working_notebook.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Goals\n",
    "\n",
    "### - Identify what is driving log error\n",
    "### - Build a model to accurately predict the log error"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Hypotheses\n",
    "What we think causes log error:\n",
    "- Location: certain geographic areas may be harder to accurately predict than others. Log error may differ by County. \n",
    "- Property Value: higher valued properties may have more variance which makes them harder to predict\n",
    "- Age of Property: newer homes may be similarily built, thus easier to predict price. Older property values may have more variance, thus making them harder to predict\n",
    "- Amenities: fireplace, pool, hot tub, and garage are nice amenities that not all properties include. These amenities may be driving log error by making property values harder to predict."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Set up Environment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "sns.set(style=\"white\", palette=\"muted\")\n",
    "#import acquire\n",
    "import prep\n",
    "import split_scale\n",
    "import explore\n",
    "import model\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "from math import sqrt\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.cluster import dbscan\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.metrics import mean_squared_error, r2_score, explained_variance_score\n",
    "\n",
    "\n",
    "from sklearn.impute import SimpleImputer\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.model_selection import train_test_split\n",
    "import warnings\n",
    "from sklearn.metrics import classification_report\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import mean_squared_error\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.tree import DecisionTreeRegressor\n",
    "from sklearn.preprocessing import StandardScaler, MinMaxScaler"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Acquisition"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "### In this section we acquire our data from the SQL database. \n",
    "\n",
    "### We  choose to filter on the following conditions based on the requirements of this project:\n",
    "- Only include properties containing latitude and longitude values.\n",
    "- Only include properties with a transaction in 2017 (using the most recent transaction date to avoid duplicates).\n",
    "- Only include single unit properties. \n",
    "  - Single unit property: a free standing property in which the owner also owns the land beneath the property. A single unit property is built for the use of one family (i.e. does not include duplexes, triplexes, etc.)\n",
    "  \n",
    "  #### Due to unforseen SQL server issues, we completed this project using a csv exported through SQL. This csv is located in our repository. This project remains reproducible both the csv and our acquire.py function. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Read in the data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv('query_result.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check the size of the data: 52,357 rows and 61 columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(52357, 61)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Preview the first five rows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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",
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       "    }\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>parcelid</th>\n",
       "      <th>id</th>\n",
       "      <th>airconditioningtypeid</th>\n",
       "      <th>architecturalstyletypeid</th>\n",
       "      <th>basementsqft</th>\n",
       "      <th>bathroomcnt</th>\n",
       "      <th>bedroomcnt</th>\n",
       "      <th>buildingclasstypeid</th>\n",
       "      <th>buildingqualitytypeid</th>\n",
       "      <th>calculatedbathnbr</th>\n",
       "      <th>...</th>\n",
       "      <th>structuretaxvaluedollarcnt</th>\n",
       "      <th>taxvaluedollarcnt</th>\n",
       "      <th>assessmentyear</th>\n",
       "      <th>landtaxvaluedollarcnt</th>\n",
       "      <th>taxamount</th>\n",
       "      <th>taxdelinquencyflag</th>\n",
       "      <th>taxdelinquencyyear</th>\n",
       "      <th>censustractandblock</th>\n",
       "      <th>logerror</th>\n",
       "      <th>transactiondate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>14297519</td>\n",
       "      <td>1727539</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.5</td>\n",
       "      <td>...</td>\n",
       "      <td>485713.0</td>\n",
       "      <td>1023282.0</td>\n",
       "      <td>2016</td>\n",
       "      <td>537569.0</td>\n",
       "      <td>11013.72</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.059063e+13</td>\n",
       "      <td>0.025595</td>\n",
       "      <td>2017-01-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>17052889</td>\n",
       "      <td>1387261</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>88000.0</td>\n",
       "      <td>464000.0</td>\n",
       "      <td>2016</td>\n",
       "      <td>376000.0</td>\n",
       "      <td>5672.48</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.111001e+13</td>\n",
       "      <td>0.055619</td>\n",
       "      <td>2017-01-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>14186244</td>\n",
       "      <td>11677</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>85289.0</td>\n",
       "      <td>564778.0</td>\n",
       "      <td>2016</td>\n",
       "      <td>479489.0</td>\n",
       "      <td>6488.30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.059022e+13</td>\n",
       "      <td>0.005383</td>\n",
       "      <td>2017-01-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12177905</td>\n",
       "      <td>2288172</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>108918.0</td>\n",
       "      <td>145143.0</td>\n",
       "      <td>2016</td>\n",
       "      <td>36225.0</td>\n",
       "      <td>1777.51</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.037300e+13</td>\n",
       "      <td>-0.103410</td>\n",
       "      <td>2017-01-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>12095076</td>\n",
       "      <td>781532</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>276684.0</td>\n",
       "      <td>773303.0</td>\n",
       "      <td>2016</td>\n",
       "      <td>496619.0</td>\n",
       "      <td>9516.26</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.037461e+13</td>\n",
       "      <td>-0.001011</td>\n",
       "      <td>2017-01-01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 61 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   parcelid       id  airconditioningtypeid  architecturalstyletypeid  \\\n",
       "0  14297519  1727539                    NaN                       NaN   \n",
       "1  17052889  1387261                    NaN                       NaN   \n",
       "2  14186244    11677                    NaN                       NaN   \n",
       "3  12177905  2288172                    NaN                       NaN   \n",
       "4  12095076   781532                    1.0                       NaN   \n",
       "\n",
       "   basementsqft  bathroomcnt  bedroomcnt  buildingclasstypeid  \\\n",
       "0           NaN          3.5           4                  NaN   \n",
       "1           NaN          1.0           2                  NaN   \n",
       "2           NaN          2.0           3                  NaN   \n",
       "3           NaN          3.0           4                  NaN   \n",
       "4           NaN          3.0           4                  NaN   \n",
       "\n",
       "   buildingqualitytypeid  calculatedbathnbr  ...  structuretaxvaluedollarcnt  \\\n",
       "0                    NaN                3.5  ...                    485713.0   \n",
       "1                    NaN                1.0  ...                     88000.0   \n",
       "2                    NaN                2.0  ...                     85289.0   \n",
       "3                    8.0                3.0  ...                    108918.0   \n",
       "4                    9.0                3.0  ...                    276684.0   \n",
       "\n",
       "   taxvaluedollarcnt  assessmentyear  landtaxvaluedollarcnt  taxamount  \\\n",
       "0          1023282.0            2016               537569.0   11013.72   \n",
       "1           464000.0            2016               376000.0    5672.48   \n",
       "2           564778.0            2016               479489.0    6488.30   \n",
       "3           145143.0            2016                36225.0    1777.51   \n",
       "4           773303.0            2016               496619.0    9516.26   \n",
       "\n",
       "   taxdelinquencyflag  taxdelinquencyyear  censustractandblock  logerror  \\\n",
       "0                 NaN                 NaN         6.059063e+13  0.025595   \n",
       "1                 NaN                 NaN         6.111001e+13  0.055619   \n",
       "2                 NaN                 NaN         6.059022e+13  0.005383   \n",
       "3                 NaN                 NaN         6.037300e+13 -0.103410   \n",
       "4                 NaN                 NaN         6.037461e+13 -0.001011   \n",
       "\n",
       "   transactiondate  \n",
       "0       2017-01-01  \n",
       "1       2017-01-01  \n",
       "2       2017-01-01  \n",
       "3       2017-01-01  \n",
       "4       2017-01-01  \n",
       "\n",
       "[5 rows x 61 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Preview the column names:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['parcelid', 'id', 'airconditioningtypeid', 'architecturalstyletypeid',\n",
       "       'basementsqft', 'bathroomcnt', 'bedroomcnt', 'buildingclasstypeid',\n",
       "       'buildingqualitytypeid', 'calculatedbathnbr', 'decktypeid',\n",
