King_County_Project.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Project2 Submission\n",
    "\n",
    "Please fill out:\n",
    "* Student name: Wonuola Abimbola, Kibae Kim\n",
    "* Student pace: full time\n",
    "* Scheduled project review date/time: 4.23 / 10:30\n",
    "* Instructor name: Fangfang"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Overview"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For this project, we will be using regression modeling to analyze house sales price in the King County area between 2014 and 2015."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Business Problem"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Do the prices of the houses sold differ depending on the city they're located in?\n",
    "2. Does renovation have an effect on house price?\n",
    "3. Do waterfront houses have higher prices than other houses?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Understanding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import statsmodels.api as sm\n",
    "from statsmodels.formula.api import ols\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.metrics import mean_squared_error\n",
    "import math\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import geopandas as gpd\n",
    "import descartes\n",
    "from pyproj import CRS\n",
    "from shapely.geometry import Point, Polygon\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Houses and Cities Databases"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We used data of King County house sales price and house information, incorporated areas of King County / city area from King County GIS Open Data, and zipcode information from Zip Codes To Go."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#loading the data as a pandas dataframe\n",
    "df = pd.read_csv('data/kc_house_data.csv') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>OBJECTID</th>\n",
       "      <th>JURIS</th>\n",
       "      <th>CITYNAME</th>\n",
       "      <th>SHAPE_Leng</th>\n",
       "      <th>SHAPE_Area</th>\n",
       "      <th>geometry</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>AL</td>\n",
       "      <td>Algona</td>\n",
       "      <td>38144.667179</td>\n",
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       "      <td>POLYGON ((-122.24022 47.29353, -122.24307 47.2...</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
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       "      <td>AU</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
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       "      <td>BA</td>\n",
       "      <td>Beaux Arts</td>\n",
       "      <td>6720.785802</td>\n",
       "      <td>2.274707e+06</td>\n",
       "      <td>POLYGON ((-122.20276 47.58679, -122.20276 47.5...</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>BD</td>\n",
       "      <td>Black Diamond</td>\n",
       "      <td>6629.569588</td>\n",
       "      <td>2.412697e+06</td>\n",
       "      <td>POLYGON ((-121.96191 47.28836, -121.96191 47.2...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>BD</td>\n",
       "      <td>Black Diamond</td>\n",
       "      <td>85786.107116</td>\n",
       "      <td>1.983661e+08</td>\n",
       "      <td>POLYGON ((-122.04854 47.34368, -122.04412 47.3...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>58</td>\n",
       "      <td>SN</td>\n",
       "      <td>Snoqualmie</td>\n",
       "      <td>114919.649620</td>\n",
       "      <td>2.009551e+08</td>\n",
       "      <td>POLYGON ((-121.82845 47.54868, -121.82841 47.5...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>59</td>\n",
       "      <td>ST</td>\n",
       "      <td>SeaTac</td>\n",
       "      <td>101640.458450</td>\n",
       "      <td>2.866419e+08</td>\n",
       "      <td>POLYGON ((-122.30332 47.48876, -122.30305 47.4...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>60</td>\n",
       "      <td>TU</td>\n",
       "      <td>Tukwila</td>\n",
       "      <td>125946.874691</td>\n",
       "      <td>2.683084e+08</td>\n",
       "      <td>POLYGON ((-122.29128 47.51595, -122.29134 47.5...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>61</td>\n",
       "      <td>WO</td>\n",
       "      <td>Woodinville</td>\n",
       "      <td>89621.634641</td>\n",
       "      <td>1.577113e+08</td>\n",
       "      <td>POLYGON ((-122.11284 47.76882, -122.11284 47.7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>62</td>\n",
       "      <td>YP</td>\n",
       "      <td>Yarrow Point</td>\n",
       "      <td>16975.521653</td>\n",
       "      <td>1.321070e+07</td>\n",
       "      <td>POLYGON ((-122.21186 47.64635, -122.21186 47.6...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>62 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    OBJECTID JURIS       CITYNAME     SHAPE_Leng    SHAPE_Area  \\\n",
       "0          1    AL         Algona   38144.667179  3.641105e+07   \n",
       "1          2    AU         Auburn  209231.046799  7.856892e+08   \n",
       "2          3    BA     Beaux Arts    6720.785802  2.274707e+06   \n",
       "3          4    BD  Black Diamond    6629.569588  2.412697e+06   \n",
       "4          5    BD  Black Diamond   85786.107116  1.983661e+08   \n",
       "..       ...   ...            ...            ...           ...   \n",
       "57        58    SN     Snoqualmie  114919.649620  2.009551e+08   \n",
       "58        59    ST         SeaTac  101640.458450  2.866419e+08   \n",
       "59        60    TU        Tukwila  125946.874691  2.683084e+08   \n",
       "60        61    WO    Woodinville   89621.634641  1.577113e+08   \n",
       "61        62    YP   Yarrow Point   16975.521653  1.321070e+07   \n",
       "\n",
       "                                             geometry  \n",
       "0   POLYGON ((-122.24022 47.29353, -122.24307 47.2...  \n",
       "1   POLYGON ((-122.22820 47.35395, -122.22546 47.3...  \n",
       "2   POLYGON ((-122.20276 47.58679, -122.20276 47.5...  \n",
       "3   POLYGON ((-121.96191 47.28836, -121.96191 47.2...  \n",
       "4   POLYGON ((-122.04854 47.34368, -122.04412 47.3...  \n",
       "..                                                ...  \n",
       "57  POLYGON ((-121.82845 47.54868, -121.82841 47.5...  \n",
       "58  POLYGON ((-122.30332 47.48876, -122.30305 47.4...  \n",
       "59  POLYGON ((-122.29128 47.51595, -122.29134 47.5...  \n",
       "60  POLYGON ((-122.11284 47.76882, -122.11284 47.7...  \n",
       "61  POLYGON ((-122.21186 47.64635, -122.21186 47.6...  \n",
       "\n",
       "[62 rows x 6 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# loading the shape file as geopandas dataframe\n",
    "gdf = gpd.read_file(\"data/mapping/Incorporated_Areas_of_King_County___city_area.shp\")\n",
    "\n",
    "gdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# reading in file to get the cities that correspond to the zipcodes\n",
    "payload=pd.read_html(\"https://www.zipcodestogo.com/Washington/\")\n",
    "df_zipcode = payload[1]\n",
    "df_zipcode = df_zipcode.drop([0,1], axis=0)\n",
    "df_zipcode = df_zipcode.drop([3], axis=1)\n",
    "df_zipcode.columns = ['zipcode', 'city', 'county']\n",
    "df_zipcode.index -= 2\n",
    "\n",
    "zipcode_dic = {}\n",
    "for i in range(len(df_zipcode)):\n",
    "    zipcode_dic[int(df_zipcode.zipcode[i])] = df_zipcode.city[i]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <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>...</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",
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       "  <tbody>\n",
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       "      <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>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>7</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",
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       "    <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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>7</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>6</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",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2487200875</td>\n",
       "      <td>12/9/2014</td>\n",
       "      <td>604000.0</td>\n",
       "      <td>4</td>\n",
       "      <td>3.00</td>\n",
       "      <td>1960</td>\n",
       "      <td>5000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>1050</td>\n",
       "      <td>910.0</td>\n",
       "      <td>1965</td>\n",
       "      <td>0.0</td>\n",
       "      <td>98136</td>\n",
       "      <td>47.5208</td>\n",
       "      <td>-122.393</td>\n",
       "      <td>1360</td>\n",
       "      <td>5000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1954400510</td>\n",
       "      <td>2/18/2015</td>\n",
       "      <td>510000.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2.00</td>\n",
       "      <td>1680</td>\n",
       "      <td>8080</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>1680</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1987</td>\n",
       "      <td>0.0</td>\n",
       "      <td>98074</td>\n",
       "      <td>47.6168</td>\n",
       "      <td>-122.045</td>\n",
       "      <td>1800</td>\n",
       "      <td>7503</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\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",
       "3  2487200875   12/9/2014  604000.0         4       3.00         1960   \n",
       "4  1954400510   2/18/2015  510000.0         3       2.00         1680   \n",
       "\n",
       "   sqft_lot  floors  waterfront  view  ...  grade  sqft_above  sqft_basement  \\\n",
       "0      5650     1.0         NaN   0.0  ...      7        1180            0.0   \n",
       "1      7242     2.0         0.0   0.0  ...      7        2170          400.0   \n",
       "2     10000     1.0         0.0   0.0  ...      6         770            0.0   \n",
       "3      5000     1.0         0.0   0.0  ...      7        1050          910.0   \n",
       "4      8080     1.0         0.0   0.0  ...      8        1680            0.0   \n",
       "\n",
       "  yr_built  yr_renovated  zipcode      lat     long  sqft_living15  sqft_lot15  \n",
       "0     1955           0.0    98178  47.5112 -122.257           1340        5650  \n",
       "1     1951        1991.0    98125  47.7210 -122.319           1690        7639  \n",
       "2     1933           NaN    98028  47.7379 -122.233           2720        8062  \n",
       "3     1965           0.0    98136  47.5208 -122.393           1360        5000  \n",
       "4     1987           0.0    98074  47.6168 -122.045           1800        7503  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# taking a look at the file\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>OBJECTID</th>\n",
       "      <th>JURIS</th>\n",
       "      <th>CITYNAME</th>\n",
       "      <th>SHAPE_Leng</th>\n",
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       "      <th>geometry</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>AL</td>\n",
       "      <td>Algona</td>\n",
       "      <td>38144.667179</td>\n",
       "      <td>3.641105e+07</td>\n",
