{
 "cells": [
  {
   "cell_type": "markdown",
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   "source": [
    "# Regression Analysis for Estimating Prices\n",
    "**By [Czarina Luna](https://www.linkedin.com/in/czarinagluna/)**\n",
    "\n",
    "### Contents\n",
    "* [I. Overview](#I.-Overview)\n",
    "* [II. Business Problem](#II.-Business-Problem)\n",
    "* [III. Data Understanding](#III.-Data-Understanding)\n",
    "    * [3.1 Exploratory Data Analysis](#3.1-Exploratory-Data-Analysis)\n",
    "    * [3.2 Geospatial Mapping](#3.2-Geospatial-Mapping)\n",
    "    * [3.3 Feature Engineering](#3.3-Feature-Engineering)\n",
    "* [IV. Data Modeling](#IV.-Data-Modeling)\n",
    "    * [4.1 Linear Regression](#4.1-Linear-Regression)\n",
    "    * [4.2 Decision Tree](#4.2-Decision-Tree)\n",
    "    * [4.3 Random Forest](#4.3-Random-Forest)\n",
    "* [V. Results](#V.-Results)\n",
    "* [VI. Further Research](#VI.-Further-Research)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## I. Overview\n",
    "\n",
    "An analysis and regression modeling of over 21,000 real estate transactions in King County, Washington is completed to improve home valuation and real estate advisory. The findings include top features that are important to the *bestimate* model, which are square footage of living space, distance to Seattle, total distance to both Seattle and Redmond, distance to Redmond, and square footage of living space of the nearest 15 neighbors. The *bestimate* model that is the tuned random forest performs best in predicting house prices based on over 20 features. It explains 88% of the variance in the data and its predictions are USD 107,000 off from the actual prices on average."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## II. Business Problem\n",
    "\n",
    "Real estate agencies in King County, Washington may be able to improve their advisory services by identifying important features that factor in home valuation based on relevant data. Doing so will allow real estate agents to provide more accurate prices to clients as supported by historical records. Using publicly available data, I describe patterns in real estate transactions such as features that likely drive prices. To take it a step further, I develop a prototype for a client-facing application that serves as a home value estimator, modeled from the data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## III. Data Understanding\n",
    "\n",
    "The [King County data](https://www.kaggle.com/datasets/harlfoxem/housesalesprediction) spans a year between 2014 and 2015 with over 21,000 real estate transactions. Among the 21 variables featured, `price` is the dependent variable to predict. A full description of all column features is provided along with other data files, available in the repository's [data folder](https://github.com/czarinagluna/regression-analysis-for-estimating-prices/tree/main/Data).\n",
    "\n",
    "To prepare the data for analysis, the pre-processing steps are taken below:\n",
    "* Convert `date` to a date time format and create `month` feature\n",
    "* Remove outliers for `price` and `bedrooms`\n",
    "* Replace values for `waterfront`, `view`, `condition`, `grade` with a number scale for consistency\n",
    "* Create `basement` feature using `sqft_basement` to determine basement or none\n",
    "* Create `renovated` feature using `yr_renovated` to determine renovation or none\n",
    "* Create `age` feature by subtracting the `yr_built` from year of `date` sold"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# Import the dataset\n",
    "data = pd.read_csv('data/kc_house_data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>date</th>\n",
       "      <th>price</th>\n",
       "      <th>bedrooms</th>\n",
       "      <th>bathrooms</th>\n",
       "      <th>sqft_living</th>\n",
       "      <th>sqft_lot</th>\n",
       "      <th>floors</th>\n",
       "      <th>waterfront</th>\n",
       "      <th>view</th>\n",
       "      <th>condition</th>\n",
       "      <th>grade</th>\n",
       "      <th>sqft_above</th>\n",
       "      <th>sqft_basement</th>\n",
       "      <th>yr_built</th>\n",
       "      <th>yr_renovated</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>lat</th>\n",
       "      <th>long</th>\n",
       "      <th>sqft_living15</th>\n",
       "      <th>sqft_lot15</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7129300520</td>\n",
       "      <td>10/13/2014</td>\n",
       "      <td>221900.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1180</td>\n",
       "      <td>5650</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NONE</td>\n",
       "      <td>Average</td>\n",
       "      <td>7 Average</td>\n",
       "      <td>1180</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1955</td>\n",
       "      <td>0.0</td>\n",
       "      <td>98178</td>\n",
       "      <td>47.5112</td>\n",
       "      <td>-122.257</td>\n",
       "      <td>1340</td>\n",
       "      <td>5650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6414100192</td>\n",
       "      <td>12/9/2014</td>\n",
       "      <td>538000.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2.25</td>\n",
       "      <td>2570</td>\n",
       "      <td>7242</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NO</td>\n",
       "      <td>NONE</td>\n",
       "      <td>Average</td>\n",
       "      <td>7 Average</td>\n",
       "      <td>2170</td>\n",
       "      <td>400.0</td>\n",
       "      <td>1951</td>\n",
       "      <td>1991.0</td>\n",
       "      <td>98125</td>\n",
       "      <td>47.7210</td>\n",
       "      <td>-122.319</td>\n",
       "      <td>1690</td>\n",
       "      <td>7639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5631500400</td>\n",
       "      <td>2/25/2015</td>\n",
       "      <td>180000.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.00</td>\n",
       "      <td>770</td>\n",
       "      <td>10000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NO</td>\n",
       "      <td>NONE</td>\n",
       "      <td>Average</td>\n",
       "      <td>6 Low Average</td>\n",
       "      <td>770</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1933</td>\n",
       "      <td>NaN</td>\n",
       "      <td>98028</td>\n",
       "      <td>47.7379</td>\n",
       "      <td>-122.233</td>\n",
       "      <td>2720</td>\n",
       "      <td>8062</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           id        date     price  bedrooms  bathrooms  sqft_living  \\\n",
       "0  7129300520  10/13/2014  221900.0         3       1.00         1180   \n",
       "1  6414100192   12/9/2014  538000.0         3       2.25         2570   \n",
       "2  5631500400   2/25/2015  180000.0         2       1.00          770   \n",
       "\n",
       "   sqft_lot  floors waterfront  view condition          grade  sqft_above  \\\n",
       "0      5650     1.0        NaN  NONE   Average      7 Average        1180   \n",
       "1      7242     2.0         NO  NONE   Average      7 Average        2170   \n",
       "2     10000     1.0         NO  NONE   Average  6 Low Average         770   \n",
       "\n",
       "  sqft_basement  yr_built  yr_renovated  zipcode      lat     long  \\\n",
       "0           0.0      1955           0.0    98178  47.5112 -122.257   \n",
       "1         400.0      1951        1991.0    98125  47.7210 -122.319   \n",
       "2           0.0      1933           NaN    98028  47.7379 -122.233   \n",
       "\n",
       "   sqft_living15  sqft_lot15  \n",
       "0           1340        5650  \n",
       "1           1690        7639  \n",
       "2           2720        8062  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.set_option('display.max_columns', 30)\n",
    "\n",
    "# Quick look at the data structure\n",
    "data.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert date to date time format\n",
    "data['date'] = pd.to_datetime(data['date'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['month'] = pd.DatetimeIndex(data['date']).month"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Summary statistics of numerical features:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>price</th>\n",
       "      <td>21597</td>\n",
       "      <td>540296</td>\n",
       "      <td>367368</td>\n",
       "      <td>78000</td>\n",
       "      <td>322000</td>\n",
       "      <td>450000</td>\n",
       "      <td>645000</td>\n",
       "      <td>7700000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bedrooms</th>\n",
       "      <td>21597</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bathrooms</th>\n",
       "      <td>21597</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sqft_living</th>\n",
       "      <td>21597</td>\n",
       "      <td>2080</td>\n",
       "      <td>918</td>\n",
       "      <td>370</td>\n",
       "      <td>1430</td>\n",
       "      <td>1910</td>\n",
       "      <td>2550</td>\n",
       "      <td>13540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sqft_lot</th>\n",
       "      <td>21597</td>\n",
       "      <td>15099</td>\n",
       "      <td>41412</td>\n",
       "      <td>520</td>\n",
       "      <td>5040</td>\n",
       "      <td>7618</td>\n",
       "      <td>10685</td>\n",
       "      <td>1651359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>floors</th>\n",
       "      <td>21597</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sqft_above</th>\n",
       "      <td>21597</td>\n",
       "      <td>1788</td>\n",
       "      <td>827</td>\n",
       "      <td>370</td>\n",
       "      <td>1190</td>\n",
       "      <td>1560</td>\n",
       "      <td>2210</td>\n",
       "      <td>9410</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yr_built</th>\n",
       "      <td>21597</td>\n",
       "      <td>1970</td>\n",
       "      <td>29</td>\n",
       "      <td>1900</td>\n",
       "      <td>1951</td>\n",
       "      <td>1975</td>\n",
       "      <td>1997</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yr_renovated</th>\n",
       "      <td>17755</td>\n",
       "      <td>83</td>\n",
       "      <td>399</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sqft_living15</th>\n",
       "      <td>21597</td>\n",
       "      <td>1986</td>\n",
       "      <td>685</td>\n",
       "      <td>399</td>\n",
       "      <td>1490</td>\n",
       "      <td>1840</td>\n",