       "       'finishedfloor1squarefeet', 'calculatedfinishedsquarefeet',\n",
       "       'finishedsquarefeet12', 'finishedsquarefeet13', 'finishedsquarefeet15',\n",
       "       'finishedsquarefeet50', 'finishedsquarefeet6', 'fips', 'fireplacecnt',\n",
       "       'fullbathcnt', 'garagecarcnt', 'garagetotalsqft', 'hashottuborspa',\n",
       "       'heatingorsystemtypeid', 'latitude', 'longitude', 'lotsizesquarefeet',\n",
       "       'poolcnt', 'poolsizesum', 'pooltypeid10', 'pooltypeid2', 'pooltypeid7',\n",
       "       'propertycountylandusecode', 'propertylandusetypeid',\n",
       "       'propertyzoningdesc', 'rawcensustractandblock', 'regionidcity',\n",
       "       'regionidcounty', 'regionidneighborhood', 'regionidzip', 'roomcnt',\n",
       "       'storytypeid', 'threequarterbathnbr', 'typeconstructiontypeid',\n",
       "       'unitcnt', 'yardbuildingsqft17', 'yardbuildingsqft26', 'yearbuilt',\n",
       "       'numberofstories', 'fireplaceflag', 'structuretaxvaluedollarcnt',\n",
       "       'taxvaluedollarcnt', 'assessmentyear', 'landtaxvaluedollarcnt',\n",
       "       'taxamount', 'taxdelinquencyflag', 'taxdelinquencyyear',\n",
       "       'censustractandblock', 'logerror', 'transactiondate'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Preparation\n",
    "### In this section we prepare the data for exploration and modeling by doing the following:\n",
    "- Drop columns missing excessive amounts of data\n",
    "- Impute missing values for columns missing only a small portion of data\n",
    "- Treat outliers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Preview nulls"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This function shows the amount of rows that have null values for each column. We use this to get an idea of which columns will likely be dropped due to insufficient data. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\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>num_rows_missing</th>\n",
       "      <th>pct_rows_missing</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>parcelid</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>airconditioningtypeid</th>\n",
       "      <td>38738</td>\n",
       "      <td>0.739882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>architecturalstyletypeid</th>\n",
       "      <td>52287</td>\n",
       "      <td>0.998663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>basementsqft</th>\n",
       "      <td>52310</td>\n",
       "      <td>0.999102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bathroomcnt</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bedroomcnt</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>buildingclasstypeid</th>\n",
       "      <td>52357</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>buildingqualitytypeid</th>\n",
       "      <td>18692</td>\n",
       "      <td>0.357011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>calculatedbathnbr</th>\n",
       "      <td>162</td>\n",
       "      <td>0.003094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>decktypeid</th>\n",
       "      <td>51968</td>\n",
       "      <td>0.992570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>finishedfloor1squarefeet</th>\n",
       "      <td>47986</td>\n",
       "      <td>0.916515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>calculatedfinishedsquarefeet</th>\n",
       "      <td>107</td>\n",
       "      <td>0.002044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>finishedsquarefeet12</th>\n",
       "      <td>273</td>\n",
       "      <td>0.005214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>finishedsquarefeet13</th>\n",
       "      <td>52357</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>finishedsquarefeet15</th>\n",
       "      <td>52357</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>finishedsquarefeet50</th>\n",
       "      <td>47986</td>\n",
       "      <td>0.916515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>finishedsquarefeet6</th>\n",
       "      <td>52191</td>\n",
       "      <td>0.996829</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fips</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fireplacecnt</th>\n",
       "      <td>45124</td>\n",
       "      <td>0.861852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fullbathcnt</th>\n",
       "      <td>162</td>\n",
       "      <td>0.003094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>garagecarcnt</th>\n",
       "      <td>34373</td>\n",
       "      <td>0.656512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>garagetotalsqft</th>\n",
       "      <td>34373</td>\n",
       "      <td>0.656512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hashottuborspa</th>\n",
       "      <td>50843</td>\n",
       "      <td>0.971083</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>heatingorsystemtypeid</th>\n",
       "      <td>18497</td>\n",
       "      <td>0.353286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>latitude</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>longitude</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lotsizesquarefeet</th>\n",
       "      <td>375</td>\n",
       "      <td>0.007162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>poolcnt</th>\n",
       "      <td>41277</td>\n",
       "      <td>0.788376</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>poolsizesum</th>\n",
       "      <td>51492</td>\n",
       "      <td>0.983479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pooltypeid2</th>\n",
       "      <td>51286</td>\n",
       "      <td>0.979544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pooltypeid7</th>\n",
       "      <td>42364</td>\n",
       "      <td>0.809137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>propertycountylandusecode</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>propertylandusetypeid</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>propertyzoningdesc</th>\n",
       "      <td>18559</td>\n",
       "      <td>0.354470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rawcensustractandblock</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>regionidcity</th>\n",
       "      <td>1036</td>\n",
       "      <td>0.019787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>regionidcounty</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>regionidneighborhood</th>\n",
       "      <td>33357</td>\n",
       "      <td>0.637107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>regionidzip</th>\n",
       "      <td>26</td>\n",
       "      <td>0.000497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>roomcnt</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>storytypeid</th>\n",
       "      <td>52310</td>\n",
       "      <td>0.999102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>threequarterbathnbr</th>\n",
       "      <td>45640</td>\n",
       "      <td>0.871708</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>typeconstructiontypeid</th>\n",
       "      <td>52281</td>\n",
       "      <td>0.998548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unitcnt</th>\n",
       "      <td>18582</td>\n",
       "      <td>0.354910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yardbuildingsqft17</th>\n",
       "      <td>50422</td>\n",
       "      <td>0.963042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yardbuildingsqft26</th>\n",
       "      <td>52294</td>\n",
       "      <td>0.998797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yearbuilt</th>\n",
       "      <td>140</td>\n",
       "      <td>0.002674</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>numberofstories</th>\n",
       "      <td>37824</td>\n",
       "      <td>0.722425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fireplaceflag</th>\n",
       "      <td>52276</td>\n",
       "      <td>0.998453</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>structuretaxvaluedollarcnt</th>\n",
       "      <td>82</td>\n",
       "      <td>0.001566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>taxvaluedollarcnt</th>\n",
       "      <td>1</td>\n",
       "      <td>0.000019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>assessmentyear</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>landtaxvaluedollarcnt</th>\n",
       "      <td>1</td>\n",
       "      <td>0.000019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>taxamount</th>\n",
       "      <td>4</td>\n",
       "      <td>0.000076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>taxdelinquencyflag</th>\n",
       "      <td>50288</td>\n",
       "      <td>0.960483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>taxdelinquencyyear</th>\n",
       "      <td>50288</td>\n",
       "      <td>0.960483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>censustractandblock</th>\n",
       "      <td>125</td>\n",
       "      <td>0.002387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>logerror</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>transactiondate</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>61 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                              num_rows_missing  pct_rows_missing\n",
       "parcelid                                     0          0.000000\n",
       "id                                           0          0.000000\n",
       "airconditioningtypeid                    38738          0.739882\n",
       "architecturalstyletypeid                 52287          0.998663\n",
       "basementsqft                             52310          0.999102\n",
       "bathroomcnt                                  0          0.000000\n",
       "bedroomcnt                                   0          0.000000\n",
       "buildingclasstypeid                      52357          1.000000\n",
       "buildingqualitytypeid                    18692          0.357011\n",