       "      <td>POLYGON ((-122.24022 47.29353, -122.24307 47.2...</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>AU</td>\n",
       "      <td>Auburn</td>\n",
       "      <td>209231.046799</td>\n",
       "      <td>7.856892e+08</td>\n",
       "      <td>POLYGON ((-122.22820 47.35395, -122.22546 47.3...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>BA</td>\n",
       "      <td>Beaux Arts</td>\n",
       "      <td>6720.785802</td>\n",
       "      <td>2.274707e+06</td>\n",
       "      <td>POLYGON ((-122.20276 47.58679, -122.20276 47.5...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>BD</td>\n",
       "      <td>Black Diamond</td>\n",
       "      <td>6629.569588</td>\n",
       "      <td>2.412697e+06</td>\n",
       "      <td>POLYGON ((-121.96191 47.28836, -121.96191 47.2...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>BD</td>\n",
       "      <td>Black Diamond</td>\n",
       "      <td>85786.107116</td>\n",
       "      <td>1.983661e+08</td>\n",
       "      <td>POLYGON ((-122.04854 47.34368, -122.04412 47.3...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   OBJECTID JURIS       CITYNAME     SHAPE_Leng    SHAPE_Area  \\\n",
       "0         1    AL         Algona   38144.667179  3.641105e+07   \n",
       "1         2    AU         Auburn  209231.046799  7.856892e+08   \n",
       "2         3    BA     Beaux Arts    6720.785802  2.274707e+06   \n",
       "3         4    BD  Black Diamond    6629.569588  2.412697e+06   \n",
       "4         5    BD  Black Diamond   85786.107116  1.983661e+08   \n",
       "\n",
       "                                            geometry  \n",
       "0  POLYGON ((-122.24022 47.29353, -122.24307 47.2...  \n",
       "1  POLYGON ((-122.22820 47.35395, -122.22546 47.3...  \n",
       "2  POLYGON ((-122.20276 47.58679, -122.20276 47.5...  \n",
       "3  POLYGON ((-121.96191 47.28836, -121.96191 47.2...  \n",
       "4  POLYGON ((-122.04854 47.34368, -122.04412 47.3...  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# looking at the first few rows of the gdf geopandas df\n",
    "gdf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<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>...</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",
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       "      <td>0.0</td>\n",
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       "      <td>7</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>7</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>6</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",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2487200875</td>\n",
       "      <td>12/9/2014</td>\n",
       "      <td>604000.0</td>\n",
       "      <td>4</td>\n",
       "      <td>3.00</td>\n",
       "      <td>1960</td>\n",
       "      <td>5000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>1050</td>\n",
       "      <td>910.0</td>\n",
       "      <td>1965</td>\n",
       "      <td>0.0</td>\n",
       "      <td>98136</td>\n",
       "      <td>47.5208</td>\n",
       "      <td>-122.393</td>\n",
       "      <td>1360</td>\n",
       "      <td>5000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1954400510</td>\n",
       "      <td>2/18/2015</td>\n",
       "      <td>510000.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2.00</td>\n",
       "      <td>1680</td>\n",
       "      <td>8080</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>1680</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1987</td>\n",
       "      <td>0.0</td>\n",
       "      <td>98074</td>\n",
       "      <td>47.6168</td>\n",
       "      <td>-122.045</td>\n",
       "      <td>1800</td>\n",
       "      <td>7503</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\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",
       "3  2487200875   12/9/2014  604000.0         4       3.00         1960   \n",
       "4  1954400510   2/18/2015  510000.0         3       2.00         1680   \n",
       "\n",
       "   sqft_lot  floors  waterfront  view  ...  grade  sqft_above  sqft_basement  \\\n",
       "0      5650     1.0         NaN   0.0  ...      7        1180            0.0   \n",
       "1      7242     2.0         0.0   0.0  ...      7        2170          400.0   \n",
       "2     10000     1.0         0.0   0.0  ...      6         770            0.0   \n",
       "3      5000     1.0         0.0   0.0  ...      7        1050          910.0   \n",
       "4      8080     1.0         0.0   0.0  ...      8        1680            0.0   \n",
       "\n",
       "  yr_built  yr_renovated  zipcode      lat     long  sqft_living15  sqft_lot15  \n",
       "0     1955           0.0    98178  47.5112 -122.257           1340        5650  \n",
       "1     1951        1991.0    98125  47.7210 -122.319           1690        7639  \n",
       "2     1933           NaN    98028  47.7379 -122.233           2720        8062  \n",
       "3     1965           0.0    98136  47.5208 -122.393           1360        5000  \n",
       "4     1987           0.0    98074  47.6168 -122.045           1800        7503  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# loading the king's county data into a different variable name in order to use for mapping purposes\n",
    "df_1 = pd.read_csv('data/kc_house_data.csv')\n",
    "df_1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# changing the data type for latitude and longitude columns from string to float\n",
    "df_1['lat'] = df_1['lat'].astype(float)\n",
    "df_1['long'] = df_1['long'].astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<shapely.geometry.point.Point at 0x1ad681bcb20>,\n",
       " <shapely.geometry.point.Point at 0x1ad681bc3a0>,\n",
       " <shapely.geometry.point.Point at 0x1ad681bc6a0>,\n",
       " <shapely.geometry.point.Point at 0x1ad681bc790>,\n",
       " <shapely.geometry.point.Point at 0x1ad681bc490>]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# generating geometry data using the lat and longitude columns\n",
    "geometry = [Point(xy) for xy in zip (df_1['long'], df_1['lat'])]\n",
    "geometry[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<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>...</th>\n",
       "      <th>sqft_above</th>\n",
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       "      <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",
       "      <th>geometry</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",
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       "    </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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</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",
       "      <td>POINT (-122.31900 47.72100)</td>\n",
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       "      <th>2</th>\n",
       "      <td>5631500400</td>\n",
       "      <td>2/25/2015</td>\n",
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       "      <td>2</td>\n",
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       "      <td>770</td>\n",
       "      <td>10000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</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",
       "      <td>POINT (-122.23300 47.73790)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2487200875</td>\n",
       "      <td>12/9/2014</td>\n",
       "      <td>604000.0</td>\n",
       "      <td>4</td>\n",
       "      <td>3.00</td>\n",
       "      <td>1960</td>\n",
       "      <td>5000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1050</td>\n",
       "      <td>910.0</td>\n",
       "      <td>1965</td>\n",
       "      <td>0.0</td>\n",
       "      <td>98136</td>\n",
       "      <td>47.5208</td>\n",
       "      <td>-122.393</td>\n",
       "      <td>1360</td>\n",
       "      <td>5000</td>\n",
       "      <td>POINT (-122.39300 47.52080)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1954400510</td>\n",
       "      <td>2/18/2015</td>\n",
       "      <td>510000.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2.00</td>\n",
       "      <td>1680</td>\n",
       "      <td>8080</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1680</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1987</td>\n",
       "      <td>0.0</td>\n",
       "      <td>98074</td>\n",
       "      <td>47.6168</td>\n",
       "      <td>-122.045</td>\n",
       "      <td>1800</td>\n",
       "      <td>7503</td>\n",
       "      <td>POINT (-122.04500 47.61680)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\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",
       "3  2487200875   12/9/2014  604000.0         4       3.00         1960   \n",
       "4  1954400510   2/18/2015  510000.0         3       2.00         1680   \n",
       "\n",
       "   sqft_lot  floors  waterfront  view  ...  sqft_above  sqft_basement  \\\n",
       "0      5650     1.0         NaN   0.0  ...        1180            0.0   \n",
       "1      7242     2.0         0.0   0.0  ...        2170          400.0   \n",
       "2     10000     1.0         0.0   0.0  ...         770            0.0   \n",
       "3      5000     1.0         0.0   0.0  ...        1050          910.0   \n",
       "4      8080     1.0         0.0   0.0  ...        1680            0.0   \n",
       "\n",
       "   yr_built yr_renovated  zipcode      lat     long  sqft_living15  \\\n",
       "0      1955          0.0    98178  47.5112 -122.257           1340   \n",
       "1      1951       1991.0    98125  47.7210 -122.319           1690   \n",
       "2      1933          NaN    98028  47.7379 -122.233           2720   \n",
       "3      1965          0.0    98136  47.5208 -122.393           1360   \n",
       "4      1987          0.0    98074  47.6168 -122.045           1800   \n",
       "\n",
       "   sqft_lot15                     geometry  \n",
       "0        5650  POINT (-122.25700 47.51120)  \n",
       "1        7639  POINT (-122.31900 47.72100)  \n",
       "2        8062  POINT (-122.23300 47.73790)  \n",
       "3        5000  POINT (-122.39300 47.52080)  \n",
       "4        7503  POINT (-122.04500 47.61680)  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#creating a geopandas df from the original file and the geometry data above using a coordinate reference system\n",
    "geo_df = gpd.GeoDataFrame(df_1, crs = CRS('EPSG:4326'), geometry = geometry)\n",
    "geo_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1152 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plotting the data on the map using matplotlib\n",
    "fig, ax = plt.subplots(figsize = (15,16))\n",
    "gdf.plot(ax=ax, alpha = 0.8, color = 'Grey')\n",
    "geo_df.plot(ax=ax,\n",
    "            column ='price',\n",
    "            cmap = 'inferno',\n",
    "            legend = True,\n",
    "            label= 'houses' ,\n",
    "            markersize = 2,\n",
    "            marker = 'o',\n",
    "            aspect = 1.5\n",
    "           )\n",
    "\n",
    "plt.legend(prop = {'size':10} )\n",
    "ax.set_title('Houses in Kings County, WA', fontdict = {'fontsize':\n",
    "                20})\n",
    "ax.set_ylabel('Latitude',fontdict = {'fontsize': 20})\n",