       "      <td>2360</td>\n",
       "      <td>6210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sqft_lot15</th>\n",
       "      <td>21597</td>\n",
       "      <td>12758</td>\n",
       "      <td>27274</td>\n",
       "      <td>651</td>\n",
       "      <td>5100</td>\n",
       "      <td>7620</td>\n",
       "      <td>10083</td>\n",
       "      <td>871200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>month</th>\n",
       "      <td>21597</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               count    mean     std    min     25%     50%     75%      max\n",
       "price          21597  540296  367368  78000  322000  450000  645000  7700000\n",
       "bedrooms       21597       3       0      1       3       3       4       33\n",
       "bathrooms      21597       2       0      0       1       2       2        8\n",
       "sqft_living    21597    2080     918    370    1430    1910    2550    13540\n",
       "sqft_lot       21597   15099   41412    520    5040    7618   10685  1651359\n",
       "floors         21597       1       0      1       1       1       2        3\n",
       "sqft_above     21597    1788     827    370    1190    1560    2210     9410\n",
       "yr_built       21597    1970      29   1900    1951    1975    1997     2015\n",
       "yr_renovated   17755      83     399      0       0       0       0     2015\n",
       "sqft_living15  21597    1986     685    399    1490    1840    2360     6210\n",
       "sqft_lot15     21597   12758   27274    651    5100    7620   10083   871200\n",
       "month          21597       6       3      1       4       6       9       12"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.drop(columns=['id', 'zipcode', 'lat', 'long']).describe().T.astype('int')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Data Cleaning**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x144 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# Create dataframe with price in millions\n",
    "price_data = data[['price']]/1000000 \n",
    "\n",
    "plt.figure(figsize=(12, 2))\n",
    "plt.style.use('bmh')\n",
    "\n",
    "sns.boxplot(x='price', data=price_data, color='teal')\n",
    "\n",
    "plt.title('Distribution of Prices (USD Million)')\n",
    "\n",
    "plt.savefig('data/images/fig0.png', dpi=200, transparent=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove outliers in prices\n",
    "data = data[(data.price < data.price.quantile(.995)) & \n",
    "            (data.price > data.price.quantile(.005))] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x144 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 2))\n",
    "sns.boxplot(x='bedrooms', data=data, color='honeydew')\n",
    "\n",
    "plt.title('Distribution of Bedrooms') \n",
    "\n",
    "plt.savefig('data/images/fig1.png', dpi=200, transparent=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Likely a typographical error, the number of 33 bedrooms is corrected to 3."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.loc[(data.bedrooms == 33), 'bedrooms'] = 3 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Replace missing values with no waterfront\n",
    "data.loc[data['waterfront'].isnull(), 'waterfront'] = 'NO'\n",
    "\n",
    "data['waterfront'] = data['waterfront'].apply(lambda x: 0 if x == 'NO' else 1) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Replace missing values with no view\n",
    "data.loc[data.view.isnull(), 'view'] = 'NONE'\n",
    "\n",
    "data['view'] = data['view'].replace({'NONE':0,\n",
    "                                     'FAIR':1, \n",
    "                                     'AVERAGE':2, \n",
    "                                     'GOOD':3, \n",
    "                                     'EXCELLENT':4}) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['condition'] = data['condition'].replace({'Poor':0, \n",
    "                                               'Fair':1, \n",
    "                                               'Average':2, \n",
    "                                               'Good':3, \n",
    "                                               'Very Good':4})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['grade'] = data['grade'].map(lambda x: int(x.split(' ')[0])) # only keep the number from string"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Replace missing values with 0 square footage of basement\n",
    "data['sqft_basement'] = data['sqft_basement'].replace('?', '0').astype('float')\n",
    "\n",
    "data['basement'] = data['sqft_basement'].apply(lambda x: 0 if x == 0 else 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Replace missing values with not renovated\n",
    "data.loc[data['yr_renovated'].isnull(), 'yr_renovated'] = 0\n",
    "\n",
    "data['renovated'] = data['yr_renovated'].apply(lambda x: 0 if x == 0 else 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['age'] = data['date'].dt.year - data['yr_built']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.1 Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Month-over-month comparison:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "date_data = data[['date', 'price']]\n",
    "date_data = data.set_index('date', drop=True).astype('float64')\n",
    "\n",
    "# Resample data to count transactions per month\n",
    "monthly_count = date_data.resample('MS').count()\n",
    "monthly_count = monthly_count.drop(monthly_count.index[-1])\n",
    "\n",
    "# Resample data to calculate mean price per month\n",
    "monthly_avg = date_data.resample('MS').mean()\n",
    "monthly_avg = monthly_avg.drop(monthly_avg.index[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(ncols=2, figsize=(12,4))\n",
    "\n",
    "monthly_count['price'].plot(title='Total Count', ax=axes[0], colormap='Set3', marker='.')\n",
    "monthly_avg['price'].plot(title='Average Price', ax=axes[1], colormap='BrBG_r', marker='.')\n",
    "\n",
    "axes[0].grid(axis='x', linewidth=0)\n",
    "axes[1].grid(axis='x', linewidth=0)\n",
    "\n",
    "plt.suptitle('Houses Sold Per Month', fontsize=14)\n",
    "\n",
    "plt.savefig('data/images/fig2.png', dpi=200, transparent=True) \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The highest peaks in the number of houses sold per month happened in the seasons of spring and summer. The decline in the months that followed dropped to the lowest point at the first month of the new year. As for the price of houses sold per month, the values followed roughly the same pattern.\n",
    "\n",
    "***\n",
    "Check for multicollinearity:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "def check_correlation(data, threshold):\n",
    "    '''Checks for the highest correlated features in a dataframe given a threshold'''\n",
    "    df = data.corr().abs().stack().reset_index().sort_values(0, ascending=False)\n",
    "    \n",
    "    df['pairs'] = list(zip(df['level_0'], df['level_1']))\n",
    "    df = df.set_index(['pairs']).drop(columns=['level_1', 'level_0'])\n",
    "    \n",
    "    df.columns = ['correlation']\n",
    "    \n",
    "    df = df.drop_duplicates()\n",
    "    df = df[(df['correlation'] > threshold) & (df['correlation'] < 1)]\n",
    "    \n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "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>correlation</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pairs</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>(yr_renovated, renovated)</th>\n",
       "      <td>0.999968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(age, yr_built)</th>\n",
       "      <td>0.999873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(sqft_living, sqft_above)</th>\n",
       "      <td>0.869907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(basement, sqft_basement)</th>\n",
       "      <td>0.826651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(sqft_living15, sqft_living)</th>\n",
       "      <td>0.753874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(sqft_living, grade)</th>\n",
       "      <td>0.751196</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              correlation\n",
       "pairs                                    \n",
       "(yr_renovated, renovated)        0.999968\n",
       "(age, yr_built)                  0.999873\n",
       "(sqft_living, sqft_above)        0.869907\n",
       "(basement, sqft_basement)        0.826651\n",
       "(sqft_living15, sqft_living)     0.753874\n",
       "(sqft_living, grade)             0.751196"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "check_correlation(data, 0.75)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Drop highly collinear features and useless feature like id\n",
    "to_drop = ['id', 'date', 'yr_renovated', 'sqft_above', 'sqft_basement', 'yr_built', 'yr_renovated']\n",
    "\n",
    "data = data.drop(columns=to_drop)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,8))\n",
    "plt.style.use('default')\n",
    "\n",
    "corr = data.corr()\n",
    "mask = np.triu(np.ones_like(corr, dtype=bool))\n",
    "\n",
    "sns.heatmap(corr.abs(), mask=mask, cmap='YlGnBu')\n",
    "\n",
    "plt.title('Feature Correlation with Price', fontsize=14)\n",
    "\n",
    "plt.savefig('data/images/fig3.png', dpi=200, transparent=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Price is strongly correlated with `sqft_living`, `grade`, `sqft_living15`, `bathrooms`, and `bathrooms`. \n",
    "\n",
    "Let's visualize their relationships and distributions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 14 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "select_features = ['price', 'bathrooms', 'sqft_living', 'grade']\n",
    "sns.pairplot(data, vars=select_features, diag_kind='kde', corner=True).fig.suptitle('Relationships between Price and Select Features', \n",
    "                                                                                    fontsize=16, y=1)\n",
    "plt.savefig('data/images/fig4.png', dpi=200, transparent=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.2 Geospatial Mapping\n",
    "\n",
    "> '*Location, location, location*'\n",
    "\n",
    "**Location is important in real estate and in analysis!**\n",
    "\n",
    "Let's map the data points."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "import geopandas as gpd\n",
    "from shapely.geometry import Point, Polygon\n",
    "\n",
    "def map_data(data_, title, name, colormap):\n",
    "    '''Plots the data points using latitude and longitude on top of King County map'''\n",