       "calculatedbathnbr                          162          0.003094\n",
       "decktypeid                               51968          0.992570\n",
       "finishedfloor1squarefeet                 47986          0.916515\n",
       "calculatedfinishedsquarefeet               107          0.002044\n",
       "finishedsquarefeet12                       273          0.005214\n",
       "finishedsquarefeet13                     52357          1.000000\n",
       "finishedsquarefeet15                     52357          1.000000\n",
       "finishedsquarefeet50                     47986          0.916515\n",
       "finishedsquarefeet6                      52191          0.996829\n",
       "fips                                         0          0.000000\n",
       "fireplacecnt                             45124          0.861852\n",
       "fullbathcnt                                162          0.003094\n",
       "garagecarcnt                             34373          0.656512\n",
       "garagetotalsqft                          34373          0.656512\n",
       "hashottuborspa                           50843          0.971083\n",
       "heatingorsystemtypeid                    18497          0.353286\n",
       "latitude                                     0          0.000000\n",
       "longitude                                    0          0.000000\n",
       "lotsizesquarefeet                          375          0.007162\n",
       "poolcnt                                  41277          0.788376\n",
       "poolsizesum                              51492          0.983479\n",
       "...                                        ...               ...\n",
       "pooltypeid2                              51286          0.979544\n",
       "pooltypeid7                              42364          0.809137\n",
       "propertycountylandusecode                    0          0.000000\n",
       "propertylandusetypeid                        0          0.000000\n",
       "propertyzoningdesc                       18559          0.354470\n",
       "rawcensustractandblock                       0          0.000000\n",
       "regionidcity                              1036          0.019787\n",
       "regionidcounty                               0          0.000000\n",
       "regionidneighborhood                     33357          0.637107\n",
       "regionidzip                                 26          0.000497\n",
       "roomcnt                                      0          0.000000\n",
       "storytypeid                              52310          0.999102\n",
       "threequarterbathnbr                      45640          0.871708\n",
       "typeconstructiontypeid                   52281          0.998548\n",
       "unitcnt                                  18582          0.354910\n",
       "yardbuildingsqft17                       50422          0.963042\n",
       "yardbuildingsqft26                       52294          0.998797\n",
       "yearbuilt                                  140          0.002674\n",
       "numberofstories                          37824          0.722425\n",
       "fireplaceflag                            52276          0.998453\n",
       "structuretaxvaluedollarcnt                  82          0.001566\n",
       "taxvaluedollarcnt                            1          0.000019\n",
       "assessmentyear                               0          0.000000\n",
       "landtaxvaluedollarcnt                        1          0.000019\n",
       "taxamount                                    4          0.000076\n",
       "taxdelinquencyflag                       50288          0.960483\n",
       "taxdelinquencyyear                       50288          0.960483\n",
       "censustractandblock                        125          0.002387\n",
       "logerror                                     0          0.000000\n",
       "transactiondate                              0          0.000000\n",
       "\n",
       "[61 rows x 2 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prep.nulls_by_col(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Running the data through our prepare function acheives the following:\n",
    "- drops 40 columns due to excess nulls, redundancy, and irrelevency\n",
    "- removes properties with tax dollar value count greater than $1 million\n",
    "- removes properties with a log error less than negative one or greater than 1\n",
    "- fills nulls with zero for fireplacecnt, garagecarcnt, poolcnt, and taxdelinquencyyear\n",
    "- impute missing values based on mode: regionidcity\n",
    "- impute missing values based on mean: calculatedfinishedsquarefeet, lotsizesquarefeet, regionidzip, and yearbuilt\n",
    "- encodes the fips columns\n",
    "- fills nulls in taxdelinquencyflag with 'N'\n",
    "#### Result: Our data is transformed from 52,357 rows x 61 columns to 46,756 rows x 21 columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 52357 entries, 0 to 52356\n",
      "Data columns (total 61 columns):\n",
      "parcelid                        52357 non-null int64\n",
      "id                              52357 non-null int64\n",
      "airconditioningtypeid           13619 non-null float64\n",
      "architecturalstyletypeid        70 non-null float64\n",
      "basementsqft                    47 non-null float64\n",
      "bathroomcnt                     52357 non-null float64\n",
      "bedroomcnt                      52357 non-null int64\n",
      "buildingclasstypeid             0 non-null float64\n",
      "buildingqualitytypeid           33665 non-null float64\n",
      "calculatedbathnbr               52195 non-null float64\n",
      "decktypeid                      389 non-null float64\n",
      "finishedfloor1squarefeet        4371 non-null float64\n",
      "calculatedfinishedsquarefeet    52250 non-null float64\n",
      "finishedsquarefeet12            52084 non-null float64\n",
      "finishedsquarefeet13            0 non-null float64\n",
      "finishedsquarefeet15            0 non-null float64\n",
      "finishedsquarefeet50            4371 non-null float64\n",
      "finishedsquarefeet6             166 non-null float64\n",
      "fips                            52357 non-null int64\n",
      "fireplacecnt                    7233 non-null float64\n",
      "fullbathcnt                     52195 non-null float64\n",
      "garagecarcnt                    17984 non-null float64\n",
      "garagetotalsqft                 17984 non-null float64\n",
      "hashottuborspa                  1514 non-null float64\n",
      "heatingorsystemtypeid           33860 non-null float64\n",
      "latitude                        52357 non-null int64\n",
      "longitude                       52357 non-null int64\n",
      "lotsizesquarefeet               51982 non-null float64\n",
      "poolcnt                         11080 non-null float64\n",
      "poolsizesum                     865 non-null float64\n",
      "pooltypeid10                    443 non-null float64\n",
      "pooltypeid2                     1071 non-null float64\n",
      "pooltypeid7                     9993 non-null float64\n",
      "propertycountylandusecode       52357 non-null object\n",
      "propertylandusetypeid           52357 non-null int64\n",
      "propertyzoningdesc              33798 non-null object\n",
      "rawcensustractandblock          52357 non-null float64\n",
      "regionidcity                    51321 non-null float64\n",
      "regionidcounty                  52357 non-null int64\n",
      "regionidneighborhood            19000 non-null float64\n",
      "regionidzip                     52331 non-null float64\n",
      "roomcnt                         52357 non-null int64\n",
      "storytypeid                     47 non-null float64\n",
      "threequarterbathnbr             6717 non-null float64\n",
      "typeconstructiontypeid          76 non-null float64\n",
      "unitcnt                         33775 non-null float64\n",
      "yardbuildingsqft17              1935 non-null float64\n",
      "yardbuildingsqft26              63 non-null float64\n",
      "yearbuilt                       52217 non-null float64\n",
      "numberofstories                 14533 non-null float64\n",
      "fireplaceflag                   81 non-null float64\n",
      "structuretaxvaluedollarcnt      52275 non-null float64\n",
      "taxvaluedollarcnt               52356 non-null float64\n",
      "assessmentyear                  52357 non-null int64\n",
      "landtaxvaluedollarcnt           52356 non-null float64\n",
      "taxamount                       52353 non-null float64\n",
      "taxdelinquencyflag              2069 non-null object\n",
      "taxdelinquencyyear              2069 non-null float64\n",
      "censustractandblock             52232 non-null float64\n",
      "logerror                        52357 non-null float64\n",
      "transactiondate                 52357 non-null object\n",
      "dtypes: float64(47), int64(10), object(4)\n",
      "memory usage: 24.4+ MB\n"
     ]
    }
   ],
   "source": [
    "data = prep.prep_zillow(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check the size of the data: 46,756 rows and 21 columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(46756, 21)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Remaining columns:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "parcelid                        float64\n",
       "bathroomcnt                     float64\n",
       "bedroomcnt                      float64\n",
       "calculatedfinishedsquarefeet    float64\n",
       "fips                            float64\n",
       "fireplacecnt                    float64\n",
       "garagecarcnt                    float64\n",
       "latitude                        float64\n",
       "longitude                       float64\n",
       "lotsizesquarefeet               float64\n",
       "poolcnt                         float64\n",
