       "auctioneerID                                                              3   \n",
       "YearMade                                                               2001   \n",
       "MachineHoursCurrentMeter                                               2838   \n",
       "UsageBand                                                              High   \n",
       "saledate                                                2004-02-26 00:00:00   \n",
       "fiModelDesc                                                             226   \n",
       "fiBaseModel                                                             226   \n",
       "fiSecondaryDesc                                                         NaN   \n",
       "fiModelSeries                                                           NaN   \n",
       "fiModelDescriptor                                                       NaN   \n",
       "ProductSize                                                             NaN   \n",
       "fiProductClassDesc        Skid Steer Loader - 1351.0 to 1601.0 Lb Operat...   \n",
       "state                                                              New York   \n",
       "ProductGroup                                                            SSL   \n",
       "ProductGroupDesc                                         Skid Steer Loaders   \n",
       "Drive_System                                                            NaN   \n",
       "Enclosure                                                             OROPS   \n",
       "Forks                                                   None or Unspecified   \n",
       "Pad_Type                                                                NaN   \n",
       "Ride_Control                                                            NaN   \n",
       "Stick                                                                   NaN   \n",
       "Transmission                                                            NaN   \n",
       "Turbocharged                                                            NaN   \n",
       "Blade_Extension                                                         NaN   \n",
       "Blade_Width                                                             NaN   \n",
       "Enclosure_Type                                                          NaN   \n",
       "Engine_Horsepower                                                       NaN   \n",
       "Hydraulics                                                        Auxiliary   \n",
       "Pushblock                                                               NaN   \n",
       "Ripper                                                                  NaN   \n",
       "Scarifier                                                               NaN   \n",
       "Tip_Control                                                             NaN   \n",
       "Tire_Size                                                               NaN   \n",
       "Coupler                                                 None or Unspecified   \n",
       "Coupler_System                                          None or Unspecified   \n",
       "Grouser_Tracks                                          None or Unspecified   \n",
       "Hydraulics_Flow                                                    Standard   \n",
       "Track_Type                                                              NaN   \n",
       "Undercarriage_Pad_Width                                                 NaN   \n",
       "Stick_Length                                                            NaN   \n",
       "Thumb                                                                   NaN   \n",
       "Pattern_Changer                                                         NaN   \n",
       "Grouser_Type                                                            NaN   \n",
       "Backhoe_Mounting                                                        NaN   \n",
       "Blade_Type                                                              NaN   \n",
       "Travel_Controls                                                         NaN   \n",
       "Differential_Type                                                       NaN   \n",
       "Steering_Controls                                                       NaN   \n",
       "\n",
       "                                                                          3  \\\n",
       "SalesID                                                             1139251   \n",
       "SalePrice                                                             38500   \n",
       "MachineID                                                           1026470   \n",
       "ModelID                                                                 332   \n",
       "datasource                                                              121   \n",
       "auctioneerID                                                              3   \n",
       "YearMade                                                               2001   \n",
       "MachineHoursCurrentMeter                                               3486   \n",
       "UsageBand                                                              High   \n",
       "saledate                                                2011-05-19 00:00:00   \n",
       "fiModelDesc                                                        PC120-6E   \n",
       "fiBaseModel                                                           PC120   \n",
       "fiSecondaryDesc                                                         NaN   \n",
       "fiModelSeries                                                           -6E   \n",
       "fiModelDescriptor                                                       NaN   \n",
       "ProductSize                                                           Small   \n",
       "fiProductClassDesc        Hydraulic Excavator, Track - 12.0 to 14.0 Metr...   \n",
       "state                                                                 Texas   \n",
       "ProductGroup                                                            TEX   \n",
       "ProductGroupDesc                                           Track Excavators   \n",
       "Drive_System                                                            NaN   \n",
       "Enclosure                                                        EROPS w AC   \n",
       "Forks                                                                   NaN   \n",
       "Pad_Type                                                                NaN   \n",
       "Ride_Control                                                            NaN   \n",
       "Stick                                                                   NaN   \n",
       "Transmission                                                            NaN   \n",
       "Turbocharged                                                            NaN   \n",
       "Blade_Extension                                                         NaN   \n",
       "Blade_Width                                                             NaN   \n",
       "Enclosure_Type                                                          NaN   \n",
       "Engine_Horsepower                                                       NaN   \n",
       "Hydraulics                                                          2 Valve   \n",
       "Pushblock                                                               NaN   \n",
       "Ripper                                                                  NaN   \n",
       "Scarifier                                                               NaN   \n",
       "Tip_Control                                                             NaN   \n",
       "Tire_Size                                                               NaN   \n",
       "Coupler                                                 None or Unspecified   \n",
       "Coupler_System                                                          NaN   \n",
       "Grouser_Tracks                                                          NaN   \n",
       "Hydraulics_Flow                                                         NaN   \n",
       "Track_Type                                                              NaN   \n",
       "Undercarriage_Pad_Width                                                 NaN   \n",
       "Stick_Length                                                            NaN   \n",
       "Thumb                                                                   NaN   \n",
       "Pattern_Changer                                                         NaN   \n",
       "Grouser_Type                                                            NaN   \n",
       "Backhoe_Mounting                                                        NaN   \n",
       "Blade_Type                                                              NaN   \n",
       "Travel_Controls                                                         NaN   \n",
       "Differential_Type                                                       NaN   \n",
       "Steering_Controls                                                       NaN   \n",
       "\n",
       "                                                                          4  \n",
       "SalesID                                                             1139253  \n",
       "SalePrice                                                             11000  \n",
       "MachineID                                                           1057373  \n",
       "ModelID                                                               17311  \n",
       "datasource                                                              121  \n",
       "auctioneerID                                                              3  \n",
       "YearMade                                                               2007  \n",
       "MachineHoursCurrentMeter                                                722  \n",
       "UsageBand                                                            Medium  \n",
       "saledate                                                2009-07-23 00:00:00  \n",
       "fiModelDesc                                                            S175  \n",
       "fiBaseModel                                                            S175  \n",
       "fiSecondaryDesc                                                         NaN  \n",
       "fiModelSeries                                                           NaN  \n",
       "fiModelDescriptor                                                       NaN  \n",
       "ProductSize                                                             NaN  \n",
       "fiProductClassDesc        Skid Steer Loader - 1601.0 to 1751.0 Lb Operat...  \n",
       "state                                                              New York  \n",
       "ProductGroup                                                            SSL  \n",
       "ProductGroupDesc                                         Skid Steer Loaders  \n",
       "Drive_System                                                            NaN  \n",
       "Enclosure                                                             EROPS  \n",
       "Forks                                                   None or Unspecified  \n",
       "Pad_Type                                                                NaN  \n",
       "Ride_Control                                                            NaN  \n",
       "Stick                                                                   NaN  \n",
       "Transmission                                                            NaN  \n",
       "Turbocharged                                                            NaN  \n",
       "Blade_Extension                                                         NaN  \n",
       "Blade_Width                                                             NaN  \n",
       "Enclosure_Type                                                          NaN  \n",
       "Engine_Horsepower                                                       NaN  \n",
       "Hydraulics                                                        Auxiliary  \n",
       "Pushblock                                                               NaN  \n",
       "Ripper                                                                  NaN  \n",
       "Scarifier                                                               NaN  \n",
       "Tip_Control                                                             NaN  \n",
       "Tire_Size                                                               NaN  \n",
       "Coupler                                                 None or Unspecified  \n",
       "Coupler_System                                          None or Unspecified  \n",
       "Grouser_Tracks                                          None or Unspecified  \n",
       "Hydraulics_Flow                                                    Standard  \n",
       "Track_Type                                                              NaN  \n",
       "Undercarriage_Pad_Width                                                 NaN  \n",
       "Stick_Length                                                            NaN  \n",
       "Thumb                                                                   NaN  \n",
       "Pattern_Changer                                                         NaN  \n",
       "Grouser_Type                                                            NaN  \n",
       "Backhoe_Mounting                                                        NaN  \n",
       "Blade_Type                                                              NaN  \n",
       "Travel_Controls                                                         NaN  \n",
       "Differential_Type                                                       NaN  \n",
       "Steering_Controls                                                       NaN  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    2006-11-16\n",
       "1    2004-03-26\n",
       "2    2004-02-26\n",
       "3    2011-05-19\n",
       "4    2009-07-23\n",
       "5    2008-12-18\n",
       "6    2004-08-26\n",
       "7    2005-11-17\n",
       "8    2009-08-27\n",
       "9    2007-08-09\n",
       "10   2008-08-21\n",
       "11   2006-08-24\n",
       "12   2005-10-20\n",
       "13   2006-01-26\n",
       "14   2006-01-03\n",
       "15   2006-11-16\n",
       "16   2007-06-14\n",
       "17   2010-01-28\n",
       "18   2006-03-09\n",
       "19   2005-11-17\n",
       "Name: saledate, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.saledate.head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sort DataFrame by saledate\n",
    "\n",
    "When working with time series data, it's a good idea to sort it by date."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "205615   1989-01-17\n",
       "274835   1989-01-31\n",
       "141296   1989-01-31\n",
       "212552   1989-01-31\n",
       "62755    1989-01-31\n",
       "54653    1989-01-31\n",
       "81383    1989-01-31\n",
       "204924   1989-01-31\n",
       "135376   1989-01-31\n",
       "113390   1989-01-31\n",
       "113394   1989-01-31\n",
       "116419   1989-01-31\n",
       "32138    1989-01-31\n",
       "127610   1989-01-31\n",
       "76171    1989-01-31\n",
       "127000   1989-01-31\n",
       "128130   1989-01-31\n",
       "127626   1989-01-31\n",
       "55455    1989-01-31\n",
       "55454    1989-01-31\n",
       "Name: saledate, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Sort DataFrame in date order\n",
    "df.sort_values(by=[\"saledate\"], inplace=True, ascending=True)\n",
    "df.saledate.head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Make a copy of the original DataFrame\n",
    "\n",
    "We make a copy of the original dataframe so when we manipulate the copy, we've still got our original data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Make a copy of the original DataFrame to perform edits on\n",
    "df_tmp = df.copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Add datetime parameters for `saledate` column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_tmp[\"saleYear\"] = df_tmp.saledate.dt.year\n",
    "df_tmp[\"saleMonth\"] = df_tmp.saledate.dt.month\n",
    "df_tmp[\"saleDay\"] = df_tmp.saledate.dt.day\n",
    "df_tmp[\"saleDayOfWeek\"] = df_tmp.saledate.dt.dayofweek\n",
    "df_tmp[\"saleDayOfYear\"] = df_tmp.saledate.dt.dayofyear"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>205615</th>\n",
       "      <th>274835</th>\n",
       "      <th>141296</th>\n",
       "      <th>212552</th>\n",
       "      <th>62755</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>SalesID</th>\n",
       "      <td>1646770</td>\n",
       "      <td>1821514</td>\n",
       "      <td>1505138</td>\n",
       "      <td>1671174</td>\n",
       "      <td>1329056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SalePrice</th>\n",
       "      <td>9500</td>\n",
       "      <td>14000</td>\n",
       "      <td>50000</td>\n",
       "      <td>16000</td>\n",
       "      <td>22000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MachineID</th>\n",
       "      <td>1126363</td>\n",
       "      <td>1194089</td>\n",
       "      <td>1473654</td>\n",
       "      <td>1327630</td>\n",
       "      <td>1336053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ModelID</th>\n",
       "      <td>8434</td>\n",
       "      <td>10150</td>\n",
       "      <td>4139</td>\n",
       "      <td>8591</td>\n",
       "      <td>4089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>datasource</th>\n",
       "      <td>132</td>\n",
       "      <td>132</td>\n",
       "      <td>132</td>\n",
       "      <td>132</td>\n",
       "      <td>132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>auctioneerID</th>\n",
       "      <td>18</td>\n",
       "      <td>99</td>\n",
       "      <td>99</td>\n",
       "      <td>99</td>\n",
       "      <td>99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YearMade</th>\n",
       "      <td>1974</td>\n",
       "      <td>1980</td>\n",
       "      <td>1978</td>\n",
       "      <td>1980</td>\n",
       "      <td>1984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MachineHoursCurrentMeter</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UsageBand</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saledate</th>\n",
       "      <td>1989-01-17 00:00:00</td>\n",
       "      <td>1989-01-31 00:00:00</td>\n",
       "      <td>1989-01-31 00:00:00</td>\n",
       "      <td>1989-01-31 00:00:00</td>\n",
       "      <td>1989-01-31 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fiModelDesc</th>\n",
       "      <td>TD20</td>\n",
       "      <td>A66</td>\n",
       "      <td>D7G</td>\n",
       "      <td>A62</td>\n",
       "      <td>D3B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fiBaseModel</th>\n",
       "      <td>TD20</td>\n",
       "      <td>A66</td>\n",
       "      <td>D7</td>\n",
       "      <td>A62</td>\n",
       "      <td>D3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fiSecondaryDesc</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>G</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fiModelSeries</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fiModelDescriptor</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ProductSize</th>\n",
       "      <td>Medium</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Large</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fiProductClassDesc</th>\n",
       "      <td>Track Type Tractor, Dozer - 105.0 to 130.0 Hor...</td>\n",
       "      <td>Wheel Loader - 120.0 to 135.0 Horsepower</td>\n",
       "      <td>Track Type Tractor, Dozer - 190.0 to 260.0 Hor...</td>\n",
       "      <td>Wheel Loader - Unidentified</td>\n",
       "      <td>Track Type Tractor, Dozer - 20.0 to 75.0 Horse...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state</th>\n",
       "      <td>Texas</td>\n",
       "      <td>Florida</td>\n",
       "      <td>Florida</td>\n",
       "      <td>Florida</td>\n",
       "      <td>Florida</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ProductGroup</th>\n",
       "      <td>TTT</td>\n",
       "      <td>WL</td>\n",
       "      <td>TTT</td>\n",
       "      <td>WL</td>\n",
       "      <td>TTT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ProductGroupDesc</th>\n",
       "      <td>Track Type Tractors</td>\n",
       "      <td>Wheel Loader</td>\n",
       "      <td>Track Type Tractors</td>\n",
       "      <td>Wheel Loader</td>\n",
       "      <td>Track Type Tractors</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Drive_System</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Enclosure</th>\n",
       "      <td>OROPS</td>\n",
       "      <td>OROPS</td>\n",
       "      <td>OROPS</td>\n",
       "      <td>EROPS</td>\n",
       "      <td>OROPS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Forks</th>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pad_Type</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ride_Control</th>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Stick</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Transmission</th>\n",
       "      <td>Direct Drive</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Standard</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Standard</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Turbocharged</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Blade_Extension</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Blade_Width</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Enclosure_Type</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Engine_Horsepower</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hydraulics</th>\n",
       "      <td>2 Valve</td>\n",
       "      <td>2 Valve</td>\n",
       "      <td>2 Valve</td>\n",
       "      <td>2 Valve</td>\n",
       "      <td>2 Valve</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pushblock</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ripper</th>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Scarifier</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tip_Control</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tire_Size</th>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Coupler</th>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Coupler_System</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Grouser_Tracks</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hydraulics_Flow</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Track_Type</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Undercarriage_Pad_Width</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Stick_Length</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thumb</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pattern_Changer</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Grouser_Type</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Backhoe_Mounting</th>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Blade_Type</th>\n",
       "      <td>Straight</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Straight</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PAT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Travel_Controls</th>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lever</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Differential_Type</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Standard</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Standard</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Steering_Controls</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Conventional</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Conventional</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saleYear</th>\n",
       "      <td>1989</td>\n",
       "      <td>1989</td>\n",
       "      <td>1989</td>\n",
       "      <td>1989</td>\n",
       "      <td>1989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saleMonth</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saleDay</th>\n",
       "      <td>17</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saleDayOfWeek</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saleDayOfYear</th>\n",
       "      <td>17</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                     205615  \\\n",
       "SalesID                                                             1646770   \n",
       "SalePrice                                                              9500   \n",
       "MachineID                                                           1126363   \n",
       "ModelID                                                                8434   \n",
       "datasource                                                              132   \n",
       "auctioneerID                                                             18   \n",
       "YearMade                                                               1974   \n",
       "MachineHoursCurrentMeter                                                NaN   \n",
       "UsageBand                                                               NaN   \n",
       "saledate                                                1989-01-17 00:00:00   \n",
       "fiModelDesc                                                            TD20   \n",
       "fiBaseModel                                                            TD20   \n",
       "fiSecondaryDesc                                                         NaN   \n",
       "fiModelSeries                                                           NaN   \n",
       "fiModelDescriptor                                                       NaN   \n",
       "ProductSize                                                          Medium   \n",
       "fiProductClassDesc        Track Type Tractor, Dozer - 105.0 to 130.0 Hor...   \n",
       "state                                                                 Texas   \n",
       "ProductGroup                                                            TTT   \n",
       "ProductGroupDesc                                        Track Type Tractors   \n",
       "Drive_System                                                            NaN   \n",
       "Enclosure                                                             OROPS   \n",
       "Forks                                                                   NaN   \n",
       "Pad_Type                                                                NaN   \n",