    "    plt.style.use('seaborn')\n",
    "    \n",
    "    fig, ax = plt.subplots(figsize=(8,8))\n",
    "    \n",
    "    king_county_fig = gpd.read_file('data/map/Incorporated_Areas_of_King_County___city_area.shp')\n",
    "    \n",
    "    geometry = [Point(xy) for xy in zip(data_['long'], data_['lat'])]\n",
    "    geo_data = gpd.GeoDataFrame(data_, crs='EPSG:4326', geometry=geometry)\n",
    "    \n",
    "    king_county_fig.plot(ax=ax, alpha=0.4, color='grey')\n",
    "    geo_data.plot(column='price', ax=ax, alpha=0.4, legend=True, markersize=8, cmap=plt.get_cmap(colormap), legend_kwds={'shrink': 0.7, 'format': '%.0f'})\n",
    "    \n",
    "    plt.xlim(data['long'].min(), data['long'].max())\n",
    "    plt.ylim(data['lat'].min(), data['lat'].max())\n",
    "    plt.ticklabel_format(style='plain')\n",
    "    \n",
    "    plt.title(title, fontsize=14)\n",
    "    \n",
    "    plt.savefig(f'data/images/{name}.png', dpi=200, transparent=True)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create dataframe of houses sold under a million dollars\n",
    "UnderMillion = data.loc[(data['price'] < 1000000)]\n",
    "\n",
    "# Create dataframe of houses sold over a million dollars\n",
    "OverMillion = data.loc[(data['price'] >= 1000000)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stored 'UnderMillion' (DataFrame)\n"
     ]
    }
   ],
   "source": [
    "# Store dataframe for retrieval in map notebook\n",
    "%store UnderMillion "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stored 'OverMillion' (DataFrame)\n"
     ]
    }
   ],
   "source": [
    "# Store dataframe for retrieval in map notebook\n",
    "%store OverMillion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "map_data(UnderMillion, 'House Prices Sold Under $1 Million', 'fig5', 'PuBuGn')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The concentrated geographic patterns reveal parts of the county populated by the more expensive houses represented by darker colors like the island at the center. The even more expensive houses sold for over a million dollars are located at about the same spots as the dark dots. \n",
    "\n",
    "Locate the highest priced houses in the data in the following map:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "map_data(OverMillion, 'House Prices Sold Over $1 Million', 'fig6', 'Greens')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "**Interactive Map**\n",
    "\n",
    "I created choropleth maps ([map notebook](https://github.com/czarinagluna/regression-analysis-for-estimating-prices/blob/main/map.ipynb)) to further understand how house prices vary by location.\n",
    "\n",
    "To interact with the maps, please use the [notebook viewer](https://nbviewer.org/github/czarinagluna/regression-analysis-for-estimating-prices/blob/main/map.ipynb)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](data/images/fig7.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.3 Feature Engineering"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "King County Population:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import data from population census\n",
    "population = pd.read_csv('data/population.csv')\n",
    "\n",
    "population_density = population.loc[:, ['City Name', 'Total Population 2010', 'Population Density (Persons / Square Mile) 2010']]\n",
    "population_density = population_density.rename(columns={'City Name':'city', 'Total Population 2010':'population', 'Population Density (Persons / Square Mile) 2010':'pop_density'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "king_county_cities = ['Algona', 'Auburn', 'Beaux Arts Village', 'Bellevue', 'Black Diamond', \n",
    "                      'Bothell', 'Burien', 'Carnation', 'Clyde Hill', 'Covington', \n",
    "                      'Des Moines', 'Duvall', 'Enumclaw', 'Federal Way', 'Hunts Point', \n",
    "                      'Issaquah', 'Kenmore', 'Kent', 'Kirkland', 'Lake Forest Park', \n",
    "                      'Maple Valley', 'Medina', 'Mercer Island', 'Milton', 'Newcastle', \n",
    "                      'Normandy Park', 'North Bend', 'Pacific', 'Redmond', 'Renton', \n",
    "                      'Sammamish', 'SeaTac', 'Seattle', 'Shoreline', 'Skykomish', \n",
    "                      'Snoqualmie', 'Tukwila', 'Woodinville', 'Yarrow Point']\n",
    "\n",
    "city_names = pd.DataFrame(king_county_cities, columns=['city'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "king_county_population = pd.merge(population_density, city_names, on=['city'])\n",
    "king_county_population = king_county_population.append({'city':'Vashon','population':10624, 'pop_density':287.22}, ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "zipcodes = pd.read_csv('data/zipcodes.csv')\n",
    "\n",
    "zipcodes['city'] = zipcodes['zipcode'].apply(lambda x: x.split('(')[1].strip('()'))\n",
    "zipcodes['zipcode'] = zipcodes['zipcode'].apply(lambda x: int(x.split()[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Map population data to cities\n",
    "king_county_zipcode = pd.merge(king_county_population, zipcodes, on=['city'])\n",
    "\n",
    "engineered_data = pd.merge(data, king_county_zipcode, how='inner', on=['zipcode'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Distance to Seattle and Redmond:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "from haversine import haversine, Unit\n",
    "\n",
    "def find_distance(center, lat, long):\n",
    "    '''Uses haversine function to find distance between a given center and a point's latitude and longitude'''\n",
    "    house = (lat, long)\n",
    "    distance = haversine(center, house, unit=Unit.MILES)\n",
    "    return distance\n",
    "\n",
    "def add_distance(data):\n",
    "    '''Applies the find_distance function to dataframe to add columns for distances to Seattle and Redmond'''\n",
    "    seattle = (47.608013, -122.335167)\n",
    "    redmond = (47.673988, -122.121513)\n",
    "    \n",
    "    data['to_seattle'] = data.apply(lambda x: find_distance(seattle, x['lat'], x['long']), axis=1)\n",
    "    data['to_redmond'] = data.apply(lambda x: find_distance(redmond, x['lat'], x['long']), axis=1)\n",
    "    data['distance'] = data['to_seattle'] + data['to_redmond']\n",
    "\n",
    "    data = data.drop(columns=['lat', 'long'])\n",
    "    return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "engineered_data = add_distance(engineered_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## IV. Data Modeling"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Train Test Split**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "X = data.drop(columns=['price'])\n",
    "y = data['price']\n",
    "\n",
    "X_tr, X_te, y_tr, y_te = train_test_split(X, y, random_state=112221)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Baseline Model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Simple linear regression using one independent variable\n",
    "from sklearn.linear_model import LinearRegression\n",
    "\n",
    "lr_model = LinearRegression()\n",
    "lr_model.fit(X_tr[['sqft_living']], y_tr)\n",
    "\n",
    "baseline_pred = lr_model.predict(X_te[['sqft_living']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Evaluate using R squared and RMSE scores\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.metrics import mean_squared_error\n",
    "\n",
    "baseline_cross_val = cross_val_score(lr_model, X_tr[['sqft_living']], y_tr, scoring='neg_root_mean_squared_error', cv=10)\n",
    "baseline_cross_val_mean = -(baseline_cross_val.mean())\n",
    "\n",
    "baseline_rmse = mean_squared_error(y_te, baseline_pred, squared=False)\n",
    "baseline_score = lr_model.score(X_te[['sqft_living']], y_te)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "metric_table = pd.DataFrame(columns = ['model', 'cv_rmse', 'test_rmse', 'test_score'])\n",
    "metric_table = metric_table.append({'model': 'simple_lr', \n",
    "                                    'cv_rmse': f'{baseline_cross_val_mean:.2f}', \n",
    "                                    'test_rmse': f'{baseline_rmse:.2f}', \n",
    "                                    'test_score': f'{baseline_score:.2f}'}, ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "scrolled": true
   },
   "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>model</th>\n",
       "      <th>cv_rmse</th>\n",
       "      <th>test_rmse</th>\n",
       "      <th>test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>simple_lr</td>\n",
       "      <td>227585.85</td>\n",
       "      <td>217065.62</td>\n",
       "      <td>0.47</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       model    cv_rmse  test_rmse test_score\n",
       "0  simple_lr  227585.85  217065.62       0.47"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metric_table"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.1 Linear Regression\n",
    "\n",
    "Multiple Linear Regression:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "def run_model(regressor, name, X_train=X_tr, X_test=X_te, y_train=y_tr, y_test=y_te):\n",
    "    '''Fits a regression model on train set, predicts on the test set, and returns cross validation and test scores'''\n",
    "    regressor.fit(X_train, y_train)\n",
    "    y_pred = regressor.predict(X_test)\n",
    "    \n",
    "    cross_val = cross_val_score(regressor, X_train, y_train, scoring='neg_root_mean_squared_error', cv=10)\n",
    "    cross_val_mean = -(cross_val.mean())\n",
    "    \n",
    "    rmse = mean_squared_error(y_test, y_pred, squared=False)\n",
    "    score = regressor.score(X_test, y_test)\n",
    "    \n",
    "    return metric_table.append({'model': name, \n",
    "                                'cv_rmse': f'{cross_val_mean:.2f}', \n",
    "                                'test_rmse': f'{rmse:.2f}', \n",
    "                                'test_score': f'{score:.2f}'}, ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\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>model</th>\n",
       "      <th>cv_rmse</th>\n",
       "      <th>test_rmse</th>\n",
       "      <th>test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>simple_lr</td>\n",
       "      <td>227585.85</td>\n",
       "      <td>217065.62</td>\n",
       "      <td>0.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>multiple_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         model    cv_rmse  test_rmse test_score\n",