       "propertylandusetypeid           float64\n",
       "regionidcity                    float64\n",
       "regionidcounty                  float64\n",
       "regionidzip                     float64\n",
       "roomcnt                         float64\n",
       "yearbuilt                       float64\n",
       "taxvaluedollarcnt               float64\n",
       "taxdelinquencyflag              float64\n",
       "taxdelinquencyyear              float64\n",
       "logerror                        float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Preview the first five rows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>parcelid</th>\n",
       "      <th>bathroomcnt</th>\n",
       "      <th>bedroomcnt</th>\n",
       "      <th>calculatedfinishedsquarefeet</th>\n",
       "      <th>fips</th>\n",
       "      <th>fireplacecnt</th>\n",
       "      <th>garagecarcnt</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>lotsizesquarefeet</th>\n",
       "      <th>...</th>\n",
       "      <th>propertylandusetypeid</th>\n",
       "      <th>regionidcity</th>\n",
       "      <th>regionidcounty</th>\n",
       "      <th>regionidzip</th>\n",
       "      <th>roomcnt</th>\n",
       "      <th>yearbuilt</th>\n",
       "      <th>taxvaluedollarcnt</th>\n",
       "      <th>taxdelinquencyflag</th>\n",
       "      <th>taxdelinquencyyear</th>\n",
       "      <th>logerror</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.040395</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.181818</td>\n",
       "      <td>0.170492</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.111111</td>\n",
       "      <td>0.750024</td>\n",
       "      <td>0.088111</td>\n",
       "      <td>0.001780</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.024423</td>\n",
       "      <td>0.426997</td>\n",
       "      <td>0.003678</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>0.644928</td>\n",
       "      <td>0.463493</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.527285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.022133</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.272727</td>\n",
       "      <td>0.142183</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.222222</td>\n",
       "      <td>0.369076</td>\n",
       "      <td>0.858200</td>\n",
       "      <td>0.001176</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.045593</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.003609</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.608696</td>\n",
       "      <td>0.564378</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.502109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.009339</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.363636</td>\n",
       "      <td>0.286662</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.611955</td>\n",
       "      <td>0.637712</td>\n",
       "      <td>0.001837</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.999987</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.001146</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.144296</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.447587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.008812</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.363636</td>\n",
       "      <td>0.361387</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.544318</td>\n",
       "      <td>0.669869</td>\n",
       "      <td>0.009004</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.110740</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.001024</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.521739</td>\n",
       "      <td>0.773125</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.498905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.008646</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.181818</td>\n",
       "      <td>0.077786</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.547032</td>\n",
       "      <td>0.638432</td>\n",
       "      <td>0.000571</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.106766</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.001129</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.318841</td>\n",
       "      <td>0.217784</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.550391</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   parcelid  bathroomcnt  bedroomcnt  calculatedfinishedsquarefeet  fips  \\\n",
       "1  0.040395          0.1    0.181818                      0.170492   1.0   \n",
       "2  0.022133          0.2    0.272727                      0.142183   0.5   \n",
       "3  0.009339          0.3    0.363636                      0.286662   0.0   \n",
       "4  0.008812          0.3    0.363636                      0.361387   0.0   \n",
       "5  0.008646          0.1    0.181818                      0.077786   0.0   \n",
       "\n",
       "   fireplacecnt  garagecarcnt  latitude  longitude  lotsizesquarefeet  ...  \\\n",
       "1           0.2      0.111111  0.750024   0.088111           0.001780  ...   \n",
       "2           0.0      0.222222  0.369076   0.858200           0.001176  ...   \n",
       "3           0.0      0.000000  0.611955   0.637712           0.001837  ...   \n",
       "4           0.0      0.000000  0.544318   0.669869           0.009004  ...   \n",
       "5           0.0      0.000000  0.547032   0.638432           0.000571  ...   \n",
       "\n",
       "   propertylandusetypeid  regionidcity  regionidcounty  regionidzip   roomcnt  \\\n",
       "1                    1.0      0.024423        0.426997     0.003678  0.416667   \n",
       "2                    1.0      0.045593        0.000000     0.003609  0.500000   \n",
       "3                    1.0      0.999987        1.000000     0.001146  0.000000   \n",
       "4                    1.0      0.110740        1.000000     0.001024  0.000000   \n",
       "5                    1.0      0.106766        1.000000     0.001129  0.000000   \n",
       "\n",
       "   yearbuilt  taxvaluedollarcnt  taxdelinquencyflag  taxdelinquencyyear  \\\n",
       "1   0.644928           0.463493                 0.0                 0.0   \n",
       "2   0.608696           0.564378                 0.0                 0.0   \n",
       "3   0.666667           0.144296                 0.0                 0.0   \n",
       "4   0.521739           0.773125                 0.0                 0.0   \n",
       "5   0.318841           0.217784                 0.0                 0.0   \n",
       "\n",
       "   logerror  \n",
       "1  0.527285  \n",
       "2  0.502109  \n",
       "3  0.447587  \n",
       "4  0.498905  \n",
       "5  0.550391  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploration"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Simple correlation matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>parcelid</th>\n",
       "      <th>bathroomcnt</th>\n",
       "      <th>bedroomcnt</th>\n",
       "      <th>calculatedfinishedsquarefeet</th>\n",
       "      <th>fips</th>\n",
       "      <th>fireplacecnt</th>\n",
       "      <th>garagecarcnt</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>lotsizesquarefeet</th>\n",
       "      <th>...</th>\n",
       "      <th>propertylandusetypeid</th>\n",
       "      <th>regionidcity</th>\n",
       "      <th>regionidcounty</th>\n",
       "      <th>regionidzip</th>\n",
       "      <th>roomcnt</th>\n",
       "      <th>yearbuilt</th>\n",
       "      <th>taxvaluedollarcnt</th>\n",
       "      <th>taxdelinquencyflag</th>\n",
       "      <th>taxdelinquencyyear</th>\n",
       "      <th>logerror</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>parcelid</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.067556</td>\n",
       "      <td>0.074868</td>\n",
       "      <td>0.072101</td>\n",
       "      <td>0.529092</td>\n",
       "      <td>0.339291</td>\n",
       "      <td>0.445554</td>\n",
       "      <td>-0.169301</td>\n",
       "      <td>-0.072063</td>\n",
       "      <td>-0.013919</td>\n",
       "      <td>...</td>\n",
       "      <td>0.006671</td>\n",
       "      <td>-0.027347</td>\n",
       "      <td>-0.387681</td>\n",
       "      <td>0.028324</td>\n",
       "      <td>0.424093</td>\n",
       "      <td>0.164711</td>\n",
       "      <td>0.088846</td>\n",
       "      <td>-0.044317</td>\n",
       "      <td>-0.044091</td>\n",
       "      <td>0.007230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bathroomcnt</th>\n",
       "      <td>0.067556</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.624234</td>\n",
       "      <td>0.799004</td>\n",
       "      <td>0.158046</td>\n",
       "      <td>0.160012</td>\n",
       "      <td>0.220746</td>\n",
       "      <td>0.049647</td>\n",
       "      <td>0.005006</td>\n",
       "      <td>0.014869</td>\n",
       "      <td>...</td>\n",
       "      <td>0.043571</td>\n",
       "      <td>-0.060170</td>\n",
       "      <td>-0.161191</td>\n",
       "      <td>0.033891</td>\n",
       "      <td>0.132278</td>\n",
       "      <td>0.540522</td>\n",
       "      <td>0.399990</td>\n",
       "      <td>-0.060032</td>\n",
       "      <td>-0.057925</td>\n",
       "      <td>0.027636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bedroomcnt</th>\n",
       "      <td>0.074868</td>\n",
       "      <td>0.624234</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.629117</td>\n",
       "      <td>0.156628</td>\n",
       "      <td>0.151163</td>\n",
       "      <td>0.199923</td>\n",
       "      <td>0.048408</td>\n",
       "      <td>-0.007811</td>\n",
       "      <td>0.001828</td>\n",
       "      <td>...</td>\n",
       "      <td>0.060512</td>\n",
       "      <td>-0.049474</td>\n",
       "      <td>-0.140770</td>\n",
       "      <td>0.021056</td>\n",
       "      <td>0.203176</td>\n",
       "      <td>0.371836</td>\n",
       "      <td>0.236200</td>\n",