       "Ride_Control                                                            NaN   \n",
       "Stick                                                                   NaN   \n",
       "Transmission                                                   Direct Drive   \n",
       "Turbocharged                                                            NaN   \n",
       "Blade_Extension                                                         NaN   \n",
       "Blade_Width                                                             NaN   \n",
       "Enclosure_Type                                                          NaN   \n",
       "Engine_Horsepower                                                       NaN   \n",
       "Hydraulics                                                          2 Valve   \n",
       "Pushblock                                                               NaN   \n",
       "Ripper                                                  None or Unspecified   \n",
       "Scarifier                                                               NaN   \n",
       "Tip_Control                                                             NaN   \n",
       "Tire_Size                                                               NaN   \n",
       "Coupler                                                                 NaN   \n",
       "Coupler_System                                                          NaN   \n",
       "Grouser_Tracks                                                          NaN   \n",
       "Hydraulics_Flow                                                         NaN   \n",
       "Track_Type                                                              NaN   \n",
       "Undercarriage_Pad_Width                                                 NaN   \n",
       "Stick_Length                                                            NaN   \n",
       "Thumb                                                                   NaN   \n",
       "Pattern_Changer                                                         NaN   \n",
       "Grouser_Type                                                            NaN   \n",
       "Backhoe_Mounting                                        None or Unspecified   \n",
       "Blade_Type                                                         Straight   \n",
       "Travel_Controls                                         None or Unspecified   \n",
       "Differential_Type                                                       NaN   \n",
       "Steering_Controls                                                       NaN   \n",
       "saleYear                                                               1989   \n",
       "saleMonth                                                                 1   \n",
       "saleDay                                                                  17   \n",
       "saleDayOfWeek                                                             1   \n",
       "saleDayOfYear                                                            17   \n",
       "\n",
       "                                                            274835  \\\n",
       "SalesID                                                    1821514   \n",
       "SalePrice                                                    14000   \n",
       "MachineID                                                  1194089   \n",
       "ModelID                                                      10150   \n",
       "datasource                                                     132   \n",
       "auctioneerID                                                    99   \n",
       "YearMade                                                      1980   \n",
       "MachineHoursCurrentMeter                                       NaN   \n",
       "UsageBand                                                      NaN   \n",
       "saledate                                       1989-01-31 00:00:00   \n",
       "fiModelDesc                                                    A66   \n",
       "fiBaseModel                                                    A66   \n",
       "fiSecondaryDesc                                                NaN   \n",
       "fiModelSeries                                                  NaN   \n",
       "fiModelDescriptor                                              NaN   \n",
       "ProductSize                                                    NaN   \n",
       "fiProductClassDesc        Wheel Loader - 120.0 to 135.0 Horsepower   \n",
       "state                                                      Florida   \n",
       "ProductGroup                                                    WL   \n",
       "ProductGroupDesc                                      Wheel Loader   \n",
       "Drive_System                                                   NaN   \n",
       "Enclosure                                                    OROPS   \n",
       "Forks                                          None or Unspecified   \n",
       "Pad_Type                                                       NaN   \n",
       "Ride_Control                                   None or Unspecified   \n",
       "Stick                                                          NaN   \n",
       "Transmission                                                   NaN   \n",
       "Turbocharged                                                   NaN   \n",
       "Blade_Extension                                                NaN   \n",
       "Blade_Width                                                    NaN   \n",
       "Enclosure_Type                                                 NaN   \n",
       "Engine_Horsepower                                              NaN   \n",
       "Hydraulics                                                 2 Valve   \n",
       "Pushblock                                                      NaN   \n",
       "Ripper                                                         NaN   \n",
       "Scarifier                                                      NaN   \n",
       "Tip_Control                                                    NaN   \n",
       "Tire_Size                                      None or Unspecified   \n",
       "Coupler                                        None or Unspecified   \n",
       "Coupler_System                                                 NaN   \n",
       "Grouser_Tracks                                                 NaN   \n",
       "Hydraulics_Flow                                                NaN   \n",
       "Track_Type                                                     NaN   \n",
       "Undercarriage_Pad_Width                                        NaN   \n",
       "Stick_Length                                                   NaN   \n",
       "Thumb                                                          NaN   \n",
       "Pattern_Changer                                                NaN   \n",
       "Grouser_Type                                                   NaN   \n",
       "Backhoe_Mounting                                               NaN   \n",
       "Blade_Type                                                     NaN   \n",
       "Travel_Controls                                                NaN   \n",
       "Differential_Type                                         Standard   \n",
       "Steering_Controls                                     Conventional   \n",
       "saleYear                                                      1989   \n",
       "saleMonth                                                        1   \n",
       "saleDay                                                         31   \n",
       "saleDayOfWeek                                                    1   \n",
       "saleDayOfYear                                                   31   \n",
       "\n",
       "                                                                     141296  \\\n",
       "SalesID                                                             1505138   \n",
       "SalePrice                                                             50000   \n",
       "MachineID                                                           1473654   \n",
       "ModelID                                                                4139   \n",
       "datasource                                                              132   \n",
       "auctioneerID                                                             99   \n",
       "YearMade                                                               1978   \n",
       "MachineHoursCurrentMeter                                                NaN   \n",
       "UsageBand                                                               NaN   \n",
       "saledate                                                1989-01-31 00:00:00   \n",
       "fiModelDesc                                                             D7G   \n",
       "fiBaseModel                                                              D7   \n",
       "fiSecondaryDesc                                                           G   \n",
       "fiModelSeries                                                           NaN   \n",
       "fiModelDescriptor                                                       NaN   \n",
       "ProductSize                                                           Large   \n",
       "fiProductClassDesc        Track Type Tractor, Dozer - 190.0 to 260.0 Hor...   \n",
       "state                                                               Florida   \n",
       "ProductGroup                                                            TTT   \n",
       "ProductGroupDesc                                        Track Type Tractors   \n",
       "Drive_System                                                            NaN   \n",
       "Enclosure                                                             OROPS   \n",
       "Forks                                                                   NaN   \n",
       "Pad_Type                                                                NaN   \n",
       "Ride_Control                                                            NaN   \n",
       "Stick                                                                   NaN   \n",
       "Transmission                                                       Standard   \n",
       "Turbocharged                                                            NaN   \n",
       "Blade_Extension                                                         NaN   \n",
       "Blade_Width                                                             NaN   \n",
       "Enclosure_Type                                                          NaN   \n",
       "Engine_Horsepower                                                       NaN   \n",
       "Hydraulics                                                          2 Valve   \n",
       "Pushblock                                                               NaN   \n",
       "Ripper                                                  None or Unspecified   \n",
       "Scarifier                                                               NaN   \n",
       "Tip_Control                                                             NaN   \n",
       "Tire_Size                                                               NaN   \n",
       "Coupler                                                                 NaN   \n",
       "Coupler_System                                                          NaN   \n",
       "Grouser_Tracks                                                          NaN   \n",
       "Hydraulics_Flow                                                         NaN   \n",
       "Track_Type                                                              NaN   \n",
       "Undercarriage_Pad_Width                                                 NaN   \n",
       "Stick_Length                                                            NaN   \n",
       "Thumb                                                                   NaN   \n",
       "Pattern_Changer                                                         NaN   \n",
       "Grouser_Type                                                            NaN   \n",
       "Backhoe_Mounting                                        None or Unspecified   \n",
       "Blade_Type                                                         Straight   \n",
       "Travel_Controls                                         None or Unspecified   \n",
       "Differential_Type                                                       NaN   \n",
       "Steering_Controls                                                       NaN   \n",
       "saleYear                                                               1989   \n",
       "saleMonth                                                                 1   \n",
       "saleDay                                                                  31   \n",
       "saleDayOfWeek                                                             1   \n",
       "saleDayOfYear                                                            31   \n",
       "\n",
       "                                               212552  \\\n",
       "SalesID                                       1671174   \n",
       "SalePrice                                       16000   \n",
       "MachineID                                     1327630   \n",
       "ModelID                                          8591   \n",
       "datasource                                        132   \n",
       "auctioneerID                                       99   \n",
       "YearMade                                         1980   \n",
       "MachineHoursCurrentMeter                          NaN   \n",
       "UsageBand                                         NaN   \n",
       "saledate                          1989-01-31 00:00:00   \n",
       "fiModelDesc                                       A62   \n",
       "fiBaseModel                                       A62   \n",
       "fiSecondaryDesc                                   NaN   \n",
       "fiModelSeries                                     NaN   \n",
       "fiModelDescriptor                                 NaN   \n",
       "ProductSize                                       NaN   \n",
       "fiProductClassDesc        Wheel Loader - Unidentified   \n",
       "state                                         Florida   \n",
       "ProductGroup                                       WL   \n",
       "ProductGroupDesc                         Wheel Loader   \n",
       "Drive_System                                      NaN   \n",
       "Enclosure                                       EROPS   \n",
       "Forks                             None or Unspecified   \n",
       "Pad_Type                                          NaN   \n",
       "Ride_Control                      None or Unspecified   \n",
       "Stick                                             NaN   \n",
       "Transmission                                      NaN   \n",
       "Turbocharged                                      NaN   \n",
       "Blade_Extension                                   NaN   \n",
       "Blade_Width                                       NaN   \n",
       "Enclosure_Type                                    NaN   \n",
       "Engine_Horsepower                                 NaN   \n",
       "Hydraulics                                    2 Valve   \n",
       "Pushblock                                         NaN   \n",
       "Ripper                                            NaN   \n",
       "Scarifier                                         NaN   \n",
       "Tip_Control                                       NaN   \n",
       "Tire_Size                         None or Unspecified   \n",
       "Coupler                           None or Unspecified   \n",
       "Coupler_System                                    NaN   \n",
       "Grouser_Tracks                                    NaN   \n",
       "Hydraulics_Flow                                   NaN   \n",
       "Track_Type                                        NaN   \n",
       "Undercarriage_Pad_Width                           NaN   \n",
       "Stick_Length                                      NaN   \n",
       "Thumb                                             NaN   \n",
       "Pattern_Changer                                   NaN   \n",
       "Grouser_Type                                      NaN   \n",
       "Backhoe_Mounting                                  NaN   \n",
       "Blade_Type                                        NaN   \n",
       "Travel_Controls                                   NaN   \n",
       "Differential_Type                            Standard   \n",
       "Steering_Controls                        Conventional   \n",
       "saleYear                                         1989   \n",
       "saleMonth                                           1   \n",
       "saleDay                                            31   \n",
       "saleDayOfWeek                                       1   \n",
       "saleDayOfYear                                      31   \n",
       "\n",
       "                                                                     62755   \n",
       "SalesID                                                             1329056  \n",
       "SalePrice                                                             22000  \n",
       "MachineID                                                           1336053  \n",
       "ModelID                                                                4089  \n",
       "datasource                                                              132  \n",
       "auctioneerID                                                             99  \n",
       "YearMade                                                               1984  \n",
       "MachineHoursCurrentMeter                                                NaN  \n",
       "UsageBand                                                               NaN  \n",
       "saledate                                                1989-01-31 00:00:00  \n",
       "fiModelDesc                                                             D3B  \n",
       "fiBaseModel                                                              D3  \n",
       "fiSecondaryDesc                                                           B  \n",
       "fiModelSeries                                                           NaN  \n",
       "fiModelDescriptor                                                       NaN  \n",
       "ProductSize                                                             NaN  \n",
       "fiProductClassDesc        Track Type Tractor, Dozer - 20.0 to 75.0 Horse...  \n",
       "state                                                               Florida  \n",
       "ProductGroup                                                            TTT  \n",
       "ProductGroupDesc                                        Track Type Tractors  \n",
       "Drive_System                                                            NaN  \n",
       "Enclosure                                                             OROPS  \n",
       "Forks                                                                   NaN  \n",
       "Pad_Type                                                                NaN  \n",
       "Ride_Control                                                            NaN  \n",
       "Stick                                                                   NaN  \n",
       "Transmission                                                       Standard  \n",
       "Turbocharged                                                            NaN  \n",
       "Blade_Extension                                                         NaN  \n",
       "Blade_Width                                                             NaN  \n",
       "Enclosure_Type                                                          NaN  \n",
       "Engine_Horsepower                                                       NaN  \n",
       "Hydraulics                                                          2 Valve  \n",
       "Pushblock                                                               NaN  \n",
       "Ripper                                                  None or Unspecified  \n",
       "Scarifier                                                               NaN  \n",
       "Tip_Control                                                             NaN  \n",
       "Tire_Size                                                               NaN  \n",
       "Coupler                                                                 NaN  \n",
       "Coupler_System                                                          NaN  \n",
       "Grouser_Tracks                                                          NaN  \n",
       "Hydraulics_Flow                                                         NaN  \n",
       "Track_Type                                                              NaN  \n",
       "Undercarriage_Pad_Width                                                 NaN  \n",
       "Stick_Length                                                            NaN  \n",
       "Thumb                                                                   NaN  \n",
       "Pattern_Changer                                                         NaN  \n",
       "Grouser_Type                                                            NaN  \n",
       "Backhoe_Mounting                                        None or Unspecified  \n",
       "Blade_Type                                                              PAT  \n",
       "Travel_Controls                                                       Lever  \n",
       "Differential_Type                                                       NaN  \n",
       "Steering_Controls                                                       NaN  \n",
       "saleYear                                                               1989  \n",
       "saleMonth                                                                 1  \n",
       "saleDay                                                                  31  \n",
       "saleDayOfWeek                                                             1  \n",
       "saleDayOfYear                                                            31  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tmp.head().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Now we've enriched our DataFrame with date time features, we can remove 'saledate'\n",
    "df_tmp.drop(\"saledate\", axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Florida           67320\n",
       "Texas             53110\n",
       "California        29761\n",
       "Washington        16222\n",
       "Georgia           14633\n",
       "Maryland          13322\n",
       "Mississippi       13240\n",
       "Ohio              12369\n",
       "Illinois          11540\n",
       "Colorado          11529\n",
       "New Jersey        11156\n",
       "North Carolina    10636\n",
       "Tennessee         10298\n",
       "Alabama           10292\n",
       "Pennsylvania      10234\n",
       "South Carolina     9951\n",
       "Arizona            9364\n",
       "New York           8639\n",
       "Connecticut        8276\n",
       "Minnesota          7885\n",
       "Missouri           7178\n",
       "Nevada             6932\n",
       "Louisiana          6627\n",
       "Kentucky           5351\n",
       "Maine              5096\n",
       "Indiana            4124\n",
       "Arkansas           3933\n",
       "New Mexico         3631\n",
       "Utah               3046\n",
       "Unspecified        2801\n",
       "Wisconsin          2745\n",
       "New Hampshire      2738\n",
       "Virginia           2353\n",
       "Idaho              2025\n",
       "Oregon             1911\n",
       "Michigan           1831\n",
       "Wyoming            1672\n",
       "Iowa               1336\n",
       "Montana            1336\n",
       "Oklahoma           1326\n",
       "Nebraska            866\n",
       "West Virginia       840\n",
       "Kansas              667\n",
       "Delaware            510\n",
       "North Dakota        480\n",
       "Alaska              430\n",
       "Massachusetts       347\n",
       "Vermont             300\n",
       "South Dakota        244\n",
       "Hawaii              118\n",
       "Rhode Island         83\n",
       "Puerto Rico          42\n",
       "Washington DC         2\n",
       "Name: state, dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check the values of different columns\n",
    "df_tmp.state.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>fiModelDesc</th>\n",
       "      <th>...</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>saleYear</th>\n",
       "      <th>saleMonth</th>\n",
       "      <th>saleDay</th>\n",
       "      <th>saleDayOfWeek</th>\n",
       "      <th>saleDayOfYear</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>205615</th>\n",
       "      <td>1646770</td>\n",
       "      <td>9500.0</td>\n",
       "      <td>1126363</td>\n",
       "      <td>8434</td>\n",
       "      <td>132</td>\n",
       "      <td>18.0</td>\n",
       "      <td>1974</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TD20</td>\n",
       "      <td>...</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>Straight</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1989</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>274835</th>\n",
       "      <td>1821514</td>\n",
       "      <td>14000.0</td>\n",
       "      <td>1194089</td>\n",
       "      <td>10150</td>\n",
       "      <td>132</td>\n",
       "      <td>99.0</td>\n",
       "      <td>1980</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A66</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Conventional</td>\n",
       "      <td>1989</td>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141296</th>\n",
       "      <td>1505138</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>1473654</td>\n",
       "      <td>4139</td>\n",
       "      <td>132</td>\n",
       "      <td>99.0</td>\n",
       "      <td>1978</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>D7G</td>\n",
       "      <td>...</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>Straight</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1989</td>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>212552</th>\n",
       "      <td>1671174</td>\n",
       "      <td>16000.0</td>\n",