    "ax.set_xlabel('Longitude',fontdict = {'fontsize': 20})\n",
    "fig.savefig('./images/kingcountyMap.png');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{98001: 'Auburn',\n",
       " 98002: 'Auburn',\n",
       " 98003: 'Federal Way',\n",
       " 98004: 'Bellevue',\n",
       " 98005: 'Bellevue',\n",
       " 98006: 'Bellevue',\n",
       " 98007: 'Bellevue',\n",
       " 98008: 'Bellevue',\n",
       " 98009: 'Bellevue',\n",
       " 98010: 'Black Diamond',\n",
       " 98011: 'Bothell',\n",
       " 98012: 'Bothell',\n",
       " 98013: 'Burton',\n",
       " 98014: 'Carnation',\n",
       " 98015: 'Bellevue',\n",
       " 98019: 'Duvall',\n",
       " 98020: 'Edmonds',\n",
       " 98021: 'Bothell',\n",
       " 98022: 'Enumclaw',\n",
       " 98023: 'Federal Way',\n",
       " 98024: 'Fall City',\n",
       " 98025: 'Hobart',\n",
       " 98026: 'Edmonds',\n",
       " 98027: 'Issaquah',\n",
       " 98028: 'Kenmore',\n",
       " 98029: 'Issaquah',\n",
       " 98030: 'Kent',\n",
       " 98031: 'Kent',\n",
       " 98032: 'Kent',\n",
       " 98033: 'Kirkland',\n",
       " 98034: 'Kirkland',\n",
       " 98035: 'Kent',\n",
       " 98036: 'Lynnwood',\n",
       " 98037: 'Lynnwood',\n",
       " 98038: 'Maple Valley',\n",
       " 98039: 'Medina',\n",
       " 98040: 'Mercer Island',\n",
       " 98041: 'Bothell',\n",
       " 98042: 'Kent',\n",
       " 98043: 'Mountlake Terrace',\n",
       " 98045: 'North Bend',\n",
       " 98046: 'Lynnwood',\n",
       " 98047: 'Pacific',\n",
       " 98050: 'Preston',\n",
       " 98051: 'Ravensdale',\n",
       " 98052: 'Redmond',\n",
       " 98053: 'Redmond',\n",
       " 98054: 'Redondo',\n",
       " 98055: 'Renton',\n",
       " 98056: 'Renton',\n",
       " 98057: 'Renton',\n",
       " 98058: 'Renton',\n",
       " 98059: 'Renton',\n",
       " 98061: 'Rollingbay',\n",
       " 98062: 'Seahurst',\n",
       " 98063: 'Federal Way',\n",
       " 98064: 'Kent',\n",
       " 98065: 'Snoqualmie',\n",
       " 98068: 'Snoqualmie Pass',\n",
       " 98070: 'Vashon',\n",
       " 98071: 'Auburn',\n",
       " 98072: 'Woodinville',\n",
       " 98073: 'Redmond',\n",
       " 98074: 'Sammamish',\n",
       " 98075: 'Sammamish',\n",
       " 98077: 'Woodinville',\n",
       " 98082: 'Mill Creek',\n",
       " 98083: 'Kirkland',\n",
       " 98087: 'Lynnwood',\n",
       " 98089: 'Kent',\n",
       " 98092: 'Auburn',\n",
       " 98093: 'Federal Way',\n",
       " 98101: 'Seattle',\n",
       " 98102: 'Seattle',\n",
       " 98103: 'Seattle',\n",
       " 98104: 'Seattle',\n",
       " 98105: 'Seattle',\n",
       " 98106: 'Seattle',\n",
       " 98107: 'Seattle',\n",
       " 98108: 'Seattle',\n",
       " 98109: 'Seattle',\n",
       " 98110: 'Bainbridge Island',\n",
       " 98111: 'Seattle',\n",
       " 98112: 'Seattle',\n",
       " 98113: 'Seattle',\n",
       " 98114: 'Seattle',\n",
       " 98115: 'Seattle',\n",
       " 98116: 'Seattle',\n",
       " 98117: 'Seattle',\n",
       " 98118: 'Seattle',\n",
       " 98119: 'Seattle',\n",
       " 98121: 'Seattle',\n",
       " 98122: 'Seattle',\n",
       " 98124: 'Seattle',\n",
       " 98125: 'Seattle',\n",
       " 98126: 'Seattle',\n",
       " 98127: 'Seattle',\n",
       " 98129: 'Seattle',\n",
       " 98131: 'Seattle',\n",
       " 98132: 'Seattle',\n",
       " 98133: 'Seattle',\n",
       " 98134: 'Seattle',\n",
       " 98136: 'Seattle',\n",
       " 98138: 'Seattle',\n",
       " 98139: 'Seattle',\n",
       " 98141: 'Seattle',\n",
       " 98144: 'Seattle',\n",
       " 98145: 'Seattle',\n",
       " 98146: 'Seattle',\n",
       " 98148: 'Seattle',\n",
       " 98151: 'Seattle',\n",
       " 98154: 'Seattle',\n",
       " 98155: 'Seattle',\n",
       " 98158: 'Seattle',\n",
       " 98160: 'Seattle',\n",
       " 98161: 'Seattle',\n",
       " 98164: 'Seattle',\n",
       " 98165: 'Seattle',\n",
       " 98166: 'Seattle',\n",
       " 98168: 'Seattle',\n",
       " 98170: 'Seattle',\n",
       " 98171: 'Seattle',\n",
       " 98174: 'Seattle',\n",
       " 98175: 'Seattle',\n",
       " 98177: 'Seattle',\n",
       " 98178: 'Seattle',\n",
       " 98181: 'Seattle',\n",
       " 98184: 'Seattle',\n",
       " 98185: 'Seattle',\n",
       " 98188: 'Seattle',\n",
       " 98190: 'Seattle',\n",
       " 98191: 'Seattle',\n",
       " 98194: 'Seattle',\n",
       " 98195: 'Seattle',\n",
       " 98198: 'Seattle',\n",
       " 98199: 'Seattle',\n",
       " 98201: 'Everett',\n",
       " 98203: 'Everett',\n",
       " 98204: 'Everett',\n",
       " 98205: 'Everett',\n",
       " 98206: 'Everett',\n",
       " 98207: 'Everett',\n",
       " 98208: 'Everett',\n",
       " 98213: 'Everett',\n",
       " 98220: 'Acme',\n",
       " 98221: 'Anacortes',\n",
       " 98222: 'Blakely Island',\n",
       " 98223: 'Arlington',\n",
       " 98224: 'Baring',\n",
       " 98225: 'Bellingham',\n",
       " 98226: 'Bellingham',\n",
       " 98227: 'Bellingham',\n",
       " 98228: 'Bellingham',\n",
       " 98229: 'Bellingham',\n",
       " 98230: 'Blaine',\n",
       " 98231: 'Blaine',\n",
       " 98232: 'Bow',\n",
       " 98233: 'Burlington',\n",
       " 98235: 'Clearlake',\n",
       " 98236: 'Clinton',\n",
       " 98237: 'Concrete',\n",
       " 98238: 'Conway',\n",
       " 98239: 'Coupeville',\n",
       " 98240: 'Custer',\n",
       " 98241: 'Darrington',\n",
       " 98243: 'Deer Harbor',\n",
       " 98244: 'Deming',\n",
       " 98245: 'Eastsound',\n",
       " 98247: 'Everson',\n",
       " 98248: 'Ferndale',\n",
       " 98249: 'Freeland',\n",
       " 98250: 'Friday Harbor',\n",
       " 98251: 'Gold Bar',\n",
       " 98252: 'Granite Falls',\n",
       " 98253: 'Greenbank',\n",
       " 98255: 'Hamilton',\n",
       " 98256: 'Index',\n",
       " 98257: 'La Conner',\n",
       " 98258: 'Lake Stevens',\n",
       " 98259: 'North Lakewood',\n",
       " 98260: 'Langley',\n",
       " 98261: 'Lopez Island',\n",
       " 98262: 'Lummi Island',\n",
       " 98263: 'Lyman',\n",
       " 98264: 'Lynden',\n",
       " 98266: 'Maple Falls',\n",
       " 98267: 'Marblemount',\n",
       " 98270: 'Marysville',\n",
       " 98271: 'Marysville',\n",
       " 98272: 'Monroe',\n",
       " 98273: 'Mount Vernon',\n",
       " 98274: 'Mount Vernon',\n",
       " 98275: 'Mukilteo',\n",
       " 98276: 'Nooksack',\n",
       " 98277: 'Oak Harbor',\n",
       " 98278: 'Oak Harbor',\n",
       " 98279: 'Olga',\n",
       " 98280: 'Orcas',\n",
       " 98281: 'Point Roberts',\n",
       " 98282: 'Camano Island',\n",
       " 98283: 'Rockport',\n",
       " 98284: 'Sedro Woolley',\n",
       " 98286: 'Shaw Island',\n",
       " 98287: 'Silvana',\n",
       " 98288: 'Skykomish',\n",
       " 98290: 'Snohomish',\n",
       " 98291: 'Snohomish',\n",
       " 98292: 'Stanwood',\n",
       " 98293: 'Startup',\n",
       " 98294: 'Sultan',\n",
       " 98295: 'Sumas',\n",
       " 98296: 'Snohomish',\n",
       " 98297: 'Waldron',\n",
       " 98303: 'Anderson Island',\n",
       " 98304: 'Ashford',\n",
       " 98305: 'Beaver',\n",
       " 98310: 'Bremerton',\n",
       " 98311: 'Bremerton',\n",
       " 98312: 'Bremerton',\n",
       " 98314: 'Bremerton',\n",
       " 98315: 'Silverdale',\n",
       " 98320: 'Brinnon',\n",
       " 98321: 'Buckley',\n",
       " 98322: 'Burley',\n",
       " 98323: 'Carbonado',\n",
       " 98324: 'Carlsborg',\n",
       " 98325: 'Chimacum',\n",
       " 98326: 'Clallam Bay',\n",
       " 98327: 'Dupont',\n",
       " 98328: 'Eatonville',\n",
       " 98329: 'Gig Harbor',\n",
       " 98330: 'Elbe',\n",
       " 98331: 'Forks',\n",
       " 98332: 'Gig Harbor',\n",
       " 98333: 'Fox Island',\n",
       " 98335: 'Gig Harbor',\n",
       " 98336: 'Glenoma',\n",
       " 98337: 'Bremerton',\n",
       " 98338: 'Graham',\n",
       " 98339: 'Port Hadlock',\n",
       " 98340: 'Hansville',\n",
       " 98342: 'Indianola',\n",
       " 98343: 'Joyce',\n",
       " 98344: 'Kapowsin',\n",
       " 98345: 'Keyport',\n",
       " 98346: 'Kingston',\n",
       " 98348: 'La Grande',\n",
       " 98349: 'Lakebay',\n",
       " 98350: 'La Push',\n",
       " 98351: 'Longbranch',\n",
       " 98352: 'Sumner',\n",
       " 98353: 'Manchester',\n",
       " 98354: 'Milton',\n",
       " 98355: 'Mineral',\n",
       " 98356: 'Morton',\n",
       " 98357: 'Neah Bay',\n",
       " 98358: 'Nordland',\n",
       " 98359: 'Olalla',\n",
       " 98360: 'Orting',\n",
       " 98361: 'Packwood',\n",
       " 98362: 'Port Angeles',\n",
       " 98363: 'Port Angeles',\n",
       " 98364: 'Port Gamble',\n",
       " 98365: 'Port Ludlow',\n",
       " 98366: 'Port Orchard',\n",
       " 98367: 'Port Orchard',\n",
       " 98368: 'Port Townsend',\n",
       " 98370: 'Poulsbo',\n",
       " 98371: 'Puyallup',\n",
       " 98372: 'Puyallup',\n",
       " 98373: 'Puyallup',\n",
       " 98374: 'Puyallup',\n",
       " 98375: 'Puyallup',\n",
       " 98376: 'Quilcene',\n",
       " 98377: 'Randle',\n",
       " 98378: 'Retsil',\n",
       " 98380: 'Seabeck',\n",
       " 98381: 'Sekiu',\n",
       " 98382: 'Sequim',\n",
       " 98383: 'Silverdale',\n",
       " 98384: 'South Colby',\n",
       " 98385: 'South Prairie',\n",
       " 98386: 'Southworth',\n",
       " 98387: 'Spanaway',\n",
       " 98388: 'Steilacoom',\n",
       " 98390: 'Sumner',\n",
       " 98391: 'Bonney Lake',\n",
       " 98392: 'Suquamish',\n",
       " 98393: 'Tracyton',\n",
       " 98394: 'Vaughn',\n",
       " 98395: 'Wauna',\n",
       " 98396: 'Wilkeson',\n",
       " 98397: 'Longmire',\n",
       " 98398: 'Paradise Inn',\n",
       " 98401: 'Tacoma',\n",
       " 98402: 'Tacoma',\n",
       " 98403: 'Tacoma',\n",
       " 98404: 'Tacoma',\n",
       " 98405: 'Tacoma',\n",
       " 98406: 'Tacoma',\n",
       " 98407: 'Tacoma',\n",
       " 98408: 'Tacoma',\n",
       " 98409: 'Tacoma',\n",
       " 98411: 'Tacoma',\n",
       " 98412: 'Tacoma',\n",
       " 98413: 'Tacoma',\n",
       " 98415: 'Tacoma',\n",
       " 98416: 'Tacoma',\n",
       " 98417: 'Tacoma',\n",
       " 98418: 'Tacoma',\n",
       " 98419: 'Tacoma',\n",
       " 98421: 'Tacoma',\n",
       " 98422: 'Tacoma',\n",
       " 98424: 'Tacoma',\n",
       " 98430: 'Camp Murray',\n",
       " 98431: 'Tacoma',\n",
       " 98433: 'Tacoma',\n",
       " 98438: 'Mcchord Afb',\n",
       " 98439: 'Lakewood',\n",
       " 98442: 'Tacoma',\n",
       " 98443: 'Tacoma',\n",
       " 98444: 'Tacoma',\n",
       " 98445: 'Tacoma',\n",
       " 98446: 'Tacoma',\n",
       " 98447: 'Tacoma',\n",
       " 98448: 'Tacoma',\n",
       " 98450: 'Tacoma',\n",
       " 98455: 'Tacoma',\n",
       " 98460: 'Tacoma',\n",
       " 98464: 'Tacoma',\n",
       " 98465: 'Tacoma',\n",
       " 98466: 'Tacoma',\n",
       " 98467: 'University Place',\n",
       " 98471: 'Tacoma',\n",
       " 98477: 'Tacoma',\n",
       " 98481: 'Tacoma',\n",
       " 98490: 'Tacoma',\n",
       " 98492: 'Lakewood',\n",
       " 98493: 'Tacoma',\n",
       " 98496: 'Lakewood',\n",
       " 98497: 'Lakewood',\n",
       " 98498: 'Lakewood',\n",
       " 98499: 'Lakewood',\n",
       " 98501: 'Olympia',\n",
       " 98502: 'Olympia',\n",
       " 98503: 'Lacey',\n",
       " 98504: 'Olympia',\n",
       " 98505: 'Olympia',\n",
       " 98506: 'Olympia',\n",
       " 98507: 'Olympia',\n",
       " 98508: 'Olympia',\n",