       "      <td>-0.045336</td>\n",
       "      <td>-0.044308</td>\n",
       "      <td>0.039754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>calculatedfinishedsquarefeet</th>\n",
       "      <td>0.072101</td>\n",
       "      <td>0.799004</td>\n",
       "      <td>0.629117</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.162633</td>\n",
       "      <td>0.199747</td>\n",
       "      <td>0.227626</td>\n",
       "      <td>0.031712</td>\n",
       "      <td>-0.002917</td>\n",
       "      <td>0.025447</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.004926</td>\n",
       "      <td>-0.058061</td>\n",
       "      <td>-0.158700</td>\n",
       "      <td>0.029220</td>\n",
       "      <td>0.149093</td>\n",
       "      <td>0.475770</td>\n",
       "      <td>0.460109</td>\n",
       "      <td>-0.049351</td>\n",
       "      <td>-0.047788</td>\n",
       "      <td>0.027443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fips</th>\n",
       "      <td>0.529092</td>\n",
       "      <td>0.158046</td>\n",
       "      <td>0.156628</td>\n",
       "      <td>0.162633</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.620868</td>\n",
       "      <td>0.872777</td>\n",
       "      <td>-0.239963</td>\n",
       "      <td>-0.192006</td>\n",
       "      <td>-0.016702</td>\n",
       "      <td>...</td>\n",
       "      <td>0.013060</td>\n",
       "      <td>-0.062120</td>\n",
       "      <td>-0.793113</td>\n",
       "      <td>0.054662</td>\n",
       "      <td>0.831342</td>\n",
       "      <td>0.327296</td>\n",
       "      <td>0.188679</td>\n",
       "      <td>-0.080075</td>\n",
       "      <td>-0.079558</td>\n",
       "      <td>0.012689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fireplacecnt</th>\n",
       "      <td>0.339291</td>\n",
       "      <td>0.160012</td>\n",
       "      <td>0.151163</td>\n",
       "      <td>0.199747</td>\n",
       "      <td>0.620868</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.534191</td>\n",
       "      <td>-0.066052</td>\n",
       "      <td>-0.224796</td>\n",
       "      <td>-0.003863</td>\n",
       "      <td>...</td>\n",
       "      <td>0.008208</td>\n",
       "      <td>-0.027174</td>\n",
       "      <td>-0.409872</td>\n",
       "      <td>0.029183</td>\n",
       "      <td>0.619804</td>\n",
       "      <td>0.203245</td>\n",
       "      <td>0.165260</td>\n",
       "      <td>-0.051517</td>\n",
       "      <td>-0.050704</td>\n",
       "      <td>0.000632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>garagecarcnt</th>\n",
       "      <td>0.445554</td>\n",
       "      <td>0.220746</td>\n",
       "      <td>0.199923</td>\n",
       "      <td>0.227626</td>\n",
       "      <td>0.872777</td>\n",
       "      <td>0.534191</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.435377</td>\n",
       "      <td>0.131245</td>\n",
       "      <td>-0.019327</td>\n",
       "      <td>...</td>\n",
       "      <td>0.014942</td>\n",
       "      <td>-0.070075</td>\n",
       "      <td>-0.907746</td>\n",
       "      <td>0.055704</td>\n",
       "      <td>0.810130</td>\n",
       "      <td>0.373620</td>\n",
       "      <td>0.233785</td>\n",
       "      <td>-0.081790</td>\n",
       "      <td>-0.080438</td>\n",
       "      <td>0.013678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>latitude</th>\n",
       "      <td>-0.169301</td>\n",
       "      <td>0.049647</td>\n",
       "      <td>0.048408</td>\n",
       "      <td>0.031712</td>\n",
       "      <td>-0.239963</td>\n",
       "      <td>-0.066052</td>\n",
       "      <td>-0.435377</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.531718</td>\n",
       "      <td>0.056274</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.007823</td>\n",
       "      <td>-0.017105</td>\n",
       "      <td>0.572667</td>\n",
       "      <td>0.018068</td>\n",
       "      <td>-0.306809</td>\n",
       "      <td>0.111885</td>\n",
       "      <td>-0.175405</td>\n",
       "      <td>0.035346</td>\n",
       "      <td>0.034828</td>\n",
       "      <td>-0.011473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>longitude</th>\n",
       "      <td>-0.072063</td>\n",
       "      <td>0.005006</td>\n",
       "      <td>-0.007811</td>\n",
       "      <td>-0.002917</td>\n",
       "      <td>-0.192006</td>\n",
       "      <td>-0.224796</td>\n",
       "      <td>0.131245</td>\n",
       "      <td>-0.531718</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.010717</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.002308</td>\n",
       "      <td>-0.006678</td>\n",
       "      <td>-0.341575</td>\n",
       "      <td>0.028224</td>\n",
       "      <td>-0.018859</td>\n",
       "      <td>0.078307</td>\n",
       "      <td>0.003146</td>\n",
       "      <td>0.004240</td>\n",
       "      <td>0.005001</td>\n",
       "      <td>0.013516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lotsizesquarefeet</th>\n",
       "      <td>-0.013919</td>\n",
       "      <td>0.014869</td>\n",
       "      <td>0.001828</td>\n",
       "      <td>0.025447</td>\n",
       "      <td>-0.016702</td>\n",
       "      <td>-0.003863</td>\n",
       "      <td>-0.019327</td>\n",
       "      <td>0.056274</td>\n",
       "      <td>-0.010717</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000077</td>\n",
       "      <td>-0.009244</td>\n",
       "      <td>0.024580</td>\n",
       "      <td>0.004698</td>\n",
       "      <td>-0.015408</td>\n",
       "      <td>0.029830</td>\n",
       "      <td>-0.001680</td>\n",
       "      <td>-0.000874</td>\n",
       "      <td>-0.000714</td>\n",
       "      <td>0.008460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>poolcnt</th>\n",
       "      <td>-0.008818</td>\n",
       "      <td>0.254149</td>\n",
       "      <td>0.215936</td>\n",
       "      <td>0.301279</td>\n",
       "      <td>0.019981</td>\n",
       "      <td>0.083578</td>\n",
       "      <td>0.055755</td>\n",
       "      <td>0.021388</td>\n",
       "      <td>0.001247</td>\n",
       "      <td>0.007824</td>\n",
       "      <td>...</td>\n",
       "      <td>0.010279</td>\n",
       "      <td>-0.029600</td>\n",
       "      <td>-0.038261</td>\n",
       "      <td>0.019649</td>\n",
       "      <td>0.082071</td>\n",
       "      <td>0.094210</td>\n",
       "      <td>0.187293</td>\n",
       "      <td>-0.020085</td>\n",
       "      <td>-0.019154</td>\n",
       "      <td>-0.036842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>propertylandusetypeid</th>\n",
       "      <td>0.006671</td>\n",
       "      <td>0.043571</td>\n",
       "      <td>0.060512</td>\n",
       "      <td>-0.004926</td>\n",
       "      <td>0.013060</td>\n",
       "      <td>0.008208</td>\n",
       "      <td>0.014942</td>\n",
       "      <td>-0.007823</td>\n",
       "      <td>-0.002308</td>\n",
       "      <td>0.000077</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.005530</td>\n",
       "      <td>-0.013132</td>\n",
       "      <td>0.000873</td>\n",
       "      <td>0.011531</td>\n",
       "      <td>-0.002325</td>\n",
       "      <td>-0.006501</td>\n",
       "      <td>-0.000707</td>\n",
       "      <td>-0.000666</td>\n",
       "      <td>0.009699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>regionidcity</th>\n",
       "      <td>-0.027347</td>\n",
       "      <td>-0.060170</td>\n",
       "      <td>-0.049474</td>\n",
       "      <td>-0.058061</td>\n",
       "      <td>-0.062120</td>\n",
       "      <td>-0.027174</td>\n",
       "      <td>-0.070075</td>\n",
       "      <td>-0.017105</td>\n",
       "      <td>-0.006678</td>\n",
       "      <td>-0.009244</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.005530</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.074872</td>\n",
       "      <td>-0.014707</td>\n",
       "      <td>-0.057591</td>\n",
       "      <td>-0.096154</td>\n",
       "      <td>-0.004984</td>\n",
       "      <td>0.005942</td>\n",
       "      <td>0.005128</td>\n",
       "      <td>0.004214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>regionidcounty</th>\n",
       "      <td>-0.387681</td>\n",
       "      <td>-0.161191</td>\n",
       "      <td>-0.140770</td>\n",
       "      <td>-0.158700</td>\n",
       "      <td>-0.793113</td>\n",
       "      <td>-0.409872</td>\n",
       "      <td>-0.907746</td>\n",
       "      <td>0.572667</td>\n",
       "      <td>-0.341575</td>\n",
       "      <td>0.024580</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.013132</td>\n",
       "      <td>0.074872</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.057067</td>\n",
       "      <td>-0.785277</td>\n",
       "      <td>-0.324130</td>\n",
       "      <td>-0.203042</td>\n",
       "      <td>0.076648</td>\n",
       "      <td>0.075335</td>\n",
       "      <td>-0.017184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>regionidzip</th>\n",
       "      <td>0.028324</td>\n",
       "      <td>0.033891</td>\n",
       "      <td>0.021056</td>\n",
       "      <td>0.029220</td>\n",
       "      <td>0.054662</td>\n",
       "      <td>0.029183</td>\n",
       "      <td>0.055704</td>\n",
       "      <td>0.018068</td>\n",
       "      <td>0.028224</td>\n",
       "      <td>0.004698</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000873</td>\n",
       "      <td>-0.014707</td>\n",
       "      <td>-0.057067</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.048056</td>\n",
       "      <td>0.063755</td>\n",
       "      <td>0.013325</td>\n",
       "      <td>-0.007565</td>\n",
       "      <td>-0.007408</td>\n",
       "      <td>0.001032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>roomcnt</th>\n",
       "      <td>0.424093</td>\n",
       "      <td>0.132278</td>\n",
       "      <td>0.203176</td>\n",
       "      <td>0.149093</td>\n",
       "      <td>0.831342</td>\n",