       "      <td>1327630</td>\n",
       "      <td>8591</td>\n",
       "      <td>132</td>\n",
       "      <td>99.0</td>\n",
       "      <td>1980</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A62</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Conventional</td>\n",
       "      <td>1989</td>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62755</th>\n",
       "      <td>1329056</td>\n",
       "      <td>22000.0</td>\n",
       "      <td>1336053</td>\n",
       "      <td>4089</td>\n",
       "      <td>132</td>\n",
       "      <td>99.0</td>\n",
       "      <td>1984</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>D3B</td>\n",
       "      <td>...</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>PAT</td>\n",
       "      <td>Lever</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1989</td>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 57 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        SalesID  SalePrice  MachineID  ModelID  datasource  auctioneerID  \\\n",
       "205615  1646770     9500.0    1126363     8434         132          18.0   \n",
       "274835  1821514    14000.0    1194089    10150         132          99.0   \n",
       "141296  1505138    50000.0    1473654     4139         132          99.0   \n",
       "212552  1671174    16000.0    1327630     8591         132          99.0   \n",
       "62755   1329056    22000.0    1336053     4089         132          99.0   \n",
       "\n",
       "        YearMade  MachineHoursCurrentMeter UsageBand fiModelDesc  ...  \\\n",
       "205615      1974                       NaN       NaN        TD20  ...   \n",
       "274835      1980                       NaN       NaN         A66  ...   \n",
       "141296      1978                       NaN       NaN         D7G  ...   \n",
       "212552      1980                       NaN       NaN         A62  ...   \n",
       "62755       1984                       NaN       NaN         D3B  ...   \n",
       "\n",
       "           Backhoe_Mounting Blade_Type      Travel_Controls Differential_Type  \\\n",
       "205615  None or Unspecified   Straight  None or Unspecified               NaN   \n",
       "274835                  NaN        NaN                  NaN          Standard   \n",
       "141296  None or Unspecified   Straight  None or Unspecified               NaN   \n",
       "212552                  NaN        NaN                  NaN          Standard   \n",
       "62755   None or Unspecified        PAT                Lever               NaN   \n",
       "\n",
       "       Steering_Controls saleYear saleMonth saleDay saleDayOfWeek  \\\n",
       "205615               NaN     1989         1      17             1   \n",
       "274835      Conventional     1989         1      31             1   \n",
       "141296               NaN     1989         1      31             1   \n",
       "212552      Conventional     1989         1      31             1   \n",
       "62755                NaN     1989         1      31             1   \n",
       "\n",
       "       saleDayOfYear  \n",
       "205615            17  \n",
       "274835            31  \n",
       "141296            31  \n",
       "212552            31  \n",
       "62755             31  \n",
       "\n",
       "[5 rows x 57 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tmp.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "412698"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_tmp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Modelling \n",
    "\n",
    "We've done enough EDA (we could always do more) but let's start to do some model-driven EDA."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "could not convert string to float: 'Low'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m        Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-26-cd4fbc98a101>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      5\u001b[0m                               random_state=42)\n\u001b[1;32m      6\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf_tmp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"SalePrice\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdf_tmp\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"SalePrice\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/usr/local/lib/python3.7/site-packages/sklearn/ensemble/_forest.py\u001b[0m in \u001b[0;36mfit\u001b[0;34m(self, X, y, sample_weight)\u001b[0m\n\u001b[1;32m    302\u001b[0m             )\n\u001b[1;32m    303\u001b[0m         X, y = self._validate_data(X, y, multi_output=True,\n\u001b[0;32m--> 304\u001b[0;31m                                    accept_sparse=\"csc\", dtype=DTYPE)\n\u001b[0m\u001b[1;32m    305\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0msample_weight\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    306\u001b[0m             \u001b[0msample_weight\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_check_sample_weight\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msample_weight\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.7/site-packages/sklearn/base.py\u001b[0m in \u001b[0;36m_validate_data\u001b[0;34m(self, X, y, reset, validate_separately, **check_params)\u001b[0m\n\u001b[1;32m    430\u001b[0m                 \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcheck_array\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mcheck_y_params\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    431\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 432\u001b[0;31m                 \u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcheck_X_y\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mcheck_params\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    433\u001b[0m             \u001b[0mout\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    434\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.7/site-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36minner_f\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     71\u001b[0m                           FutureWarning)\n\u001b[1;32m     72\u001b[0m         \u001b[0mkwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0marg\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0marg\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mparameters\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 73\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     74\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0minner_f\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     75\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.7/site-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36mcheck_X_y\u001b[0;34m(X, y, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, multi_output, ensure_min_samples, ensure_min_features, y_numeric, estimator)\u001b[0m\n\u001b[1;32m    801\u001b[0m                     \u001b[0mensure_min_samples\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mensure_min_samples\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    802\u001b[0m                     \u001b[0mensure_min_features\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mensure_min_features\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 803\u001b[0;31m                     estimator=estimator)\n\u001b[0m\u001b[1;32m    804\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mmulti_output\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    805\u001b[0m         y = check_array(y, accept_sparse='csr', force_all_finite=True,\n",
      "\u001b[0;32m/usr/local/lib/python3.7/site-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36minner_f\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     71\u001b[0m                           FutureWarning)\n\u001b[1;32m     72\u001b[0m         \u001b[0mkwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0marg\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0marg\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mparameters\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 73\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     74\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0minner_f\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     75\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.7/site-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36mcheck_array\u001b[0;34m(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, estimator)\u001b[0m\n\u001b[1;32m    597\u001b[0m                     \u001b[0marray\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0marray\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcasting\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"unsafe\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    598\u001b[0m                 \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 599\u001b[0;31m                     \u001b[0marray\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0masarray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0morder\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0morder\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    600\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mComplexWarning\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    601\u001b[0m                 raise ValueError(\"Complex data not supported\\n\"\n",
      "\u001b[0;32m/usr/local/lib/python3.7/site-packages/numpy/core/_asarray.py\u001b[0m in \u001b[0;36masarray\u001b[0;34m(a, dtype, order)\u001b[0m\n\u001b[1;32m     83\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     84\u001b[0m     \"\"\"\n\u001b[0;32m---> 85\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0morder\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0morder\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     86\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     87\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: could not convert string to float: 'Low'"
     ]
    }
   ],
   "source": [
    "# Let's build a machine learning model \n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "\n",
    "model = RandomForestRegressor(n_jobs=-1,\n",
    "                              random_state=42)\n",
    "\n",
    "model.fit(df_tmp.drop(\"SalePrice\", axis=1), df_tmp[\"SalePrice\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 412698 entries, 205615 to 409203\n",
      "Data columns (total 57 columns):\n",
      "SalesID                     412698 non-null int64\n",
      "SalePrice                   412698 non-null float64\n",
      "MachineID                   412698 non-null int64\n",
      "ModelID                     412698 non-null int64\n",
      "datasource                  412698 non-null int64\n",
      "auctioneerID                392562 non-null float64\n",
      "YearMade                    412698 non-null int64\n",
      "MachineHoursCurrentMeter    147504 non-null float64\n",
      "UsageBand                   73670 non-null object\n",
      "fiModelDesc                 412698 non-null object\n",
      "fiBaseModel                 412698 non-null object\n",
      "fiSecondaryDesc             271971 non-null object\n",
      "fiModelSeries               58667 non-null object\n",
      "fiModelDescriptor           74816 non-null object\n",
      "ProductSize                 196093 non-null object\n",
      "fiProductClassDesc          412698 non-null object\n",
      "state                       412698 non-null object\n",
      "ProductGroup                412698 non-null object\n",
      "ProductGroupDesc            412698 non-null object\n",
      "Drive_System                107087 non-null object\n",
      "Enclosure                   412364 non-null object\n",
      "Forks                       197715 non-null object\n",
      "Pad_Type                    81096 non-null object\n",
      "Ride_Control                152728 non-null object\n",
      "Stick                       81096 non-null object\n",
      "Transmission                188007 non-null object\n",
      "Turbocharged                81096 non-null object\n",
      "Blade_Extension             25983 non-null object\n",
      "Blade_Width                 25983 non-null object\n",
      "Enclosure_Type              25983 non-null object\n",
      "Engine_Horsepower           25983 non-null object\n",
      "Hydraulics                  330133 non-null object\n",
      "Pushblock                   25983 non-null object\n",
      "Ripper                      106945 non-null object\n",
      "Scarifier                   25994 non-null object\n",
      "Tip_Control                 25983 non-null object\n",
      "Tire_Size                   97638 non-null object\n",
      "Coupler                     220679 non-null object\n",
      "Coupler_System              44974 non-null object\n",
      "Grouser_Tracks              44875 non-null object\n",
      "Hydraulics_Flow             44875 non-null object\n",
      "Track_Type                  102193 non-null object\n",
      "Undercarriage_Pad_Width     102916 non-null object\n",
      "Stick_Length                102261 non-null object\n",
      "Thumb                       102332 non-null object\n",
      "Pattern_Changer             102261 non-null object\n",
      "Grouser_Type                102193 non-null object\n",
      "Backhoe_Mounting            80712 non-null object\n",
      "Blade_Type                  81875 non-null object\n",
      "Travel_Controls             81877 non-null object\n",
      "Differential_Type           71564 non-null object\n",
      "Steering_Controls           71522 non-null object\n",
      "saleYear                    412698 non-null int64\n",
      "saleMonth                   412698 non-null int64\n",
      "saleDay                     412698 non-null int64\n",
      "saleDayOfWeek               412698 non-null int64\n",
      "saleDayOfYear               412698 non-null int64\n",
      "dtypes: float64(3), int64(10), object(44)\n",
      "memory usage: 182.6+ MB\n"
     ]
    }
   ],
   "source": [
    "df_tmp.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('O')"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tmp[\"UsageBand\"].dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SalesID                          0\n",
       "SalePrice                        0\n",
       "MachineID                        0\n",
       "ModelID                          0\n",
       "datasource                       0\n",
       "auctioneerID                 20136\n",
       "YearMade                         0\n",
       "MachineHoursCurrentMeter    265194\n",
       "UsageBand                   339028\n",
       "fiModelDesc                      0\n",
       "fiBaseModel                      0\n",
       "fiSecondaryDesc             140727\n",
       "fiModelSeries               354031\n",
       "fiModelDescriptor           337882\n",
       "ProductSize                 216605\n",
       "fiProductClassDesc               0\n",
       "state                            0\n",
       "ProductGroup                     0\n",
       "ProductGroupDesc                 0\n",
       "Drive_System                305611\n",
       "Enclosure                      334\n",
       "Forks                       214983\n",
       "Pad_Type                    331602\n",
       "Ride_Control                259970\n",
       "Stick                       331602\n",
       "Transmission                224691\n",
       "Turbocharged                331602\n",
       "Blade_Extension             386715\n",
       "Blade_Width                 386715\n",
       "Enclosure_Type              386715\n",
       "Engine_Horsepower           386715\n",
       "Hydraulics                   82565\n",
       "Pushblock                   386715\n",
       "Ripper                      305753\n",
       "Scarifier                   386704\n",
       "Tip_Control                 386715\n",
       "Tire_Size                   315060\n",
       "Coupler                     192019\n",
       "Coupler_System              367724\n",
       "Grouser_Tracks              367823\n",
       "Hydraulics_Flow             367823\n",
       "Track_Type                  310505\n",
       "Undercarriage_Pad_Width     309782\n",
       "Stick_Length                310437\n",
       "Thumb                       310366\n",
       "Pattern_Changer             310437\n",
       "Grouser_Type                310505\n",
       "Backhoe_Mounting            331986\n",
       "Blade_Type                  330823\n",
       "Travel_Controls             330821\n",
       "Differential_Type           341134\n",
       "Steering_Controls           341176\n",
       "saleYear                         0\n",
       "saleMonth                        0\n",
       "saleDay                          0\n",
       "saleDayOfWeek                    0\n",
       "saleDayOfYear                    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tmp.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Convert string to categories\n",
    "\n",
    "One way we can turn all of our data into numbers is by converting them into pandas catgories.\n",
    "\n",
    "We can check the different datatypes compatible with pandas here: https://pandas.pydata.org/pandas-docs/stable/reference/general_utility_functions.html#data-types-related-functionality"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>205615</th>\n",
       "      <th>274835</th>\n",
       "      <th>141296</th>\n",
       "      <th>212552</th>\n",
       "      <th>62755</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>SalesID</th>\n",
       "      <td>1646770</td>\n",
       "      <td>1821514</td>\n",
       "      <td>1505138</td>\n",
       "      <td>1671174</td>\n",
       "      <td>1329056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SalePrice</th>\n",
       "      <td>9500</td>\n",
       "      <td>14000</td>\n",
       "      <td>50000</td>\n",
       "      <td>16000</td>\n",
       "      <td>22000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MachineID</th>\n",
       "      <td>1126363</td>\n",
       "      <td>1194089</td>\n",
       "      <td>1473654</td>\n",
       "      <td>1327630</td>\n",
       "      <td>1336053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ModelID</th>\n",
       "      <td>8434</td>\n",
       "      <td>10150</td>\n",
       "      <td>4139</td>\n",
       "      <td>8591</td>\n",
       "      <td>4089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>datasource</th>\n",
       "      <td>132</td>\n",
       "      <td>132</td>\n",
       "      <td>132</td>\n",
       "      <td>132</td>\n",
       "      <td>132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>auctioneerID</th>\n",
       "      <td>18</td>\n",
       "      <td>99</td>\n",
       "      <td>99</td>\n",
       "      <td>99</td>\n",
       "      <td>99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YearMade</th>\n",
       "      <td>1974</td>\n",
       "      <td>1980</td>\n",
       "      <td>1978</td>\n",
       "      <td>1980</td>\n",
       "      <td>1984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MachineHoursCurrentMeter</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UsageBand</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fiModelDesc</th>\n",
       "      <td>TD20</td>\n",
       "      <td>A66</td>\n",
       "      <td>D7G</td>\n",
       "      <td>A62</td>\n",
       "      <td>D3B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fiBaseModel</th>\n",
       "      <td>TD20</td>\n",
       "      <td>A66</td>\n",
       "      <td>D7</td>\n",
       "      <td>A62</td>\n",
       "      <td>D3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fiSecondaryDesc</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>G</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fiModelSeries</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fiModelDescriptor</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ProductSize</th>\n",
       "      <td>Medium</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Large</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fiProductClassDesc</th>\n",
       "      <td>Track Type Tractor, Dozer - 105.0 to 130.0 Hor...</td>\n",
       "      <td>Wheel Loader - 120.0 to 135.0 Horsepower</td>\n",
       "      <td>Track Type Tractor, Dozer - 190.0 to 260.0 Hor...</td>\n",
       "      <td>Wheel Loader - Unidentified</td>\n",
       "      <td>Track Type Tractor, Dozer - 20.0 to 75.0 Horse...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state</th>\n",
       "      <td>Texas</td>\n",
       "      <td>Florida</td>\n",
       "      <td>Florida</td>\n",
       "      <td>Florida</td>\n",
       "      <td>Florida</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ProductGroup</th>\n",
       "      <td>TTT</td>\n",
       "      <td>WL</td>\n",
       "      <td>TTT</td>\n",
       "      <td>WL</td>\n",
       "      <td>TTT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ProductGroupDesc</th>\n",
       "      <td>Track Type Tractors</td>\n",
       "      <td>Wheel Loader</td>\n",
       "      <td>Track Type Tractors</td>\n",
       "      <td>Wheel Loader</td>\n",
       "      <td>Track Type Tractors</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Drive_System</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Enclosure</th>\n",
       "      <td>OROPS</td>\n",
       "      <td>OROPS</td>\n",
       "      <td>OROPS</td>\n",
       "      <td>EROPS</td>\n",
       "      <td>OROPS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Forks</th>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pad_Type</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ride_Control</th>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Stick</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Transmission</th>\n",
       "      <td>Direct Drive</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Standard</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Standard</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Turbocharged</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Blade_Extension</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Blade_Width</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Enclosure_Type</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Engine_Horsepower</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hydraulics</th>\n",
       "      <td>2 Valve</td>\n",
       "      <td>2 Valve</td>\n",
       "      <td>2 Valve</td>\n",
       "      <td>2 Valve</td>\n",
       "      <td>2 Valve</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pushblock</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ripper</th>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Scarifier</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tip_Control</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tire_Size</th>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Coupler</th>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Coupler_System</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Grouser_Tracks</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hydraulics_Flow</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Track_Type</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Undercarriage_Pad_Width</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Stick_Length</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thumb</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pattern_Changer</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Grouser_Type</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Backhoe_Mounting</th>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Blade_Type</th>\n",
       "      <td>Straight</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Straight</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PAT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Travel_Controls</th>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lever</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Differential_Type</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Standard</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Standard</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Steering_Controls</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Conventional</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Conventional</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saleYear</th>\n",
       "      <td>1989</td>\n",
       "      <td>1989</td>\n",
       "      <td>1989</td>\n",
       "      <td>1989</td>\n",
       "      <td>1989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saleMonth</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saleDay</th>\n",
       "      <td>17</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saleDayOfWeek</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saleDayOfYear</th>\n",
       "      <td>17</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                     205615  \\\n",
       "SalesID                                                             1646770   \n",
       "SalePrice                                                              9500   \n",
       "MachineID                                                           1126363   \n",
       "ModelID                                                                8434   \n",
       "datasource                                                              132   \n",
       "auctioneerID                                                             18   \n",
       "YearMade                                                               1974   \n",
       "MachineHoursCurrentMeter                                                NaN   \n",
       "UsageBand                                                               NaN   \n",
       "fiModelDesc                                                            TD20   \n",
       "fiBaseModel                                                            TD20   \n",
       "fiSecondaryDesc                                                         NaN   \n",
       "fiModelSeries                                                           NaN   \n",
       "fiModelDescriptor                                                       NaN   \n",
       "ProductSize                                                          Medium   \n",
       "fiProductClassDesc        Track Type Tractor, Dozer - 105.0 to 130.0 Hor...   \n",
       "state                                                                 Texas   \n",
       "ProductGroup                                                            TTT   \n",
       "ProductGroupDesc                                        Track Type Tractors   \n",
       "Drive_System                                                            NaN   \n",