       "0    simple_lr  227585.85  217065.62       0.47\n",
       "1  multiple_lr  206288.15  198811.78       0.56"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Use multiple numerical features\n",
    "num_feat = ['bedrooms', 'bathrooms', 'sqft_living', 'sqft_lot', 'floors', 'sqft_living15', 'sqft_lot15', 'age']\n",
    "\n",
    "metric_table = run_model(lr_model, 'multiple_lr', X_tr[num_feat], X_te[num_feat])\n",
    "metric_table"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Standardization:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "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>model</th>\n",
       "      <th>cv_rmse</th>\n",
       "      <th>test_rmse</th>\n",
       "      <th>test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>simple_lr</td>\n",
       "      <td>227585.85</td>\n",
       "      <td>217065.62</td>\n",
       "      <td>0.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>multiple_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>standardized_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             model    cv_rmse  test_rmse test_score\n",
       "0        simple_lr  227585.85  217065.62       0.47\n",
       "1      multiple_lr  206288.15  198811.78       0.56\n",
       "2  standardized_lr  206288.15  198811.78       0.56"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "scaler = StandardScaler()\n",
    "\n",
    "X_sc_tr = pd.DataFrame(scaler.fit_transform(X_tr[num_feat], y_tr), columns=X_tr[num_feat].columns, index=X_tr[num_feat].index)\n",
    "X_sc_te = pd.DataFrame(scaler.transform(X_te[num_feat]), columns=X_te[num_feat].columns, index=X_te[num_feat].index)\n",
    "\n",
    "metric_table = run_model(lr_model, 'standardized_lr', X_sc_tr, X_sc_te)\n",
    "metric_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Data with engineered features such as population and distance\n",
    "X_ = engineered_data.drop(columns=['price'])\n",
    "y_ = engineered_data['price']\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X_, y_, random_state=112221)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stored 'X_train' (DataFrame)\n"
     ]
    }
   ],
   "source": [
    "# Store for retrieval in grid search notebook\n",
    "%store X_train "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stored 'y_train' (Series)\n"
     ]
    }
   ],
   "source": [
    "# Store for retrieval in grid search notebook\n",
    "%store y_train "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\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>model</th>\n",
       "      <th>cv_rmse</th>\n",
       "      <th>test_rmse</th>\n",
       "      <th>test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>simple_lr</td>\n",
       "      <td>227585.85</td>\n",
       "      <td>217065.62</td>\n",
       "      <td>0.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>multiple_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>standardized_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>feature_lr</td>\n",
       "      <td>177887.09</td>\n",
       "      <td>173055.45</td>\n",
       "      <td>0.68</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             model    cv_rmse  test_rmse test_score\n",
       "0        simple_lr  227585.85  217065.62       0.47\n",
       "1      multiple_lr  206288.15  198811.78       0.56\n",
       "2  standardized_lr  206288.15  198811.78       0.56\n",
       "3       feature_lr  177887.09  173055.45       0.68"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_feat.extend(['population', 'pop_density', 'to_seattle', 'to_redmond', 'distance'])\n",
    "\n",
    "X_scaled_train = pd.DataFrame(scaler.fit_transform(X_train[num_feat], y_train), columns=X_train[num_feat].columns, index=X_train[num_feat].index)\n",
    "X_scaled_test = pd.DataFrame(scaler.transform(X_test[num_feat]), columns=X_test[num_feat].columns, index=X_test[num_feat].index)\n",
    "\n",
    "metric_table = run_model(lr_model, 'feature_lr', X_scaled_train, X_scaled_test, y_train, y_test)\n",
    "metric_table"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Machine Learning Pipeline:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.impute import SimpleImputer\n",
    "from sklearn.preprocessing import OneHotEncoder\n",
    "\n",
    "num_pipe = Pipeline(steps=[\n",
    "    ('num_imputer', SimpleImputer(strategy='median')),\n",
    "    ('scaler', StandardScaler())\n",
    "])\n",
    "\n",
    "# Perform one hot encoding on categorical features\n",
    "cat_pipe = Pipeline(steps=[\n",
    "    ('cat_imputer', SimpleImputer(strategy='most_frequent')),\n",
    "    ('ohe', OneHotEncoder(handle_unknown='ignore'))\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.compose import ColumnTransformer\n",
    "\n",
    "num_features = ['bedrooms', 'bathrooms', 'sqft_living', 'sqft_lot', 'floors', 'sqft_living15', 'sqft_lot15', \n",
    "                'age', 'population', 'pop_density', 'to_seattle', 'to_redmond', 'distance']\n",
    "cat_features = ['waterfront', 'view', 'condition', 'grade', 'zipcode', 'month', 'basement', 'renovated', 'city']\n",
    "\n",
    "col_transformer = ColumnTransformer([\n",
    "    ('num_transformer', num_pipe, num_features),\n",
    "    ('cat_transformer', cat_pipe, cat_features)\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\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>model</th>\n",
       "      <th>cv_rmse</th>\n",
       "      <th>test_rmse</th>\n",
       "      <th>test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>simple_lr</td>\n",
       "      <td>227585.85</td>\n",
       "      <td>217065.62</td>\n",
       "      <td>0.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>multiple_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>standardized_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>feature_lr</td>\n",
       "      <td>177887.09</td>\n",
       "      <td>173055.45</td>\n",
       "      <td>0.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>pipeline_lr</td>\n",
       "      <td>124231.74</td>\n",
       "      <td>119145.65</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             model    cv_rmse  test_rmse test_score\n",
       "0        simple_lr  227585.85  217065.62       0.47\n",
       "1      multiple_lr  206288.15  198811.78       0.56\n",
       "2  standardized_lr  206288.15  198811.78       0.56\n",
       "3       feature_lr  177887.09  173055.45       0.68\n",
       "4      pipeline_lr  124231.74  119145.65       0.85"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Multiple linear regression using all features\n",
    "lr_pipe = Pipeline(steps=[\n",
    "    ('col_transformer', col_transformer),\n",
    "    ('lr', LinearRegression())\n",
    "])\n",
    "\n",
    "metric_table = run_model(lr_pipe, 'pipeline_lr', X_train, X_test, y_train, y_test)\n",
    "metric_table"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ridge and Lasso Regression:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>model</th>\n",
       "      <th>cv_rmse</th>\n",
       "      <th>test_rmse</th>\n",
       "      <th>test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>simple_lr</td>\n",
       "      <td>227585.85</td>\n",
       "      <td>217065.62</td>\n",
       "      <td>0.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>multiple_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>standardized_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>feature_lr</td>\n",
       "      <td>177887.09</td>\n",
       "      <td>173055.45</td>\n",
       "      <td>0.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>pipeline_lr</td>\n",
       "      <td>124231.74</td>\n",
       "      <td>119145.65</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ridge_lr</td>\n",
       "      <td>124635.57</td>\n",
       "      <td>119894.29</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             model    cv_rmse  test_rmse test_score\n",
       "0        simple_lr  227585.85  217065.62       0.47\n",
       "1      multiple_lr  206288.15  198811.78       0.56\n",
       "2  standardized_lr  206288.15  198811.78       0.56\n",
       "3       feature_lr  177887.09  173055.45       0.68\n",
       "4      pipeline_lr  124231.74  119145.65       0.85\n",
       "5         ridge_lr  124635.57  119894.29       0.85"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.linear_model import Ridge\n",
    "\n",
    "ridge_pipe = Pipeline(steps=[\n",
    "    ('col_transformer', col_transformer),\n",
    "    ('ridge', Ridge())\n",
    "])\n",
    "\n",
    "metric_table = run_model(ridge_pipe, 'ridge_lr', X_train, X_test, y_train, y_test)\n",
    "metric_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "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>model</th>\n",
       "      <th>cv_rmse</th>\n",
       "      <th>test_rmse</th>\n",
       "      <th>test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>simple_lr</td>\n",
       "      <td>227585.85</td>\n",
       "      <td>217065.62</td>\n",
       "      <td>0.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>multiple_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>standardized_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>feature_lr</td>\n",
       "      <td>177887.09</td>\n",
       "      <td>173055.45</td>\n",
       "      <td>0.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>pipeline_lr</td>\n",
       "      <td>124231.74</td>\n",
       "      <td>119145.65</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ridge_lr</td>\n",
       "      <td>124635.57</td>\n",
       "      <td>119894.29</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>lasso_lr</td>\n",
       "      <td>124231.29</td>\n",
       "      <td>119121.01</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             model    cv_rmse  test_rmse test_score\n",
       "0        simple_lr  227585.85  217065.62       0.47\n",
       "1      multiple_lr  206288.15  198811.78       0.56\n",
       "2  standardized_lr  206288.15  198811.78       0.56\n",
       "3       feature_lr  177887.09  173055.45       0.68\n",
       "4      pipeline_lr  124231.74  119145.65       0.85\n",
       "5         ridge_lr  124635.57  119894.29       0.85\n",
       "6         lasso_lr  124231.29  119121.01       0.85"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.linear_model import Lasso\n",
    "\n",
    "lasso_pipe = Pipeline(steps=[\n",
    "    ('col_transformer', col_transformer),\n",