       " 98509: 'Lacey',\n",
       " 98511: 'Tumwater',\n",
       " 98512: 'Olympia',\n",
       " 98513: 'Olympia',\n",
       " 98516: 'Olympia',\n",
       " 98520: 'Aberdeen',\n",
       " 98522: 'Adna',\n",
       " 98524: 'Allyn',\n",
       " 98526: 'Amanda Park',\n",
       " 98527: 'Bay Center',\n",
       " 98528: 'Belfair',\n",
       " 98530: 'Bucoda',\n",
       " 98531: 'Centralia',\n",
       " 98532: 'Chehalis',\n",
       " 98533: 'Cinebar',\n",
       " 98535: 'Copalis Beach',\n",
       " 98536: 'Copalis Crossing',\n",
       " 98537: 'Cosmopolis',\n",
       " 98538: 'Curtis',\n",
       " 98539: 'Doty',\n",
       " 98540: 'East Olympia',\n",
       " 98541: 'Elma',\n",
       " 98542: 'Ethel',\n",
       " 98544: 'Galvin',\n",
       " 98546: 'Grapeview',\n",
       " 98547: 'Grayland',\n",
       " 98548: 'Hoodsport',\n",
       " 98550: 'Hoquiam',\n",
       " 98552: 'Humptulips',\n",
       " 98554: 'Lebam',\n",
       " 98555: 'Lilliwaup',\n",
       " 98556: 'Littlerock',\n",
       " 98557: 'Mccleary',\n",
       " 98558: 'Mckenna',\n",
       " 98559: 'Malone',\n",
       " 98560: 'Matlock',\n",
       " 98561: 'Menlo',\n",
       " 98562: 'Moclips',\n",
       " 98563: 'Montesano',\n",
       " 98564: 'Mossyrock',\n",
       " 98565: 'Napavine',\n",
       " 98566: 'Neilton',\n",
       " 98568: 'Oakville',\n",
       " 98569: 'Ocean Shores',\n",
       " 98570: 'Onalaska',\n",
       " 98571: 'Pacific Beach',\n",
       " 98572: 'Pe Ell',\n",
       " 98575: 'Quinault',\n",
       " 98576: 'Rainier',\n",
       " 98577: 'Raymond',\n",
       " 98579: 'Rochester',\n",
       " 98580: 'Roy',\n",
       " 98581: 'Ryderwood',\n",
       " 98582: 'Salkum',\n",
       " 98583: 'Satsop',\n",
       " 98584: 'Shelton',\n",
       " 98585: 'Silver Creek',\n",
       " 98586: 'South Bend',\n",
       " 98587: 'Taholah',\n",
       " 98588: 'Tahuya',\n",
       " 98589: 'Tenino',\n",
       " 98590: 'Tokeland',\n",
       " 98591: 'Toledo',\n",
       " 98592: 'Union',\n",
       " 98593: 'Vader',\n",
       " 98595: 'Westport',\n",
       " 98596: 'Winlock',\n",
       " 98597: 'Yelm',\n",
       " 98599: 'Olympia',\n",
       " 98601: 'Amboy',\n",
       " 98602: 'Appleton',\n",
       " 98603: 'Ariel',\n",
       " 98604: 'Battle Ground',\n",
       " 98605: 'Bingen',\n",
       " 98606: 'Brush Prairie',\n",
       " 98607: 'Camas',\n",
       " 98609: 'Carrolls',\n",
       " 98610: 'Carson',\n",
       " 98611: 'Castle Rock',\n",
       " 98612: 'Cathlamet',\n",
       " 98613: 'Centerville',\n",
       " 98614: 'Chinook',\n",
       " 98616: 'Cougar',\n",
       " 98617: 'Dallesport',\n",
       " 98619: 'Glenwood',\n",
       " 98620: 'Goldendale',\n",
       " 98621: 'Grays River',\n",
       " 98622: 'Heisson',\n",
       " 98623: 'Husum',\n",
       " 98624: 'Ilwaco',\n",
       " 98625: 'Kalama',\n",
       " 98626: 'Kelso',\n",
       " 98628: 'Klickitat',\n",
       " 98629: 'La Center',\n",
       " 98631: 'Long Beach',\n",
       " 98632: 'Longview',\n",
       " 98635: 'Lyle',\n",
       " 98637: 'Nahcotta',\n",
       " 98638: 'Naselle',\n",
       " 98639: 'North Bonneville',\n",
       " 98640: 'Ocean Park',\n",
       " 98641: 'Oysterville',\n",
       " 98642: 'Ridgefield',\n",
       " 98643: 'Rosburg',\n",
       " 98644: 'Seaview',\n",
       " 98645: 'Silverlake',\n",
       " 98647: 'Skamokawa',\n",
       " 98648: 'Stevenson',\n",
       " 98649: 'Toutle',\n",
       " 98650: 'Trout Lake',\n",
       " 98651: 'Underwood',\n",
       " 98660: 'Vancouver',\n",
       " 98661: 'Vancouver',\n",
       " 98662: 'Vancouver',\n",
       " 98663: 'Vancouver',\n",
       " 98664: 'Vancouver',\n",
       " 98665: 'Vancouver',\n",
       " 98666: 'Vancouver',\n",
       " 98667: 'Vancouver',\n",
       " 98668: 'Vancouver',\n",
       " 98670: 'Wahkiacus',\n",
       " 98671: 'Washougal',\n",
       " 98672: 'White Salmon',\n",
       " 98673: 'Wishram',\n",
       " 98674: 'Woodland',\n",
       " 98675: 'Yacolt',\n",
       " 98682: 'Vancouver',\n",
       " 98683: 'Vancouver',\n",
       " 98684: 'Vancouver',\n",
       " 98685: 'Vancouver',\n",
       " 98686: 'Vancouver',\n",
       " 98687: 'Vancouver',\n",
       " 98801: 'Wenatchee',\n",
       " 98802: 'East Wenatchee',\n",
       " 98807: 'Wenatchee',\n",
       " 98811: 'Ardenvoir',\n",
       " 98812: 'Brewster',\n",
       " 98813: 'Bridgeport',\n",
       " 98814: 'Carlton',\n",
       " 98815: 'Cashmere',\n",
       " 98816: 'Chelan',\n",
       " 98817: 'Chelan Falls',\n",
       " 98819: 'Conconully',\n",
       " 98821: 'Dryden',\n",
       " 98822: 'Entiat',\n",
       " 98823: 'Ephrata',\n",
       " 98824: 'George',\n",
       " 98826: 'Leavenworth',\n",
       " 98827: 'Loomis',\n",
       " 98828: 'Malaga',\n",
       " 98829: 'Malott',\n",
       " 98830: 'Mansfield',\n",
       " 98831: 'Manson',\n",
       " 98832: 'Marlin',\n",
       " 98833: 'Mazama',\n",
       " 98834: 'Methow',\n",
       " 98836: 'Monitor',\n",
       " 98837: 'Moses Lake',\n",
       " 98840: 'Okanogan',\n",
       " 98841: 'Omak',\n",
       " 98843: 'Orondo',\n",
       " 98844: 'Oroville',\n",
       " 98845: 'Palisades',\n",
       " 98846: 'Pateros',\n",
       " 98847: 'Peshastin',\n",
       " 98848: 'Quincy',\n",
       " 98849: 'Riverside',\n",
       " 98850: 'Rock Island',\n",
       " 98851: 'Soap Lake',\n",
       " 98852: 'Stehekin',\n",
       " 98853: 'Stratford',\n",
       " 98855: 'Tonasket',\n",
       " 98856: 'Twisp',\n",
       " 98857: 'Warden',\n",
       " 98858: 'Waterville',\n",
       " 98859: 'Wauconda',\n",
       " 98860: 'Wilson Creek',\n",
       " 98862: 'Winthrop',\n",
       " 98901: 'Yakima',\n",
       " 98902: 'Yakima',\n",
       " 98903: 'Yakima',\n",
       " 98904: 'Yakima',\n",
       " 98907: 'Yakima',\n",
       " 98908: 'Yakima',\n",
       " 98909: 'Yakima',\n",
       " 98920: 'Brownstown',\n",
       " 98921: 'Buena',\n",
       " 98922: 'Cle Elum',\n",
       " 98923: 'Cowiche',\n",
       " 98925: 'Easton',\n",
       " 98926: 'Ellensburg',\n",
       " 98929: 'Goose Prairie',\n",
       " 98930: 'Grandview',\n",
       " 98932: 'Granger',\n",
       " 98933: 'Harrah',\n",
       " 98934: 'Kittitas',\n",
       " 98935: 'Mabton',\n",
       " 98936: 'Moxee',\n",
       " 98937: 'Naches',\n",
       " 98938: 'Outlook',\n",
       " 98939: 'Parker',\n",
       " 98940: 'Ronald',\n",
       " 98941: 'Roslyn',\n",
       " 98942: 'Selah',\n",
       " 98943: 'South Cle Elum',\n",
       " 98944: 'Sunnyside',\n",
       " 98946: 'Thorp',\n",
       " 98947: 'Tieton',\n",
       " 98948: 'Toppenish',\n",
       " 98950: 'Vantage',\n",
       " 98951: 'Wapato',\n",
       " 98952: 'White Swan',\n",
       " 98953: 'Zillah',\n",
       " 99001: 'Airway Heights',\n",
       " 99003: 'Chattaroy',\n",
       " 99004: 'Cheney',\n",
       " 99005: 'Colbert',\n",
       " 99006: 'Deer Park',\n",
       " 99008: 'Edwall',\n",
       " 99009: 'Elk',\n",
       " 99011: 'Fairchild Air Force Base',\n",
       " 99012: 'Fairfield',\n",
       " 99013: 'Ford',\n",
       " 99014: 'Four Lakes',\n",
       " 99016: 'Greenacres',\n",
       " 99017: 'Lamont',\n",
       " 99018: 'Latah',\n",
       " 99019: 'Liberty Lake',\n",
       " 99020: 'Marshall',\n",
       " 99021: 'Mead',\n",
       " 99022: 'Medical Lake',\n",
       " 99023: 'Mica',\n",
       " 99025: 'Newman Lake',\n",
       " 99026: 'Nine Mile Falls',\n",
       " 99027: 'Otis Orchards',\n",
       " 99029: 'Reardan',\n",
       " 99030: 'Rockford',\n",
       " 99031: 'Spangle',\n",
       " 99032: 'Sprague',\n",
       " 99033: 'Tekoa',\n",
       " 99034: 'Tumtum',\n",
       " 99036: 'Valleyford',\n",
       " 99037: 'Veradale',\n",
       " 99039: 'Waverly',\n",
       " 99040: 'Wellpinit',\n",
       " 99101: 'Addy',\n",
       " 99102: 'Albion',\n",
       " 99103: 'Almira',\n",
       " 99104: 'Belmont',\n",
       " 99105: 'Benge',\n",
       " 99107: 'Boyds',\n",
       " 99109: 'Chewelah',\n",
       " 99110: 'Clayton',\n",
       " 99111: 'Colfax',\n",
       " 99113: 'Colton',\n",
       " 99114: 'Colville',\n",
       " 99115: 'Coulee City',\n",
       " 99116: 'Coulee Dam',\n",
       " 99117: 'Creston',\n",
       " 99118: 'Curlew',\n",
       " 99119: 'Cusick',\n",
       " 99121: 'Danville',\n",
       " 99122: 'Davenport',\n",
       " 99123: 'Electric City',\n",
       " 99124: 'Elmer City',\n",
       " 99125: 'Endicott',\n",
       " 99126: 'Evans',\n",
       " 99128: 'Farmington',\n",
       " 99129: 'Fruitland',\n",
       " 99130: 'Garfield',\n",
       " 99131: 'Gifford',\n",
       " 99133: 'Grand Coulee',\n",
       " 99134: 'Harrington',\n",
       " 99135: 'Hartline',\n",
       " 99136: 'Hay',\n",
       " 99137: 'Hunters',\n",
       " 99138: 'Inchelium',\n",
       " 99139: 'Ione',\n",
       " 99140: 'Keller',\n",
       " 99141: 'Kettle Falls',\n",
       " 99143: 'Lacrosse',\n",
       " 99144: 'Lamona',\n",
       " 99146: 'Laurier',\n",
       " 99147: 'Lincoln',\n",
       " 99148: 'Loon Lake',\n",
       " 99149: 'Malden',\n",
       " 99150: 'Malo',\n",
       " 99151: 'Marcus',\n",
       " 99152: 'Metaline',\n",
       " 99153: 'Metaline Falls',\n",
       " 99154: 'Mohler',\n",
       " 99155: 'Nespelem',\n",
       " 99156: 'Newport',\n",
       " 99157: 'Northport',\n",
       " 99158: 'Oakesdale',\n",
       " 99159: 'Odessa',\n",
       " 99160: 'Orient',\n",
       " 99161: 'Palouse',\n",
       " 99163: 'Pullman',\n",
       " 99164: 'Pullman',\n",
       " 99165: 'Pullman',\n",
       " 99166: 'Republic',\n",
       " 99167: 'Rice',\n",
       " 99169: 'Ritzville',\n",
       " 99170: 'Rosalia',\n",
       " 99171: 'Saint John',\n",
       " 99173: 'Springdale',\n",
       " 99174: 'Steptoe',\n",
       " 99176: 'Thornton',\n",
       " 99179: 'Uniontown',\n",
       " 99180: 'Usk',\n",
       " 99181: 'Valley',\n",
       " 99185: 'Wilbur',\n",
       " 99201: 'Spokane',\n",
       " 99202: 'Spokane',\n",
       " 99203: 'Spokane',\n",
       " 99204: 'Spokane',\n",
       " 99205: 'Spokane',\n",
       " 99206: 'Spokane',\n",
       " 99207: 'Spokane',\n",
       " 99208: 'Spokane',\n",
       " 99209: 'Spokane',\n",
       " 99210: 'Spokane',\n",
       " 99211: 'Spokane',\n",
       " 99212: 'Spokane',\n",
       " 99213: 'Spokane',\n",
       " 99214: 'Spokane',\n",
       " 99215: 'Spokane',\n",
       " 99216: 'Spokane',\n",
       " 99217: 'Spokane',\n",
       " 99218: 'Spokane',\n",
       " 99219: 'Spokane',\n",
       " 99220: 'Spokane',\n",
       " 99223: 'Spokane',\n",
       " 99224: 'Spokane',\n",
       " 99228: 'Spokane',\n",
       " 99251: 'Spokane',\n",
       " 99252: 'Spokane',\n",
       " 99256: 'Spokane',\n",
       " 99258: 'Spokane',\n",
       " 99260: 'Spokane',\n",
       " 99299: 'Spokane',\n",
       " 99301: 'Pasco',\n",
       " 99302: 'Pasco',\n",
       " 99320: 'Benton City',\n",
       " 99321: 'Beverly',\n",
       " 99322: 'Bickleton',\n",
       " 99323: 'Burbank',\n",
       " 99324: 'College Place',\n",
       " 99326: 'Connell',\n",
       " 99328: 'Dayton',\n",
       " 99329: 'Dixie',\n",
       " 99330: 'Eltopia',\n",
       " 99333: 'Hooper',\n",
       " 99335: 'Kahlotus',\n",
       " 99336: 'Kennewick',\n",