       "Enclosure                                                             OROPS   \n",
       "Forks                                                                   NaN   \n",
       "Pad_Type                                                                NaN   \n",
       "Ride_Control                                                            NaN   \n",
       "Stick                                                                   NaN   \n",
       "Transmission                                                   Direct Drive   \n",
       "Turbocharged                                                            NaN   \n",
       "Blade_Extension                                                         NaN   \n",
       "Blade_Width                                                             NaN   \n",
       "Enclosure_Type                                                          NaN   \n",
       "Engine_Horsepower                                                       NaN   \n",
       "Hydraulics                                                          2 Valve   \n",
       "Pushblock                                                               NaN   \n",
       "Ripper                                                  None or Unspecified   \n",
       "Scarifier                                                               NaN   \n",
       "Tip_Control                                                             NaN   \n",
       "Tire_Size                                                               NaN   \n",
       "Coupler                                                                 NaN   \n",
       "Coupler_System                                                          NaN   \n",
       "Grouser_Tracks                                                          NaN   \n",
       "Hydraulics_Flow                                                         NaN   \n",
       "Track_Type                                                              NaN   \n",
       "Undercarriage_Pad_Width                                                 NaN   \n",
       "Stick_Length                                                            NaN   \n",
       "Thumb                                                                   NaN   \n",
       "Pattern_Changer                                                         NaN   \n",
       "Grouser_Type                                                            NaN   \n",
       "Backhoe_Mounting                                        None or Unspecified   \n",
       "Blade_Type                                                         Straight   \n",
       "Travel_Controls                                         None or Unspecified   \n",
       "Differential_Type                                                       NaN   \n",
       "Steering_Controls                                                       NaN   \n",
       "saleYear                                                               1989   \n",
       "saleMonth                                                                 1   \n",
       "saleDay                                                                  17   \n",
       "saleDayOfWeek                                                             1   \n",
       "saleDayOfYear                                                            17   \n",
       "\n",
       "                                                            274835  \\\n",
       "SalesID                                                    1821514   \n",
       "SalePrice                                                    14000   \n",
       "MachineID                                                  1194089   \n",
       "ModelID                                                      10150   \n",
       "datasource                                                     132   \n",
       "auctioneerID                                                    99   \n",
       "YearMade                                                      1980   \n",
       "MachineHoursCurrentMeter                                       NaN   \n",
       "UsageBand                                                      NaN   \n",
       "fiModelDesc                                                    A66   \n",
       "fiBaseModel                                                    A66   \n",
       "fiSecondaryDesc                                                NaN   \n",
       "fiModelSeries                                                  NaN   \n",
       "fiModelDescriptor                                              NaN   \n",
       "ProductSize                                                    NaN   \n",
       "fiProductClassDesc        Wheel Loader - 120.0 to 135.0 Horsepower   \n",
       "state                                                      Florida   \n",
       "ProductGroup                                                    WL   \n",
       "ProductGroupDesc                                      Wheel Loader   \n",
       "Drive_System                                                   NaN   \n",
       "Enclosure                                                    OROPS   \n",
       "Forks                                          None or Unspecified   \n",
       "Pad_Type                                                       NaN   \n",
       "Ride_Control                                   None or Unspecified   \n",
       "Stick                                                          NaN   \n",
       "Transmission                                                   NaN   \n",
       "Turbocharged                                                   NaN   \n",
       "Blade_Extension                                                NaN   \n",
       "Blade_Width                                                    NaN   \n",
       "Enclosure_Type                                                 NaN   \n",
       "Engine_Horsepower                                              NaN   \n",
       "Hydraulics                                                 2 Valve   \n",
       "Pushblock                                                      NaN   \n",
       "Ripper                                                         NaN   \n",
       "Scarifier                                                      NaN   \n",
       "Tip_Control                                                    NaN   \n",
       "Tire_Size                                      None or Unspecified   \n",
       "Coupler                                        None or Unspecified   \n",
       "Coupler_System                                                 NaN   \n",
       "Grouser_Tracks                                                 NaN   \n",
       "Hydraulics_Flow                                                NaN   \n",
       "Track_Type                                                     NaN   \n",
       "Undercarriage_Pad_Width                                        NaN   \n",
       "Stick_Length                                                   NaN   \n",
       "Thumb                                                          NaN   \n",
       "Pattern_Changer                                                NaN   \n",
       "Grouser_Type                                                   NaN   \n",
       "Backhoe_Mounting                                               NaN   \n",
       "Blade_Type                                                     NaN   \n",
       "Travel_Controls                                                NaN   \n",
       "Differential_Type                                         Standard   \n",
       "Steering_Controls                                     Conventional   \n",
       "saleYear                                                      1989   \n",
       "saleMonth                                                        1   \n",
       "saleDay                                                         31   \n",
       "saleDayOfWeek                                                    1   \n",
       "saleDayOfYear                                                   31   \n",
       "\n",
       "                                                                     141296  \\\n",
       "SalesID                                                             1505138   \n",
       "SalePrice                                                             50000   \n",
       "MachineID                                                           1473654   \n",
       "ModelID                                                                4139   \n",
       "datasource                                                              132   \n",
       "auctioneerID                                                             99   \n",
       "YearMade                                                               1978   \n",
       "MachineHoursCurrentMeter                                                NaN   \n",
       "UsageBand                                                               NaN   \n",
       "fiModelDesc                                                             D7G   \n",
       "fiBaseModel                                                              D7   \n",
       "fiSecondaryDesc                                                           G   \n",
       "fiModelSeries                                                           NaN   \n",
       "fiModelDescriptor                                                       NaN   \n",
       "ProductSize                                                           Large   \n",
       "fiProductClassDesc        Track Type Tractor, Dozer - 190.0 to 260.0 Hor...   \n",
       "state                                                               Florida   \n",
       "ProductGroup                                                            TTT   \n",
       "ProductGroupDesc                                        Track Type Tractors   \n",
       "Drive_System                                                            NaN   \n",
       "Enclosure                                                             OROPS   \n",
       "Forks                                                                   NaN   \n",
       "Pad_Type                                                                NaN   \n",
       "Ride_Control                                                            NaN   \n",
       "Stick                                                                   NaN   \n",
       "Transmission                                                       Standard   \n",
       "Turbocharged                                                            NaN   \n",
       "Blade_Extension                                                         NaN   \n",
       "Blade_Width                                                             NaN   \n",
       "Enclosure_Type                                                          NaN   \n",
       "Engine_Horsepower                                                       NaN   \n",
       "Hydraulics                                                          2 Valve   \n",
       "Pushblock                                                               NaN   \n",
       "Ripper                                                  None or Unspecified   \n",
       "Scarifier                                                               NaN   \n",
       "Tip_Control                                                             NaN   \n",
       "Tire_Size                                                               NaN   \n",
       "Coupler                                                                 NaN   \n",
       "Coupler_System                                                          NaN   \n",
       "Grouser_Tracks                                                          NaN   \n",
       "Hydraulics_Flow                                                         NaN   \n",
       "Track_Type                                                              NaN   \n",
       "Undercarriage_Pad_Width                                                 NaN   \n",
       "Stick_Length                                                            NaN   \n",
       "Thumb                                                                   NaN   \n",
       "Pattern_Changer                                                         NaN   \n",
       "Grouser_Type                                                            NaN   \n",
       "Backhoe_Mounting                                        None or Unspecified   \n",
       "Blade_Type                                                         Straight   \n",
       "Travel_Controls                                         None or Unspecified   \n",
       "Differential_Type                                                       NaN   \n",
       "Steering_Controls                                                       NaN   \n",
       "saleYear                                                               1989   \n",
       "saleMonth                                                                 1   \n",
       "saleDay                                                                  31   \n",
       "saleDayOfWeek                                                             1   \n",
       "saleDayOfYear                                                            31   \n",
       "\n",
       "                                               212552  \\\n",
       "SalesID                                       1671174   \n",
       "SalePrice                                       16000   \n",
       "MachineID                                     1327630   \n",
       "ModelID                                          8591   \n",
       "datasource                                        132   \n",
       "auctioneerID                                       99   \n",
       "YearMade                                         1980   \n",
       "MachineHoursCurrentMeter                          NaN   \n",
       "UsageBand                                         NaN   \n",
       "fiModelDesc                                       A62   \n",
       "fiBaseModel                                       A62   \n",
       "fiSecondaryDesc                                   NaN   \n",
       "fiModelSeries                                     NaN   \n",
       "fiModelDescriptor                                 NaN   \n",
       "ProductSize                                       NaN   \n",
       "fiProductClassDesc        Wheel Loader - Unidentified   \n",
       "state                                         Florida   \n",
       "ProductGroup                                       WL   \n",
       "ProductGroupDesc                         Wheel Loader   \n",
       "Drive_System                                      NaN   \n",
       "Enclosure                                       EROPS   \n",
       "Forks                             None or Unspecified   \n",
       "Pad_Type                                          NaN   \n",
       "Ride_Control                      None or Unspecified   \n",
       "Stick                                             NaN   \n",
       "Transmission                                      NaN   \n",
       "Turbocharged                                      NaN   \n",
       "Blade_Extension                                   NaN   \n",
       "Blade_Width                                       NaN   \n",
       "Enclosure_Type                                    NaN   \n",
       "Engine_Horsepower                                 NaN   \n",
       "Hydraulics                                    2 Valve   \n",
       "Pushblock                                         NaN   \n",
       "Ripper                                            NaN   \n",
       "Scarifier                                         NaN   \n",
       "Tip_Control                                       NaN   \n",
       "Tire_Size                         None or Unspecified   \n",
       "Coupler                           None or Unspecified   \n",
       "Coupler_System                                    NaN   \n",
       "Grouser_Tracks                                    NaN   \n",
       "Hydraulics_Flow                                   NaN   \n",
       "Track_Type                                        NaN   \n",
       "Undercarriage_Pad_Width                           NaN   \n",
       "Stick_Length                                      NaN   \n",
       "Thumb                                             NaN   \n",
       "Pattern_Changer                                   NaN   \n",
       "Grouser_Type                                      NaN   \n",
       "Backhoe_Mounting                                  NaN   \n",
       "Blade_Type                                        NaN   \n",
       "Travel_Controls                                   NaN   \n",
       "Differential_Type                            Standard   \n",
       "Steering_Controls                        Conventional   \n",
       "saleYear                                         1989   \n",
       "saleMonth                                           1   \n",
       "saleDay                                            31   \n",
       "saleDayOfWeek                                       1   \n",
       "saleDayOfYear                                      31   \n",
       "\n",
       "                                                                     62755   \n",
       "SalesID                                                             1329056  \n",
       "SalePrice                                                             22000  \n",
       "MachineID                                                           1336053  \n",
       "ModelID                                                                4089  \n",
       "datasource                                                              132  \n",
       "auctioneerID                                                             99  \n",
       "YearMade                                                               1984  \n",
       "MachineHoursCurrentMeter                                                NaN  \n",
       "UsageBand                                                               NaN  \n",
       "fiModelDesc                                                             D3B  \n",
       "fiBaseModel                                                              D3  \n",
       "fiSecondaryDesc                                                           B  \n",
       "fiModelSeries                                                           NaN  \n",
       "fiModelDescriptor                                                       NaN  \n",
       "ProductSize                                                             NaN  \n",
       "fiProductClassDesc        Track Type Tractor, Dozer - 20.0 to 75.0 Horse...  \n",
       "state                                                               Florida  \n",
       "ProductGroup                                                            TTT  \n",
       "ProductGroupDesc                                        Track Type Tractors  \n",
       "Drive_System                                                            NaN  \n",
       "Enclosure                                                             OROPS  \n",
       "Forks                                                                   NaN  \n",
       "Pad_Type                                                                NaN  \n",
       "Ride_Control                                                            NaN  \n",
       "Stick                                                                   NaN  \n",
       "Transmission                                                       Standard  \n",
       "Turbocharged                                                            NaN  \n",
       "Blade_Extension                                                         NaN  \n",
       "Blade_Width                                                             NaN  \n",
       "Enclosure_Type                                                          NaN  \n",
       "Engine_Horsepower                                                       NaN  \n",
       "Hydraulics                                                          2 Valve  \n",
       "Pushblock                                                               NaN  \n",
       "Ripper                                                  None or Unspecified  \n",
       "Scarifier                                                               NaN  \n",
       "Tip_Control                                                             NaN  \n",
       "Tire_Size                                                               NaN  \n",
       "Coupler                                                                 NaN  \n",
       "Coupler_System                                                          NaN  \n",
       "Grouser_Tracks                                                          NaN  \n",
       "Hydraulics_Flow                                                         NaN  \n",
       "Track_Type                                                              NaN  \n",
       "Undercarriage_Pad_Width                                                 NaN  \n",
       "Stick_Length                                                            NaN  \n",
       "Thumb                                                                   NaN  \n",
       "Pattern_Changer                                                         NaN  \n",
       "Grouser_Type                                                            NaN  \n",
       "Backhoe_Mounting                                        None or Unspecified  \n",
       "Blade_Type                                                              PAT  \n",
       "Travel_Controls                                                       Lever  \n",
       "Differential_Type                                                       NaN  \n",
       "Steering_Controls                                                       NaN  \n",
       "saleYear                                                               1989  \n",
       "saleMonth                                                                 1  \n",
       "saleDay                                                                  31  \n",
       "saleDayOfWeek                                                             1  \n",
       "saleDayOfYear                                                            31  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tmp.head().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.api.types.is_string_dtype(df_tmp[\"UsageBand\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "UsageBand\n",
      "fiModelDesc\n",
      "fiBaseModel\n",
      "fiSecondaryDesc\n",
      "fiModelSeries\n",
      "fiModelDescriptor\n",
      "ProductSize\n",
      "fiProductClassDesc\n",
      "state\n",
      "ProductGroup\n",
      "ProductGroupDesc\n",
      "Drive_System\n",
      "Enclosure\n",
      "Forks\n",
      "Pad_Type\n",
      "Ride_Control\n",
      "Stick\n",
      "Transmission\n",
      "Turbocharged\n",
      "Blade_Extension\n",
      "Blade_Width\n",
      "Enclosure_Type\n",
      "Engine_Horsepower\n",
      "Hydraulics\n",
      "Pushblock\n",
      "Ripper\n",
      "Scarifier\n",
      "Tip_Control\n",
      "Tire_Size\n",
      "Coupler\n",
      "Coupler_System\n",
      "Grouser_Tracks\n",
      "Hydraulics_Flow\n",
      "Track_Type\n",
      "Undercarriage_Pad_Width\n",
      "Stick_Length\n",
      "Thumb\n",
      "Pattern_Changer\n",
      "Grouser_Type\n",
      "Backhoe_Mounting\n",
      "Blade_Type\n",
      "Travel_Controls\n",
      "Differential_Type\n",
      "Steering_Controls\n"
     ]
    }
   ],
   "source": [
    "# Find the columns which contain strings\n",
    "for label, content in df_tmp.items():\n",
    "    if pd.api.types.is_string_dtype(content):\n",
    "        print(label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this is a key: key1 this is a value: hello\n",
      "this is a key: key2 this is a value: world!\n"
     ]
    }
   ],
   "source": [
    "# If you're wondering what df.items() does, here's an example\n",
    "random_dict = {\"key1\": \"hello\",\n",
    "               \"key2\": \"world!\"}\n",
    "\n",
    "for key, value in random_dict.items():\n",
    "    print(f\"this is a key: {key}\",\n",
    "          f\"this is a value: {value}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This will turn all of the string value into category values\n",
    "for label, content in df_tmp.items():\n",
    "    if pd.api.types.is_string_dtype(content):\n",
    "        df_tmp[label] = content.astype(\"category\").cat.as_ordered()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 412698 entries, 205615 to 409203\n",
      "Data columns (total 57 columns):\n",
      "SalesID                     412698 non-null int64\n",
      "SalePrice                   412698 non-null float64\n",
      "MachineID                   412698 non-null int64\n",
      "ModelID                     412698 non-null int64\n",
      "datasource                  412698 non-null int64\n",
      "auctioneerID                392562 non-null float64\n",
      "YearMade                    412698 non-null int64\n",
      "MachineHoursCurrentMeter    147504 non-null float64\n",
      "UsageBand                   73670 non-null category\n",
      "fiModelDesc                 412698 non-null category\n",
      "fiBaseModel                 412698 non-null category\n",
      "fiSecondaryDesc             271971 non-null category\n",
      "fiModelSeries               58667 non-null category\n",
      "fiModelDescriptor           74816 non-null category\n",
      "ProductSize                 196093 non-null category\n",
      "fiProductClassDesc          412698 non-null category\n",
      "state                       412698 non-null category\n",
      "ProductGroup                412698 non-null category\n",
      "ProductGroupDesc            412698 non-null category\n",
      "Drive_System                107087 non-null category\n",
      "Enclosure                   412364 non-null category\n",
      "Forks                       197715 non-null category\n",
      "Pad_Type                    81096 non-null category\n",
      "Ride_Control                152728 non-null category\n",
      "Stick                       81096 non-null category\n",
      "Transmission                188007 non-null category\n",
      "Turbocharged                81096 non-null category\n",
      "Blade_Extension             25983 non-null category\n",
      "Blade_Width                 25983 non-null category\n",
      "Enclosure_Type              25983 non-null category\n",