    "    ('lasso', Lasso(max_iter=2000))\n",
    "])\n",
    "\n",
    "metric_table = run_model(lasso_pipe, 'lasso_lr', X_train, X_test, y_train, y_test)\n",
    "metric_table"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Polynomial Regression:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "scrolled": true
   },
   "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>model</th>\n",
       "      <th>cv_rmse</th>\n",
       "      <th>test_rmse</th>\n",
       "      <th>test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>simple_lr</td>\n",
       "      <td>227585.85</td>\n",
       "      <td>217065.62</td>\n",
       "      <td>0.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>multiple_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>standardized_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>feature_lr</td>\n",
       "      <td>177887.09</td>\n",
       "      <td>173055.45</td>\n",
       "      <td>0.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>pipeline_lr</td>\n",
       "      <td>124231.74</td>\n",
       "      <td>119145.65</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ridge_lr</td>\n",
       "      <td>124635.57</td>\n",
       "      <td>119894.29</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>lasso_lr</td>\n",
       "      <td>124231.29</td>\n",
       "      <td>119121.01</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>poly_lr</td>\n",
       "      <td>112687.15</td>\n",
       "      <td>110277.17</td>\n",
       "      <td>0.87</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             model    cv_rmse  test_rmse test_score\n",
       "0        simple_lr  227585.85  217065.62       0.47\n",
       "1      multiple_lr  206288.15  198811.78       0.56\n",
       "2  standardized_lr  206288.15  198811.78       0.56\n",
       "3       feature_lr  177887.09  173055.45       0.68\n",
       "4      pipeline_lr  124231.74  119145.65       0.85\n",
       "5         ridge_lr  124635.57  119894.29       0.85\n",
       "6         lasso_lr  124231.29  119121.01       0.85\n",
       "7          poly_lr  112687.15  110277.17       0.87"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import PolynomialFeatures\n",
    "\n",
    "poly_col_transformer = ColumnTransformer([\n",
    "    ('num_transformer', num_pipe, num_features),\n",
    "    ('polynomial', PolynomialFeatures(2), num_features),\n",
    "    ('cat_transformer', cat_pipe, cat_features),\n",
    "])\n",
    "\n",
    "poly_pipe = Pipeline(steps=[\n",
    "    ('poly_col_transformer', poly_col_transformer),\n",
    "    ('lr', LinearRegression())\n",
    "])\n",
    "\n",
    "metric_table = run_model(poly_pipe, 'poly_lr', X_train, X_test, y_train, y_test)\n",
    "metric_table"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.2 Decision Tree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "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>model</th>\n",
       "      <th>cv_rmse</th>\n",
       "      <th>test_rmse</th>\n",
       "      <th>test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>simple_lr</td>\n",
       "      <td>227585.85</td>\n",
       "      <td>217065.62</td>\n",
       "      <td>0.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>multiple_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>standardized_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>feature_lr</td>\n",
       "      <td>177887.09</td>\n",
       "      <td>173055.45</td>\n",
       "      <td>0.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>pipeline_lr</td>\n",
       "      <td>124231.74</td>\n",
       "      <td>119145.65</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ridge_lr</td>\n",
       "      <td>124635.57</td>\n",
       "      <td>119894.29</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>lasso_lr</td>\n",
       "      <td>124231.29</td>\n",
       "      <td>119121.01</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>poly_lr</td>\n",
       "      <td>112687.15</td>\n",
       "      <td>110277.17</td>\n",
       "      <td>0.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>default_dt</td>\n",
       "      <td>165174.85</td>\n",
       "      <td>162057.54</td>\n",
       "      <td>0.72</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             model    cv_rmse  test_rmse test_score\n",
       "0        simple_lr  227585.85  217065.62       0.47\n",
       "1      multiple_lr  206288.15  198811.78       0.56\n",
       "2  standardized_lr  206288.15  198811.78       0.56\n",
       "3       feature_lr  177887.09  173055.45       0.68\n",
       "4      pipeline_lr  124231.74  119145.65       0.85\n",
       "5         ridge_lr  124635.57  119894.29       0.85\n",
       "6         lasso_lr  124231.29  119121.01       0.85\n",
       "7          poly_lr  112687.15  110277.17       0.87\n",
       "8       default_dt  165174.85  162057.54       0.72"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.tree import DecisionTreeRegressor\n",
    "\n",
    "dt_pipe = Pipeline(steps=[\n",
    "    ('col_transformer', col_transformer),\n",
    "    ('decision_tree', DecisionTreeRegressor())\n",
    "])\n",
    "\n",
    "metric_table = run_model(dt_pipe, 'default_dt', X_train, X_test, y_train, y_test)\n",
    "metric_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stored 'dt_pipe' (Pipeline)\n"
     ]
    }
   ],
   "source": [
    "# Store for retrieval in grid search notebook\n",
    "%store dt_pipe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "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>model</th>\n",
       "      <th>cv_rmse</th>\n",
       "      <th>test_rmse</th>\n",
       "      <th>test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>simple_lr</td>\n",
       "      <td>227585.85</td>\n",
       "      <td>217065.62</td>\n",
       "      <td>0.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>multiple_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>standardized_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>feature_lr</td>\n",
       "      <td>177887.09</td>\n",
       "      <td>173055.45</td>\n",
       "      <td>0.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>pipeline_lr</td>\n",
       "      <td>124231.74</td>\n",
       "      <td>119145.65</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ridge_lr</td>\n",
       "      <td>124635.57</td>\n",
       "      <td>119894.29</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>lasso_lr</td>\n",
       "      <td>124231.29</td>\n",
       "      <td>119121.01</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>poly_lr</td>\n",
       "      <td>112687.15</td>\n",
       "      <td>110277.17</td>\n",
       "      <td>0.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>default_dt</td>\n",
       "      <td>165174.85</td>\n",
       "      <td>162057.54</td>\n",
       "      <td>0.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>poly_dt</td>\n",
       "      <td>170853.84</td>\n",
       "      <td>163749.93</td>\n",
       "      <td>0.71</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             model    cv_rmse  test_rmse test_score\n",
       "0        simple_lr  227585.85  217065.62       0.47\n",
       "1      multiple_lr  206288.15  198811.78       0.56\n",
       "2  standardized_lr  206288.15  198811.78       0.56\n",
       "3       feature_lr  177887.09  173055.45       0.68\n",
       "4      pipeline_lr  124231.74  119145.65       0.85\n",
       "5         ridge_lr  124635.57  119894.29       0.85\n",
       "6         lasso_lr  124231.29  119121.01       0.85\n",
       "7          poly_lr  112687.15  110277.17       0.87\n",
       "8       default_dt  165174.85  162057.54       0.72\n",
       "9          poly_dt  170853.84  163749.93       0.71"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "poly_dt = Pipeline(steps=[\n",
    "    ('poly_col_transformer', poly_col_transformer),\n",
    "    ('decision_tree', DecisionTreeRegressor())\n",
    "])\n",
    "\n",
    "metric_table = run_model(poly_dt, 'poly_dt', X_train, X_test, y_train, y_test)\n",
    "metric_table"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Grid search ([notebook](https://github.com/czarinagluna/regression-analysis-for-estimating-prices/blob/main/gridsearch.ipynb)) is performed to find the optimal parameters of the Decision Tree model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>model</th>\n",
       "      <th>cv_rmse</th>\n",
       "      <th>test_rmse</th>\n",
       "      <th>test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>simple_lr</td>\n",
       "      <td>227585.85</td>\n",
       "      <td>217065.62</td>\n",
       "      <td>0.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>multiple_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>standardized_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>feature_lr</td>\n",
       "      <td>177887.09</td>\n",
       "      <td>173055.45</td>\n",
       "      <td>0.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>pipeline_lr</td>\n",
       "      <td>124231.74</td>\n",
       "      <td>119145.65</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ridge_lr</td>\n",
       "      <td>124635.57</td>\n",
       "      <td>119894.29</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>lasso_lr</td>\n",
       "      <td>124231.29</td>\n",
       "      <td>119121.01</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>poly_lr</td>\n",
       "      <td>112687.15</td>\n",
       "      <td>110277.17</td>\n",
       "      <td>0.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>default_dt</td>\n",
       "      <td>165174.85</td>\n",
       "      <td>162057.54</td>\n",
       "      <td>0.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>poly_dt</td>\n",
       "      <td>170853.84</td>\n",
       "      <td>163749.93</td>\n",
       "      <td>0.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>tuned_dt</td>\n",
       "      <td>142144.75</td>\n",
       "      <td>138223.89</td>\n",
       "      <td>0.80</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              model    cv_rmse  test_rmse test_score\n",
       "0         simple_lr  227585.85  217065.62       0.47\n",
       "1       multiple_lr  206288.15  198811.78       0.56\n",
       "2   standardized_lr  206288.15  198811.78       0.56\n",
       "3        feature_lr  177887.09  173055.45       0.68\n",