       " 99337: 'Kennewick',\n",
       " 99338: 'Kennewick',\n",
       " 99341: 'Lind',\n",
       " 99343: 'Mesa',\n",
       " 99344: 'Othello',\n",
       " 99345: 'Paterson',\n",
       " 99346: 'Plymouth',\n",
       " 99347: 'Pomeroy',\n",
       " 99348: 'Prescott',\n",
       " 99349: 'Mattawa',\n",
       " 99350: 'Prosser',\n",
       " 99352: 'Richland',\n",
       " 99353: 'West Richland',\n",
       " 99354: 'Richland',\n",
       " 99356: 'Roosevelt',\n",
       " 99357: 'Royal City',\n",
       " 99359: 'Starbuck',\n",
       " 99360: 'Touchet',\n",
       " 99361: 'Waitsburg',\n",
       " 99362: 'Walla Walla',\n",
       " 99363: 'Wallula',\n",
       " 99371: 'Washtucna',\n",
       " 99401: 'Anatone',\n",
       " 99402: 'Asotin',\n",
       " 99403: 'Clarkston'}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# taking a look at the dictionary containing the zipcodes and their cities\n",
    "zipcode_dic"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Preparation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Cleaning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To clean data, we first checked duplicated values, common range of some values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 267 duplicated houses.\n"
     ]
    }
   ],
   "source": [
    "# check how many houses have duplicate sales in 2014 and 2015.\n",
    "duplicated_val = sum(df.duplicated(subset=['bedrooms', 'bathrooms', 'sqft_living', 'yr_built', 'sqft_lot']))\n",
    "print(\"There are \" + str(duplicated_val) + \" duplicated houses.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "97.55% of houses which sold in 2014, 2015 are between 2 and 5 bedrooms house\n"
     ]
    }
   ],
   "source": [
    "# find the amount of bedrooms most common among the houses sold in 2014 and 2015\n",
    "df.groupby(['bedrooms']).count()\n",
    "bedrooms_2_5 = round(df[(df.bedrooms<=5) & (df.bedrooms>=2)].price.count() / len(df) * 100, 2)\n",
    "print(str(bedrooms_2_5) + \"% of houses which sold in 2014, 2015 are between 2 and 5 bedrooms house\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "98.42% of houses which sold in 2014, 2015 are between 1 and 4 bathrooms house\n"
     ]
    }
   ],
   "source": [
    "# find the amount of bathrooms most common among the houses sold in 2014 and 2015\n",
    "df.groupby(['bathrooms']).count()\n",
    "bathrooms_1_4 = round(df[(df.bathrooms<=4) & (df.bathrooms>=1)].price.count() / len(df) * 100, 2)\n",
    "print(str(bathrooms_1_4) + \"% of houses which sold in 2014, 2015 are between 1 and 4 bathrooms house\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "744 houses are renovated\n"
     ]
    }
   ],
   "source": [
    "# find the number of renovated houses\n",
    "renovated = len(df[df.yr_renovated > 0])\n",
    "print(str(renovated) + \" houses are renovated\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# compare by using barplot\n",
    "Total_house = [len(df), len(df), len(df), len(df)]\n",
    "result = [duplicated_val, len(df[df.yr_renovated > 0]), df[(df.bedrooms<=5) & (df.bedrooms>=2)].price.count(), df[(df.bathrooms<=4) & (df.bathrooms>=1)].price.count()]\n",
    "x_ticks = [\"Duplicated\", \"Renovated\", \"2-5 Bedrooms\", \"1-4 Bathrooms\"]\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(12,12))\n",
    "\n",
    "ax = sns.barplot(x=x_ticks, y=Total_house, color='b', label=\"Total Houses\")\n",
    "ax = sns.barplot(x=x_ticks, y=result, color='r', label=\"Matched Number of Houses\")\n",
    "ax.set(ylabel=\"Number of Houses\", title = 'Barplot showing the amount of houses that are duplicated, renovated, have 2-5 bedrooms and 1-4 bedrooms')\n",
    "ax.legend()\n",
    "plt.show()\n",
    "fig.savefig('./images/data_cleaning.png');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# drop duplicate data entries\n",
    "df.drop_duplicates(subset=['bedrooms', 'bathrooms', 'sqft_living', 'sqft_lot', 'yr_built'], inplace = True)\n",
    "\n",
    "# subset houses which have 2-5 bedrooms, 1-4 bathrooms\n",
    "df = df[(df.bedrooms<=5) & (df.bedrooms>=2)]\n",
    "df = df[(df.bathrooms<=4) & (df.bathrooms>=1)]\n",
    "\n",
    "# drop nan values from yr_renovated, waterfront columns\n",
    "df.dropna(subset=['yr_renovated', 'waterfront'], inplace=True)\n",
    "\n",
    "# drop id, lat, long, sqft_living15, sqft_lot15, view, sqft_basement, sqft_above, sqft_lot, \n",
    "#which we are not going to use for our model\n",
    "df.drop(['id', 'lat', 'long', 'sqft_living15', 'sqft_lot15', 'view', 'sqft_basement', 'sqft_above'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# make year, month columns\n",
    "df['year'] = pd.DatetimeIndex(df['date']).year\n",
    "df['month'] = pd.DatetimeIndex(df['date']).month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# calculated amount of year between year renovated and year sold and put in a new column\n",
    "df['yr_from_renovated'] = df.year - df.yr_renovated"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x1152 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create regression plots to check the relationship between price and other variables\n",
    "fig, axes = plt.subplots(3, 3, figsize=(16,16))\n",
    "ax1 = axes[0][0]\n",
    "ax2 = axes[0][1]\n",
    "ax3 = axes[0][2]\n",
    "ax4 = axes[1][0]\n",
    "ax5 = axes[1][1]\n",
    "ax6 = axes[1][2]\n",
    "ax7 = axes[2][0]\n",
    "ax8 = axes[2][1]\n",
    "ax9 = axes[2][2]\n",
    "\n",
    "X = df.drop('price', axis = 1)\n",
    "y = df['price']\n",
    "sns.regplot(x=X['sqft_living'], y=y,line_kws={\"color\": \"red\"}, ax=ax1)\n",
    "sns.regplot(x=X['bedrooms'], y=y, line_kws={\"color\": \"red\"}, ax=ax2)\n",
    "sns.regplot(x=X['bathrooms'], y=y, line_kws={\"color\": \"red\"}, ax=ax3)\n",
    "sns.regplot(x=X['sqft_lot'], y=y, line_kws={\"color\": \"red\"}, ax=ax4)\n",
    "sns.regplot(x=X['floors'], y=y, line_kws={\"color\": \"red\"}, ax=ax5)\n",
    "sns.regplot(x=X['waterfront'], y=y, line_kws={\"color\": \"red\"}, ax=ax6)\n",
    "sns.regplot(x=X['condition'], y=y, line_kws={\"color\": \"red\"}, ax=ax7)\n",
    "sns.regplot(x=X['grade'], y=y, line_kws={\"color\": \"red\"}, ax=ax8)\n",
    "sns.regplot(x=X['yr_built'], y=y, line_kws={\"color\": \"red\"}, ax=ax9)\n",
    "fig.savefig('./images/regression_plots.png');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Feature Engineering"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cities"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We tried to use the city names instead of the zipcodes. Even though using zipcode as dummy variables can lead us to better fit model but they are so many, and we thought categorized cities can also explain the price differences between area. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# mapping cities' name by using zipcode and putting them in a new 'city' column\n",
    "df['city'] = df['zipcode'].map(zipcode_dic)\n",
    "\n",
    "# getting the top 5 and last five cities by price\n",
    "group_df2 = df.groupby(['city']).price.mean()\n",
    "high_price_cities = ['Sammamish', 'Bellevue', 'Medina', 'Mercer Island']\n",
    "low_price_cities = ['Auburn', 'Enumclaw', 'Federal Way', 'Kent', 'Maple Valley']\n",
    "\n",
    "# make dummy variables with categorized cities (high_price_cities,low_price_cities) by using average house prices\n",
    "def high_price_city(row):\n",
    "    if row['city'] in high_price_cities:\n",
    "        value = 1\n",
    "    else:\n",
    "        value = 0\n",
    "    return value\n",
    "\n",
    "def low_price_city(row):\n",
    "    if row['city'] in low_price_cities:\n",
    "        value = 1\n",
    "    else:\n",
    "        value = 0\n",
    "    return value\n",
    "\n",
    "df['high_price_cities'] = df.apply(high_price_city, axis=1)\n",
    "df['low_price_cities'] = df.apply(low_price_city, axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Years Between Date Sold and Date Renovated "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We made dummy variables for houses sold less than 20 years after renovation and those sold more than 20 years after renovation. Because some houses recently renovated will be priced higher than those not renovated, and also if it was sold more than 20 years after, then there will be no big differences compared to houses that were not renovated."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# make dummy variables of year between sale date and renovation date (less than 20 years and more than 20 years)\n",
    "def f_0_20(row):\n",
    "    if row['yr_renovated'] != 0:\n",
    "        if row['year'] - row['yr_renovated'] <= 20:\n",
    "            val = 1\n",
    "        else:\n",
    "            val = 0\n",
    "    else:\n",
    "        val = 0\n",
    "    return val\n",
    "\n",
    "\n",
    "def f_20_over(row):\n",
    "    if row['yr_renovated'] != 0:\n",
    "        if row['year'] - row['yr_renovated'] > 20:\n",
    "            val = 1\n",
    "        else:\n",
    "            val = 0\n",
    "    else:\n",
    "        val = 0\n",
    "    return val\n",
    "\n",
    "\n",
    "\n",
    "df['renov_0_20yr'] = df.apply(f_0_20, axis=1)\n",
    "df['renov_20yr_over'] = df.apply(f_20_over, axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Waterfront"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A house which located front of water is usually more expensive. The value of waterfront are 0 or 1 which means it already set as dummy variable so we just used it."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Relationships between Price and Dummy Variables"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are significant gaps depending on average price cities, years after renovation, and whether they have a waterfront or not."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Waterfront or not average house price\n",
    "avg_waterfront = df[df.waterfront == 1].price.mean()\n",
    "avg_not_waterfront = df[df.waterfront != 1].price.mean()\n",
    "average_price = df.price.mean()\n",
    "\n",
    "x1 = ['Waterfront', 'Not Waterfront']\n",
    "y1 = [avg_waterfront, avg_not_waterfront]\n",
    "\n",
    "# average price for houses that were renovated (less than 20 year, more than 20 years) and those that were not renovated\n",
    "avg_renov_0_20yr = df[df.renov_0_20yr == 1].price.mean()\n",
    "avg_renov_20yr_over = df[df.renov_20yr_over == 1].price.mean()\n",
    "avg_not_renov = df[(df.renov_0_20yr != 1) & (df.renov_20yr_over != 1)].price.mean()\n",
    "\n",
    "x2 = ['Renovation(0~20)', 'Renovation(20~)', 'No Renovation']\n",
    "y2 = [avg_renov_0_20yr, avg_renov_20yr_over, avg_not_renov]\n",
    "\n",
    "# High, middle, low average price cities' average house price\n",
    "avg_high_price_cities = df[df.high_price_cities == 1].price.mean()\n",
    "avg_low_price_cities = df[df.low_price_cities == 1].price.mean()\n",
    "avg_middle_price_cities = df[(df.high_price_cities != 1) & (df.low_price_cities != 1)].price.mean()\n",
    "\n",
    "x3 = ['High Price Cities', 'Middle Price Cities', 'Low Price Cities']\n",
    "y3 = [avg_high_price_cities, avg_middle_price_cities, avg_low_price_cities]\n",
    "\n",
    "\n",
    "# plotting the barplot\n",
    "fig, axs = plt.subplots(1,3, figsize=(20,4))\n",