      "Engine_Horsepower           25983 non-null category\n",
      "Hydraulics                  330133 non-null category\n",
      "Pushblock                   25983 non-null category\n",
      "Ripper                      106945 non-null category\n",
      "Scarifier                   25994 non-null category\n",
      "Tip_Control                 25983 non-null category\n",
      "Tire_Size                   97638 non-null category\n",
      "Coupler                     220679 non-null category\n",
      "Coupler_System              44974 non-null category\n",
      "Grouser_Tracks              44875 non-null category\n",
      "Hydraulics_Flow             44875 non-null category\n",
      "Track_Type                  102193 non-null category\n",
      "Undercarriage_Pad_Width     102916 non-null category\n",
      "Stick_Length                102261 non-null category\n",
      "Thumb                       102332 non-null category\n",
      "Pattern_Changer             102261 non-null category\n",
      "Grouser_Type                102193 non-null category\n",
      "Backhoe_Mounting            80712 non-null category\n",
      "Blade_Type                  81875 non-null category\n",
      "Travel_Controls             81877 non-null category\n",
      "Differential_Type           71564 non-null category\n",
      "Steering_Controls           71522 non-null category\n",
      "saleYear                    412698 non-null int64\n",
      "saleMonth                   412698 non-null int64\n",
      "saleDay                     412698 non-null int64\n",
      "saleDayOfWeek               412698 non-null int64\n",
      "saleDayOfYear               412698 non-null int64\n",
      "dtypes: category(44), float64(3), int64(10)\n",
      "memory usage: 63.3 MB\n"
     ]
    }
   ],
   "source": [
    "df_tmp.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Alabama', 'Alaska', 'Arizona', 'Arkansas', 'California', 'Colorado',\n",
       "       'Connecticut', 'Delaware', 'Florida', 'Georgia', 'Hawaii', 'Idaho',\n",
       "       'Illinois', 'Indiana', 'Iowa', 'Kansas', 'Kentucky', 'Louisiana',\n",
       "       'Maine', 'Maryland', 'Massachusetts', 'Michigan', 'Minnesota',\n",
       "       'Mississippi', 'Missouri', 'Montana', 'Nebraska', 'Nevada',\n",
       "       'New Hampshire', 'New Jersey', 'New Mexico', 'New York',\n",
       "       'North Carolina', 'North Dakota', 'Ohio', 'Oklahoma', 'Oregon',\n",
       "       'Pennsylvania', 'Puerto Rico', 'Rhode Island', 'South Carolina',\n",
       "       'South Dakota', 'Tennessee', 'Texas', 'Unspecified', 'Utah', 'Vermont',\n",
       "       'Virginia', 'Washington', 'Washington DC', 'West Virginia', 'Wisconsin',\n",
       "       'Wyoming'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tmp.state.cat.categories"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "205615    43\n",
       "274835     8\n",
       "141296     8\n",
       "212552     8\n",
       "62755      8\n",
       "          ..\n",
       "410879     4\n",
       "412476     4\n",
       "411927     4\n",
       "407124     4\n",
       "409203     4\n",
       "Length: 412698, dtype: int8"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tmp.state.cat.codes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Thanks to pandas Categories we now have a way to access all of our data in the form of numbers.\n",
    "\n",
    "But we still have a bunch of missing data..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SalesID                     0.000000\n",
       "SalePrice                   0.000000\n",
       "MachineID                   0.000000\n",
       "ModelID                     0.000000\n",
       "datasource                  0.000000\n",
       "auctioneerID                0.048791\n",
       "YearMade                    0.000000\n",
       "MachineHoursCurrentMeter    0.642586\n",
       "UsageBand                   0.821492\n",
       "fiModelDesc                 0.000000\n",
       "fiBaseModel                 0.000000\n",
       "fiSecondaryDesc             0.340993\n",
       "fiModelSeries               0.857845\n",
       "fiModelDescriptor           0.818715\n",
       "ProductSize                 0.524851\n",
       "fiProductClassDesc          0.000000\n",
       "state                       0.000000\n",
       "ProductGroup                0.000000\n",
       "ProductGroupDesc            0.000000\n",
       "Drive_System                0.740520\n",
       "Enclosure                   0.000809\n",
       "Forks                       0.520921\n",
       "Pad_Type                    0.803498\n",
       "Ride_Control                0.629928\n",
       "Stick                       0.803498\n",
       "Transmission                0.544444\n",
       "Turbocharged                0.803498\n",
       "Blade_Extension             0.937041\n",
       "Blade_Width                 0.937041\n",
       "Enclosure_Type              0.937041\n",
       "Engine_Horsepower           0.937041\n",
       "Hydraulics                  0.200062\n",
       "Pushblock                   0.937041\n",
       "Ripper                      0.740864\n",
       "Scarifier                   0.937014\n",
       "Tip_Control                 0.937041\n",
       "Tire_Size                   0.763415\n",
       "Coupler                     0.465277\n",
       "Coupler_System              0.891024\n",
       "Grouser_Tracks              0.891264\n",
       "Hydraulics_Flow             0.891264\n",
       "Track_Type                  0.752378\n",
       "Undercarriage_Pad_Width     0.750626\n",
       "Stick_Length                0.752213\n",
       "Thumb                       0.752041\n",
       "Pattern_Changer             0.752213\n",
       "Grouser_Type                0.752378\n",
       "Backhoe_Mounting            0.804428\n",
       "Blade_Type                  0.801610\n",
       "Travel_Controls             0.801606\n",
       "Differential_Type           0.826595\n",
       "Steering_Controls           0.826697\n",
       "saleYear                    0.000000\n",
       "saleMonth                   0.000000\n",
       "saleDay                     0.000000\n",
       "saleDayOfWeek               0.000000\n",
       "saleDayOfYear               0.000000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check missing data\n",
    "df_tmp.isnull().sum()/len(df_tmp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Save preprocessed data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Export current tmp dataframe\n",
    "df_tmp.to_csv(\"data/train_tmp.csv\",\n",
    "              index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>SalesID</th>\n",
       "      <td>1646770</td>\n",
       "      <td>1821514</td>\n",
       "      <td>1505138</td>\n",
       "      <td>1671174</td>\n",
       "      <td>1329056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SalePrice</th>\n",
       "      <td>9500</td>\n",
       "      <td>14000</td>\n",
       "      <td>50000</td>\n",
       "      <td>16000</td>\n",
       "      <td>22000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MachineID</th>\n",
       "      <td>1126363</td>\n",
       "      <td>1194089</td>\n",
       "      <td>1473654</td>\n",
       "      <td>1327630</td>\n",
       "      <td>1336053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ModelID</th>\n",
       "      <td>8434</td>\n",
       "      <td>10150</td>\n",
       "      <td>4139</td>\n",
       "      <td>8591</td>\n",
       "      <td>4089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>datasource</th>\n",
       "      <td>132</td>\n",
       "      <td>132</td>\n",
       "      <td>132</td>\n",
       "      <td>132</td>\n",
       "      <td>132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>auctioneerID</th>\n",
       "      <td>18</td>\n",
       "      <td>99</td>\n",
       "      <td>99</td>\n",
       "      <td>99</td>\n",
       "      <td>99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YearMade</th>\n",
       "      <td>1974</td>\n",
       "      <td>1980</td>\n",
       "      <td>1978</td>\n",
       "      <td>1980</td>\n",
       "      <td>1984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MachineHoursCurrentMeter</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UsageBand</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fiModelDesc</th>\n",
       "      <td>TD20</td>\n",
       "      <td>A66</td>\n",
       "      <td>D7G</td>\n",
       "      <td>A62</td>\n",
       "      <td>D3B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fiBaseModel</th>\n",
       "      <td>TD20</td>\n",
       "      <td>A66</td>\n",
       "      <td>D7</td>\n",
       "      <td>A62</td>\n",
       "      <td>D3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fiSecondaryDesc</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>G</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fiModelSeries</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fiModelDescriptor</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ProductSize</th>\n",
       "      <td>Medium</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Large</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fiProductClassDesc</th>\n",
       "      <td>Track Type Tractor, Dozer - 105.0 to 130.0 Hor...</td>\n",
       "      <td>Wheel Loader - 120.0 to 135.0 Horsepower</td>\n",
       "      <td>Track Type Tractor, Dozer - 190.0 to 260.0 Hor...</td>\n",
       "      <td>Wheel Loader - Unidentified</td>\n",
       "      <td>Track Type Tractor, Dozer - 20.0 to 75.0 Horse...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state</th>\n",
       "      <td>Texas</td>\n",
       "      <td>Florida</td>\n",
       "      <td>Florida</td>\n",
       "      <td>Florida</td>\n",
       "      <td>Florida</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ProductGroup</th>\n",
       "      <td>TTT</td>\n",
       "      <td>WL</td>\n",
       "      <td>TTT</td>\n",
       "      <td>WL</td>\n",
       "      <td>TTT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ProductGroupDesc</th>\n",
       "      <td>Track Type Tractors</td>\n",
       "      <td>Wheel Loader</td>\n",
       "      <td>Track Type Tractors</td>\n",
       "      <td>Wheel Loader</td>\n",
       "      <td>Track Type Tractors</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Drive_System</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Enclosure</th>\n",
       "      <td>OROPS</td>\n",
       "      <td>OROPS</td>\n",
       "      <td>OROPS</td>\n",
       "      <td>EROPS</td>\n",
       "      <td>OROPS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Forks</th>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pad_Type</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ride_Control</th>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Stick</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Transmission</th>\n",
       "      <td>Direct Drive</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Standard</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Standard</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Turbocharged</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Blade_Extension</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Blade_Width</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Enclosure_Type</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Engine_Horsepower</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hydraulics</th>\n",
       "      <td>2 Valve</td>\n",
       "      <td>2 Valve</td>\n",
       "      <td>2 Valve</td>\n",
       "      <td>2 Valve</td>\n",
       "      <td>2 Valve</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pushblock</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ripper</th>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Scarifier</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tip_Control</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tire_Size</th>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Coupler</th>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Coupler_System</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Grouser_Tracks</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hydraulics_Flow</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Track_Type</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Undercarriage_Pad_Width</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Stick_Length</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thumb</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pattern_Changer</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Grouser_Type</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Backhoe_Mounting</th>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Blade_Type</th>\n",
       "      <td>Straight</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Straight</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PAT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Travel_Controls</th>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lever</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Differential_Type</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Standard</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Standard</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Steering_Controls</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Conventional</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Conventional</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saleYear</th>\n",
       "      <td>1989</td>\n",
       "      <td>1989</td>\n",
       "      <td>1989</td>\n",
       "      <td>1989</td>\n",
       "      <td>1989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saleMonth</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saleDay</th>\n",
       "      <td>17</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saleDayOfWeek</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saleDayOfYear</th>\n",
       "      <td>17</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                          0  \\\n",
       "SalesID                                                             1646770   \n",
       "SalePrice                                                              9500   \n",
       "MachineID                                                           1126363   \n",
       "ModelID                                                                8434   \n",
       "datasource                                                              132   \n",
       "auctioneerID                                                             18   \n",
       "YearMade                                                               1974   \n",
       "MachineHoursCurrentMeter                                                NaN   \n",
       "UsageBand                                                               NaN   \n",
       "fiModelDesc                                                            TD20   \n",
       "fiBaseModel                                                            TD20   \n",
       "fiSecondaryDesc                                                         NaN   \n",
       "fiModelSeries                                                           NaN   \n",
       "fiModelDescriptor                                                       NaN   \n",
       "ProductSize                                                          Medium   \n",
       "fiProductClassDesc        Track Type Tractor, Dozer - 105.0 to 130.0 Hor...   \n",
       "state                                                                 Texas   \n",
       "ProductGroup                                                            TTT   \n",
       "ProductGroupDesc                                        Track Type Tractors   \n",
       "Drive_System                                                            NaN   \n",
       "Enclosure                                                             OROPS   \n",
       "Forks                                                                   NaN   \n",
       "Pad_Type                                                                NaN   \n",
       "Ride_Control                                                            NaN   \n",
       "Stick                                                                   NaN   \n",
       "Transmission                                                   Direct Drive   \n",
       "Turbocharged                                                            NaN   \n",
       "Blade_Extension                                                         NaN   \n",
       "Blade_Width                                                             NaN   \n",
       "Enclosure_Type                                                          NaN   \n",
       "Engine_Horsepower                                                       NaN   \n",
       "Hydraulics                                                          2 Valve   \n",
       "Pushblock                                                               NaN   \n",
       "Ripper                                                  None or Unspecified   \n",
       "Scarifier                                                               NaN   \n",
       "Tip_Control                                                             NaN   \n",
       "Tire_Size                                                               NaN   \n",
       "Coupler                                                                 NaN   \n",
       "Coupler_System                                                          NaN   \n",
       "Grouser_Tracks                                                          NaN   \n",
       "Hydraulics_Flow                                                         NaN   \n",
       "Track_Type                                                              NaN   \n",
       "Undercarriage_Pad_Width                                                 NaN   \n",
       "Stick_Length                                                            NaN   \n",
       "Thumb                                                                   NaN   \n",
       "Pattern_Changer                                                         NaN   \n",
       "Grouser_Type                                                            NaN   \n",
       "Backhoe_Mounting                                        None or Unspecified   \n",
       "Blade_Type                                                         Straight   \n",
       "Travel_Controls                                         None or Unspecified   \n",
       "Differential_Type                                                       NaN   \n",
       "Steering_Controls                                                       NaN   \n",
       "saleYear                                                               1989   \n",
       "saleMonth                                                                 1   \n",
       "saleDay                                                                  17   \n",
       "saleDayOfWeek                                                             1   \n",
       "saleDayOfYear                                                            17   \n",
       "\n",
       "                                                                 1  \\\n",
       "SalesID                                                    1821514   \n",
       "SalePrice                                                    14000   \n",
       "MachineID                                                  1194089   \n",
       "ModelID                                                      10150   \n",
       "datasource                                                     132   \n",
       "auctioneerID                                                    99   \n",
       "YearMade                                                      1980   \n",
       "MachineHoursCurrentMeter                                       NaN   \n",
       "UsageBand                                                      NaN   \n",
       "fiModelDesc                                                    A66   \n",
       "fiBaseModel                                                    A66   \n",
       "fiSecondaryDesc                                                NaN   \n",
       "fiModelSeries                                                  NaN   \n",
       "fiModelDescriptor                                              NaN   \n",
       "ProductSize                                                    NaN   \n",
       "fiProductClassDesc        Wheel Loader - 120.0 to 135.0 Horsepower   \n",
       "state                                                      Florida   \n",
       "ProductGroup                                                    WL   \n",
       "ProductGroupDesc                                      Wheel Loader   \n",
       "Drive_System                                                   NaN   \n",
       "Enclosure                                                    OROPS   \n",
       "Forks                                          None or Unspecified   \n",
       "Pad_Type                                                       NaN   \n",
       "Ride_Control                                   None or Unspecified   \n",
       "Stick                                                          NaN   \n",
       "Transmission                                                   NaN   \n",
       "Turbocharged                                                   NaN   \n",
       "Blade_Extension                                                NaN   \n",
       "Blade_Width                                                    NaN   \n",
       "Enclosure_Type                                                 NaN   \n",
       "Engine_Horsepower                                              NaN   \n",
       "Hydraulics                                                 2 Valve   \n",
       "Pushblock                                                      NaN   \n",
       "Ripper                                                         NaN   \n",
       "Scarifier                                                      NaN   \n",
       "Tip_Control                                                    NaN   \n",
       "Tire_Size                                      None or Unspecified   \n",
       "Coupler                                        None or Unspecified   \n",
       "Coupler_System                                                 NaN   \n",
       "Grouser_Tracks                                                 NaN   \n",
       "Hydraulics_Flow                                                NaN   \n",
       "Track_Type                                                     NaN   \n",
       "Undercarriage_Pad_Width                                        NaN   \n",
       "Stick_Length                                                   NaN   \n",
       "Thumb                                                          NaN   \n",
       "Pattern_Changer                                                NaN   \n",
       "Grouser_Type                                                   NaN   \n",
       "Backhoe_Mounting                                               NaN   \n",
       "Blade_Type                                                     NaN   \n",
       "Travel_Controls                                                NaN   \n",
       "Differential_Type                                         Standard   \n",
       "Steering_Controls                                     Conventional   \n",
       "saleYear                                                      1989   \n",
       "saleMonth                                                        1   \n",
       "saleDay                                                         31   \n",
       "saleDayOfWeek                                                    1   \n",
       "saleDayOfYear                                                   31   \n",
       "\n",
       "                                                                          2  \\\n",
       "SalesID                                                             1505138   \n",
       "SalePrice                                                             50000   \n",
       "MachineID                                                           1473654   \n",
       "ModelID                                                                4139   \n",
       "datasource                                                              132   \n",
       "auctioneerID                                                             99   \n",
       "YearMade                                                               1978   \n",
       "MachineHoursCurrentMeter                                                NaN   \n",
       "UsageBand                                                               NaN   \n",
       "fiModelDesc                                                             D7G   \n",
       "fiBaseModel                                                              D7   \n",
       "fiSecondaryDesc                                                           G   \n",
       "fiModelSeries                                                           NaN   \n",
       "fiModelDescriptor                                                       NaN   \n",
       "ProductSize                                                           Large   \n",
       "fiProductClassDesc        Track Type Tractor, Dozer - 190.0 to 260.0 Hor...   \n",
       "state                                                               Florida   \n",
       "ProductGroup                                                            TTT   \n",
       "ProductGroupDesc                                        Track Type Tractors   \n",
       "Drive_System                                                            NaN   \n",
       "Enclosure                                                             OROPS   \n",
       "Forks                                                                   NaN   \n",
       "Pad_Type                                                                NaN   \n",
       "Ride_Control                                                            NaN   \n",
       "Stick                                                                   NaN   \n",
       "Transmission                                                       Standard   \n",
       "Turbocharged                                                            NaN   \n",
       "Blade_Extension                                                         NaN   \n",
       "Blade_Width                                                             NaN   \n",