       "4       pipeline_lr  124231.74  119145.65       0.85\n",
       "5          ridge_lr  124635.57  119894.29       0.85\n",
       "6          lasso_lr  124231.29  119121.01       0.85\n",
       "7           poly_lr  112687.15  110277.17       0.87\n",
       "8        default_dt  165174.85  162057.54       0.72\n",
       "9           poly_dt  170853.84  163749.93       0.71\n",
       "10         tuned_dt  142144.75  138223.89       0.80"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tuned_dt = Pipeline(steps=[\n",
    "    ('col_transformer', col_transformer),\n",
    "    ('decision_tree', DecisionTreeRegressor(criterion='friedman_mse', max_depth=None, min_samples_leaf=5, min_samples_split=45))\n",
    "])\n",
    "\n",
    "metric_table = run_model(tuned_dt, 'tuned_dt', X_train, X_test, y_train, y_test)\n",
    "metric_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\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>model</th>\n",
       "      <th>cv_rmse</th>\n",
       "      <th>test_rmse</th>\n",
       "      <th>test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>simple_lr</td>\n",
       "      <td>227585.85</td>\n",
       "      <td>217065.62</td>\n",
       "      <td>0.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>multiple_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>standardized_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>feature_lr</td>\n",
       "      <td>177887.09</td>\n",
       "      <td>173055.45</td>\n",
       "      <td>0.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>pipeline_lr</td>\n",
       "      <td>124231.74</td>\n",
       "      <td>119145.65</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ridge_lr</td>\n",
       "      <td>124635.57</td>\n",
       "      <td>119894.29</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>lasso_lr</td>\n",
       "      <td>124231.29</td>\n",
       "      <td>119121.01</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>poly_lr</td>\n",
       "      <td>112687.15</td>\n",
       "      <td>110277.17</td>\n",
       "      <td>0.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>default_dt</td>\n",
       "      <td>165174.85</td>\n",
       "      <td>162057.54</td>\n",
       "      <td>0.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>poly_dt</td>\n",
       "      <td>170853.84</td>\n",
       "      <td>163749.93</td>\n",
       "      <td>0.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>tuned_dt</td>\n",
       "      <td>142144.75</td>\n",
       "      <td>138223.89</td>\n",
       "      <td>0.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>poly_tuned_dt</td>\n",
       "      <td>147828.92</td>\n",
       "      <td>137763.62</td>\n",
       "      <td>0.80</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              model    cv_rmse  test_rmse test_score\n",
       "0         simple_lr  227585.85  217065.62       0.47\n",
       "1       multiple_lr  206288.15  198811.78       0.56\n",
       "2   standardized_lr  206288.15  198811.78       0.56\n",
       "3        feature_lr  177887.09  173055.45       0.68\n",
       "4       pipeline_lr  124231.74  119145.65       0.85\n",
       "5          ridge_lr  124635.57  119894.29       0.85\n",
       "6          lasso_lr  124231.29  119121.01       0.85\n",
       "7           poly_lr  112687.15  110277.17       0.87\n",
       "8        default_dt  165174.85  162057.54       0.72\n",
       "9           poly_dt  170853.84  163749.93       0.71\n",
       "10         tuned_dt  142144.75  138223.89       0.80\n",
       "11    poly_tuned_dt  147828.92  137763.62       0.80"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "poly_tuned_dt = Pipeline(steps=[\n",
    "    ('poly_col_transformer', poly_col_transformer),\n",
    "    ('decision_tree', DecisionTreeRegressor(criterion='friedman_mse', max_depth=None, min_samples_leaf=5, min_samples_split=45))\n",
    "])\n",
    "\n",
    "metric_table = run_model(poly_tuned_dt, 'poly_tuned_dt', X_train, X_test, y_train, y_test)\n",
    "metric_table"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.3 Random Forest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>model</th>\n",
       "      <th>cv_rmse</th>\n",
       "      <th>test_rmse</th>\n",
       "      <th>test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>simple_lr</td>\n",
       "      <td>227585.85</td>\n",
       "      <td>217065.62</td>\n",
       "      <td>0.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>multiple_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>standardized_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>feature_lr</td>\n",
       "      <td>177887.09</td>\n",
       "      <td>173055.45</td>\n",
       "      <td>0.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>pipeline_lr</td>\n",
       "      <td>124231.74</td>\n",
       "      <td>119145.65</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ridge_lr</td>\n",
       "      <td>124635.57</td>\n",
       "      <td>119894.29</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>lasso_lr</td>\n",
       "      <td>124231.29</td>\n",
       "      <td>119121.01</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>poly_lr</td>\n",
       "      <td>112687.15</td>\n",
       "      <td>110277.17</td>\n",
       "      <td>0.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>default_dt</td>\n",
       "      <td>165174.85</td>\n",
       "      <td>162057.54</td>\n",
       "      <td>0.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>poly_dt</td>\n",
       "      <td>170853.84</td>\n",
       "      <td>163749.93</td>\n",
       "      <td>0.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>tuned_dt</td>\n",
       "      <td>142144.75</td>\n",
       "      <td>138223.89</td>\n",
       "      <td>0.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>poly_tuned_dt</td>\n",
       "      <td>147828.92</td>\n",
       "      <td>137763.62</td>\n",
       "      <td>0.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>default_rf</td>\n",
       "      <td>113631.61</td>\n",
       "      <td>106799.75</td>\n",
       "      <td>0.88</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              model    cv_rmse  test_rmse test_score\n",
       "0         simple_lr  227585.85  217065.62       0.47\n",
       "1       multiple_lr  206288.15  198811.78       0.56\n",
       "2   standardized_lr  206288.15  198811.78       0.56\n",
       "3        feature_lr  177887.09  173055.45       0.68\n",
       "4       pipeline_lr  124231.74  119145.65       0.85\n",
       "5          ridge_lr  124635.57  119894.29       0.85\n",
       "6          lasso_lr  124231.29  119121.01       0.85\n",
       "7           poly_lr  112687.15  110277.17       0.87\n",
       "8        default_dt  165174.85  162057.54       0.72\n",
       "9           poly_dt  170853.84  163749.93       0.71\n",
       "10         tuned_dt  142144.75  138223.89       0.80\n",
       "11    poly_tuned_dt  147828.92  137763.62       0.80\n",
       "12       default_rf  113631.61  106799.75       0.88"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "\n",
    "rf_pipe = Pipeline(steps=[\n",
    "    ('col_transformer', col_transformer),\n",
    "    ('random_forest', RandomForestRegressor())\n",
    "])\n",
    "\n",
    "metric_table = run_model(rf_pipe, 'default_rf', X_train, X_test, y_train, y_test)\n",
    "metric_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stored 'rf_pipe' (Pipeline)\n"
     ]
    }
   ],
   "source": [
    "# Store for retrieval in grid search notebook\n",
    "%store rf_pipe"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Grid search ([notebook](https://github.com/czarinagluna/regression-analysis-for-estimating-prices/blob/main/gridsearch.ipynb)) is performed to find the optimal parameters of the Random Forest model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>model</th>\n",
       "      <th>cv_rmse</th>\n",
       "      <th>test_rmse</th>\n",
       "      <th>test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>simple_lr</td>\n",
       "      <td>227585.85</td>\n",
       "      <td>217065.62</td>\n",
       "      <td>0.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>multiple_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>standardized_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>feature_lr</td>\n",
       "      <td>177887.09</td>\n",
       "      <td>173055.45</td>\n",
       "      <td>0.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>pipeline_lr</td>\n",
       "      <td>124231.74</td>\n",
       "      <td>119145.65</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ridge_lr</td>\n",
       "      <td>124635.57</td>\n",
       "      <td>119894.29</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>lasso_lr</td>\n",
       "      <td>124231.29</td>\n",
       "      <td>119121.01</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>poly_lr</td>\n",
       "      <td>112687.15</td>\n",
       "      <td>110277.17</td>\n",
       "      <td>0.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>default_dt</td>\n",
       "      <td>165174.85</td>\n",
       "      <td>162057.54</td>\n",
       "      <td>0.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>poly_dt</td>\n",
       "      <td>170853.84</td>\n",
       "      <td>163749.93</td>\n",
       "      <td>0.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>tuned_dt</td>\n",
       "      <td>142144.75</td>\n",
       "      <td>138223.89</td>\n",
       "      <td>0.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>poly_tuned_dt</td>\n",
       "      <td>147828.92</td>\n",
       "      <td>137763.62</td>\n",
       "      <td>0.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>default_rf</td>\n",
       "      <td>113631.61</td>\n",
       "      <td>106799.75</td>\n",
       "      <td>0.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>tuned_rf</td>\n",
       "      <td>113358.20</td>\n",
       "      <td>106711.56</td>\n",
       "      <td>0.88</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              model    cv_rmse  test_rmse test_score\n",
       "0         simple_lr  227585.85  217065.62       0.47\n",
       "1       multiple_lr  206288.15  198811.78       0.56\n",
       "2   standardized_lr  206288.15  198811.78       0.56\n",
       "3        feature_lr  177887.09  173055.45       0.68\n",