    "\n",
    "axs[0].bar(x3, y3)\n",
    "axs[0].hlines(y=average_price,xmin=-0.5, xmax=2.5, color='r', linestyle='-', label=\"Average House Price\")\n",
    "axs[0].set_ylabel('Average Price')\n",
    "axs[0].legend()\n",
    "\n",
    "axs[1].bar(x2, y2)\n",
    "axs[1].hlines(y=average_price,xmin=-0.5, xmax=2.5, color='r', linestyle='-', label=\"Average House Price\")\n",
    "axs[1].set_ylabel('Average Price')\n",
    "axs[1].legend()\n",
    "\n",
    "axs[2].bar(x1, y1)\n",
    "axs[2].hlines(y=average_price,xmin=-0.5, xmax=1.5, color='r', linestyle='-', label=\"Average House Price\")\n",
    "axs[2].set_ylabel('Average Price')\n",
    "axs[2].legend()\n",
    "fig.savefig('./images/Price&dummy_variables.png');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Testing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We tested several models with different variables or squared variables, we removed some multicollinearity found best R-squared model. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['bedrooms_squared'] = df.bedrooms*df.bedrooms\n",
    "df['bathrooms_squared'] = df.bathrooms*df.bathrooms\n",
    "df['grade_squared'] = df.grade*df.grade"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>OLS Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>          <td>price</td>      <th>  R-squared:         </th>  <td>   0.695</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared:    </th>  <td>   0.695</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th>  <td>   3123.</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>             <td>Fri, 23 Apr 2021</td> <th>  Prob (F-statistic):</th>   <td>  0.00</td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                 <td>00:22:01</td>     <th>  Log-Likelihood:    </th> <td>-2.0356e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Observations:</th>      <td> 15071</td>      <th>  AIC:               </th>  <td>4.071e+05</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Residuals:</th>          <td> 15059</td>      <th>  BIC:               </th>  <td>4.072e+05</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Model:</th>              <td>    11</td>      <th>                     </th>      <td> </td>     \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>      <td>nonrobust</td>    <th>                     </th>      <td> </td>     \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "          <td></td>             <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th>         <td> 5.102e+06</td> <td> 1.36e+05</td> <td>   37.445</td> <td> 0.000</td> <td> 4.83e+06</td> <td> 5.37e+06</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>bedrooms</th>          <td>-3.454e+04</td> <td> 2327.884</td> <td>  -14.838</td> <td> 0.000</td> <td>-3.91e+04</td> <td>   -3e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>bathrooms_squared</th> <td> 1.364e+04</td> <td>  775.553</td> <td>   17.592</td> <td> 0.000</td> <td> 1.21e+04</td> <td> 1.52e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>sqft_living</th>       <td>  131.4079</td> <td>    3.391</td> <td>   38.748</td> <td> 0.000</td> <td>  124.760</td> <td>  138.055</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>waterfront</th>        <td> 6.504e+05</td> <td> 1.86e+04</td> <td>   35.026</td> <td> 0.000</td> <td> 6.14e+05</td> <td> 6.87e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>condition</th>         <td> 2.524e+04</td> <td> 2472.375</td> <td>   10.210</td> <td> 0.000</td> <td> 2.04e+04</td> <td> 3.01e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>grade_squared</th>     <td> 7258.7638</td> <td>  133.503</td> <td>   54.372</td> <td> 0.000</td> <td> 6997.082</td> <td> 7520.446</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>yr_built</th>          <td>-2692.5769</td> <td>   68.311</td> <td>  -39.417</td> <td> 0.000</td> <td>-2826.474</td> <td>-2558.679</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>renov_0_20yr</th>      <td>  8.24e+04</td> <td> 9713.576</td> <td>    8.483</td> <td> 0.000</td> <td> 6.34e+04</td> <td> 1.01e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>renov_20yr_over</th>   <td>-1.142e+04</td> <td> 1.22e+04</td> <td>   -0.934</td> <td> 0.350</td> <td>-3.54e+04</td> <td> 1.26e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>high_price_cities</th> <td> 1.283e+05</td> <td> 4870.133</td> <td>   26.340</td> <td> 0.000</td> <td> 1.19e+05</td> <td> 1.38e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>low_price_cities</th>  <td>-1.582e+05</td> <td> 3998.069</td> <td>  -39.561</td> <td> 0.000</td> <td>-1.66e+05</td> <td> -1.5e+05</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Omnibus:</th>       <td>8572.319</td> <th>  Durbin-Watson:     </th>  <td>   1.964</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Omnibus):</th>  <td> 0.000</td>  <th>  Jarque-Bera (JB):  </th> <td>200718.008</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Skew:</th>           <td> 2.271</td>  <th>  Prob(JB):          </th>  <td>    0.00</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Kurtosis:</th>       <td>20.292</td>  <th>  Cond. No.          </th>  <td>2.74e+05</td> \n",
       "</tr>\n",
       "</table><br/><br/>Notes:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.<br/>[2] The condition number is large, 2.74e+05. This might indicate that there are<br/>strong multicollinearity or other numerical problems."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                            OLS Regression Results                            \n",
       "==============================================================================\n",
       "Dep. Variable:                  price   R-squared:                       0.695\n",
       "Model:                            OLS   Adj. R-squared:                  0.695\n",
       "Method:                 Least Squares   F-statistic:                     3123.\n",
       "Date:                Fri, 23 Apr 2021   Prob (F-statistic):               0.00\n",
       "Time:                        00:22:01   Log-Likelihood:            -2.0356e+05\n",
       "No. Observations:               15071   AIC:                         4.071e+05\n",
       "Df Residuals:                   15059   BIC:                         4.072e+05\n",
       "Df Model:                          11                                         \n",
       "Covariance Type:            nonrobust                                         \n",
       "=====================================================================================\n",
       "                        coef    std err          t      P>|t|      [0.025      0.975]\n",
       "-------------------------------------------------------------------------------------\n",
       "Intercept          5.102e+06   1.36e+05     37.445      0.000    4.83e+06    5.37e+06\n",
       "bedrooms          -3.454e+04   2327.884    -14.838      0.000   -3.91e+04      -3e+04\n",
       "bathrooms_squared  1.364e+04    775.553     17.592      0.000    1.21e+04    1.52e+04\n",
       "sqft_living         131.4079      3.391     38.748      0.000     124.760     138.055\n",
       "waterfront         6.504e+05   1.86e+04     35.026      0.000    6.14e+05    6.87e+05\n",
       "condition          2.524e+04   2472.375     10.210      0.000    2.04e+04    3.01e+04\n",
       "grade_squared      7258.7638    133.503     54.372      0.000    6997.082    7520.446\n",
       "yr_built          -2692.5769     68.311    -39.417      0.000   -2826.474   -2558.679\n",
       "renov_0_20yr        8.24e+04   9713.576      8.483      0.000    6.34e+04    1.01e+05\n",
       "renov_20yr_over   -1.142e+04   1.22e+04     -0.934      0.350   -3.54e+04    1.26e+04\n",
       "high_price_cities  1.283e+05   4870.133     26.340      0.000    1.19e+05    1.38e+05\n",
       "low_price_cities  -1.582e+05   3998.069    -39.561      0.000   -1.66e+05    -1.5e+05\n",
       "==============================================================================\n",
       "Omnibus:                     8572.319   Durbin-Watson:                   1.964\n",
       "Prob(Omnibus):                  0.000   Jarque-Bera (JB):           200718.008\n",
       "Skew:                           2.271   Prob(JB):                         0.00\n",
       "Kurtosis:                      20.292   Cond. No.                     2.74e+05\n",
       "==============================================================================\n",
       "\n",
       "Notes:\n",
       "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
       "[2] The condition number is large, 2.74e+05. This might indicate that there are\n",
       "strong multicollinearity or other numerical problems.\n",
       "\"\"\""
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr_model = ols(formula='price ~ bedrooms + bathrooms_squared + sqft_living + waterfront + condition + grade_squared + yr_built +renov_0_20yr + renov_20yr_over + high_price_cities + low_price_cities', data=df).fit()\n",
    "lr_model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# make predicted price column\n",
    "df['predicted_price'] = (5.102e+06) - (3.454e+04)*df.bedrooms + (1.364e+04)*df.bathrooms_squared + (131.4079)*df.sqft_living + (6.504e+05)*df.waterfront + (2.524e+04)*df.condition + (7258.7638)*df.grade_squared - (2692.5769)*df.yr_built + (8.24e+04)*df.renov_0_20yr - (1.142e+04)*df.renov_20yr_over + (1.283e+05)*df.high_price_cities - (1.582e+05)*df.low_price_cities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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MmDEUoDdvvpevfMVALUmaOLq7u1m0aFGry9AEtrP3UETclVJasrP97fIhSZIkZWCgliRJkjIwUEuSpElnIndpVWvtyXvHQC1JkiaVQqHAo48+aqjWbksp8eijj24bt3q0HOVDkiRNKnPmzGHNmjVs3Lix1aVoAioUCsyZM2e3jjFQS5KkSWXKlCnbZhCUxoJdPiRJkqQMDNSSJElSBgZqSZIkKQMDtSRJkpSBgVqSJEnKwEAtSZIkZWCgliRJkjIwUEuSJEkZGKglSZKkDAzUkiRJUgYGakmSJCkDA7UkSZKUgYFakiRJysBALUmSJGVgoJYkSZIyMFBLkiRJGRioJUmSpAzaWl2AxreUqhSLy7etL1q0iLY23zaSJElbmYw0olJpOZdcUmbWLCiVilxzDSxevLjVZUmSJI0bBmrtUqGwkBkzDNGSJEk7Yx9qSZIkKQMDtSRJkpSBgVqSJEnKwEAtSZIkZWCgliRJkjJoaqCOiPdGxP0RcV9EXBMRhYg4ICJ+HBEP1R9nNex/WUT0RMSDEXFyM2uTJEmS9oamBeqIOAx4D7AkpXQkkAfOBi4FbkopHQHcVF8nIrrqz78QOAX4YkTkm1WfJEmStDc0u8tHG9AeEW3AdGAtcBpwdf35q4HT68unAd9MKVVSSiuAHuDFTa5PkiRJyqRpgTql9FvgCmAVsA54IqV0I3BwSmldfZ91wEH1Qw4DVjecYk19myRJkjRuNW2mxHrf6NOA+cDjwLci4o9GOmQn29JOznsBcAHA4Ycfnr1QjVpKVXp7HyafH+qJ09nZSVubk21KkqR9WzPT0OuAFSmljQAR8R/A7wGPRMQhKaV1EXEIsKG+/xpgbsPxcxjqIrKdlNJVwFUAS5YseUbgVvOUyw9TufhimDWLnlIJli6lq6ur1WVJkiS1VDP7UK8CXhoR0yMigNcC3cANwLn1fc4FvlNfvgE4OyKmRcR84Ajg9ibWpz3wvEKBro4OFra3t7oUSZKkcaFpLdQppdsi4jrgbqAK/IqhluUZwLURcT5DofvM+v73R8S1wLL6/u9KKQ02qz5JkiRpb2hqB9iU0oeBD++wucJQa/XO9r8cuLyZNUmSJEl7kzMlSpIkSRkYqCVJkqQMDNSSJElSBgZqSZIkKQMDtSRJkpSBgVqSJEnKwEAtSZIkZWCgliRJkjIwUEuSJEkZGKglSZKkDAzUkiRJUgYGakmSJCkDA7UkSZKUgYFakiRJysBALUmSJGVgoJYkSZIyaGt1AWqNarVKd3f3tvVFixbR1ubbQZIkaXeZoPZR3d3dnHNOkfb2Tvr7u/nYx4p0dnZSLBZJaeFunatarVIsFretd3Z2Gs4lSdI+w9SzD2tv72TGjMX09xe55JIys2bBpk0PUyjMYebM0Z+nWCzSc9ZZLGxvp6dUgqVL6erqal7hkiRJ44iBWgAUCgu3hes9sbC9na6Ojr1clSRJ0vjnTYmSJElSBgZqSZIkKQMDtSRJkpSBgVqSJEnKwEAtSZIkZWCgliRJkjIwUEuSJEkZGKglSZKkDAzUkiRJUgbOlKg9Uk2JlT09APT09LAgpRZXJEmS1BoGau2RleUy5QsvhFmzWLVpE4cWCjBjRqvLkiRJGnN2+dAeW1Ao0NXRweGFQqtLkSRJahkDtSRJkpSBgVqSJEnKwEAtSZIkZWCgliRJkjJwlA8Nq1arUqmsBrbQ1zeTcnk1qeDweJIkSY0M1BpWqVTknas/w5zcDKZsmMGtA49QmTu11WVJkiSNKwZqjWhObioLcu1MyXfwcBimJUmSdmQfakmSJCkDA7UkSZKUgYFakiRJysBALUmSJGVgoJYkSZIyMFBLkiRJGRioJUmSpAwM1JIkSVIGBmpJkiQpAwO1JEmSlIGBWpIkScrAQC1JkiRlYKCWJEmSMmhrdQGafKrVKvfee++29UWLFtHW5ltNkiRNTqYc7XXLly/nAx8YpL29k1KpyDXXwOLFi1tdliRJUlMYqNUU7e2dzJhhiJYkSZOffaglSZKkDAzUkiRJUgYGakmSJCkDA7UkSZKUgYFakiRJysBALUmSJGXgsHnaIyklypUKm/v6KJfLlIFaSq0uS5IkacwZqLVHKpUKq1cNUHgE1myBwdoA/bP6qabE6tWrKZUgIk+p1Eu1+txWlytJktQ0BmrtschNJZ/vIDdYIkj09/fzQKXC9L/7Oz70xAHk89NZWd3Eww9/mmOPPbbV5UqSJDVF0/pQR8TzI+Kehq8nI+KvI+KAiPhxRDxUf5zVcMxlEdETEQ9GxMnNqk17X6ptYXlvjTVroPC7xDymsSDfwdwotLo0SZKkpmpaoE4pPZhSOialdAzwIqAf+E/gUuCmlNIRwE31dSKiCzgbeCFwCvDFiMg3qz7tfblcO7lcgVxMbXUpkiRJY2asRvl4LdCbUnoYOA24ur79auD0+vJpwDdTSpWU0gqgB3jxGNUnSZIk7ZGxCtRnA9fUlw9OKa0DqD8eVN9+GLC64Zg19W2SJEnSuNX0QB0RU4FTgW/tatedbHvGOGwRcUFE3BkRd27cuHFvlChJkiTtsbFoof7/gLtTSo/U1x+JiEMA6o8b6tvXAHMbjpsDrN3xZCmlq1JKS1JKS2bPnt3EsiVJkqRdG4tAfQ5Pd/cAuAE4t758LvCdhu1nR8S0iJgPHAHcPgb1SZIkSXusqeNQR8R04PXAOxo2fxK4NiLOB1YBZwKklO6PiGuBZUAVeFdKabCZ9UmSJElZNTVQp5T6gWfvsO1Rhkb92Nn+lwOXN7MmSZIkaW8aq1E+JEmSpEnJQC1JkiRlYKCWJEmSMjBQS5IkSRkYqCVJkqQMmjrKh8aParVKd3f3tvVisUhKC1tYkSRJ0uRgoN5HdHd3c845RdrbOwHYtOlhCoU5zJzZ4sIkSZImOAP1PqS9vZMZMxYD0N9fHPPrV6tVisWnr9vZ2Ulbm29BSZI0sZlmNGaKxSI9Z53FwvZ2ekolWLqUrq6uVpclSZKUiYFaY2pheztdHR2tLkOSJGmvcZQPSZIkKQMDtSRJkpSBgVqSJEnKwEAtSZIkZWCg1m5IVAYG2NzXR6VSAVKrC5IkSWo5R/nQqNVqA6xfl3hgE6wvb2FOTG11SZIkSS1nC7V2Sy6mkc93EDGl1aVIkiSNCwZqSZIkKQO7fKglqimxsqdn27rTkEuSpInKBKOWWFkuU77wQpg1y2nIJUnShGagVsssKBSchlySJE149qGWJEmSMjBQS5IkSRkYqCVJkqQMDNSSJElSBgZqSZIkKQMDtSRJkpSBgVqSJEnKwEAtSZIkZWCgliRJkjIwUEuSJEkZGKglSZKkDAzUkiRJUgYGakmSJCkDA7UkSZKUgYFakiRJysBALUmSJGVgoJYkSZIyMFBLkiRJGRioJUmSpAwM1JIkSVIGBmpJkiQpAwO1JEmSlIGBWpIkScrAQC1JkiRlYKCWJEmSMjBQS5IkSRkYqCVJkqQMDNSSJElSBgZqSZIkKQMDtSRJkpSBgVqSJEnKwECtphpMidWrV7Ns2TJ6enqopdTqkiRJkvaqtlYXoMltXaow+4or4GtfY9WmTRxaKMCMGa0uS5Ikaa+xhVpNN3/qVLo6Oji8UGh1KZIkSXudgVqSJEnKwEAtSZIkZWCgliRJkjIwUEuSJEkZGKglSZKkDAzUkiRJUgYGakmSJCkDA7UkSZKUgYFakiRJysBALUmSJGXQ1EAdEftHxHUR8UBEdEfEyyLigIj4cUQ8VH+c1bD/ZRHRExEPRsTJzaxNkiRJ2hua3UL9WeCHKaUXAEcD3cClwE0ppSOAm+rrREQXcDbwQuAU4IsRkW9yfZIkSVImTQvUEbEfcALwLwAppYGU0uPAacDV9d2uBk6vL58GfDOlVEkprQB6gBc3qz5JkiRpb2hmC/UCYCPwrxHxq4j4ckR0AAenlNYB1B8Pqu9/GLC64fg19W3biYgLIuLOiLhz48aNTSx/35TSIOXyCvr6llEq9bS6HEmSpHGvrcnnPg54d0rptoj4LPXuHcOInWxLz9iQ0lXAVQBLlix5xvPKZmBgLe9c/Xnmb3g2d1Q3kWpbvHVVkiRpBM2MSmuANSml2+rr1zEUsB+JiEMA6o8bGvaf23D8HGBtE+vTMObkprEg38FzotDqUiRJksa9pgXqlNJ6YHVEPL++6bXAMuAG4Nz6tnOB79SXbwDOjohpETEfOAK4vVn1aawkKgMDbO7ro1wuUy6XqSX/sCBJkiaPZnb5AHg38I2ImAosB97OUIi/NiLOB1YBZwKklO6PiGsZCt1V4F0ppcEm16cmq9UGWL8u8cAmWLMFBmsD9M/qb3VZkiRJe01TA3VK6R5gyU6eeu0w+18OXN7MmjT2cjGNfL6D3GBppx3lJUmSJjJvN5MkSZIyMFBLkiRJGRioJUmSpAwM1JIkSVIGBmpJkiQpAwO1JEmSlIGBWpIkScrAQC1JkiRlYKCWJEmSMjBQS5IkSRkYqCVJkqQMDNSSJElSBgZqSZIkKQMDtSRJkpSBgVqSJEnKwEAtSZIkZWCgliRJkjIwUEuSJEkZGKglSZKkDAzUkiRJUgYGakmSJCkDA7UkSZKUgYFakiRJysBALUmSJGVgoJYkSZIyaGt1ARJAtVrl3nvv3W7bokWLaGvzLSpJksY304paJyU29/XRXyrx85/8hH/+58OYPv0FAJRKRa65BhYvXtziIiVJkkZmoFbLlCsVlq2AlQSf+cxa9tvvZcyYYYCWJEkTi4FaLZXLTycPTJ16aKtLkSRJ2iMGarXcYEoMDKwHVtDXNxOAlKr49pQkSROBiUUtt7ZW5t3r/425+RuYsmEGq2slvjzv48DzWl2aJEnSLhmoNcYS/f39lCsVKgMDFFICYE5MYUGunSn5jhbXJ0mStHsM1BpTqbaF5b1TWQNsGRxg5pRaq0uSJEnKxECtMZfLtZMjT6420OpSJEmSMnOmREmSJCkDA7UkSZKUgYFakiRJysBALUmSJGVgoJYkSZIyMFBLkiRJGThsnsadwZQol1fT2wv5fJ7Ozk7a2nyrSpKk8cmUonFnba3MO1dfwZwP7kcPwNKldHV1tbosSZKknTJQa1yak5vKC9rbmd7qQiRJknbBPtSSJElSBgZqSZIkKQMDtSRJkpSBgVqSJEnKwEAtSZIkZWCgliRJkjIwUEuSJEkZGKglSZKkDAzUkiRJUgYGakmSJCkDA7UkSZKUgYFakiRJysBALUmSJGVgoJYkSZIyMFBLkiRJGRioJUmSpAwM1JIkSVIGBmpJkiQpAwO1JEmSlMEuA3VE/FVE7BdD/iUi7o6Ik8aiOI2NlAYpl1fQ17eMgYH1QGp1SZIkSRNG2yj2+dOU0mcj4mRgNvB24F+BG5tamcbMwMBa3rn688zf8GxuLa8mRUerS5IkSZowRtPlI+qPbwD+NaX064ZtIx8YsTIi7o2IeyLizvq2AyLixxHxUP1xVsP+l0VET0Q8WA/wGiNzctNYkO/g4JjS6lIkSZImlNEE6rsi4kaGAvWPImImUNuNa7w6pXRMSmlJff1S4KaU0hHATfV1IqILOBt4IXAK8MWIyO/GdSRJkqQxN5pAfT5Doff4lFI/MJWhbh976jTg6vry1cDpDdu/mVKqpJRWAD3AizNcR5IkSWq60QTqBHQB76mvdwCFUZ4/ATdGxF0RcUF928EppXUA9ceD6tsPA1Y3HLumvm07EXFBRNwZEXdu3LhxlGVIkiRJzTGamxK/yFAXj9cAHwOeAr4NHD+KY1+eUlobEQcBP46IB0bYd2f9sp8x3ERK6SrgKoAlS5Y4HMUIqtUq3d3dABSLRVJa2OKKJEmSJp/RBOqXpJSOi4hfAaSUNkXE1NGcPKW0tv64ISL+k6EuHI9ExCEppXURcQiwob77GmBuw+FzgLWjfSF6pu7ubs45p0h7eyebNj1MoTCHmTNbXZUkSdLkMpouH1vqNwcmgIiYzShuSoyIjvoNjEREB3AScB9wA3Bufbdzge/Ul28Azo6IaRExHzgCuH03Xot2or29kxkzFjNt2nNbXYokSdKkNJoW6s8B/wkcFBGXA28BPjCK4w4G/jMitl7n31NKP4yIO4BrI+J8YBVwJkBK6f6IuBZYBlSBd6WUBnf3BUmSJEljaZeBOqX0jYi4C3gtQ/2cT08pdY/iuOXA0TvZ/mj9XDs75nLg8l2dW5IkSRovRjP1+POAFSmlLzDUZeP1EbF/swuTJEmSJoLR9KH+NjAYEQuBLwPzgX9valWSJEnSBDGaQF1LKVWBNwOfTSm9FzikuWVJkiRJE8NoR/k4B/gT4Lv1bVOaV5IkSZI0cYwmUL8deBlweUppRX1Iu683tyxJkiRpYhjNKB/LeHracVJKK4BPNrMoSZIkaaLYZaCOiBXsfArwBU2pSJIkSZpARjOxy5KG5QJDE7Ec0JxyJEmSpIlll32oU0qPNnz9NqX0f4HXNL80SZIkafwbTZeP4xpWcwy1WM9sWkWSJEnSBDKaLh9/37BcBVYCf9iUaiRJkqQJZjSjfLx6LAqRJEmSJqLRdPl4FvBh4IT6pp8BH0spPdHMwiSAakqs7OnZtt7Z2Ulb22j+sCJJkjQ2RpNMvgLcx9PdPP4Y+FeGpiKXmmpluUz5wgth1ix6SiVYupSurq5WlyVJkrTNaAL181JKf9Cw/tGIuKdJ9UjPsKBQoKujo9VlSJIk7dRoph4vRcQrtq5ExMuBUvNKkgAS/f39lMtlyuUytfSMuYUkSZLGhdG0UP8FcHW9L3UAjwHnNbMoKdW2sLx3KmuAwdoA/bP6W12SJEnSTo1mlI97gKMjYr/6+pPNLkoCyOXayZEnWl2IJEnSCIYN1BHxvmG2A5BS+kyTapIkSZImjJH6UM9s+Lpoh3VnSpQkSZIYoYU6pfTRrcsRcXrjuiRJkqQhoxnlA8AhFiRJkqSdGG2gliRJkrQTI92UeC9Pt0wvjIjfbH0KSCmlo5pdnCRJkjTejTRs3pvGrApJkiRpghrppsSHx7IQSZIkaSKyD7UkSZKUgYFakiRJymDYQB0RN9Uf/8/YlSNJkiRNLCPdlHhIRJwInBoR32RodI9tUkp3N7UySZIkaQIYKVB/CLgUmAN8ZofnEvCaZhUlSZIkTRQjjfJxHXBdRHwwpfTxMaxJkiRJmjBGaqEGIKX08Yg4FTihvunmlNJ3m1uWJEmSNDHscpSPiPg74K+AZfWvv6pvkyRJkvZ5u2yhBt4IHJNSqgFExNXAr4DLmlmYJEmSNBGMdhzq/RuWn9WEOiRJkqQJaTQt1H8H/CoifsrQ0HknYOu0JEmSBIzupsRrIuJm4HiGAvUlKaX1zS5MkiRJmghG00JNSmkdcEOTa5EkSZImnNH2oZYkSZK0EwZqSZIkKYMRA3VE5CLivrEqRpIkSZpoRgzU9bGnfx0Rh49RPZIkSdKEMpqbEg8B7o+I24G+rRtTSqc2rSpJkiRpghhNoP5o06uQJEmSJqjRjEP9s4h4LnBESum/I2I6kG9+aZIkSdL4t8tRPiLiz4HrgH+qbzoMuL6JNUmSJEkTxmiGzXsX8HLgSYCU0kPAQc0sSpIkSZooRhOoKymlga0rEdEGpOaVJEmSJE0cownUP4uIvwHaI+L1wLeA/2puWZIkSdLEMJpAfSmwEbgXeAfwfeADzSxKkiRJmihGM8pHLSKuBm5jqKvHgyklu3xIkiRJjCJQR8QbgSuBXiCA+RHxjpTSD5pdnCRJkjTejWZil78HXp1S6gGIiOcB3wMM1JIkSdrnjSZQb9gapuuWAxuaVI/GSEqDVCor6OubycDAehy4RZIkac8MG6gj4s31xfsj4vvAtQylrjOBO8agNjXRwMBa3rn688zf8GxuLa8mRUerS5IkSZqQRmqh/v2G5UeAE+vLG4FZTatIY2ZObhoL8h2siCmtLkWSJGnCGjZQp5TePpaFSJIkSRPRaEb5mA+8G5jXuH9K6dTmlSVJkiRNDKO5KfF64F8Ymh2x1tRqJEmSpAlmNIG6nFL6XNMrkSRJkiag0QTqz0bEh4EbgcrWjSmlu5tWlbSdRH9/P/0RrCkW6ezspK1tNG9dSZKk5htNKlkM/DHwGp7u8pHq61LTpdoWlvdOZVUuz99ctJLnPa+bxYsXt7osSZIkYHSB+gxgQUppoNnFSMPJ5drJ5/MUCvNaXYokSdJ2cqPY59fA/nt6gYjIR8SvIuK79fUDIuLHEfFQ/XFWw76XRURPRDwYESfv6TUlSZKksTKaQH0w8EBE/Cgibtj6tRvX+Cugu2H9UuCmlNIRwE31dSKiCzgbeCFwCvDFiMjvxnUkSZKkMTeaLh8f3tOTR8Qc4I3A5cD76ptPA15VX74auBm4pL79mymlCrAiInqAFwO/3NPrS5IkSc22y0CdUvpZhvP/X+B/AzMbth2cUlpXP/e6iDiovv0w4NaG/dbUt20nIi4ALgA4/PDDM5QmSZIkZbfLLh8R8VREPFn/KkfEYEQ8OYrj3gRsSCndNcpaYifb0jM2pHRVSmlJSmnJ7NmzR3lqSZIkqTlG00Ld2LpMRJzOUFeMXXk5cGpEvAEoAPtFxNeBRyLikHrr9CHAhvr+a4C5DcfPAdaO4joahZQGqVRW0Nc39M85MLCenfy+IkmSpN2027NjpJSuj4hLR7HfZcBlABHxKuCilNIfRcSngXOBT9Yfv1M/5Abg3yPiM8ChwBHA7btbn3ZuYGAt71z9eeZveDYAt5ZXk6KjxVVJkiRNfLsM1BHx5obVHLCEbE2bnwSujYjzgVXAmQAppfsj4lpgGVAF3pVSGsxwHe1gTm4aC/JDIXpFTGlxNZIkSZPDaFqof79huQqsZGhEjlFLKd3M0GgepJQeBV47zH6XMzQiiCRJkjQhjKYP9dvHohBJkiRpIho2UEfEh0Y4LqWUPt6EeiRJkqQJZaQW6r6dbOsAzgeeDRioJUmStM8bNlCnlP5+63JEzGRoCvG3A98E/n644yRJkqR9yYh9qCPiAIamDH8bQ9OEH5dS2jQWhUmSJEkTwUh9qD8NvBm4ClicUto8ZlVJkiRJE8RIU49fyNAEKx8A1jZMP/7UaKYelyRJkvYFI/WhHilsS5IkSWLkFmpJkiRJu2CgliRJkjIwUEuSJEkZ7HLqcWk8SWmQYrG43bZFixbR1uZbWZIktYYpRBNKpbKaSy6ZzaxZQ+ulUpFrroHFixe3tjBJkrTPMlBrwikUFjJjhgFakiSND/ahliRJkjIwUEuSJEkZGKglSZKkDAzUkiRJUgYGak0YgykxMLCecnkFfX3LqNWqrS5JkiTJUT40caytlXn3+n9jbv4G1q/P8+9dS1tdkiRJkoFaE8ucmMKCXDtTcvlWlyJJkgTY5UOSJEnKxEAtSZIkZWCgliRJkjIwUEuSJEkZGKglSZKkDBzlQxPSYEqUSj2kVKO3F/L5PJ2dnbS1+ZaWJEljy/ShCWltrcx5vRcyNwrM+SD0ACxdSldXV6tLkyRJ+xgDtSasuVFgQb6dF7TD9FYXI0mS9ln2oZYkSZIyMFBLkiRJGdjlY5KpVqsUi0UAisUi/f0QkWdgYD2QWlucJEnSJGSgnmSKxSI9Z53FwvZ2Vj7yCG9fD/OnHcyt5dWk6Gh1eU1TTYmVPT3b1h3xQ5IkjRUTxyS0sL2dro4O7ps6lVoOFuQ7WBFTWl1WU60slylfeCHMmkVPqeSIH5IkacwYqDVpLCgU6OqYvK3wkiRpfPKmREmSJCkDW6g1qTXepAn2rZYkSXufyUKTWuNNmvatliRJzWCg1qS39SZNSZKkZrAPtSRJkpSBgVqSJEnKwEAtSZIkZWCgliRJkjLwpkRNbCnR31+iXKlQBmoptboiSZK0jzFQa0Kr1Uos762xBhisDdA/q7/VJUmSpH2MgVoTXi7XTo480epCJEnSPsk+1JIkSVIGBmpJkiQpA7t8aNKppsTKnh4Aenp6WOCNipIkqYkM1Jp0VpbLlC+8EGbNYtWmTRxaKMCMGa0uS5IkTVJ2+ZhEqtUqxWKR/lKJzX19VCoVYN9snV1QKNDV0cHhhUKrS5EkSZOcgXoS6e7u5qKLVrJ8OTzwAKxfv4VUa3VVkiRJk5uBepIpFOaRz7eTz3cQMaXV5UiSJE16BmpJkiQpAwO1JEmSlIGBWpIkScrAYfM0adVSolwuUwY29/VRS8nfICVJ0l5noNak1d/fz6pVFWq5aUxd209uQTC91UVJkqRJxwY7TWq53DRyuQK5vFFakiQ1h4FakiRJysBALUmSJGVgoJYkSZIyMFBLkiRJGRioJUmSpAyaFqgjohARt0fEryPi/oj4aH37ARHx44h4qP44q+GYyyKiJyIejIiTm1WbJEmStLc0s4W6ArwmpXQ0cAxwSkS8FLgUuCmldARwU32diOgCzgZeCJwCfDEi8k2sT5IkScqsaYE6DdlcX51S/0rAacDV9e1XA6fXl08DvplSqqSUVgA9wIubVZ8mo0R/f//Q7IjlMv39/Qy95SRJkpqnqTMl1luY7wIWAl9IKd0WEQenlNYBpJTWRcRB9d0PA25tOHxNfduO57wAuADg8MMPb2b5mmBSbQvLe6eyBqgBbZSp1ZJ3CkiSpKZqatRIKQ2mlI4B5gAvjogjR9g9dnaKnZzzqpTSkpTSktmzZ++lSjVZ5HLtQzMj1r8kSZKabUza7lJKjwM3M9Q3+pGIOASg/rihvtsaYG7DYXOAtWNRnyRJkrSnmjnKx+yI2L++3A68DngAuAE4t77bucB36ss3AGdHxLSImA8cAdzerPokSZKkvaGZfagPAa6u96POAdemlL4bEb8Ero2I84FVwJkAKaX7I+JaYBlQBd6VUhpsYn2SJElSZk0L1Cml3wDH7mT7o8BrhznmcuDyZtUkSZIk7W2OfyBJkiRlYKCWJEmSMjBQS5IkSRkYqCVJkqQMDNSSJElSBgZqSZIkKQMDtSRJkpSBgVqSJEnKwEAtSZIkZWCgliRJkjIwUEuSJEkZGKglSZKkDAzUkiRJUgZtrS5AGhMpUSqVWFMsMjg4yKJFi2hr8+0vSZKys4Va+4RarcSa1YkPfADOOadId3d3q0uSJEmThE102mfUYioROVKC3t5e8vk8nZ2dtlRLkqRMTBLaZ6xLA5zXeyFzo8CcD8KDKdHziU+wcOFCAMO1JEnaI6YH7VPmRoEF+XZe0A5rSyXKF14Is2bRUyrB0qV0dXW1ukRJkjTBGKi1T1tQKNDV0dHqMiRJ0gTmTYmSJElSBrZQa9+TEv39JcqVCmVgc18ftZT87VKSJO0RA7X2ObVaieW9NdYANWDq2n5yC4LprS5MkiRNSAZq7ZNyuXZy5MkBuXw7UGp1SZIkaYLyr9ySJElSBgZqSZIkKQMDtSRJkpSBgVqSJEnKwEAtSZIkZWCgliRJkjIwUEuSJEkZGKglSZKkDAzUkiRJUgYGakmSJCkDA7UkSZKUgYFakiRJysBALUmSJGVgoJYkSZIyMFBLkiRJGRioJUmSpAwM1JIkSVIGBmpJkiQpAwO1JEmSlIGBWpIkScqgrdUFKLtqtUqxWKS3t5dyeTWk1OqSJEmS9hkG6kmgWCzSc9ZZzAHOWPMkg/n9gBmtLkuSJGmfYKCeJBa2t3M4cEiUW12KJEnSPsU+1JIkSVIGtlBLKVEqlVhTLDI4OMiiRYtoa/O/hiRJGh1bqLXPq9VKPLyqxkUXreaMM27iu9/9LtVqtdVlSZKkCcJmOAlYH8FfrP0cc6NA5eIyxc5Ourq6Wl2WJEmaAAzUUt3cKLAg3w6FVlciSZImErt8SJIkSRkYqCVJkqQMDNSSJElSBgZqSZIkKQMDtSRJkpSBgVqSJEnKwEAtSZIkZWCgliRJkjIwUEuSJEkZOFOi1CglSqUSa4pFBgcHWbRoEW1t/jeRJEnDs4VaalCrlVizOvGBD8A55xTp7u5udUmSJGmcs+lN2kHkpjF9eicpDba6FEmSNAHYQi1JkiRl0LRAHRFzI+KnEdEdEfdHxF/Vtx8QET+OiIfqj7MajrksInoi4sGIOLlZtUmSJEl7SzNbqKvAhSmlRcBLgXdFRBdwKXBTSukI4Kb6OvXnzgZeCJwCfDEi8k2sT5IkScqsaYE6pbQupXR3ffkpoBs4DDgNuLq+29XA6fXl04BvppQqKaUVQA/w4mbVN1lUq1WKxSL9pRL9/f1AanVJkiRJ+5Qx6UMdEfOAY4HbgINTSutgKHQDB9V3OwxY3XDYmvq2Hc91QUTcGRF3bty4sal1TwTd3d1cdNFKli+H5b1lajUDtSRJ0lhqeqCOiBnAt4G/Tik9OdKuO9n2jHSYUroqpbQkpbRk9uzZe6vMCa1QmEc+304uV2h1KZIkSfucpgbqiJjCUJj+RkrpP+qbH4mIQ+rPHwJsqG9fA8xtOHwOsLaZ9UmSJElZNXOUjwD+BehOKX2m4akbgHPry+cC32nYfnZETIuI+cARwO3Nqk+SJEnaG5o5scvLgT8G7o2Ie+rb/gb4JHBtRJwPrALOBEgp3R8R1wLLGBoh5F3JmTUkSZI0zjUtUKeUfs7O+0UDvHaYYy4HLm9WTZIkSdLe5kyJkiRJUgYGakmSJCkDA7UkSZKUgYFakiRJysBALUmSJGVgoJYkSZIyMFBLkiRJGRioJUmSpAwM1JIkSVIGBmpJkiQpAwO1JEmSlIGBWpIkScrAQC1JkiRlYKCWJEmSMjBQS5IkSRm0tboAabxKqUqxuHy7bYsWLaKtzf82kiTpaSYDaQeDKVEq9VAqLee97x3goIMWENFGqVTkmmtg8eLFrS5RkiSNIwZqaQfr0gDn9V7IYSmxppa49jlvoqOjq9VlSZKkccpALe3E3CgwLxJQa3UpkiRpnDNQT0DVapVisQhAb28v5fJqSKnFVUmSJO2bDNQTULFYpOess1jY3s6cUokz1jzJYH6/VpclSZK0TzJQT1AL29vp6uhgM3BIlFtdzqS19QZFgFKpl95eR/qQJEnbMxVII9h6g+K8tlkMDpaoXFym2NlJV5c3KUqSpCEGamkX5kaBBfkOBgEKra5GkiSNN86UKEmSJGVgoJYkSZIysMuHNFopUSqVWFMsMjg46M2JkiQJsIVaGrVarcSa1YkPfADOOadId3d3q0uSJEnjgIFa2g21mEpEDsjT29tLtVptdUmSJKnF/Hu1tBu2DqM3NwoOoSdJkgADtbTbhobRa3cIPUmSBNjlQ5IkScrEQC1JkiRlYKCWJEmSMjBQS5IkSRkYqCVJkqQMDNSSJElSBgZqSZIkKQMDtSRJkpSBE7tIe6iaEj09PdvWOzs7aWvzv5QkSfsaP/2lPbSqUoELL4RZs+gplWDpUqchlyRpH2SgljJYUCjQ1dGx3bZqtUqxWNxum63XkiRNXn7CS3tZsVik56yzWNjeDmDrtSRJk5yBWmqChe3tz2i5liRJk5OjfEiSJEkZGKglSZKkDAzUkiRJUgYGakmSJCkDA7UkSZKUgYFakiRJysBALUmSJGXgONTSnkiJSqVCGdjc18dArcaqnh4Aenp6WJBSa+uTJEljxkAt7YFarcT69YkpeZi6tp+Vh1bgwgth1ixWbdrEoYUCzJjR6jIlSdIYsMuHtIcippLLFcjl2qlUKhwKHA4cBGALtSRJ+wxbqKWMGlurC4/AqkqFQw9vdVWSJGms2EIt7QVbW6vz+Q5yuWmtLkeSJI0hA7UkSZKUgV0+pL0uURnYwua+PgBqKfmbqyRJk5iBWtrLarUB1q9LPLAJaoP95BYE01tdlCRJahoDtdQEuZhGPt9RXytt216tVikWi9vWOzs7aWvzv6EkSROZn+TSGCoWi/ScdRYL29vpKZVg6VK6urpaXZYkScrAQC2NsYXt7XR1dOx6R0mSNCF4r5QkSZKUgYFakiRJyqBpgToivhIRGyLivoZtB0TEjyPiofrjrIbnLouInoh4MCJOblZd0lirpkRPTw/Lli2jp6eHmtOSS5I0qTSzhfqrwCk7bLsUuCmldARwU32diOgCzgZeWD/mixGRb2Jt0phZValQvvBCOO88Vl14IeVyudUlSZKkvahpgTqldAvw2A6bTwOuri9fDZzesP2bKaVKSmkF0AO8uFm1SWNtQaFAV0cHhxcKrS5FkiTtZWPdh/rglNI6gPrjQfXthwGrG/ZbU9/2DBFxQUTcGRF3bty4sanFSpIkSbsyXobNi51s22lH05TSVcBVAEuWLLEzqiaFHSd8ASd9kSRpohjrT+tHIuKQlNK6iDgE2FDfvgaY27DfHGDtGNc2rjUGrp6eHhZ4Y9vEkBKVSoUysLmvj5QSxDN/f2yc8AVw0hdJkiaQsQ7UNwDnAp+sP36nYfu/R8RngEOBI4Dbx7i2ca0xcK3atIlDCwWYMaPVZWkXarUS69cnpuRh6tp+KodWYJh+1E74IknSxNS0QB0R1wCvAg6MiDXAhxkK0tdGxPnAKuBMgJTS/RFxLbAMqALvSikNNqu2iWpr4OoplVpdinZDxFRyuQK5fDtQaXU5kiRpL2taoE4pnTPMU68dZv/LgcubVY8kSZLUDM6UKEmSJGVgoJYkSZIyMFBLkiRJGRioJUmSpAycNWICSilRrlTY3NdHf38/w8yBI0mSpDFgoJ6AKpUKq1cNUHgEqlvK1GrJvzVMQNWUWNnTAzhZjyRJE5mBeoKK3FTy+Q5qg/1Qc1zqCWGHWRMfePxx0oUXwqxZTtYjSdIEZqCWxkjjrImFR2BVpcJLD5/mZD2SJE1wdhSQxtDWWRPz+Q5yuWmtLkeSJO0FBmpJkiQpA7t8SONQ4w2LAJ2dnbS1+d9VkqTxyE9oaRxaWS5Trt+w2FMqwdKldHV1tbosSZK0EwZqaZxaUCjQ1dHR6jIkSdIu2IdakiRJysBALUmSJGVgoJYkSZIyMFBLkiRJGRioJUmSpAwc5UNqmURlYAub+/ool8swbeczJzomtSRJ45ufylKL1GoDrF+XeGATrKpUOPTwne/nmNSSJI1vBmqphXIxjXy+g1xu563TWzkmtSRJ45d9qCVJkqQMDNSSJElSBnb5kCYQb1CUJGn88ZNYmkC8QVGSpPHHQC1NMN6gKEnS+GKgliaoHbt/gF1AJElqBT95pQmqsfsHYBcQSZJaxEAtTWCN3T+qKdHjDYuSJI05P22lSWKkGxar1Srd3d3b9l20aJFhW5KkvcRPVGmcqaVEuVymDGzu66NcLsO0kWdS3Gq4Gxa7u7s555wi7e2dlEpFrrkGFi9evJcrlyRp32SglsaZ/v5+Vq2qUMtNo/AIrKpUOPTwoedSSpQrlW1Bu8xQAM9FDHu+arVKb28vkCciT6GwYExehyRJ+woD9ThWrVYpFosA9PT0sCClFleksZLLTSOXK5DPd5DLPd06XalUWL1qgMIjsGYLDNYG6J/Vz4wdWqUbRwDp6emhcvHFfGhtgbUBX573ceB5Y/lyJEma1AzU41ixWKTnrLNY2N7Oqk2bOLRQgBkzWl2WmiJRGdjC5r4++vv7geF/eYrc1KGgPVhiuHbpxv7UqzZt4higkG8nv8N+O/atBvtXS5K0u/zUHOcWtrfT1dExdJOZJq1abYD16xIPbILqljK1WoLc1mefDtuVSoUpTB3VObf2p+4plaBcBmAwJcrl1fT2Qj6fp1gs8v73DzB9+iIA+1dLkrQHDNTSOJGLaeTzHdQG+6H29C9QjWF7fXkLc2J0gXpn1tbKvHP1Fcz54H7Q3k5l0yZi2qeZMcMALUnSnjJQSxPA1rAdMWXYfXa8YXG4kUHm5KbygvZ2ZnR00F8qjdS7RJIkjYKBWpokGm9YbBwZZE85drUkSaPjp2OLNY7ksZUz3GlPbbthMTe6catH4tjVkiSNjqmtxRpH8gB4sL+fnk98goULFzpUnlquvb3T/tWSJO2CgXoc2DqSB0BPqbTdcGeHFgrUOjq2mzlvd0Z6kCRJUnMZqMeh7YY745kz52Ud6UGSJEl7T27Xu2g8aJw5b6SRHiRJkjS2DNSSJElSBnb5aIHGkT288VCSJGliM1C3QOPIHltvPGTGjFaXpX1QtT4VeV/fMgBSqpLlx8KOY1eD41dLkiY/P+VaZOvIHltvPJRaYVWlwjtXX8H8DV9jda3El+d9HHjeLo8bbtKXxrGrAcevliTtEwzU0j4n0d/fDwzNrjgnN5UF+Y7t9qhWq/T29lIqQUT+GS3XI0360syxq529UZI0HvlJJO1jUm0Ly3un0jZl+yEYB1OiXF7JTTet5Oabb+ZZn/40H3p0P9ZG8M/P/QiNE3oWi0UKhYVjPumLszdKksYjA7U0oW3f2jzaCX9yufZnDMG4tlbmHas+xcGXtHN3VDmmtoV5U6aRz+WpVFZzySWzmTVraN9Nmx6mUJjDzJl7/QXtkrM3SpLGGwO1NIEN19oMicrAFjb39VEul6kMDFAYxWgyc2IKz2vbn0cYIJee3O65xhbp/v6nm6tTqlIsLgeGWq5TWrh3Xtxe4o2SkqRm8xNlnKqltG268f6UAIfW087trLW5Vhtg/brEA5tgzRbYMjjAzCm1ply/VFrOJZeUmTVr5JbrxmBbrVYBtgu1zQq53igpSWo2A/U41TjdeBtlarXkNDzaLbmYRj7fQW6wRK420NRrbW29bmy53lFjsN206afAwcyadRTQ/JBrNxFJUjMZqMexrdON50hQc3g9jT+1WpVKZTWwhc2b2ymXHyZiaDklKJeX09sLKSUeeughIE9EnqlT55DLPdeQK0maFAzUknZLY4h+7LFHeMfqzzA3N4N71m7h2dU+5ub35561W5gNzI0Ccz4It5TLPGtggA/9bj/WBvzjc86nUHhuq1+KJEl7hYFa0m4plYq8c/VnmJObwT2xhTkEC3LtrCfPwTGwbflQYEG+nRe0w1rgAKCQbyffpLoco1qS1Cp+2kga0WBKDAysB1bQ1zeTUqlnaDKYenCG3eufveP5tt4suCeq1SrLlg1Nm14sFnn/+weYPn3RqPtkjxTCDeiSpNHy00HSiNbWyrx7/b8xN38DUzbM4I7qJlJty+hukk2J/v4S5Upl29B9jef77bocX13wCVKqUSwOkupD+y1fvpznPve52wLscGH24YcfJvfBD7KwvZ3Kpk3EtE/vVr/skSaKcRIZSdJoGagl7dKcmMKCXDtT8h2sHiwx2lbpWq3E8t4aa9h+6L6t51vPAOf1XsjcKLDyfU8yOHUqCwoFeopP8IEjPkd7+/Po7+/mYx8r0tnZudNxrhe2t9PV0cGT/f2Uy6vp61tGqdRLb+9QEN+VkUYAcXQQSdJoGKglNVUu106O/LBD982NAgvy7TC1zIJCgRe0t7O8DaZP76Sjo4v+/uKoxrleVanwztVXMH/D1xgcLFG5uEyxc8+7k4zW3ugaYvcSSZrY/IktadwZTIlSqQegPqLIc5g+fdEzZmhcuXIlc0olNjM09fqc3FQW5DsYBCg0p7Ydw2+xWORDH6oxffoL9rhriN1LJGliM1CPkWq1SrE4FAZ6enpYMIppoKV91bpU4bzeC5nXNostWx7j4cEaX2+fTqWympTKPPVUO48//jP+z/9ZzaFPJsjvOPV68+w48+JQq/nLmTFjcX0a9qdD/9aW5sb//zD082BwcHBbK3SxWNxuavdW2Nut5E75Lmlf4k+2MVIsFuk56ywWtrezatMmDi0UYMaMVpcljQ8pUalUKAP9KQGJudHOgnwHWwb7WVMrcV7vhRyWEncNVnjOusK2Zabs/4yp10e+VJVicTnAdn2yG7fv+NyOGvtWN7aaN07D3tjSXCwWKf7hHzInAoBlTzzBx6a+l1mzXgeM3JVlrOztVvI9nfJ9uGBvQJc0nvmTqIme0SpdKNDV0UFPyVkPpUa1Won16xNT8tBGmVotPWMUkblRYF4k1tTSdss7lRKlUok1xSKDg4PUavPo6xsaXm/Tpp/w1389wLOelefJJ29j5sznMHPm9mF4aL89C7nDtTTPiaC2PJHLT2dK5QmYe8hOQ/lYagypI7WS72nr9Z7c1DlcsN/TgC5JY2HcBeqIOAX4LJAHvpxS+mSLSxq1Hf+s29PTQ+1v/obO6dNtlZZ2IWIquVyBHAlq2X7prNVKPLyqxkcuWs3AwGpgBe979KvMzU/n1vJqDmIKC554Disq67ly6nHbjps2bR4RW6eeyZFStX6+Mjfd9D/09vbS29tLX9/h2/Yrl1cSUaKvbyaVymqmTXsOsH2Ld29vL88ulWjPzRpqTc9Nbah1++nb+/sforc3Tz6fZ8GCBfUp24dUq0P1bG2x3Wr58qdb1ndUrVZpa2sjn89z2GGH0dbWtl1Xk639v0f6BWK4kLtj0G6sb6QW/h3r27FP+nDBvjGgD9e9ZrRGavEeL91f9qSOvXHMaI8brfFw061/4VCzjat3Ugx9Qn0BeD2wBrgjIm5IKS1rbWXbawzOjR8gjQEaYNWmTbzUVmmpJdZH8BdrP7eta8ihU/ZnQb6DFTGFwxi6ebEcUxgYWENf3zIqldUMDKzgz1cOBe+e8jq+8Jy/oqNjFhs3fpst//vrDEyZxbqB9bw92llQGArO2wL6hnpAn/spAPr7H+K9713JfvvlKZdX8/HVFZ7XViPP1slt1tSH+OvZbvr2AwcHmPPB/egBih//OB/4wGBDf+2fAgcza9ZR25YLhQ7OLf4lc2I6d0eVgxMcRgKmcHdUOXCwn8Nz+7E2n+M9B57B1KlHs//+XZTLD/Pkk7cxdepxHHjg0zd81mpV+vuL3HTTanp7e3nuc5/L8uXLG37ZyNPb28uiRYt20p+8sb7hA/qOLeNbQ/3QOUb3l4Htv7/L+cQnurcNkziaCXpGavEeqfvLaCcD2vGXi8bXONIvJY3nG+0vMsO9rtG24u9O6/9wr3Gk78XeuHF3tPbk33u051BrTJR/j/FW0YuBnpTScoCI+CZwGjCuAnWxWORHp57K3GnTuOOppzgAeN7Mmdzx1FO8aNo0qAdqgOXlMtP7+lhVLlOGEZeBbesA6wY3U6sNMEhifW0A6j+81tdKDDJAfuB3DFaf3PbcSPs1Lo/0XOPybwefpFLrh+rj5BkY1X6/jeqwxwy3347HjGa/30aVaoLBenAY7rmdfW8aj9nVfo3fz+G+13v736fxmJH2m8j/PqP9t8r6fX8O00gkUtrCquqTz9jvV4NPcvrav+OwjVcyOLiZZbUtVPMzGCTYmMrbnrt3y++oxdPDhtTSAIODQ78kp1SlRmJwsERKW+jru4ONGwts2vRD/vB33+PQjTNZNtjHqlTd9j1svO6ywT5qqUpiCoNRJaUtlEolShH86tZbKZefA/UJ24dmmKxSKnVsW4b2Uf/s2rLld8Bvefzxxzh1zac5sDbAI+lqvsfGekt+L+Xy7bzx4Y/Sd3GOmyP49sF/xMDABnK5gzhn07eYnRK/eecWVr///QwODlIuM2x9AwM/A9YBQy35N9001Fq/cuVKrrjiYaZNO4TNm+9l2rTF2/rANx634zGbNkGp1Auw3fd3bfVx3vOeszjggCrl8io+/emhccth6Of1xRc/RKFw+HbPNbZub7V1247PNa4Pd74dn3vyyduJmMXMmUfw5JO3Uygc3/jRsN21RjrfcPVtPWboezv869rZ6xzudY/muOFe466+F42vfzQ17ak9+fce7TnUGjv+e3znO+Ozq1ekcTTaRES8BTglpfRn9fU/Bl6SUvrLhn0uAC6orz4feHDMC83mQOB3rS5C44rvCTXy/aBGvh+0I98TrfPclNLsnT0x3lqoYyfbtkv8KaWrgKvGppy9LyLuTCktaXUdGj98T6iR7wc18v2gHfmeGJ9yu95lTK0B5jaszwHWtqgWSZIkaZfGW6C+AzgiIuZHxFTgbOCGFtckSZIkDWtcdflIKVUj4i+BHzF0l8tXUkr3t7isvW3CdldR0/ieUCPfD2rk+0E78j0xDo2rmxIlSZKkiWa8dfmQJEmSJhQDtSRJkpSBgXoMRcQpEfFgRPRExKWtrketExFfiYgNEXFfq2tR60XE3Ij4aUR0R8T9EfFXra5JrRURhYi4PSJ+XX9PfLTVNan1IiIfEb+KiO+2uhZtz0A9RhqmVf//gC7gnIjoam1VaqGvAqe0ugiNG1XgwpTSIuClwLv8+bDPqwCvSSkdDRwDnBIRL21tSRoH/gro3uVeGnMG6rGzbVr1lNIAsHVade2DUkq3AI+1ug6NDymldSmlu+vLTzH0gXlYa6tSK6Uhm+urU+pfjiKwD4uIOcAbgS+3uhY9k4F67BwGrG5YX4MfmJJ2EBHzgGOB21pcilqs/uf9e4ANwI9TSr4n9m3/F/jfQK3FdWgnDNRjZ5fTqkvat0XEDODbwF+nlJ5sdT1qrZTSYErpGIZmDX5xRBzZ4pLUIhHxJmBDSumuVteinTNQjx2nVZc0rIiYwlCY/kZK6T9aXY/Gj5TS48DNeN/FvuzlwKkRsZKhLqOviYivt7YkNTJQjx2nVZe0UxERwL8A3Smlz7S6HrVeRMyOiP3ry+3A64AHWlqUWialdFlKaU5KaR5D+eEnKaU/anFZamCgHiMppSqwdVr1buDaSTitukYpIq4Bfgk8PyLWRMT5ra5JLfVy4I8ZanW6p/71hlYXpZY6BPhpRPyGoQaZH6eUHCpNGqecelySJEnKwBZqSZIkKQMDtSRJkpSBgVqSJEnKwEAtSZIkZWCgliRJ0qQVEV+JiA0Rcd8o9//DiFgWEfdHxL+P6hhH+ZCkfUdEfAy4JaX0362uRZLGQkScAGwG/i2lNOKMoxFxBHAt8JqU0qaIOCiltGGX1zBQS9K+ISLyKaXBVtchSWMtIuYB390aqCPiecAXgNlAP/DnKaUHIuJTQDGl9OXdOb9dPiRpEoiIeRHxQERcHRG/iYjrImJ6RKyMiA9FxM+BMyPiqxHxlvoxx0fELyLi1xFxe0TMjIh8RHw6Iu6on+cdLX5pktQMVwHvTim9CLgI+GJ9eyfQGRH/ExG3RsQpozlZW5OKlCSNvecD56eU/icivgL8r/r2ckrpFQBbPxwiYiqwFDgrpXRHROwHlIDzgSdSSsdHxDTgfyLixpTSijF/NZLUBBExA/g94FsRsXXztPpjG3AE8CpgDvD/IuLIlNLjI53TQC1Jk8fqlNL/1Je/Drynvrx0J/s+H1iXUroDIKX0JEBEnAQctbUVG3gWQx8uBmpJk0UOeDyldMxOnlsD3JpS2gKsiIgHGfoZeMeuTihJmhx2vClm63rfTvaNney/dfu7U0rH1L/mp5Ru3JtFSlIr1RsQVkTEmQAx5Oj609cDr65vP5ChLiDLd3VOA7UkTR6HR8TL6svnAD8fYd8HgEMj4niAev/pNuBHwF9ExJT69s6I6Ghm0ZLUTBFxDfBL4PkRsSYizgfeBpwfEb8G7gdOq+/+I+DRiFgG/BS4OKX06C6v4SgfkjTx1e9g/z5wC0N9Ax8C/hhYBixJKf2uvt9XGbrT/bp6mP480M5Q/+nXMXS3+98Cv89Qa/VG4PSU0hNj+XokaSIxUEvSJLDjkFCSpLFjlw9JkiQpA1uoJUmSpAxsoZYkSZIyMFBLkiRJGRioJUmSpAwM1JIkSVIGBmpJkiQpg/8fUP7oFXArA2kAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# compare real price and predicted price by using histplot\n",
    "Total_house = [len(df), len(df), len(df), len(df)]\n",
    "result = [duplicated_val, len(df[df.yr_renovated > 0]), df[(df.bedrooms<=5) & (df.bedrooms>=2)].price.count(), df[(df.bathrooms<=4) & (df.bathrooms>=1)].price.count()]\n",
    "x_ticks = [\"Duplicated\", \"Renovated\", \"2-5 Bedrooms\", \"1-4 Bathrooms\"]\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(12,12))\n",
    "\n",
    "ax = sns.histplot(df.price, color='b', label=\"Real House Price\")\n",
    "ax = sns.histplot(df.predicted_price, color='r', label=\"Predicted House Price\")\n",
    "ax.set(ylabel=\"Number of Houses\")\n",
    "ax.legend()\n",
    "plt.show()\n",
    "fig.savefig('./images/Real_predicted_price.png');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train RMSE:  174598.4615113213\n",
      "Test RMSE:  189719.023194724\n"
     ]
    }
   ],
   "source": [
    "# train test\n",
    "price = df.price\n",
    "bedrooms = df.bedrooms\n",
    "bathrooms_squared = df.bathrooms_squared\n",
    "sqft_living = df.sqft_living\n",
    "waterfront = df.waterfront\n",
    "condition = df.condition\n",
    "grade_squared = df.grade_squared\n",
    "yr_built = df.yr_built\n",
    "renov_0_20yr = df.renov_0_20yr\n",
    "renov_20yr_over = df.renov_20yr_over\n",
    "high_price_cities = df.high_price_cities\n",
    "low_price_cities = df.low_price_cities\n",
    "\n",
    "data = pd.concat([price, bedrooms, bathrooms_squared, sqft_living, waterfront, condition, grade_squared, yr_built, renov_0_20yr, renov_20yr_over, high_price_cities, low_price_cities], axis=1)\n",
    "y = data[['price']]\n",
    "X = data.drop(['price'], axis=1)\n",
    "\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=1000)\n",
    "linreg = LinearRegression()\n",
    "linreg.fit(X_train, y_train)\n",
    "\n",
    "y_hat_train = linreg.predict(X_train)\n",
    "y_hat_test = linreg.predict(X_test)\n",
    "\n",
    "train_residuals = y_hat_train - y_train\n",
    "test_residuals = y_hat_test - y_test\n",
    "\n",
    "mse_train = np.sum((y_train-y_hat_train)**2)/len(y_train)\n",
    "mse_test = np.sum((y_test-y_hat_test)**2)/len(y_test)\n",
    "\n",
    "\n",
    "train_mse = mean_squared_error(y_train, y_hat_train)\n",
    "test_mse = mean_squared_error(y_test, y_hat_test)\n",
    "\n",
    "train_rmse = np.sqrt(train_mse)\n",
    "print('Train RMSE: ',train_rmse)\n",
    "\n",
    "test_rmse = np.sqrt(test_mse)\n",
    "print('Test RMSE: ',test_rmse)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "geo_env",
   "language": "python",
   "name": "geo_env"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}