       "Enclosure_Type                                                          NaN   \n",
       "Engine_Horsepower                                                       NaN   \n",
       "Hydraulics                                                          2 Valve   \n",
       "Pushblock                                                               NaN   \n",
       "Ripper                                                  None or Unspecified   \n",
       "Scarifier                                                               NaN   \n",
       "Tip_Control                                                             NaN   \n",
       "Tire_Size                                                               NaN   \n",
       "Coupler                                                                 NaN   \n",
       "Coupler_System                                                          NaN   \n",
       "Grouser_Tracks                                                          NaN   \n",
       "Hydraulics_Flow                                                         NaN   \n",
       "Track_Type                                                              NaN   \n",
       "Undercarriage_Pad_Width                                                 NaN   \n",
       "Stick_Length                                                            NaN   \n",
       "Thumb                                                                   NaN   \n",
       "Pattern_Changer                                                         NaN   \n",
       "Grouser_Type                                                            NaN   \n",
       "Backhoe_Mounting                                        None or Unspecified   \n",
       "Blade_Type                                                         Straight   \n",
       "Travel_Controls                                         None or Unspecified   \n",
       "Differential_Type                                                       NaN   \n",
       "Steering_Controls                                                       NaN   \n",
       "saleYear                                                               1989   \n",
       "saleMonth                                                                 1   \n",
       "saleDay                                                                  31   \n",
       "saleDayOfWeek                                                             1   \n",
       "saleDayOfYear                                                            31   \n",
       "\n",
       "                                                    3  \\\n",
       "SalesID                                       1671174   \n",
       "SalePrice                                       16000   \n",
       "MachineID                                     1327630   \n",
       "ModelID                                          8591   \n",
       "datasource                                        132   \n",
       "auctioneerID                                       99   \n",
       "YearMade                                         1980   \n",
       "MachineHoursCurrentMeter                          NaN   \n",
       "UsageBand                                         NaN   \n",
       "fiModelDesc                                       A62   \n",
       "fiBaseModel                                       A62   \n",
       "fiSecondaryDesc                                   NaN   \n",
       "fiModelSeries                                     NaN   \n",
       "fiModelDescriptor                                 NaN   \n",
       "ProductSize                                       NaN   \n",
       "fiProductClassDesc        Wheel Loader - Unidentified   \n",
       "state                                         Florida   \n",
       "ProductGroup                                       WL   \n",
       "ProductGroupDesc                         Wheel Loader   \n",
       "Drive_System                                      NaN   \n",
       "Enclosure                                       EROPS   \n",
       "Forks                             None or Unspecified   \n",
       "Pad_Type                                          NaN   \n",
       "Ride_Control                      None or Unspecified   \n",
       "Stick                                             NaN   \n",
       "Transmission                                      NaN   \n",
       "Turbocharged                                      NaN   \n",
       "Blade_Extension                                   NaN   \n",
       "Blade_Width                                       NaN   \n",
       "Enclosure_Type                                    NaN   \n",
       "Engine_Horsepower                                 NaN   \n",
       "Hydraulics                                    2 Valve   \n",
       "Pushblock                                         NaN   \n",
       "Ripper                                            NaN   \n",
       "Scarifier                                         NaN   \n",
       "Tip_Control                                       NaN   \n",
       "Tire_Size                         None or Unspecified   \n",
       "Coupler                           None or Unspecified   \n",
       "Coupler_System                                    NaN   \n",
       "Grouser_Tracks                                    NaN   \n",
       "Hydraulics_Flow                                   NaN   \n",
       "Track_Type                                        NaN   \n",
       "Undercarriage_Pad_Width                           NaN   \n",
       "Stick_Length                                      NaN   \n",
       "Thumb                                             NaN   \n",
       "Pattern_Changer                                   NaN   \n",
       "Grouser_Type                                      NaN   \n",
       "Backhoe_Mounting                                  NaN   \n",
       "Blade_Type                                        NaN   \n",
       "Travel_Controls                                   NaN   \n",
       "Differential_Type                            Standard   \n",
       "Steering_Controls                        Conventional   \n",
       "saleYear                                         1989   \n",
       "saleMonth                                           1   \n",
       "saleDay                                            31   \n",
       "saleDayOfWeek                                       1   \n",
       "saleDayOfYear                                      31   \n",
       "\n",
       "                                                                          4  \n",
       "SalesID                                                             1329056  \n",
       "SalePrice                                                             22000  \n",
       "MachineID                                                           1336053  \n",
       "ModelID                                                                4089  \n",
       "datasource                                                              132  \n",
       "auctioneerID                                                             99  \n",
       "YearMade                                                               1984  \n",
       "MachineHoursCurrentMeter                                                NaN  \n",
       "UsageBand                                                               NaN  \n",
       "fiModelDesc                                                             D3B  \n",
       "fiBaseModel                                                              D3  \n",
       "fiSecondaryDesc                                                           B  \n",
       "fiModelSeries                                                           NaN  \n",
       "fiModelDescriptor                                                       NaN  \n",
       "ProductSize                                                             NaN  \n",
       "fiProductClassDesc        Track Type Tractor, Dozer - 20.0 to 75.0 Horse...  \n",
       "state                                                               Florida  \n",
       "ProductGroup                                                            TTT  \n",
       "ProductGroupDesc                                        Track Type Tractors  \n",
       "Drive_System                                                            NaN  \n",
       "Enclosure                                                             OROPS  \n",
       "Forks                                                                   NaN  \n",
       "Pad_Type                                                                NaN  \n",
       "Ride_Control                                                            NaN  \n",
       "Stick                                                                   NaN  \n",
       "Transmission                                                       Standard  \n",
       "Turbocharged                                                            NaN  \n",
       "Blade_Extension                                                         NaN  \n",
       "Blade_Width                                                             NaN  \n",
       "Enclosure_Type                                                          NaN  \n",
       "Engine_Horsepower                                                       NaN  \n",
       "Hydraulics                                                          2 Valve  \n",
       "Pushblock                                                               NaN  \n",
       "Ripper                                                  None or Unspecified  \n",
       "Scarifier                                                               NaN  \n",
       "Tip_Control                                                             NaN  \n",
       "Tire_Size                                                               NaN  \n",
       "Coupler                                                                 NaN  \n",
       "Coupler_System                                                          NaN  \n",
       "Grouser_Tracks                                                          NaN  \n",
       "Hydraulics_Flow                                                         NaN  \n",
       "Track_Type                                                              NaN  \n",
       "Undercarriage_Pad_Width                                                 NaN  \n",
       "Stick_Length                                                            NaN  \n",
       "Thumb                                                                   NaN  \n",
       "Pattern_Changer                                                         NaN  \n",
       "Grouser_Type                                                            NaN  \n",
       "Backhoe_Mounting                                        None or Unspecified  \n",
       "Blade_Type                                                              PAT  \n",
       "Travel_Controls                                                       Lever  \n",
       "Differential_Type                                                       NaN  \n",
       "Steering_Controls                                                       NaN  \n",
       "saleYear                                                               1989  \n",
       "saleMonth                                                                 1  \n",
       "saleDay                                                                  31  \n",
       "saleDayOfWeek                                                             1  \n",
       "saleDayOfYear                                                            31  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Import preprocessed data\n",
    "df_tmp = pd.read_csv(\"data/train_tmp.csv\",\n",
    "                     low_memory=False)\n",
    "df_tmp.head().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SalesID                          0\n",
       "SalePrice                        0\n",
       "MachineID                        0\n",
       "ModelID                          0\n",
       "datasource                       0\n",
       "auctioneerID                 20136\n",
       "YearMade                         0\n",
       "MachineHoursCurrentMeter    265194\n",
       "UsageBand                   339028\n",
       "fiModelDesc                      0\n",
       "fiBaseModel                      0\n",
       "fiSecondaryDesc             140727\n",
       "fiModelSeries               354031\n",
       "fiModelDescriptor           337882\n",
       "ProductSize                 216605\n",
       "fiProductClassDesc               0\n",
       "state                            0\n",
       "ProductGroup                     0\n",
       "ProductGroupDesc                 0\n",
       "Drive_System                305611\n",
       "Enclosure                      334\n",
       "Forks                       214983\n",
       "Pad_Type                    331602\n",
       "Ride_Control                259970\n",
       "Stick                       331602\n",
       "Transmission                224691\n",
       "Turbocharged                331602\n",
       "Blade_Extension             386715\n",
       "Blade_Width                 386715\n",
       "Enclosure_Type              386715\n",
       "Engine_Horsepower           386715\n",
       "Hydraulics                   82565\n",
       "Pushblock                   386715\n",
       "Ripper                      305753\n",
       "Scarifier                   386704\n",
       "Tip_Control                 386715\n",
       "Tire_Size                   315060\n",
       "Coupler                     192019\n",
       "Coupler_System              367724\n",
       "Grouser_Tracks              367823\n",
       "Hydraulics_Flow             367823\n",
       "Track_Type                  310505\n",
       "Undercarriage_Pad_Width     309782\n",
       "Stick_Length                310437\n",
       "Thumb                       310366\n",
       "Pattern_Changer             310437\n",
       "Grouser_Type                310505\n",
       "Backhoe_Mounting            331986\n",
       "Blade_Type                  330823\n",
       "Travel_Controls             330821\n",
       "Differential_Type           341134\n",
       "Steering_Controls           341176\n",
       "saleYear                         0\n",
       "saleMonth                        0\n",
       "saleDay                          0\n",
       "saleDayOfWeek                    0\n",
       "saleDayOfYear                    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tmp.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fill missing values \n",
    "\n",
    "### Fill numerical missing values first"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SalesID\n",
      "SalePrice\n",
      "MachineID\n",
      "ModelID\n",
      "datasource\n",
      "auctioneerID\n",
      "YearMade\n",
      "MachineHoursCurrentMeter\n",
      "saleYear\n",
      "saleMonth\n",
      "saleDay\n",
      "saleDayOfWeek\n",
      "saleDayOfYear\n"
     ]
    }
   ],
   "source": [
    "for label, content in df_tmp.items():\n",
    "    if pd.api.types.is_numeric_dtype(content):\n",
    "        print(label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0          8434\n",
       "1         10150\n",
       "2          4139\n",
       "3          8591\n",
       "4          4089\n",
       "          ...  \n",
       "412693     5266\n",
       "412694    19330\n",
       "412695    17244\n",
       "412696     3357\n",
       "412697     4701\n",
       "Name: ModelID, Length: 412698, dtype: int64"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tmp.ModelID"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "auctioneerID\n",
      "MachineHoursCurrentMeter\n"
     ]
    }
   ],
   "source": [
    "# Check for which numeric columns have null values\n",
    "for label, content in df_tmp.items():\n",
    "    if pd.api.types.is_numeric_dtype(content):\n",
    "        if pd.isnull(content).sum():\n",
    "            print(label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fill numeric rows with the median\n",
    "for label, content in df_tmp.items():\n",
    "    if pd.api.types.is_numeric_dtype(content):\n",
    "        if pd.isnull(content).sum():\n",
    "            # Add a binary column which tells us if the data was missing or not\n",
    "            df_tmp[label+\"_is_missing\"] = pd.isnull(content)\n",
    "            # Fill missing numeric values with median\n",
    "            df_tmp[label] = content.fillna(content.median())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(100.0, 999100.8991008991, 100.0, 100.0)"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Demonstrate how median is more robust than mean\n",
    "hundreds = np.full((1000,), 100)\n",
    "hundreds_billion = np.append(hundreds, 1000000000)\n",
    "np.mean(hundreds), np.mean(hundreds_billion), np.median(hundreds), np.median(hundreds_billion)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Check if there's any null numeric values\n",
    "for label, content in df_tmp.items():\n",
    "    if pd.api.types.is_numeric_dtype(content):\n",
    "        if pd.isnull(content).sum():\n",
    "            print(label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    392562\n",
       "True      20136\n",
       "Name: auctioneerID_is_missing, dtype: int64"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check to see how many examples were missing\n",
    "df_tmp.auctioneerID_is_missing.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SalesID                                     0\n",
       "SalePrice                                   0\n",
       "MachineID                                   0\n",
       "ModelID                                     0\n",
       "datasource                                  0\n",
       "auctioneerID                                0\n",
       "YearMade                                    0\n",
       "MachineHoursCurrentMeter                    0\n",
       "UsageBand                              339028\n",
       "fiModelDesc                                 0\n",
       "fiBaseModel                                 0\n",
       "fiSecondaryDesc                        140727\n",
       "fiModelSeries                          354031\n",
       "fiModelDescriptor                      337882\n",
       "ProductSize                            216605\n",
       "fiProductClassDesc                          0\n",
       "state                                       0\n",
       "ProductGroup                                0\n",
       "ProductGroupDesc                            0\n",
       "Drive_System                           305611\n",
       "Enclosure                                 334\n",
       "Forks                                  214983\n",
       "Pad_Type                               331602\n",
       "Ride_Control                           259970\n",
       "Stick                                  331602\n",
       "Transmission                           224691\n",
       "Turbocharged                           331602\n",
       "Blade_Extension                        386715\n",
       "Blade_Width                            386715\n",
       "Enclosure_Type                         386715\n",
       "Engine_Horsepower                      386715\n",
       "Hydraulics                              82565\n",
       "Pushblock                              386715\n",
       "Ripper                                 305753\n",
       "Scarifier                              386704\n",
       "Tip_Control                            386715\n",
       "Tire_Size                              315060\n",
       "Coupler                                192019\n",
       "Coupler_System                         367724\n",
       "Grouser_Tracks                         367823\n",
       "Hydraulics_Flow                        367823\n",
       "Track_Type                             310505\n",
       "Undercarriage_Pad_Width                309782\n",
       "Stick_Length                           310437\n",
       "Thumb                                  310366\n",
       "Pattern_Changer                        310437\n",
       "Grouser_Type                           310505\n",
       "Backhoe_Mounting                       331986\n",
       "Blade_Type                             330823\n",
       "Travel_Controls                        330821\n",
       "Differential_Type                      341134\n",
       "Steering_Controls                      341176\n",
       "saleYear                                    0\n",
       "saleMonth                                   0\n",
       "saleDay                                     0\n",
       "saleDayOfWeek                               0\n",
       "saleDayOfYear                               0\n",
       "auctioneerID_is_missing                     0\n",
       "MachineHoursCurrentMeter_is_missing         0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tmp.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Filling and turning categorical variables into numbers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "UsageBand\n",
      "fiModelDesc\n",
      "fiBaseModel\n",
      "fiSecondaryDesc\n",
      "fiModelSeries\n",
      "fiModelDescriptor\n",
      "ProductSize\n",
      "fiProductClassDesc\n",
      "state\n",
      "ProductGroup\n",
      "ProductGroupDesc\n",
      "Drive_System\n",
      "Enclosure\n",
      "Forks\n",
      "Pad_Type\n",
      "Ride_Control\n",
      "Stick\n",
      "Transmission\n",
      "Turbocharged\n",
      "Blade_Extension\n",
      "Blade_Width\n",
      "Enclosure_Type\n",
      "Engine_Horsepower\n",
      "Hydraulics\n",
      "Pushblock\n",
      "Ripper\n",
      "Scarifier\n",
      "Tip_Control\n",
      "Tire_Size\n",
      "Coupler\n",
      "Coupler_System\n",
      "Grouser_Tracks\n",
      "Hydraulics_Flow\n",
      "Track_Type\n",
      "Undercarriage_Pad_Width\n",
      "Stick_Length\n",
      "Thumb\n",
      "Pattern_Changer\n",
      "Grouser_Type\n",
      "Backhoe_Mounting\n",
      "Blade_Type\n",
      "Travel_Controls\n",
      "Differential_Type\n",
      "Steering_Controls\n"
     ]
    }
   ],
   "source": [
    "# Check for columns which aren't numeric\n",
    "for label, content in df_tmp.items():\n",
    "    if not pd.api.types.is_numeric_dtype(content):\n",
    "        print(label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Turn categorical variables into numbers and fill missing\n",
    "for label, content in df_tmp.items():\n",
    "    if not pd.api.types.is_numeric_dtype(content):\n",
    "        # Add binary column to indicate whether sample had missing value\n",
    "        df_tmp[label+\"_is_missing\"] = pd.isnull(content)\n",
    "        # Turn categories into numbers and add +1\n",
    "        df_tmp[label] = pd.Categorical(content).codes+1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([44,  9,  9, ...,  5,  5,  5], dtype=int8)"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# + 1 to turn -1 to 0, so we know 0 is missing value\n",
    "pd.Categorical(df_tmp[\"state\"]).codes+1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 412698 entries, 0 to 412697\n",
      "Columns: 103 entries, SalesID to Steering_Controls_is_missing\n",
      "dtypes: bool(46), float64(3), int16(4), int64(10), int8(40)\n",
      "memory usage: 77.9 MB\n"
     ]
    }
   ],
   "source": [
    "df_tmp.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>SalesID</th>\n",
       "      <td>1646770</td>\n",
       "      <td>1821514</td>\n",
       "      <td>1505138</td>\n",
       "      <td>1671174</td>\n",
       "      <td>1329056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SalePrice</th>\n",
       "      <td>9500</td>\n",
       "      <td>14000</td>\n",
       "      <td>50000</td>\n",
       "      <td>16000</td>\n",
       "      <td>22000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MachineID</th>\n",
       "      <td>1126363</td>\n",
       "      <td>1194089</td>\n",
       "      <td>1473654</td>\n",
       "      <td>1327630</td>\n",
       "      <td>1336053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ModelID</th>\n",
       "      <td>8434</td>\n",
       "      <td>10150</td>\n",
       "      <td>4139</td>\n",
       "      <td>8591</td>\n",
       "      <td>4089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>datasource</th>\n",
       "      <td>132</td>\n",
       "      <td>132</td>\n",
       "      <td>132</td>\n",
       "      <td>132</td>\n",
       "      <td>132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Backhoe_Mounting_is_missing</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Blade_Type_is_missing</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Travel_Controls_is_missing</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Differential_Type_is_missing</th>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Steering_Controls_is_missing</th>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>103 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    0        1        2        3        4\n",
       "SalesID                       1646770  1821514  1505138  1671174  1329056\n",
       "SalePrice                        9500    14000    50000    16000    22000\n",
       "MachineID                     1126363  1194089  1473654  1327630  1336053\n",
       "ModelID                          8434    10150     4139     8591     4089\n",
       "datasource                        132      132      132      132      132\n",
       "...                               ...      ...      ...      ...      ...\n",
       "Backhoe_Mounting_is_missing     False     True    False     True    False\n",
       "Blade_Type_is_missing           False     True    False     True    False\n",
       "Travel_Controls_is_missing      False     True    False     True    False\n",
       "Differential_Type_is_missing     True    False     True    False     True\n",
       "Steering_Controls_is_missing     True    False     True    False     True\n",
       "\n",
       "[103 rows x 5 columns]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tmp.head().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SalesID                         0\n",
       "SalePrice                       0\n",
       "MachineID                       0\n",
       "ModelID                         0\n",
       "datasource                      0\n",
       "                               ..\n",
       "Backhoe_Mounting_is_missing     0\n",
       "Blade_Type_is_missing           0\n",
       "Travel_Controls_is_missing      0\n",
       "Differential_Type_is_missing    0\n",