       "      <td>0.619804</td>\n",
       "      <td>0.810130</td>\n",
       "      <td>-0.306809</td>\n",
       "      <td>-0.018859</td>\n",
       "      <td>-0.015408</td>\n",
       "      <td>...</td>\n",
       "      <td>0.011531</td>\n",
       "      <td>-0.057591</td>\n",
       "      <td>-0.785277</td>\n",
       "      <td>0.048056</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.200796</td>\n",
       "      <td>0.115580</td>\n",
       "      <td>-0.071583</td>\n",
       "      <td>-0.070638</td>\n",
       "      <td>0.014843</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yearbuilt</th>\n",
       "      <td>0.164711</td>\n",
       "      <td>0.540522</td>\n",
       "      <td>0.371836</td>\n",
       "      <td>0.475770</td>\n",
       "      <td>0.327296</td>\n",
       "      <td>0.203245</td>\n",
       "      <td>0.373620</td>\n",
       "      <td>0.111885</td>\n",
       "      <td>0.078307</td>\n",
       "      <td>0.029830</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.002325</td>\n",
       "      <td>-0.096154</td>\n",
       "      <td>-0.324130</td>\n",
       "      <td>0.063755</td>\n",
       "      <td>0.200796</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.266682</td>\n",
       "      <td>-0.068216</td>\n",
       "      <td>-0.065508</td>\n",
       "      <td>0.015641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>taxvaluedollarcnt</th>\n",
       "      <td>0.088846</td>\n",
       "      <td>0.399990</td>\n",
       "      <td>0.236200</td>\n",
       "      <td>0.460109</td>\n",
       "      <td>0.188679</td>\n",
       "      <td>0.165260</td>\n",
       "      <td>0.233785</td>\n",
       "      <td>-0.175405</td>\n",
       "      <td>0.003146</td>\n",
       "      <td>-0.001680</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.006501</td>\n",
       "      <td>-0.004984</td>\n",
       "      <td>-0.203042</td>\n",
       "      <td>0.013325</td>\n",
       "      <td>0.115580</td>\n",
       "      <td>0.266682</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.045699</td>\n",
       "      <td>-0.041961</td>\n",
       "      <td>-0.028880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>taxdelinquencyflag</th>\n",
       "      <td>-0.044317</td>\n",
       "      <td>-0.060032</td>\n",
       "      <td>-0.045336</td>\n",
       "      <td>-0.049351</td>\n",
       "      <td>-0.080075</td>\n",
       "      <td>-0.051517</td>\n",
       "      <td>-0.081790</td>\n",
       "      <td>0.035346</td>\n",
       "      <td>0.004240</td>\n",
       "      <td>-0.000874</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000707</td>\n",
       "      <td>0.005942</td>\n",
       "      <td>0.076648</td>\n",
       "      <td>-0.007565</td>\n",
       "      <td>-0.071583</td>\n",
       "      <td>-0.068216</td>\n",
       "      <td>-0.045699</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.983964</td>\n",
       "      <td>0.025705</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>taxdelinquencyyear</th>\n",
       "      <td>-0.044091</td>\n",
       "      <td>-0.057925</td>\n",
       "      <td>-0.044308</td>\n",
       "      <td>-0.047788</td>\n",
       "      <td>-0.079558</td>\n",
       "      <td>-0.050704</td>\n",
       "      <td>-0.080438</td>\n",
       "      <td>0.034828</td>\n",
       "      <td>0.005001</td>\n",
       "      <td>-0.000714</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000666</td>\n",
       "      <td>0.005128</td>\n",
       "      <td>0.075335</td>\n",
       "      <td>-0.007408</td>\n",
       "      <td>-0.070638</td>\n",
       "      <td>-0.065508</td>\n",
       "      <td>-0.041961</td>\n",
       "      <td>0.983964</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.020211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>logerror</th>\n",
       "      <td>0.007230</td>\n",
       "      <td>0.027636</td>\n",
       "      <td>0.039754</td>\n",
       "      <td>0.027443</td>\n",
       "      <td>0.012689</td>\n",
       "      <td>0.000632</td>\n",
       "      <td>0.013678</td>\n",
       "      <td>-0.011473</td>\n",
       "      <td>0.013516</td>\n",
       "      <td>0.008460</td>\n",
       "      <td>...</td>\n",
       "      <td>0.009699</td>\n",
       "      <td>0.004214</td>\n",
       "      <td>-0.017184</td>\n",
       "      <td>0.001032</td>\n",
       "      <td>0.014843</td>\n",
       "      <td>0.015641</td>\n",
       "      <td>-0.028880</td>\n",
       "      <td>0.025705</td>\n",
       "      <td>0.020211</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>21 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                              parcelid  bathroomcnt  bedroomcnt  \\\n",
       "parcelid                      1.000000     0.067556    0.074868   \n",
       "bathroomcnt                   0.067556     1.000000    0.624234   \n",
       "bedroomcnt                    0.074868     0.624234    1.000000   \n",
       "calculatedfinishedsquarefeet  0.072101     0.799004    0.629117   \n",
       "fips                          0.529092     0.158046    0.156628   \n",
       "fireplacecnt                  0.339291     0.160012    0.151163   \n",
       "garagecarcnt                  0.445554     0.220746    0.199923   \n",
       "latitude                     -0.169301     0.049647    0.048408   \n",
       "longitude                    -0.072063     0.005006   -0.007811   \n",
       "lotsizesquarefeet            -0.013919     0.014869    0.001828   \n",
       "poolcnt                      -0.008818     0.254149    0.215936   \n",
       "propertylandusetypeid         0.006671     0.043571    0.060512   \n",
       "regionidcity                 -0.027347    -0.060170   -0.049474   \n",
       "regionidcounty               -0.387681    -0.161191   -0.140770   \n",
       "regionidzip                   0.028324     0.033891    0.021056   \n",
       "roomcnt                       0.424093     0.132278    0.203176   \n",
       "yearbuilt                     0.164711     0.540522    0.371836   \n",
       "taxvaluedollarcnt             0.088846     0.399990    0.236200   \n",
       "taxdelinquencyflag           -0.044317    -0.060032   -0.045336   \n",
       "taxdelinquencyyear           -0.044091    -0.057925   -0.044308   \n",
       "logerror                      0.007230     0.027636    0.039754   \n",
       "\n",
       "                              calculatedfinishedsquarefeet      fips  \\\n",
       "parcelid                                          0.072101  0.529092   \n",
       "bathroomcnt                                       0.799004  0.158046   \n",
       "bedroomcnt                                        0.629117  0.156628   \n",
       "calculatedfinishedsquarefeet                      1.000000  0.162633   \n",
       "fips                                              0.162633  1.000000   \n",
       "fireplacecnt                                      0.199747  0.620868   \n",
       "garagecarcnt                                      0.227626  0.872777   \n",
       "latitude                                          0.031712 -0.239963   \n",
       "longitude                                        -0.002917 -0.192006   \n",
       "lotsizesquarefeet                                 0.025447 -0.016702   \n",
       "poolcnt                                           0.301279  0.019981   \n",
       "propertylandusetypeid                            -0.004926  0.013060   \n",
       "regionidcity                                     -0.058061 -0.062120   \n",
       "regionidcounty                                   -0.158700 -0.793113   \n",
       "regionidzip                                       0.029220  0.054662   \n",
       "roomcnt                                           0.149093  0.831342   \n",
       "yearbuilt                                         0.475770  0.327296   \n",
       "taxvaluedollarcnt                                 0.460109  0.188679   \n",
       "taxdelinquencyflag                               -0.049351 -0.080075   \n",
       "taxdelinquencyyear                               -0.047788 -0.079558   \n",
       "logerror                                          0.027443  0.012689   \n",
       "\n",
       "                              fireplacecnt  garagecarcnt  latitude  longitude  \\\n",
       "parcelid                          0.339291      0.445554 -0.169301  -0.072063   \n",
       "bathroomcnt                       0.160012      0.220746  0.049647   0.005006   \n",
       "bedroomcnt                        0.151163      0.199923  0.048408  -0.007811   \n",
       "calculatedfinishedsquarefeet      0.199747      0.227626  0.031712  -0.002917   \n",
       "fips                              0.620868      0.872777 -0.239963  -0.192006   \n",
       "fireplacecnt                      1.000000      0.534191 -0.066052  -0.224796   \n",
       "garagecarcnt                      0.534191      1.000000 -0.435377   0.131245   \n",
       "latitude                         -0.066052     -0.435377  1.000000  -0.531718   \n",
       "longitude                        -0.224796      0.131245 -0.531718   1.000000   \n",
       "lotsizesquarefeet                -0.003863     -0.019327  0.056274  -0.010717   \n",
       "poolcnt                           0.083578      0.055755  0.021388   0.001247   \n",
       "propertylandusetypeid             0.008208      0.014942 -0.007823  -0.002308   \n",
       "regionidcity                     -0.027174     -0.070075 -0.017105  -0.006678   \n",
       "regionidcounty                   -0.409872     -0.907746  0.572667  -0.341575   \n",
       "regionidzip                       0.029183      0.055704  0.018068   0.028224   \n",
       "roomcnt                           0.619804      0.810130 -0.306809  -0.018859   \n",
       "yearbuilt                         0.203245      0.373620  0.111885   0.078307   \n",
       "taxvaluedollarcnt                 0.165260      0.233785 -0.175405   0.003146   \n",