       "4       pipeline_lr  124231.74  119145.65       0.85\n",
       "5          ridge_lr  124635.57  119894.29       0.85\n",
       "6          lasso_lr  124231.29  119121.01       0.85\n",
       "7           poly_lr  112687.15  110277.17       0.87\n",
       "8        default_dt  165174.85  162057.54       0.72\n",
       "9           poly_dt  170853.84  163749.93       0.71\n",
       "10         tuned_dt  142144.75  138223.89       0.80\n",
       "11    poly_tuned_dt  147828.92  137763.62       0.80\n",
       "12       default_rf  113631.61  106799.75       0.88\n",
       "13         tuned_rf  113358.20  106711.56       0.88"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tuned_rf = Pipeline(steps=[\n",
    "    ('col_transformer', col_transformer),\n",
    "    ('random_forest', RandomForestRegressor(criterion='friedman_mse', max_depth=None, min_samples_leaf=1, min_samples_split=2, n_estimators=150))\n",
    "])\n",
    "\n",
    "metric_table = run_model(tuned_rf, 'tuned_rf', X_train, X_test, y_train, y_test)\n",
    "metric_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "scrolled": false
   },
   "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>model</th>\n",
       "      <th>cv_rmse</th>\n",
       "      <th>test_rmse</th>\n",
       "      <th>test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>simple_lr</td>\n",
       "      <td>227585.85</td>\n",
       "      <td>217065.62</td>\n",
       "      <td>0.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>multiple_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>standardized_lr</td>\n",
       "      <td>206288.15</td>\n",
       "      <td>198811.78</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>feature_lr</td>\n",
       "      <td>177887.09</td>\n",
       "      <td>173055.45</td>\n",
       "      <td>0.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>pipeline_lr</td>\n",
       "      <td>124231.74</td>\n",
       "      <td>119145.65</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ridge_lr</td>\n",
       "      <td>124635.57</td>\n",
       "      <td>119894.29</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>lasso_lr</td>\n",
       "      <td>124231.29</td>\n",
       "      <td>119121.01</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>poly_lr</td>\n",
       "      <td>112687.15</td>\n",
       "      <td>110277.17</td>\n",
       "      <td>0.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>default_dt</td>\n",
       "      <td>165174.85</td>\n",
       "      <td>162057.54</td>\n",
       "      <td>0.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>poly_dt</td>\n",
       "      <td>170853.84</td>\n",
       "      <td>163749.93</td>\n",
       "      <td>0.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>tuned_dt</td>\n",
       "      <td>142144.75</td>\n",
       "      <td>138223.89</td>\n",
       "      <td>0.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>poly_tuned_dt</td>\n",
       "      <td>147828.92</td>\n",
       "      <td>137763.62</td>\n",
       "      <td>0.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>default_rf</td>\n",
       "      <td>113631.61</td>\n",
       "      <td>106799.75</td>\n",
       "      <td>0.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>tuned_rf</td>\n",
       "      <td>113358.20</td>\n",
       "      <td>106711.56</td>\n",
       "      <td>0.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>poly_tuned_rf</td>\n",
       "      <td>115789.84</td>\n",
       "      <td>107797.20</td>\n",
       "      <td>0.88</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              model    cv_rmse  test_rmse test_score\n",
       "0         simple_lr  227585.85  217065.62       0.47\n",
       "1       multiple_lr  206288.15  198811.78       0.56\n",
       "2   standardized_lr  206288.15  198811.78       0.56\n",
       "3        feature_lr  177887.09  173055.45       0.68\n",
       "4       pipeline_lr  124231.74  119145.65       0.85\n",
       "5          ridge_lr  124635.57  119894.29       0.85\n",
       "6          lasso_lr  124231.29  119121.01       0.85\n",
       "7           poly_lr  112687.15  110277.17       0.87\n",
       "8        default_dt  165174.85  162057.54       0.72\n",
       "9           poly_dt  170853.84  163749.93       0.71\n",
       "10         tuned_dt  142144.75  138223.89       0.80\n",
       "11    poly_tuned_dt  147828.92  137763.62       0.80\n",
       "12       default_rf  113631.61  106799.75       0.88\n",
       "13         tuned_rf  113358.20  106711.56       0.88\n",
       "14    poly_tuned_rf  115789.84  107797.20       0.88"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "poly_tuned_rf = Pipeline(steps=[\n",
    "    ('poly_col_transformer', poly_col_transformer),\n",
    "    ('random_forest', RandomForestRegressor(criterion='friedman_mse', max_depth=None, min_samples_leaf=1, min_samples_split=2, n_estimators=150))\n",
    "])\n",
    "\n",
    "metric_table = run_model(poly_tuned_rf, 'poly_tuned_rf', X_train, X_test, y_train, y_test)\n",
    "metric_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "# The best model with the best estimate \n",
    "bestimate_model = tuned_rf\n",
    "bestimate_model.fit(X_train, y_train)\n",
    "bestimate_pred = bestimate_model.predict(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## V. Results\n",
    "\n",
    "Model Performance:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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oeXh4KCAgQDVr1tTAgQPl6+uratWqKSgoSHFxcZayt9xyi2699VY5OztrwIABatWqldUVi5KUlJSk9evXa9asWapevboqVaqkmTNn6n//+5/27NlTqv0ZMmSIXFxc5OXlVar7X00l6T9bGDx4sG666Sa5urpq7Nix8vDwKLR+9T///KM9e/bo6aeflpeXl3x8fDRt2jStWbOmVFc7u7i4qH///nJ1dZW7u3up2365ceni4mJV7uabb9by5cvVoEEDJScnKyUlRVWrVrW62iksLEydOnWSs7OzBg8erLy8PB0/flxxcXHatWuXpkyZIi8vL9WuXVvjx4+33K9atWpas2aNunXrprS0NJ06dUo+Pj5WdV+8v46Ojvruu+80YcIEVa9eXT4+PnriiSdM9/WHH37Qyy+/rLffflv+/v6mx2Tt2rVq1aqV+vXrJ2dnZ3Xv3l3h4eGl7uugoCAFBATI29u71HVczk8//aTs7Gw99thjcnNzU+3atTVx4kQtXbpUUvGOX0ndfvvt8vDwkLe3t7744gtFRESoZ8+ecnJyUtu2bTV06FDL45fUzTffLF9f36vSV//GjBkzVK1aNdWsWVOPPvqo1q1bZ7n6v0DVqlU1ZcoUubm56cYbb9SwYcP0zTffyDAMffHFF3rsscfk7+8vNzc3PfLII8rJydFPP/1k+ti9evVSixYt5OrqqoEDByo1NVVJSUlldm65lgYMGCBXV1er8fLNN9+oZ8+e6tChg5ydnTVixAi1aNHCcvvy5cv10EMPqUmTJnJ1ddWkSZNUs2ZNSRXvObOksrKy9PDDD6tXr176+eeftWPHDtWrV08vv/yyJGn16tXavXu3vvvuO23dutXyrQFJWrx4sdLS0rR582b9+OOPqlmzpl555RVJF65+mTdvnmbPnq3ffvtNM2fO1LPPPqsNGzaUqp1///23vvvuOy1ZskSOjtfXy+Wi5qIvv/xSw4YNU4cOHeTk5KQOHTpo2LBh+uKLLwrdf/DgwVbz18qVKzV48OBStaWsztdX8tNPP8nDw0MPPvigXFxcFBISYtn/kj6fTZgwQW+88Ya8vLx06tQpubm5SbpwhfPVZDbHlWf2Gt9mr1crkgYNGmjAgAFycnJS165dVbNmTR09etT0tczu3bt18uRJPfHEE3Jzc1PTpk0tVw8Wx+rVqzV06FC1bNlSrq6umjhxonx8fK7inporS/NtcTzyyCNyd3dX/fr1FRYWZrnS9tNPP9Wdd96pdu3aycnJSeHh4erWrZu++OILZWdnl+q9VQFbv2cqjethXpfK5+vw0rDXHCNJ/v7+6tChgypVqlRkFnetMccUn63fT9n/6KNYgoODtWDBAn3yySd6//335e7urlGjRqlt27aFyl685o+Tk5PVGxRHR0erNRAbNGhgdd/atWsrMTHRaltBeDx06FCr7U5OToqNjVWrVq1KvD+1atUq8X2ulZL0ny1cfAwcHBzk5+dX6BjExsYqLy9PXbt2tdru6uqqmJiYEr9QrFmzpk3CgcuNy4cfftiqnGEYev311/Xjjz+qWrVqat68uXJycqz6siCIkmQJ4/Pz8y2B7Q033GC5vV69elZl//vf/+qLL76Qg4ODAgIClJaWZvXkdvH+pqSkKDs7W7Vr17bc7u/vf8X9/PPPPzV16lS9/PLLatOmjSTzYxIfH2/V5oJ2l3apl6t5zsTFxSk5OVnt2rWzbDMMQzk5OUpKSpKrq6vp8Supi/cnLi5O27dvt/rabV5entVxLm3dZUn9+vUt/1+7dm1lZ2fr7NmzVmXq1Klj9WFU7dq1tX79eiUnJysjI0MTJ060OndzcnKK9QHfxedXwbmRn59fZueWa6mo8RIfH6+WLVtabbt4njh58qTq1Klj+dvJyclyvle058yScnFx0Zdffqn69esrKytLcXFxqlq1qv73v/9Jktzd3RUbG6vly5fr5ptv1sSJEzV58mTLbfv27dOqVavUqVMnvfDCC5bx9vXXX1veOEiyeuPQo0ePErezV69e5SrgLYmi5qIzZ84Uei6sW7euNm3aVOj+3bp109NPP63NmzfrhhtuUFxcnGV5t5Iqj2M7Pj5etWvXloODg2VbvXr1tHfv3hI/nyUlJWnu3LmKiopS3bp1LfNDfn7+Vd+HK81x5Zm9xrfZ69WK5OLXHNKFeT8/P9/0tUx2drZ8fHysQsCS9GFCQoLV6/uLn5vtpSzNt8Vx6fuxgtf6Betuf/7555bb8/LydNNNN5XqvdXFbP2eqTSuh3ldKp+vw0vDXnOMVPZetzDHFJ+tjx1hejlx4sQJVa9eXR988IGys7O1bds2jR8/vshf4b34ScDMpVeWxsbGFvo1Y19fX0nSd999ZzX4Dx48WOoX3iVp47VWnLY5OjoqKyvL8ve/+UGbi49Bfn6+Tpw4YTVRSJKfn5/c3d21Y8cOyw9bZGdnKyYmxmoCLS5b9f/lxuWlb9BeeeUVnThxQps2bbJ8Eti3b99iPYafn5+kC2vmNW7cWJJ06tQpy+3fffedPv30U33++eeWvnjuuee0f/9+S5mL99fHx0dubm6KiYlRo0aNCtV3qSNHjmjs2LGaOHGiVSBjdkz8/PwKXTF88dUJJXU1zxk/Pz/Vq1dP69ats2xLS0tTUlKSqlWrpmeeeaZEx8/R0dHqh4KKejF88f74+flp4MCBVmuIJiQklDqsL6vzS3x8vGXMxcbGysPDQz4+Plbr6xXsd8E+xMbG6oYbbrCM28WLFysoKMhS/vDhw5Y5ujTK6txyLRXVZj8/P8XExFhtO3XqlJo2bSrpQlhy4sQJy22GYejkyZOSKt5zZkk5Ojpq27ZtevDBB5WRkaEmTZrI2dnZcr7fdtttysnJ0bJly/Taa6+pevXqGjt2rO688049+OCDcnV11fLlyzVnzhz5+/vr8ccfV8+ePXX69Oliv3EojrL2ZsmWipqL/Pz8Cq2PGRMTU+gNq3Thw7a+fftqzZo1uuGGG9SnTx95enqWqi3lcWz7+fkpLi5O+fn5ljfrBa8jSvp8NnHiRHXr1k0ffPCBnJ2dlZKSoq+++spye3GeT0u7D1ea48oze41vs9er14uLXysU/KBhSkpKsT58N3sts3fvXiUnJys9PV2VKlWSVLI+vHRcG4ZxTa4GvpKyNN/+m/nEz89PAwYM0EMPPWTZduLECbm7u8vLy6tE762KqtuW75lK43qY16Xy+Zx6qbI8x0hlr4+ZY4rP1sfu+v/Y6jrxv//9Tw888ID27dsnV1dXVa9eXZKsAsPS2LBhg7Zu3arc3FwtX75c+/fv1+23325VxtfXV7fccovmzp2rlJQU5eTk6O2339aQIUN07ty5f/X45VXjxo21a9cuxcfHKzMzU2+99dZlT043NzelpaVd9gl32bJl+ueff5Sdna233npLhmEU+mpb69atVb9+fc2bN0/p6enKzMzUCy+8oHvvvdfywzr2cLlx6ePjI1dXV6Wmpkq6EMy6ubnJyclJWVlZWrx4sfbv31+sX2a/4YYb1LlzZ7344os6e/asEhMTtXDhQsvtqampcnR0lLu7uwzD0M8//6xVq1Zdtm5XV1cNGDBAb775pk6dOqXU1FT95z//KbLs6dOn9cADD6hfv3669957rW4zOyb9+vXT/v379dVXXyk3N1e//PJLqZcbuNrCw8OVnp6u999/X9nZ2Tp37pymTZumyZMny8HBwfT4ubm56fz588rNzZV04fzYsmWLzp07p9TUVL333ntXfPwhQ4bov//9r3755Rfl5+fr6NGjGjlypBYvXnzV9/1aevXVV5WWlqb4+HjNnz9f/fv3L/T1wMTERL377rvKycnR33//rWXLlumOO+6Qo6OjhgwZoldffVWnTp1Sfn6+Vq5cqdtvv/2yP0JaHGV1brG3wYMH64cfftCPP/6o3NxcrVy5Un/99Zfl9mHDhmnx4sU6cuSIZe4ueMPOc+aVJSUl6bnnntPrr7+uX3/9VR9//LE6depkuf3IkSNq2bKlli5dql27dmny5Ml65plndODAAUVHR6tbt25avny5duzYoUGDBmny5MlKTU1V3bp1i/3GoTjK2pslWypqLho+fLi+/PJLbdu2TXl5edq+fbu+/PLLy37Vd8iQIdqyZYs2bNigQYMGXeM9sK9u3brJMAwtWLBA2dnZ+ueffyw/XlXS57PU1FS5u7vLyclJycnJev755yXJ8vzauHFjbdy4UZmZmUpMTLT6cfZLXfy6y4zZHHfp83p5Yq/xbfZ6VSrZMSprCtper149OTs7a82aNZIu/DDj9u3bi1WH2WuZ4OBgNWzYUM8//7zOnz+vY8eOlei14B133KGvvvpKu3fvtjz3XvxtX7P3ZFeDPefbS8db48aNtX79euXm5ur48eNavnx5sesaOnSolixZor///lvShfeAgwYN0n//+98Svbcqitl7poJQ/WqeO9fDvF7elYc5pixijrEfwvRyolevXho9erQefvhhBQUFaeLEiZo5c6ZlyYnSCg0N1Xvvvaf27dvrs88+07vvvlvklXMvv/yyvL29NWDAAN10003avHmz3n///VK/SS3vhg0bpuDgYPXr1089evRQ7dq1L/s1wvDwcJ05c0YhISFFBint27fXnDlzdNNNN2nHjh1avHixKleubFXG2dlZixYt0unTp9WzZ0917txZx48f14cffnhNP7W/1JXG5bBhw/T444/r9ddf16RJk5SZmamOHTuqW7du+vPPP9W/f/9ifxj06quvqnLlygoPD9fgwYPVsWNHy20DBw5Ux44dddttt+mmm27S22+/rXvuuccSchVl1qxZat26tfr27auePXte9jz64osvFBsbq2+//VZt27ZVcHCwgoODddttt5keE39/f73zzjtaunSpQkJCFBkZWaqlBq4FLy8vffTRR9qxY4duvvlmde/eXY6Ojnr77bclyfT4tWvXTtWrV1e7du0UHR2tMWPGqHr16oqIiFD//v0LfdvlUm3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\n",