       "Steering_Controls_is_missing    0\n",
       "Length: 103, dtype: int64"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tmp.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that all of data is numeric as well as our dataframe has no missing values, we should be able to build a machine learning model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <th></th>\n",
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       "      <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>fiModelDesc</th>\n",
       "      <th>...</th>\n",
       "      <th>Undercarriage_Pad_Width_is_missing</th>\n",
       "      <th>Stick_Length_is_missing</th>\n",
       "      <th>Thumb_is_missing</th>\n",
       "      <th>Pattern_Changer_is_missing</th>\n",
       "      <th>Grouser_Type_is_missing</th>\n",
       "      <th>Backhoe_Mounting_is_missing</th>\n",
       "      <th>Blade_Type_is_missing</th>\n",
       "      <th>Travel_Controls_is_missing</th>\n",
       "      <th>Differential_Type_is_missing</th>\n",
       "      <th>Steering_Controls_is_missing</th>\n",
       "    </tr>\n",
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       "      <th>0</th>\n",
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       "      <td>14000.0</td>\n",
       "      <td>1194089</td>\n",
       "      <td>10150</td>\n",
       "      <td>132</td>\n",
       "      <td>99.0</td>\n",
       "      <td>1980</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1820</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1505138</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>1473654</td>\n",
       "      <td>4139</td>\n",
       "      <td>132</td>\n",
       "      <td>99.0</td>\n",
       "      <td>1978</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2348</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1671174</td>\n",
       "      <td>16000.0</td>\n",
       "      <td>1327630</td>\n",
       "      <td>8591</td>\n",
       "      <td>132</td>\n",
       "      <td>99.0</td>\n",
       "      <td>1980</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1819</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1329056</td>\n",
       "      <td>22000.0</td>\n",
       "      <td>1336053</td>\n",
       "      <td>4089</td>\n",
       "      <td>132</td>\n",
       "      <td>99.0</td>\n",
       "      <td>1984</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2119</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 103 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   SalesID  SalePrice  MachineID  ModelID  datasource  auctioneerID  YearMade  \\\n",
       "0  1646770     9500.0    1126363     8434         132          18.0      1974   \n",
       "1  1821514    14000.0    1194089    10150         132          99.0      1980   \n",
       "2  1505138    50000.0    1473654     4139         132          99.0      1978   \n",
       "3  1671174    16000.0    1327630     8591         132          99.0      1980   \n",
       "4  1329056    22000.0    1336053     4089         132          99.0      1984   \n",
       "\n",
       "   MachineHoursCurrentMeter  UsageBand  fiModelDesc  ...  \\\n",
       "0                       0.0          0         4593  ...   \n",
       "1                       0.0          0         1820  ...   \n",
       "2                       0.0          0         2348  ...   \n",
       "3                       0.0          0         1819  ...   \n",
       "4                       0.0          0         2119  ...   \n",
       "\n",
       "   Undercarriage_Pad_Width_is_missing  Stick_Length_is_missing  \\\n",
       "0                                True                     True   \n",
       "1                                True                     True   \n",
       "2                                True                     True   \n",
       "3                                True                     True   \n",
       "4                                True                     True   \n",
       "\n",
       "   Thumb_is_missing  Pattern_Changer_is_missing  Grouser_Type_is_missing  \\\n",
       "0              True                        True                     True   \n",
       "1              True                        True                     True   \n",
       "2              True                        True                     True   \n",
       "3              True                        True                     True   \n",
       "4              True                        True                     True   \n",
       "\n",
       "   Backhoe_Mounting_is_missing  Blade_Type_is_missing  \\\n",
       "0                        False                  False   \n",
       "1                         True                   True   \n",
       "2                        False                  False   \n",
       "3                         True                   True   \n",
       "4                        False                  False   \n",
       "\n",
       "   Travel_Controls_is_missing  Differential_Type_is_missing  \\\n",
       "0                       False                          True   \n",
       "1                        True                         False   \n",
       "2                       False                          True   \n",
       "3                        True                         False   \n",
       "4                       False                          True   \n",
       "\n",
       "   Steering_Controls_is_missing  \n",
       "0                          True  \n",
       "1                         False  \n",
       "2                          True  \n",
       "3                         False  \n",
       "4                          True  \n",
       "\n",
       "[5 rows x 103 columns]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tmp.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "412698"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_tmp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 18min 33s, sys: 12.1 s, total: 18min 45s\n",
      "Wall time: 8min 52s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "RandomForestRegressor(n_jobs=-1, random_state=42)"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "# Instantiate model\n",
    "model = RandomForestRegressor(n_jobs=-1,\n",
    "                              random_state=42)\n",
    "\n",
    "# Fit the model\n",
    "model.fit(df_tmp.drop(\"SalePrice\", axis=1), df_tmp[\"SalePrice\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9875468079970562"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Score the model\n",
    "model.score(df_tmp.drop(\"SalePrice\", axis=1), df_tmp[\"SalePrice\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Question:** Why doesn't the above metric hold water? (why isn't the metric reliable)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Splitting data into train/validation sets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         1989\n",
       "1         1989\n",
       "2         1989\n",
       "3         1989\n",
       "4         1989\n",
       "          ... \n",
       "412693    2012\n",
       "412694    2012\n",
       "412695    2012\n",
       "412696    2012\n",
       "412697    2012\n",
       "Name: saleYear, Length: 412698, dtype: int64"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tmp.saleYear"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2009    43849\n",
       "2008    39767\n",
       "2011    35197\n",
       "2010    33390\n",
       "2007    32208\n",
       "2006    21685\n",
       "2005    20463\n",
       "2004    19879\n",
       "2001    17594\n",
       "2000    17415\n",
       "2002    17246\n",
       "2003    15254\n",
       "1998    13046\n",
       "1999    12793\n",
       "2012    11573\n",
       "1997     9785\n",
       "1996     8829\n",
       "1995     8530\n",
       "1994     7929\n",
       "1993     6303\n",
       "1992     5519\n",
       "1991     5109\n",
       "1989     4806\n",
       "1990     4529\n",
       "Name: saleYear, dtype: int64"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tmp.saleYear.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(11573, 401125)"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Split data into training and validation\n",
    "df_val = df_tmp[df_tmp.saleYear == 2012]\n",
    "df_train = df_tmp[df_tmp.saleYear != 2012]\n",
    "\n",
    "len(df_val), len(df_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((401125, 102), (401125,), (11573, 102), (11573,))"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Split data into X & y\n",
    "X_train, y_train = df_train.drop(\"SalePrice\", axis=1), df_train.SalePrice\n",
    "X_valid, y_valid = df_val.drop(\"SalePrice\", axis=1), df_val.SalePrice\n",
    "\n",
    "X_train.shape, y_train.shape, X_valid.shape, y_valid.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0          9500.0\n",
       "1         14000.0\n",
       "2         50000.0\n",
       "3         16000.0\n",
       "4         22000.0\n",
       "           ...   \n",
       "401120    29000.0\n",
       "401121    11000.0\n",
       "401122    11000.0\n",
       "401123    18000.0\n",
       "401124    13500.0\n",
       "Name: SalePrice, Length: 401125, dtype: float64"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Building an evaluation function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create evaluation function (the competition uses RMSLE)\n",
    "from sklearn.metrics import mean_squared_log_error, mean_absolute_error, r2_score\n",
    "\n",
    "def rmsle(y_test, y_preds):\n",
    "    \"\"\"\n",
    "    Caculates root mean squared log error between predictions and\n",
    "    true labels.\n",
    "    \"\"\"\n",
    "    return np.sqrt(mean_squared_log_error(y_test, y_preds))\n",
    "\n",
    "# Create function to evaluate model on a few different levels\n",
    "def show_scores(model):\n",
    "    train_preds = model.predict(X_train)\n",
    "    val_preds = model.predict(X_valid)\n",
    "    scores = {\"Training MAE\": mean_absolute_error(y_train, train_preds),\n",
    "              \"Valid MAE\": mean_absolute_error(y_valid, val_preds),\n",
    "              \"Training RMSLE\": rmsle(y_train, train_preds),\n",
    "              \"Valid RMSLE\": rmsle(y_valid, val_preds),\n",
    "              \"Training R^2\": r2_score(y_train, train_preds),\n",
    "              \"Valid R^2\": r2_score(y_valid, val_preds)}\n",
    "    return scores"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Testing our model on a subset (to tune the hyperparameters)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "# # This takes far too long... for experimenting\n",
    "\n",
    "# %%time\n",
    "# model = RandomForestRegressor(n_jobs=-1, \n",
    "#                               random_state=42)\n",
    "\n",
    "# model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "401125"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(X_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Change max_samples value\n",
    "model = RandomForestRegressor(n_jobs=-1,\n",
    "                              random_state=42,\n",
    "                              max_samples=10000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 34.3 s, sys: 820 ms, total: 35.1 s\n",
      "Wall time: 15.6 s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "RandomForestRegressor(max_samples=10000, n_jobs=-1, random_state=42)"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "# Cutting down on the max number of samples each estimator can see improves training time\n",
    "model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "40.1125"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# original dataset size = X_train.shape[0] * 100\n",
    "# new dataset size = 10000 * 100\n",
    "# 40 times smaller\n",
    "(X_train.shape[0] * 100) / 1000000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1000000"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "10000 * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Training MAE': 5561.2988092240585,\n",
       " 'Valid MAE': 7177.26365505919,\n",
       " 'Training RMSLE': 0.257745378256977,\n",
       " 'Valid RMSLE': 0.29362638671089003,\n",
       " 'Training R^2': 0.8606658995199189,\n",
       " 'Valid R^2': 0.8320374995090507}"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "show_scores(model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Hyerparameter tuning with RandomizedSearchCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 2 candidates, totalling 10 fits\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.\n",
      "[Parallel(n_jobs=1)]: Done  10 out of  10 | elapsed:  1.0min finished\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 27.2 s, sys: 7.38 s, total: 34.6 s\n",
      "Wall time: 1min 5s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "RandomizedSearchCV(cv=5,\n",
       "                   estimator=RandomForestRegressor(n_jobs=-1, random_state=42),\n",
       "                   n_iter=2,\n",
       "                   param_distributions={'max_depth': [None, 3, 5, 10],\n",
       "                                        'max_features': [0.5, 1, 'sqrt',\n",
       "                                                         'auto'],\n",
       "                                        'max_samples': [10000],\n",
       "                                        'min_samples_leaf': array([ 1,  3,  5,  7,  9, 11, 13, 15, 17, 19]),\n",
       "                                        'min_samples_split': array([ 2,  4,  6,  8, 10, 12, 14, 16, 18]),\n",
       "                                        'n_estimators': array([10, 20, 30, 40, 50, 60, 70, 80, 90])},\n",
       "                   verbose=True)"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "from sklearn.model_selection import RandomizedSearchCV\n",
    "\n",
    "# Different RandomForestRegressor hyperparameters\n",
    "rf_grid = {\"n_estimators\": np.arange(10, 100, 10),\n",
    "           \"max_depth\": [None, 3, 5, 10],\n",
    "           \"min_samples_split\": np.arange(2, 20, 2),\n",
    "           \"min_samples_leaf\": np.arange(1, 20, 2),\n",
    "           \"max_features\": [0.5, 1, \"sqrt\", \"auto\"],\n",
    "           \"max_samples\": [10000]}\n",
    "\n",
    "# Instantiate RandomizedSearchCV model\n",
    "rs_model = RandomizedSearchCV(RandomForestRegressor(n_jobs=-1,\n",
    "                                                    random_state=42),\n",
    "                              param_distributions=rf_grid,\n",
    "                              n_iter=2,\n",
    "                              cv=5,\n",
    "                              verbose=True)\n",
    "\n",
    "# Fit the RandomizedSearchCV model\n",
    "rs_model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'n_estimators': 30,\n",
       " 'min_samples_split': 2,\n",
       " 'min_samples_leaf': 5,\n",
       " 'max_samples': 10000,\n",
       " 'max_features': 1,\n",
       " 'max_depth': 10}"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find the best model hyperparameters\n",
    "rs_model.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Training MAE': 11989.618967270111,\n",
       " 'Valid MAE': 13743.860411930342,\n",
       " 'Training RMSLE': 0.5176940973275121,\n",
       " 'Valid RMSLE': 0.5289148986841782,\n",
       " 'Training R^2': 0.4690288930433294,\n",
       " 'Valid R^2': 0.47071070331329556}"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Evaluate the RandomizedSearch model\n",
    "show_scores(rs_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Train a model with the best hyperparamters\n",
    "\n",
    "**Note:** These were found after 100 iterations of `RandomizedSearchCV`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 3min 15s, sys: 2.17 s, total: 3min 18s\n",
      "Wall time: 1min 31s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "RandomForestRegressor(max_features=0.5, min_samples_split=14, n_estimators=40,\n",
       "                      n_jobs=-1, random_state=42)"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "# Most ideal hyperparamters\n",
    "ideal_model = RandomForestRegressor(n_estimators=40,\n",
    "                                    min_samples_leaf=1,\n",
    "                                    min_samples_split=14,\n",
    "                                    max_features=0.5,\n",
    "                                    n_jobs=-1,\n",
    "                                    max_samples=None,\n",
    "                                    random_state=42) # random state so our results are reproducible\n",
    "\n",
    "# Fit the ideal model\n",
    "ideal_model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Training MAE': 2953.8161137163484,\n",
       " 'Valid MAE': 5951.247761444453,\n",
       " 'Training RMSLE': 0.14469006962371858,\n",
       " 'Valid RMSLE': 0.24524163989538328,\n",
       " 'Training R^2': 0.9588145522577225,\n",
       " 'Valid R^2': 0.8818019502450094}"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Scores for ideal_model (trained on all the data)\n",
    "show_scores(ideal_model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Training MAE': 11989.618967270111,\n",
       " 'Valid MAE': 13743.860411930342,\n",
       " 'Training RMSLE': 0.5176940973275121,\n",
       " 'Valid RMSLE': 0.5289148986841782,\n",
       " 'Training R^2': 0.4690288930433294,\n",
       " 'Valid R^2': 0.47071070331329556}"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Scores on rs_model (only trained on ~10,000 examples)\n",
    "show_scores(rs_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Make predictions on test data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SalesID</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>...</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1227829</td>\n",
       "      <td>1006309</td>\n",
       "      <td>3168</td>\n",
       "      <td>121</td>\n",
       "      <td>3</td>\n",
       "      <td>1999</td>\n",
       "      <td>3688.0</td>\n",
       "      <td>Low</td>\n",
       "      <td>2012-05-03</td>\n",
       "      <td>580G</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1227844</td>\n",
       "      <td>1022817</td>\n",
       "      <td>7271</td>\n",
       "      <td>121</td>\n",
       "      <td>3</td>\n",
       "      <td>1000</td>\n",
       "      <td>28555.0</td>\n",
       "      <td>High</td>\n",
       "      <td>2012-05-10</td>\n",
       "      <td>936</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Conventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1227847</td>\n",
       "      <td>1031560</td>\n",
       "      <td>22805</td>\n",
       "      <td>121</td>\n",
       "      <td>3</td>\n",
       "      <td>2004</td>\n",
       "      <td>6038.0</td>\n",
       "      <td>Medium</td>\n",
       "      <td>2012-05-10</td>\n",
       "      <td>EC210BLC</td>\n",
       "      <td>...</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>9' 6\"</td>\n",
       "      <td>Manual</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>Double</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1227848</td>\n",
       "      <td>56204</td>\n",
       "      <td>1269</td>\n",
       "      <td>121</td>\n",
       "      <td>3</td>\n",
       "      <td>2006</td>\n",
       "      <td>8940.0</td>\n",
       "      <td>High</td>\n",
       "      <td>2012-05-10</td>\n",
       "      <td>330CL</td>\n",
       "      <td>...</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>Manual</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Triple</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1227863</td>\n",
       "      <td>1053887</td>\n",
       "      <td>22312</td>\n",
       "      <td>121</td>\n",
       "      <td>3</td>\n",
       "      <td>2005</td>\n",
       "      <td>2286.0</td>\n",
       "      <td>Low</td>\n",
       "      <td>2012-05-10</td>\n",
       "      <td>650K</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>PAT</td>\n",
       "      <td>None or Unspecified</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 52 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   SalesID  MachineID  ModelID  datasource  auctioneerID  YearMade  \\\n",
       "0  1227829    1006309     3168         121             3      1999   \n",
       "1  1227844    1022817     7271         121             3      1000   \n",
       "2  1227847    1031560    22805         121             3      2004   \n",
       "3  1227848      56204     1269         121             3      2006   \n",
       "4  1227863    1053887    22312         121             3      2005   \n",
       "\n",
       "   MachineHoursCurrentMeter UsageBand   saledate fiModelDesc  ...  \\\n",
       "0                    3688.0       Low 2012-05-03        580G  ...   \n",
       "1                   28555.0      High 2012-05-10         936  ...   \n",
       "2                    6038.0    Medium 2012-05-10    EC210BLC  ...   \n",
       "3                    8940.0      High 2012-05-10       330CL  ...   \n",
       "4                    2286.0       Low 2012-05-10        650K  ...   \n",
       "\n",
       "  Undercarriage_Pad_Width         Stick_Length   Thumb      Pattern_Changer  \\\n",
       "0                     NaN                  NaN     NaN                  NaN   \n",
       "1                     NaN                  NaN     NaN                  NaN   \n",
       "2     None or Unspecified                9' 6\"  Manual  None or Unspecified   \n",
       "3     None or Unspecified  None or Unspecified  Manual                  Yes   \n",
       "4                     NaN                  NaN     NaN                  NaN   \n",
       "\n",
       "  Grouser_Type     Backhoe_Mounting Blade_Type      Travel_Controls  \\\n",
       "0          NaN                  NaN        NaN                  NaN   \n",
       "1          NaN                  NaN        NaN                  NaN   \n",
       "2       Double                  NaN        NaN                  NaN   \n",
       "3       Triple                  NaN        NaN                  NaN   \n",
       "4          NaN  None or Unspecified        PAT  None or Unspecified   \n",
       "\n",
       "  Differential_Type Steering_Controls  \n",
       "0               NaN               NaN  \n",
       "1          Standard      Conventional  \n",
       "2               NaN               NaN  \n",
       "3               NaN               NaN  \n",
       "4               NaN               NaN  \n",
       "\n",
       "[5 rows x 52 columns]"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Import the test data\n",
    "df_test = pd.read_csv(\"data/Test.csv\",\n",
    "                      low_memory=False,\n",
    "                      parse_dates=[\"saledate\"])\n",
    "\n",
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "could not convert string to float: 'Low'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m-------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                              Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-81-dcaddf54aa59>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# Make predictions on the test dataset\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mtest_preds\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mideal_model\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf_test\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/usr/local/lib/python3.7/site-packages/sklearn/ensemble/_forest.py\u001b[0m in \u001b[0;36mpredict\u001b[0;34m(self, X)\u001b[0m\n\u001b[1;32m    781\u001b[0m         \u001b[0mcheck_is_fitted\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    782\u001b[0m         \u001b[0;31m# Check data\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 783\u001b[0;31m         \u001b[0mX\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_X_predict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    784\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    785\u001b[0m         \u001b[0;31m# Assign chunk of trees to jobs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.7/site-packages/sklearn/ensemble/_forest.py\u001b[0m in \u001b[0;36m_validate_X_predict\u001b[0;34m(self, X)\u001b[0m\n\u001b[1;32m    419\u001b[0m         \u001b[0mcheck_is_fitted\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    420\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 421\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mestimators_\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_X_predict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcheck_input\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    422\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    423\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mproperty\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.7/site-packages/sklearn/tree/_classes.py\u001b[0m in \u001b[0;36m_validate_X_predict\u001b[0;34m(self, X, check_input)\u001b[0m\n\u001b[1;32m    386\u001b[0m         \u001b[0;34m\"\"\"Validate X whenever one tries to predict, apply, predict_proba\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    387\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mcheck_input\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 388\u001b[0;31m             \u001b[0mX\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcheck_array\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mDTYPE\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maccept_sparse\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"csr\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    389\u001b[0m             if issparse(X) and (X.indices.dtype != np.intc or\n\u001b[1;32m    390\u001b[0m                                 X.indptr.dtype != np.intc):\n",
      "\u001b[0;32m/usr/local/lib/python3.7/site-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36minner_f\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     71\u001b[0m                           FutureWarning)\n\u001b[1;32m     72\u001b[0m         \u001b[0mkwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0marg\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0marg\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mparameters\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 73\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     74\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0minner_f\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     75\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.7/site-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36mcheck_array\u001b[0;34m(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, estimator)\u001b[0m\n\u001b[1;32m    597\u001b[0m                     \u001b[0marray\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0marray\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcasting\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"unsafe\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    598\u001b[0m                 \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 599\u001b[0;31m                     \u001b[0marray\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0masarray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0morder\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0morder\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    600\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mComplexWarning\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    601\u001b[0m                 raise ValueError(\"Complex data not supported\\n\"\n",