       "taxdelinquencyflag               -0.051517     -0.081790  0.035346   0.004240   \n",
       "taxdelinquencyyear               -0.050704     -0.080438  0.034828   0.005001   \n",
       "logerror                          0.000632      0.013678 -0.011473   0.013516   \n",
       "\n",
       "                              lotsizesquarefeet  ...  propertylandusetypeid  \\\n",
       "parcelid                              -0.013919  ...               0.006671   \n",
       "bathroomcnt                            0.014869  ...               0.043571   \n",
       "bedroomcnt                             0.001828  ...               0.060512   \n",
       "calculatedfinishedsquarefeet           0.025447  ...              -0.004926   \n",
       "fips                                  -0.016702  ...               0.013060   \n",
       "fireplacecnt                          -0.003863  ...               0.008208   \n",
       "garagecarcnt                          -0.019327  ...               0.014942   \n",
       "latitude                               0.056274  ...              -0.007823   \n",
       "longitude                             -0.010717  ...              -0.002308   \n",
       "lotsizesquarefeet                      1.000000  ...               0.000077   \n",
       "poolcnt                                0.007824  ...               0.010279   \n",
       "propertylandusetypeid                  0.000077  ...               1.000000   \n",
       "regionidcity                          -0.009244  ...              -0.005530   \n",
       "regionidcounty                         0.024580  ...              -0.013132   \n",
       "regionidzip                            0.004698  ...               0.000873   \n",
       "roomcnt                               -0.015408  ...               0.011531   \n",
       "yearbuilt                              0.029830  ...              -0.002325   \n",
       "taxvaluedollarcnt                     -0.001680  ...              -0.006501   \n",
       "taxdelinquencyflag                    -0.000874  ...              -0.000707   \n",
       "taxdelinquencyyear                    -0.000714  ...              -0.000666   \n",
       "logerror                               0.008460  ...               0.009699   \n",
       "\n",
       "                              regionidcity  regionidcounty  regionidzip  \\\n",
       "parcelid                         -0.027347       -0.387681     0.028324   \n",
       "bathroomcnt                      -0.060170       -0.161191     0.033891   \n",
       "bedroomcnt                       -0.049474       -0.140770     0.021056   \n",
       "calculatedfinishedsquarefeet     -0.058061       -0.158700     0.029220   \n",
       "fips                             -0.062120       -0.793113     0.054662   \n",
       "fireplacecnt                     -0.027174       -0.409872     0.029183   \n",
       "garagecarcnt                     -0.070075       -0.907746     0.055704   \n",
       "latitude                         -0.017105        0.572667     0.018068   \n",
       "longitude                        -0.006678       -0.341575     0.028224   \n",
       "lotsizesquarefeet                -0.009244        0.024580     0.004698   \n",
       "poolcnt                          -0.029600       -0.038261     0.019649   \n",
       "propertylandusetypeid            -0.005530       -0.013132     0.000873   \n",
       "regionidcity                      1.000000        0.074872    -0.014707   \n",
       "regionidcounty                    0.074872        1.000000    -0.057067   \n",
       "regionidzip                      -0.014707       -0.057067     1.000000   \n",
       "roomcnt                          -0.057591       -0.785277     0.048056   \n",
       "yearbuilt                        -0.096154       -0.324130     0.063755   \n",
       "taxvaluedollarcnt                -0.004984       -0.203042     0.013325   \n",
       "taxdelinquencyflag                0.005942        0.076648    -0.007565   \n",
       "taxdelinquencyyear                0.005128        0.075335    -0.007408   \n",
       "logerror                          0.004214       -0.017184     0.001032   \n",
       "\n",
       "                               roomcnt  yearbuilt  taxvaluedollarcnt  \\\n",
       "parcelid                      0.424093   0.164711           0.088846   \n",
       "bathroomcnt                   0.132278   0.540522           0.399990   \n",
       "bedroomcnt                    0.203176   0.371836           0.236200   \n",
       "calculatedfinishedsquarefeet  0.149093   0.475770           0.460109   \n",
       "fips                          0.831342   0.327296           0.188679   \n",
       "fireplacecnt                  0.619804   0.203245           0.165260   \n",
       "garagecarcnt                  0.810130   0.373620           0.233785   \n",
       "latitude                     -0.306809   0.111885          -0.175405   \n",
       "longitude                    -0.018859   0.078307           0.003146   \n",
       "lotsizesquarefeet            -0.015408   0.029830          -0.001680   \n",
       "poolcnt                       0.082071   0.094210           0.187293   \n",
       "propertylandusetypeid         0.011531  -0.002325          -0.006501   \n",
       "regionidcity                 -0.057591  -0.096154          -0.004984   \n",
       "regionidcounty               -0.785277  -0.324130          -0.203042   \n",
       "regionidzip                   0.048056   0.063755           0.013325   \n",
       "roomcnt                       1.000000   0.200796           0.115580   \n",
       "yearbuilt                     0.200796   1.000000           0.266682   \n",
       "taxvaluedollarcnt             0.115580   0.266682           1.000000   \n",
       "taxdelinquencyflag           -0.071583  -0.068216          -0.045699   \n",
       "taxdelinquencyyear           -0.070638  -0.065508          -0.041961   \n",
       "logerror                      0.014843   0.015641          -0.028880   \n",
       "\n",
       "                              taxdelinquencyflag  taxdelinquencyyear  logerror  \n",
       "parcelid                               -0.044317           -0.044091  0.007230  \n",
       "bathroomcnt                            -0.060032           -0.057925  0.027636  \n",
       "bedroomcnt                             -0.045336           -0.044308  0.039754  \n",
       "calculatedfinishedsquarefeet           -0.049351           -0.047788  0.027443  \n",
       "fips                                   -0.080075           -0.079558  0.012689  \n",
       "fireplacecnt                           -0.051517           -0.050704  0.000632  \n",
       "garagecarcnt                           -0.081790           -0.080438  0.013678  \n",
       "latitude                                0.035346            0.034828 -0.011473  \n",
       "longitude                               0.004240            0.005001  0.013516  \n",
       "lotsizesquarefeet                      -0.000874           -0.000714  0.008460  \n",
       "poolcnt                                -0.020085           -0.019154 -0.036842  \n",
       "propertylandusetypeid                  -0.000707           -0.000666  0.009699  \n",
       "regionidcity                            0.005942            0.005128  0.004214  \n",
       "regionidcounty                          0.076648            0.075335 -0.017184  \n",
       "regionidzip                            -0.007565           -0.007408  0.001032  \n",
       "roomcnt                                -0.071583           -0.070638  0.014843  \n",
       "yearbuilt                              -0.068216           -0.065508  0.015641  \n",
       "taxvaluedollarcnt                      -0.045699           -0.041961 -0.028880  \n",
       "taxdelinquencyflag                      1.000000            0.983964  0.025705  \n",
       "taxdelinquencyyear                      0.983964            1.000000  0.020211  \n",
       "logerror                                0.025705            0.020211  1.000000  \n",
       "\n",
       "[21 rows x 21 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.corr()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "| Variable | Logerror Correlation (absolute value)   |\n",
    "|----|----|\n",
    "|logerror| 1|\n",
    "|bedroomcnt|\t0.039754|\n",
    "|poolcnt\t|0.036842|\n",
    "|taxvaluedollarcnt|\t0.02888|\n",
    "|bathroomcnt|\t0.027636|\n",
    "|calculatedfinishedsquarefeet|\t0.027443|\n",
    "|taxdelinquencyflag|\t0.025705|\n",
    "|taxdelinquencyyear|\t0.020211|\n",
    "|regionidcounty|\t0.017184|\n",
    "|yearbuilt|\t0.015641|\n",
    "|roomcnt|\t0.014843|\n",
    "|garagecarcnt|\t0.013678|\n",
    "|longitude|\t0.013516|\n",
    "|fips|\t0.012689|\n",
    "|latitude|\t0.011473|\n",
    "|propertylandusetypeid|\t0.009699|\n",
    "|lotsizesquarefeet|\t0.00846|\n",
    "|parcelid|\t0.00723|\n",
    "|regionidcity|\t0.004214|\n",
    "|regionidzip|\t0.001032|\n",
    "|fireplacecnt|\t0.000632|"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Property Value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<<<<|_AVERAGE_LOG_ERROR_PER_COUNTY_|>>>>>\n",
      "county\n",
      "LA               0.505380\n",
      "Orange_County    0.507641\n",
      "Ventura          0.506357\n",
      "Name: logerror, dtype: float64\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x216 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "explore.mean_logerror_county(data)\n",
    "    \n",
    "g = sns.FacetGrid(data, col = 'county')\n",
    "g = g.map(plt.scatter, 'logerror', 'taxvaluedollarcnt', alpha = .2)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Findings\n",
    "- There is corrolation in price when it comes to log error"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Age of Property"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Does Age of Property effect Log Error?')"