      "text/plain": [
       "<Figure size 1800x1200 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize the metrics evaluated per model\n",
    "metric_table[['cv_rmse', 'test_rmse', 'test_score']] = metric_table[['cv_rmse', 'test_rmse', 'test_score']].astype('float')\n",
    "\n",
    "plt.style.use('bmh')\n",
    "fig, axes = plt.subplots(nrows=2, figsize=(18,12))\n",
    "\n",
    "# First metric is the R-squared score\n",
    "sns.barplot(x='model', y='test_score', data=metric_table, palette='BuPu', ax=axes[0], zorder=99)\n",
    "axes[0].set_xlabel('')\n",
    "axes[0].set_ylabel('R²')\n",
    "axes[0].set_ylim(0, 1)\n",
    "axes[0].set_title('Comparison of Model Performance: R²')\n",
    "\n",
    "# Second metric is the root mean squared error\n",
    "sns.barplot(x='model', y='test_rmse', data=metric_table, palette='BuPu', ax=axes[1], zorder=99)\n",
    "axes[1].set_xlabel('')\n",
    "axes[1].set_ylabel('RMSE')\n",
    "axes[1].set_title('Comparison of Model Performance: Root Mean Squared Error')\n",
    "\n",
    "plt.savefig('data/images/fig8.png', dpi=200, transparent=True) \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Baseline to *Bestimate* Model**\n",
    "\n",
    "The baseline model `simple_lr` significantly improved to the `tuned_rf`, our *bestimate* model:\n",
    "* from an R-squared of 0.47 to 0.88, and\n",
    "* from a Root Mean Squared Error of USD 217,000 to USD  107,000\n",
    "\n",
    "To visualize the significant difference, let's plot how far away the predictions of the baseline model are to the actual prices versus how much closer the predictions of the bestimate model are:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('default')\n",
    "fig, axes = plt.subplots(ncols=2, figsize=(12,6))\n",
    "\n",
    "# Perfect line where the predicted price is equal to the actual price\n",
    "perfect_line = np.arange(0, 3)\n",
    "\n",
    "# Baseline simple linear regression model\n",
    "axes[0].plot(perfect_line, linestyle='--', color='black', label='prediction value')\n",
    "axes[0].scatter(y_test/1000000, baseline_pred/1000000, alpha=0.1, color='cornflowerblue', label='price')\n",
    "axes[0].set_xlabel('Predicted Price in Millions')\n",
    "axes[0].set_ylabel('Actual Price in Millions')\n",
    "axes[0].set_title('Baseline Model \\n R²: 47%  RMSE: $217,000')\n",
    "axes[0].set_xlim(0, 2)\n",
    "axes[0].set_ylim(0, 2)\n",
    "axes[0].legend()\n",
    "\n",
    "# Bestimate random forest model\n",
    "axes[1].plot(perfect_line, linestyle='--', color='black', label='prediction value')\n",
    "axes[1].scatter(y_test/1000000, bestimate_pred/1000000, alpha=0.1, color='plum', label='price')\n",
    "axes[1].set_xlabel('Predicted Price in Millions')\n",
    "axes[1].set_ylabel('Actual Price in Millions')\n",
    "axes[1].set_title('Bestimate Model \\n R²: 88%  RMSE: $107,000')\n",
    "axes[1].set_xlim(0, 2)\n",
    "axes[1].set_ylim(0, 2)\n",
    "axes[1].legend()\n",
    "\n",
    "plt.savefig('data/images/fig9.png', dpi=200, transparent=True) \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Important features under the *bestimate* model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.inspection import permutation_importance\n",
    "result = permutation_importance(bestimate_model, X_test, y_test, n_repeats=10, random_state=112221, n_jobs=2)\n",
    "sorted_idx = result.importances_mean.argsort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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7tWTJEsdjxo8fr5dffll+fn5Or11VVaXZs2dr2LBhatOmjVatWqULL7zQcf+VV14pu93u9Fy/VV9fr1WrVikpKUkeHv93krOvr698fX0NjLQ13Dl4iAZ8vVOr+6XpsXmvmV0OcMrLyspSenq62WUAlkBeAOPIC+AaMgMYR15gpoaGBm3cuFEZGRny8jry+axuc6ZrYGCg4/vGxkZdccUVevLJJw/bLzY21vG9t7e3031NSwJIvy4v0HSW6W/9dntsbKz69u2rt956S+eee64WLFigsWPHOvZdtGiR/va3v+mZZ55Rr169FBwcrKeeekrr1q076ntpbGxsdukC6de/KvxRwcHB8vR033VPfX39jr0TAIemv2wCODbyAhhHXgDXkBnAOPICK3Cbputv9ezZU4sXL1ZiYuJRO85Hk56ervz8fBUUFDiWF8jKytKBAweUlpbm2G/48OG69957df3112vr1q267rrrHPd9+eWX6t27t2677TbHtqbT5Zv4+PiooaHhsPoXLlyo6OhohYSENFtfbGysvv76a8eZrvX19fruu+/Us2fP43q/AAAAAAAAAFqG21xI67fGjx+vsrIyXX/99frmm2+0bds2ffLJJxo9evRhDc4jufjii3X66adr+PDh+v777/XNN99oxIgRysjI0JlnnunY76qrrtLBgwd16623qm/fvk6LOXfq1Enffvut/vvf/yo3N1cPPfSQ1q9f7/Q6iYmJ+vHHH5WTk6PS0lIdOnRIw4cPV2RkpAYNGqQvv/xSeXl5WrVqle68807H+hZ33nmnpk2bpvfff1/Z2dm67bbbtH///j8+eG6gtrbG7BIAS2lauwfAsZEXwDjyAriGzADGkRdYgVs2Xdu1a6evvvpKDQ0NuuSSS9StWzfdeeedCg0NdVrL9GhsNpuWLFmisLAwXXjhhbr44ouVlJSkhQsXOu0XEhKiK664Qhs3btTw4cOd7hs3bpyuuuoqDR06VOecc4727t3rdNarJI0ZM0YpKSk688wzFRUVpa+++koBAQH64osvFB8fr6uuukppaWkaPXq0qqurHWe+3nXXXRoxYoRGjhzpWLrgyiuv/AOjBgAAAAAAAKAluMWFtGBM04W0unfv7tZrur5y/8OKn/Nf7RwzQDc/+pDZ5QCnvLq6usMuPAigeeQFMI68AK4hM4Bx5AVmMnohLbc80xWtW319vSQpwD/A5EoAaygsLDS7BMAyyAtgHHkBXENmAOPIC6yApivcTlPTFYAx1dXVZpcAWAZ5AYwjL4BryAxgHHmBFdB0hds52qndAA7n5+dndgmAZZAXwDjyAriGzADGkRdYAU1XuJ2Q0FCzSwAsJT4+3uwSAMsgL4Bx5AVwDZkBjCMvsAKarnA7HXufqbI7rtbFI64zuxTAEnJzc80uAbAM8gIYR14A15AZwDjyAivgc9hwO2Fto3Xe/XeZXQYAAAAAAABaKc50hduJiooyuwTAUsgMYBx5AYwjL4BryAxgHHmBFdB0hdvhQlqAa8gMYBx5AYwjL4BryAxgHHmBFdB0hdspKioyuwTAUsgMYBx5AYwjL4BryAxgHHmBFdB0BQAAAAAAAIAWRNMVbicpKcnsEgBLITOAceQFMI68AK4hM4Bx5AVWQNMVbqekpMTsEgBLITOAceQFMI68AK4hM4Bx5AVWQNMVbqeystLsEgBLITOAceQFMI68AK4hM4Bx5AVWQNMVbsfHx8fsEgBLITOAceQFMI68AK4hM4Bx5AVWQNMVboe1XQDXkBnAOPICGEdeANeQGcA48gIroOkKt5OdnW12CYClkBnAOPICGEdeANeQGcA48gIroOkKAAAAAAAAAC2IpivcTkREhNklAJZCZgDjyAtgHHkBXENmAOPIC6yApivcjq+vr9klAJZCZgDjyAtgHHkBXENmAOPIC6yApivczq5du8wuAbAUMgMYR14A48gL4BoyAxhHXmAFNF0BAAAAAAAAoAXRdIXb6dixo9klAJZCZgDjyAtgHHkBXENmAOPIC6yApivcTmlpqdklAJZCZgDjyAtgHHkBXENmAOPIC6yApivczoE9pfrpg0/UUFVjdimAJZSXl5tdAmAZ5AUwjrwAriEzgHHkBVZA0xVu56dPVqpwTKa+WPie2aUAluDl5WV2CYBlkBfAOPICuIbMAMaRF1gBTVe4HXtjoySpqKjI5EoAa+jSpYvZJQCWQV4A48gL4BoyAxhHXmAFNF3hdljbBXBNVlaW2SUAlkFeAOPIC+AaMgMYR15gBTRdAQAAAAAAAKAF0XSFW6mqqlJFRYUkqbikRFVVVSZXBJz6wsPDzS4BsAzyAhhHXgDXkBnAOPICK6DpCreyefNmvbv4XUnS/PnztHnzZpMrAk59AQEBZpcAWAZ5AYwjL4BryAxgHHmBFdB0tajMzEz16NHD7DIAuIGdO3eaXQJgGeQFMI68AK4hM4Bx5AVWQNPVAmw2m5YsWWJ2GQAAAAAAAAAMoOkKAK1cQkKC2SUAlkFeAOPIC+AaMgMYR15gBTRdXdCnTx9NmDBBEydOVFhYmNq2batXXnlFlZWVGjVqlIKDg5WcnKz//Oc/jsesWrVKZ599tnx9fRUbG6v77rtP9fX1Ts95xx136J577lF4eLhiYmKUmZnpuD8xMVGSdOWVV8pmszluN5k3b54SExMVGhqq6667TuXl5SdyCAC4oX379pldAmAZ5AUwjrwAriEzgHHkBVZA09VFb7zxhiIjI/XNN99owoQJuvXWW3Xttdeqd+/e+v7773XJJZfohhtuUFVVlQoLCzVw4ECdddZZ2rhxo1588UW99tpreuyxxw57zsDAQK1bt07Tp0/XI488ohUrVkiS1q9fL0l6/fXXVVRU5LgtSVu3btWSJUv04Ycf6sMPP9SqVas0bdq0Y76H8vJyHTx40PFVW1vbgiNkrpqamqPeBnC4gwcPml0CYBnkBTCOvACuITOAceQFVuBldgFW0717dz344IOSpMmTJ2vatGmKjIzUmDFjJElTpkzRiy++qB9//FEffPCB4uLiNGvWLNlsNqWmpmrXrl269957NWXKFHl4/NrzPv300zV16lRJUufOnTVr1ix99tln6tevn6KioiRJbdq0UUxMjFMtjY2Nmjt3roKDgyVJN9xwgz777DM9/vjjR30P3bp1U1VVleP2qFGjNGHCBMXGxmrr1q2SpLZt28put2v37t2Ounbu3Knq6mr5+fkpLi5OmzdvliRFR0fLw8NDxcXFkqTk5GQVFxersrJSvr6+SkxMVE5OjiQpMjJSPj4+2rVrlySpY8eO2rNnjyoqKuTt7a1OnTpp06ZNkqTw8HD5+/ursLBQ0q9n/ZaVlengwYPy9PRUSkqKNm3aJLvdrjZt2ig4OFhr1651eq9r165VSEiI0tLSlJOTo4aGBoWEhCgsLEw7duyQJHXo0EFVVVUqKyuTJKWnpys3N1f19fUKDg5WZGSk8vLyJEnt2rVTbW2t9u7dK0lKTU3Vtm3bVFdXp8DAQLVt21bbtm2TJMXGxqq+vl579uyRJHXp0kX5+fmqqamRv7+/2rdvry1btjjGW5JKSkokSZ06dVJhYaFjvOPj45WbmytJioqKkpeXl4qKiiRJSUlJKikpUWVlpXx8fJSUlKTs7GxJUkREhHx9fZ3Gu7S0VOXl5fLy8lKXLl2UlZXlGO+AgADHguQJCQnat2/fEcc7JCRE+fn5kqS4uDiVl5dr//79stlsh413eHi4tm/fLklq3769qqurHeOdlpamLVu26NChQwoKClJUVJTTeNfV1am0tFSSlJKSou3bt6u2tlaBgYGKiYlxHLMxMTFqbGx0OmYLCgoc492hQwenY9ZmsznGOzk5WUVFRaqqqpKvr68SEhKOOt67d+9WRUVFs+Pt5+fX7DH7+/EOCwtTUFCQCgoKJEnx8fE6cOCADhw4IA8PD6Wmpio7O1uNjY0KDQ1VaGio03hXVFQ4/rr722O2ufGuqalp9pgNCgpSdHS0KioqlJWV1ewxu2PHDtXW1iogIMAt5ojfjvfBgwePeMwyRzBHHGmOqKqqUn19fauaI452zDJHMEccbY6ora1VVlZWq5ojWuPvEcwRLTdHNDQ0qKSkpNXMEa3x9wjmiJabI5r+D9Oa5ojW9nvEqTxH+Pv7ywib3W63G9oT6tOnj7p27arZs2c7tiUkJOj222/X3XffLUmy2+3y8PDQ0qVLNXfuXIWGhur111937L9x40b16NFDO3bsUHx8fLPPOWjQIEVERGjOnDmSfr2Q1vvvv6/Bgwc79snMzNQ777yjX375xbFtxowZev755x0h+736+nqtWrVKSUlJjoavJPn6+srX1/ePDc4pYt26dbp14GA94d1R9x/K04vLl+icc84xuywAAAAAAAC4gYaGBm3cuFEZGRny8jry+awsL+Aib29vp9s2m81pm81mk/TrWah2u91xu0lTj/u325t7zsbGxuOqxcjjgoODFRIS4vhyl4arJPn5+R31NoDDNf01F8CxkRfAOPICuIbMAMaRF1gBTdcTKD09XWvWrNFvTyZes2aNgoOD1b59e8PP4+3trYaGhhNRIgCIDzwAxpEXwDjyAriGzADGkRdYAU3XE+i2225TQUGBJkyYoOzsbC1dulRTp07VpEmTnD7efyyJiYn67LPPVFxczBX6ALS4Nm3amF0CYBnkBTCOvACuITOAceQFVkDT9QRq3769li9frm+++Ubdu3fXuHHjdNNNNzkuxGXUM888oxUrViguLk5/+tOfTlC1AFqrkJAQs0sALIO8AMaRF8A1ZAYwjrzACriQVivSdCGt7t27y9PT0+xyToiqqipNu3Wiev/3Z2UNPV/j/pGpgIAAs8sCTmlZWVlKT083uwzAEsgLYBx5AVxDZgDjyAvMxIW00CoFBAQoMiJCkhTTti0NVwAAAAAAAJx0NF3hdoL5mAHgkri4OLNLACyDvADGkRfANWQGMI68wApousLt1NXVml0CYCn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      "text/plain": [
       "<Figure size 1600x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('bmh')\n",
    "fig, ax = plt.subplots(figsize=(16,12))\n",
    "\n",
    "ax.boxplot(result.importances[sorted_idx].T, vert=False, labels=X_test.columns[sorted_idx], )\n",
    "ax.set_title('Permutation Importances', fontsize=16)\n",
    "ax.set_xlabel('Mean of Feature Importance')\n",
    "ax.set_ylabel('Feature')\n",
    "\n",
    "plt.savefig('data/images/fig10.png', dpi=200, transparent=True) \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For advisory, the top five features with the highest mean feature importances to the model are:\n",
    "1. Square footage of living space\n",
    "2. Distance to Seattle\n",
    "3. Total distance to both Seattle and Redmond\n",
    "4. Distance to Redmond\n",
    "5. Square footage of living space of the nearest 15 neighbors\n",
    "\n",
    "The other important features that follows are overall grade related to the construction and design of the house, quality of view from the house, zipcode, whether the house is on a waterfront, and square footage of lot.\n",
    "***\n",
    "**Model Deployment**\n",
    "\n",
    "Finally, I deploy the Random Forest regression model ([demo](https://streamlit.io/)) as a prototype I develop for a client-facing application that serves as a Home Value Estimator."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## VI. Further Research\n",
    "\n",
    "For further research, the data should be updated to more recent transactions in King County, and more features should be added such as more information on comparable and neighboring houses."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Contact\n",
    "\n",
    "Feel free to contact me for any questions and connect with me on [Linkedin](https://www.linkedin.com/in/czarinagluna/)."
   ]
  }
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