      "\u001b[0;32m/usr/local/lib/python3.7/site-packages/numpy/core/_asarray.py\u001b[0m in \u001b[0;36masarray\u001b[0;34m(a, dtype, order)\u001b[0m\n\u001b[1;32m     83\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     84\u001b[0m     \"\"\"\n\u001b[0;32m---> 85\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0morder\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0morder\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     86\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     87\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: could not convert string to float: 'Low'"
     ]
    }
   ],
   "source": [
    "# Make predictions on the test dataset\n",
    "test_preds = ideal_model.predict(df_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Preprocessing the data (getting the test dataset in the same format as our training dataset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "def preprocess_data(df):\n",
    "    \"\"\"\n",
    "    Performs transformations on df and returns transformed df.\n",
    "    \"\"\"\n",
    "    df[\"saleYear\"] = df.saledate.dt.year\n",
    "    df[\"saleMonth\"] = df.saledate.dt.month\n",
    "    df[\"saleDay\"] = df.saledate.dt.day\n",
    "    df[\"saleDayOfWeek\"] = df.saledate.dt.dayofweek\n",
    "    df[\"saleDayOfYear\"] = df.saledate.dt.dayofyear\n",
    "    \n",
    "    df.drop(\"saledate\", axis=1, inplace=True)\n",
    "    \n",
    "    # Fill the numeric rows with median\n",
    "    for label, content in df.items():\n",
    "        if pd.api.types.is_numeric_dtype(content):\n",
    "            if pd.isnull(content).sum():\n",
    "                # Add a binary column which tells us if the data was missing or not\n",
    "                df[label+\"_is_missing\"] = pd.isnull(content)\n",
    "                # Fill missing numeric values with median\n",
    "                df[label] = content.fillna(content.median())\n",
    "    \n",
    "        # Filled categorical missing data and turn categories into numbers\n",
    "        if not pd.api.types.is_numeric_dtype(content):\n",
    "            df[label+\"_is_missing\"] = pd.isnull(content)\n",
    "            # We add +1 to the category code because pandas encodes missing categories as -1\n",
    "            df[label] = pd.Categorical(content).codes+1\n",
    "    \n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SalesID</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>fiModelDesc</th>\n",
       "      <th>fiBaseModel</th>\n",
       "      <th>...</th>\n",
       "      <th>Undercarriage_Pad_Width_is_missing</th>\n",
       "      <th>Stick_Length_is_missing</th>\n",
       "      <th>Thumb_is_missing</th>\n",
       "      <th>Pattern_Changer_is_missing</th>\n",
       "      <th>Grouser_Type_is_missing</th>\n",
       "      <th>Backhoe_Mounting_is_missing</th>\n",
       "      <th>Blade_Type_is_missing</th>\n",
       "      <th>Travel_Controls_is_missing</th>\n",
       "      <th>Differential_Type_is_missing</th>\n",
       "      <th>Steering_Controls_is_missing</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1227829</td>\n",
       "      <td>1006309</td>\n",
       "      <td>3168</td>\n",
       "      <td>121</td>\n",
       "      <td>3</td>\n",
       "      <td>1999</td>\n",
       "      <td>3688.0</td>\n",
       "      <td>2</td>\n",
       "      <td>499</td>\n",
       "      <td>180</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1227844</td>\n",
       "      <td>1022817</td>\n",
       "      <td>7271</td>\n",
       "      <td>121</td>\n",
       "      <td>3</td>\n",
       "      <td>1000</td>\n",
       "      <td>28555.0</td>\n",
       "      <td>1</td>\n",
       "      <td>831</td>\n",
       "      <td>292</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1227847</td>\n",
       "      <td>1031560</td>\n",
       "      <td>22805</td>\n",
       "      <td>121</td>\n",
       "      <td>3</td>\n",
       "      <td>2004</td>\n",
       "      <td>6038.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1177</td>\n",
       "      <td>404</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1227848</td>\n",
       "      <td>56204</td>\n",
       "      <td>1269</td>\n",
       "      <td>121</td>\n",
       "      <td>3</td>\n",
       "      <td>2006</td>\n",
       "      <td>8940.0</td>\n",
       "      <td>1</td>\n",
       "      <td>287</td>\n",
       "      <td>113</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1227863</td>\n",
       "      <td>1053887</td>\n",
       "      <td>22312</td>\n",
       "      <td>121</td>\n",
       "      <td>3</td>\n",
       "      <td>2005</td>\n",
       "      <td>2286.0</td>\n",
       "      <td>2</td>\n",
       "      <td>566</td>\n",
       "      <td>196</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 101 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   SalesID  MachineID  ModelID  datasource  auctioneerID  YearMade  \\\n",
       "0  1227829    1006309     3168         121             3      1999   \n",
       "1  1227844    1022817     7271         121             3      1000   \n",
       "2  1227847    1031560    22805         121             3      2004   \n",
       "3  1227848      56204     1269         121             3      2006   \n",
       "4  1227863    1053887    22312         121             3      2005   \n",
       "\n",
       "   MachineHoursCurrentMeter  UsageBand  fiModelDesc  fiBaseModel  ...  \\\n",
       "0                    3688.0          2          499          180  ...   \n",
       "1                   28555.0          1          831          292  ...   \n",
       "2                    6038.0          3         1177          404  ...   \n",
       "3                    8940.0          1          287          113  ...   \n",
       "4                    2286.0          2          566          196  ...   \n",
       "\n",
       "   Undercarriage_Pad_Width_is_missing  Stick_Length_is_missing  \\\n",
       "0                                True                     True   \n",
       "1                                True                     True   \n",
       "2                               False                    False   \n",
       "3                               False                    False   \n",
       "4                                True                     True   \n",
       "\n",
       "   Thumb_is_missing  Pattern_Changer_is_missing  Grouser_Type_is_missing  \\\n",
       "0              True                        True                     True   \n",
       "1              True                        True                     True   \n",
       "2             False                       False                    False   \n",
       "3             False                       False                    False   \n",
       "4              True                        True                     True   \n",
       "\n",
       "   Backhoe_Mounting_is_missing  Blade_Type_is_missing  \\\n",
       "0                         True                   True   \n",
       "1                         True                   True   \n",
       "2                         True                   True   \n",
       "3                         True                   True   \n",
       "4                        False                  False   \n",
       "\n",
       "   Travel_Controls_is_missing  Differential_Type_is_missing  \\\n",
       "0                        True                          True   \n",
       "1                        True                         False   \n",
       "2                        True                          True   \n",
       "3                        True                          True   \n",
       "4                       False                          True   \n",
       "\n",
       "   Steering_Controls_is_missing  \n",
       "0                          True  \n",
       "1                         False  \n",
       "2                          True  \n",
       "3                          True  \n",
       "4                          True  \n",
       "\n",
       "[5 rows x 101 columns]"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Process the test data \n",
    "df_test = preprocess_data(df_test)\n",
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Number of features of the model must match the input. Model n_features is 102 and input n_features is 101 ",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m-------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                              Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-84-816969861579>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# Make predictions on updated test data\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mtest_preds\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mideal_model\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf_test\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/usr/local/lib/python3.7/site-packages/sklearn/ensemble/_forest.py\u001b[0m in \u001b[0;36mpredict\u001b[0;34m(self, X)\u001b[0m\n\u001b[1;32m    781\u001b[0m         \u001b[0mcheck_is_fitted\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    782\u001b[0m         \u001b[0;31m# Check data\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 783\u001b[0;31m         \u001b[0mX\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_X_predict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    784\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    785\u001b[0m         \u001b[0;31m# Assign chunk of trees to jobs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.7/site-packages/sklearn/ensemble/_forest.py\u001b[0m in \u001b[0;36m_validate_X_predict\u001b[0;34m(self, X)\u001b[0m\n\u001b[1;32m    419\u001b[0m         \u001b[0mcheck_is_fitted\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    420\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 421\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mestimators_\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_X_predict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcheck_input\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    422\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    423\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mproperty\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.7/site-packages/sklearn/tree/_classes.py\u001b[0m in \u001b[0;36m_validate_X_predict\u001b[0;34m(self, X, check_input)\u001b[0m\n\u001b[1;32m    397\u001b[0m                              \u001b[0;34m\"match the input. Model n_features is %s and \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    398\u001b[0m                              \u001b[0;34m\"input n_features is %s \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 399\u001b[0;31m                              % (self.n_features_, n_features))\n\u001b[0m\u001b[1;32m    400\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    401\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: Number of features of the model must match the input. Model n_features is 102 and input n_features is 101 "
     ]
    }
   ],
   "source": [
    "# Make predictions on updated test data\n",
    "test_preds = ideal_model.predict(df_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
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       "      <th>SalesID</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",
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       "      <th>fiModelDesc</th>\n",
       "      <th>fiBaseModel</th>\n",
       "      <th>...</th>\n",
       "      <th>Undercarriage_Pad_Width_is_missing</th>\n",
       "      <th>Stick_Length_is_missing</th>\n",
       "      <th>Thumb_is_missing</th>\n",
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       "      <th>Grouser_Type_is_missing</th>\n",
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      "text/plain": [
       "   SalesID  MachineID  ModelID  datasource  auctioneerID  YearMade  \\\n",
       "0  1646770    1126363     8434         132          18.0      1974   \n",
       "1  1821514    1194089    10150         132          99.0      1980   \n",
       "2  1505138    1473654     4139         132          99.0      1978   \n",
       "3  1671174    1327630     8591         132          99.0      1980   \n",
       "4  1329056    1336053     4089         132          99.0      1984   \n",
       "\n",
       "   MachineHoursCurrentMeter  UsageBand  fiModelDesc  fiBaseModel  ...  \\\n",
       "0                       0.0          0         4593         1744  ...   \n",
       "1                       0.0          0         1820          559  ...   \n",
       "2                       0.0          0         2348          713  ...   \n",
       "3                       0.0          0         1819          558  ...   \n",
       "4                       0.0          0         2119          683  ...   \n",
       "\n",
       "   Undercarriage_Pad_Width_is_missing  Stick_Length_is_missing  \\\n",
       "0                                True                     True   \n",
       "1                                True                     True   \n",
       "2                                True                     True   \n",
       "3                                True                     True   \n",
       "4                                True                     True   \n",
       "\n",
       "   Thumb_is_missing  Pattern_Changer_is_missing  Grouser_Type_is_missing  \\\n",
       "0              True                        True                     True   \n",
       "1              True                        True                     True   \n",
       "2              True                        True                     True   \n",
       "3              True                        True                     True   \n",
       "4              True                        True                     True   \n",
       "\n",
       "   Backhoe_Mounting_is_missing  Blade_Type_is_missing  \\\n",
       "0                        False                  False   \n",
       "1                         True                   True   \n",
       "2                        False                  False   \n",
       "3                         True                   True   \n",
       "4                        False                  False   \n",
       "\n",
       "   Travel_Controls_is_missing  Differential_Type_is_missing  \\\n",
       "0                       False                          True   \n",
       "1                        True                         False   \n",
       "2                       False                          True   \n",
       "3                        True                         False   \n",
       "4                       False                          True   \n",
       "\n",
       "   Steering_Controls_is_missing  \n",
       "0                          True  \n",
       "1                         False  \n",
       "2                          True  \n",
       "3                         False  \n",
       "4                          True  \n",
       "\n",
       "[5 rows x 102 columns]"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'auctioneerID_is_missing'}"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# We can find how the columns differ using sets\n",
    "set(X_train.columns) - set(df_test.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 102 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   SalesID  MachineID  ModelID  datasource  auctioneerID  YearMade  \\\n",
       "0  1227829    1006309     3168         121             3      1999   \n",
       "1  1227844    1022817     7271         121             3      1000   \n",
       "2  1227847    1031560    22805         121             3      2004   \n",
       "3  1227848      56204     1269         121             3      2006   \n",
       "4  1227863    1053887    22312         121             3      2005   \n",
       "\n",
       "   MachineHoursCurrentMeter  UsageBand  fiModelDesc  fiBaseModel  ...  \\\n",
       "0                    3688.0          2          499          180  ...   \n",
       "1                   28555.0          1          831          292  ...   \n",
       "2                    6038.0          3         1177          404  ...   \n",
       "3                    8940.0          1          287          113  ...   \n",
       "4                    2286.0          2          566          196  ...   \n",
       "\n",
       "   Stick_Length_is_missing  Thumb_is_missing  Pattern_Changer_is_missing  \\\n",
       "0                     True              True                        True   \n",
       "1                     True              True                        True   \n",
       "2                    False             False                       False   \n",
       "3                    False             False                       False   \n",
       "4                     True              True                        True   \n",
       "\n",
       "   Grouser_Type_is_missing  Backhoe_Mounting_is_missing  \\\n",
       "0                     True                         True   \n",
       "1                     True                         True   \n",
       "2                    False                         True   \n",
       "3                    False                         True   \n",
       "4                     True                        False   \n",
       "\n",
       "   Blade_Type_is_missing  Travel_Controls_is_missing  \\\n",
       "0                   True                        True   \n",
       "1                   True                        True   \n",
       "2                   True                        True   \n",
       "3                   True                        True   \n",
       "4                  False                       False   \n",
       "\n",
       "   Differential_Type_is_missing  Steering_Controls_is_missing  \\\n",
       "0                          True                          True   \n",
       "1                         False                         False   \n",
       "2                          True                          True   \n",
       "3                          True                          True   \n",
       "4                          True                          True   \n",
       "\n",
       "   auctioneerID_is_missing  \n",
       "0                    False  \n",
       "1                    False  \n",
       "2                    False  \n",
       "3                    False  \n",
       "4                    False  \n",
       "\n",
       "[5 rows x 102 columns]"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Manually adjust df_test to have auctioneerID_is_missing column\n",
    "df_test[\"auctioneerID_is_missing\"] = False\n",
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Make predictions on the test data\n",
    "test_preds = ideal_model.predict(df_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([20614.36780887, 19897.80170658, 44852.21959446, ...,\n",
       "       14296.98620472, 22164.85757662, 31683.80063427])"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_preds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We've made some predictions but they're not in the same format Kaggle is asking for: https://www.kaggle.com/c/bluebook-for-bulldozers/overview/evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SalesID</th>\n",
       "      <th>SalesPrice</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1227829</td>\n",
       "      <td>20614.367809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1227844</td>\n",
       "      <td>19897.801707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1227847</td>\n",
       "      <td>44852.219594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1227848</td>\n",
       "      <td>68346.325323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1227863</td>\n",
       "      <td>39487.349708</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12452</th>\n",
       "      <td>6643171</td>\n",
       "      <td>46466.092910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12453</th>\n",
       "      <td>6643173</td>\n",
       "      <td>17500.493352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12454</th>\n",
       "      <td>6643184</td>\n",
       "      <td>14296.986205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12455</th>\n",
       "      <td>6643186</td>\n",
       "      <td>22164.857577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12456</th>\n",
       "      <td>6643196</td>\n",
       "      <td>31683.800634</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12457 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       SalesID    SalesPrice\n",
       "0      1227829  20614.367809\n",
       "1      1227844  19897.801707\n",
       "2      1227847  44852.219594\n",
       "3      1227848  68346.325323\n",
       "4      1227863  39487.349708\n",
       "...        ...           ...\n",
       "12452  6643171  46466.092910\n",
       "12453  6643173  17500.493352\n",
       "12454  6643184  14296.986205\n",
       "12455  6643186  22164.857577\n",
       "12456  6643196  31683.800634\n",
       "\n",
       "[12457 rows x 2 columns]"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Format predictions into the same format Kaggle is after\n",
    "df_preds = pd.DataFrame()\n",
    "df_preds[\"SalesID\"] = df_test[\"SalesID\"]\n",
    "df_preds[\"SalesPrice\"] = test_preds\n",
    "df_preds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Export prediction data\n",
    "df_preds.to_csv(\"data/test_predictions.csv\", index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feature Importance\n",
    "\n",
    "Feature importance seeks to figure out which different attributes of the data were most importance when it comes to predicting the **target variable** (SalePrice)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3.39445533e-02, 1.81148281e-02, 4.09167072e-02, 1.70752171e-03,\n",
       "       3.40797459e-03, 2.08200698e-01, 2.95067052e-03, 1.10113725e-03,\n",
       "       4.16122668e-02, 4.71911805e-02, 6.23815431e-02, 4.67433955e-03,\n",
       "       1.52524442e-02, 1.52517337e-01, 4.72224713e-02, 5.96817956e-03,\n",
       "       1.29351899e-03, 2.78088439e-03, 2.37248769e-03, 6.17114453e-02,\n",
       "       8.13525488e-04, 3.61873268e-05, 9.19098115e-04, 2.23170993e-04,\n",
       "       1.28102678e-03, 2.06519636e-05, 2.01477316e-03, 6.63364759e-03,\n",
       "       2.15274492e-03, 2.50178165e-03, 4.63902393e-03, 3.85873985e-03,\n",
       "       2.76062667e-03, 1.00782454e-03, 2.47969268e-04, 6.04239818e-03,\n",
       "       7.64997072e-04, 1.57100537e-02, 2.29716203e-03, 2.58372272e-03,\n",
       "       8.07637426e-04, 9.18548690e-04, 1.35656446e-03, 5.81458569e-04,\n",
       "       4.96716928e-04, 3.79552257e-04, 5.31712788e-04, 2.71823509e-03,\n",
       "       8.34294376e-04, 3.12136841e-04, 2.14075157e-04, 7.42422919e-02,\n",
       "       3.80158492e-03, 5.67641024e-03, 2.87154703e-03, 9.83349904e-03,\n",
       "       2.65470837e-04, 1.57946459e-03, 3.10058108e-04, 0.00000000e+00,\n",
       "       0.00000000e+00, 2.27421721e-03, 1.05632062e-03, 5.42819222e-03,\n",
       "       3.48484864e-02, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
       "       0.00000000e+00, 1.90858845e-05, 9.09490682e-06, 1.31265147e-04,\n",
       "       5.29163902e-06, 1.11952381e-04, 4.78452431e-06, 3.43582863e-04,\n",
       "       5.57068428e-06, 1.07167376e-03, 3.99179008e-03, 4.07753410e-03,\n",
       "       1.05749617e-04, 2.76528927e-03, 2.59244312e-05, 3.51888176e-04,\n",
       "       2.31519337e-03, 1.99211177e-03, 4.02034629e-03, 2.03778082e-04,\n",
       "       1.13483313e-02, 9.02551628e-04, 1.58182497e-03, 4.63243398e-05,\n",
       "       2.92071004e-04, 3.11923094e-05, 1.56873538e-04, 2.87205987e-05,\n",
       "       3.80543083e-05, 2.55045807e-04, 1.66878572e-04, 2.10341792e-04,\n",
       "       1.26024842e-04, 9.40663015e-05])"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find feature importance of our best model\n",
    "ideal_model.feature_importances_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Helper function for plotting feature importance\n",
    "def plot_features(columns, importances, n=20):\n",
    "    df = (pd.DataFrame({\"features\": columns,\n",
    "                        \"feature_importances\": importances})\n",
    "          .sort_values(\"feature_importances\", ascending=False)\n",
    "          .reset_index(drop=True))\n",
    "    \n",
    "    # Plot the dataframe\n",
    "    fig, ax = plt.subplots()\n",
    "    ax.barh(df[\"features\"][:n], df[\"feature_importances\"][:20])\n",
    "    ax.set_ylabel(\"Features\")\n",
    "    ax.set_xlabel(\"Feature importance\")\n",
    "    ax.invert_yaxis()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_features(X_train.columns, ideal_model.feature_importances_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "OROPS                  177971\n",
       "EROPS                  141769\n",
       "EROPS w AC              92601\n",
       "EROPS AC                   18\n",
       "NO ROPS                     3\n",
       "None or Unspecified         2\n",
       "Name: Enclosure, dtype: int64"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Enclosure\"].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Question to finish:** Why might knowing the feature importances of a trained machine learning model be helpful?\n",
    "\n",
    "**Final challenge/extension:** What other machine learning models could you try on our dataset? \n",
    "**Hint:** https://scikit-learn.org/stable/tutorial/machine_learning_map/index.html check out the regression section of this map, or try to look at something like CatBoost.ai or XGBooost.ai."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}