      ]
     },
     "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": [
    "ax = sns.scatterplot(x='logerror',y='yearbuilt', data = data)\n",
    "ax.set_title(\"Does Age of Property effect Log Error?\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Finding: \n",
    "- There is no direct correlation between log error and year built. We hypothesized that newer home prices would be easier to predict and older homes would have greater log errors. This chart does not support those findings. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Finding Optimal Cluster Count\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   k           sse\n",
      "0  1  35835.363729\n",
      "1  2  19694.499239\n",
      "2  3  15177.258872\n",
      "3  4  12261.860230\n",
      "4  5  10058.121808\n",
      "5  6   9197.709059\n",
      "6  7   7934.331600\n",
      "7  8   7186.005321\n",
      "8  9   6518.522630\n"
     ]
    },
    {
     "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": [
    "data = data.drop(columns = ['county'])\n",
    "explore.inertia_cluster(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 3-4 seemed to be the optimal number of clusters, but not enough "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Clustering by log error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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": [
    "train, test = model.cluster_zillow(data, return_type = 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Clustering by Tax Value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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": [
    "train, test = model.cluster_zillow(data, return_type = 1, return_cluster_column = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Findings\n",
    "- There is no statistical corrolation between the value of the house and the log error when it comes to lat long"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<<|_AVERAGE_ERROR_BY_CLUSTER_|>>\n",
      "cluster\n",
      "0    0.503603\n",
      "1    0.508957\n",
      "2    0.504269\n",
      "3    0.505445\n",
      "Name: logerror, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "sns.scatterplot('logerror', 'taxvaluedollarcnt', hue = 'cluster', data = train)\n",
    "plt.show()\n",
    "print('<<|_AVERAGE_ERROR_BY_CLUSTER_|>>')\n",
    "print(train.groupby('cluster')['logerror'].mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Modeling"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Split Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 80% train, 20% test, random state = 123\n",
    "train, test = split_scale.split_my_data(data)\n",
    "train = prep.zillow_scale(train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train = train.drop(columns=['logerror'])\n",
    "y_train = train[['logerror']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_test = test.drop(columns=['logerror'])\n",
    "y_test = test['logerror']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Scale Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "#scale using min max scaler\n",
    "X_train_scaled = split_scale.min_max_scaler(X_train)\n",
    "y_train_scaled = split_scale.min_max_scaler(y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Baseline\n",
    "#### Our baseline model is the mean log error. If we were to predict the mean log error for each property, how effective of a model would we have? "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\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>actual</th>\n",
       "      <th>baseline</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.492654</td>\n",
       "      <td>0.506051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.517621</td>\n",
       "      <td>0.506051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.517002</td>\n",
       "      <td>0.506051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.540456</td>\n",
       "      <td>0.506051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.524998</td>\n",
       "      <td>0.506051</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     actual  baseline\n",
       "0  0.492654  0.506051\n",
       "1  0.517621  0.506051\n",
       "2  0.517002  0.506051\n",
       "3  0.540456  0.506051\n",
       "4  0.524998  0.506051"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "baseline = pd.DataFrame({'actual':y_train.logerror}).reset_index(drop=True)\n",
    "baseline['baseline'] = y_train.mean()[0]\n",
    "baseline.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Baseline Evaluation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE: 0.0567378132266\n"
     ]
    }
   ],
   "source": [
    "MSE_baseline = mean_squared_error(baseline.actual, baseline.baseline)\n",
    "RMSE_baseline = sqrt(MSE_baseline)\n",
    "print('RMSE:', RMSE_baseline)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model 1\n",
    "- Linear regression model with all 20 features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.50948669],\n",
       "       [0.50268382],\n",
       "       [0.5026168 ],\n",
       "       ...,\n",
       "       [0.51217331],\n",
       "       [0.50011667],\n",
       "       [0.49877007]])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lm1=LinearRegression()\n",
    "lm1.fit(X_train_scaled, y_train_scaled)\n",
    "yhat_lm1=lm1.predict(X_train_scaled)\n",
    "yhat_lm1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model 1 Evaluation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE: 0.05650539605276414\n"
     ]
    }
   ],
   "source": [
    "MSE_1 = mean_squared_error(yhat_lm1, y_train)\n",
    "RMSE_1 = sqrt(MSE_1)\n",
    "print('RMSE:' ,RMSE_1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model 2\n",
    "- Linear regression with top 6 features: \n",
    "\n",
    "\n",
    "    - bedroomcnt\n",
    "    - poolcnt\n",
    "    - taxvaluedollarcnt\n",
    "    - bathroomcnt\n",
    "    - calculatedfinishedsquarefeet\n",
    "    - taxdelinquencyflag"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.51178181],\n",
       "       [0.5028749 ],\n",
       "       [0.50428666],\n",
       "       ...,\n",
       "       [0.51047568],\n",
       "       [0.50178783],\n",
       "       [0.50112054]])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train_2 = X_train_scaled[['bedroomcnt','poolcnt', 'taxvaluedollarcnt', 'calculatedfinishedsquarefeet', 'taxdelinquencyflag']]\n",
    "lm2=LinearRegression()\n",
    "lm2.fit(X_train_2,y_train_scaled)\n",
    "yhat_lm2=lm2.predict(X_train_2)\n",
    "yhat_lm2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model 2 Evaluation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE: 0.05656078462843578\n"
     ]
    }
   ],
   "source": [
    "MSE_2 = mean_squared_error(yhat_lm2, y_train)\n",
    "RMSE_2 = sqrt(MSE_2)\n",
    "print('RMSE:',RMSE_2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model 3\n",
    "- Decision Tree with all 20 features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "tree = DecisionTreeRegressor(max_depth = 6, random_state = 123)\n",
    "tree.fit(X_train_scaled, y_train)\n",
    "y_pred_t = tree.predict(X_train_scaled)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model 3 Evaluation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE: 0.05576253399653005\n"
     ]
    }
   ],
   "source": [
    "MSE_3 = mean_squared_error(y_train, y_pred_t)\n",
    "RMSE_3 = sqrt(MSE_3)\n",
    "print('RMSE:',RMSE_3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model 4\n",
    "- Random Forest with all 20 features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "forest = RandomForestRegressor(max_depth = 8, random_state = 123).fit(X_train_scaled, y_train)\n",
    "y_pred_for = forest.predict(X_train_scaled)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model 4 Evaluation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE: 0.05463516130409284\n"
     ]
    }
   ],
   "source": [
    "MSE_4 = mean_squared_error(y_train, y_pred_for)\n",
    "RMSE_4 = sqrt(MSE_4)\n",
    "print('RMSE:',RMSE_4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model 4 is our best model. It slightly outperforms our baseline model."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Applying model to test data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred_for_test = forest.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE: 0.05714264450764453\n"
     ]
    }
   ],
   "source": [
    "MSE_4 = mean_squared_error(y_test, y_pred_for_test)\n",
    "RMSE_4 = sqrt(MSE_4)\n",
    "print('RMSE:',RMSE_4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Conclusions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- No variables significantly correlated with log error.\n",
    "- Clustering did not prove helpful for this project.\n",
    "- Our best model slightly outperformed the basline model when training. However, it slightly underperformed when testing."
   ]
  }
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