real_estate_of_nyc_knn.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Housing - KNN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "from sklearn.linear_model import LinearRegression\n",
    "\n",
    "sns.set()\n",
    "\n",
    "pd.set_option('display.max_columns', 500)\n",
    "pd.set_option('display.max_rows', None)\n",
    "pd.set_option('display.max_colwidth', 250)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>borough</th>\n",
       "      <th>neighborhood</th>\n",
       "      <th>building_class</th>\n",
       "      <th>building_class_map</th>\n",
       "      <th>building_category</th>\n",
       "      <th>building_category_map</th>\n",
       "      <th>building_type</th>\n",
       "      <th>tax_class</th>\n",
       "      <th>tax_class_map</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>total_units</th>\n",
       "      <th>gross_square_feet</th>\n",
       "      <th>year_built</th>\n",
       "      <th>sale_date</th>\n",
       "      <th>sale_month</th>\n",
       "      <th>sale_year</th>\n",
       "      <th>sale_price</th>\n",
       "      <th>log_sale_price</th>\n",
       "      <th>log_gross_square_feet</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>BATH BEACH</td>\n",
       "      <td>A9</td>\n",
       "      <td>A</td>\n",
       "      <td>ONE FAMILY HOMES</td>\n",
       "      <td>FAMILY</td>\n",
       "      <td>RESIDENTIAL</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>11214</td>\n",
       "      <td>1</td>\n",
       "      <td>1492</td>\n",
       "      <td>1930</td>\n",
       "      <td>2013-06-06</td>\n",
       "      <td>6</td>\n",
       "      <td>2013</td>\n",
       "      <td>560000.0</td>\n",
       "      <td>13.235692</td>\n",
       "      <td>7.307873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>BATH BEACH</td>\n",
       "      <td>A1</td>\n",
       "      <td>A</td>\n",
       "      <td>ONE FAMILY HOMES</td>\n",
       "      <td>FAMILY</td>\n",
       "      <td>RESIDENTIAL</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>11214</td>\n",
       "      <td>1</td>\n",
       "      <td>1724</td>\n",
       "      <td>1930</td>\n",
       "      <td>2012-12-18</td>\n",
       "      <td>12</td>\n",
       "      <td>2012</td>\n",
       "      <td>860000.0</td>\n",
       "      <td>13.664688</td>\n",
       "      <td>7.452402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>BATH BEACH</td>\n",
       "      <td>A9</td>\n",
       "      <td>A</td>\n",
       "      <td>ONE FAMILY HOMES</td>\n",
       "      <td>FAMILY</td>\n",
       "      <td>RESIDENTIAL</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>11214</td>\n",
       "      <td>1</td>\n",
       "      <td>2132</td>\n",
       "      <td>1930</td>\n",
       "      <td>2012-08-24</td>\n",
       "      <td>8</td>\n",
       "      <td>2012</td>\n",
       "      <td>508000.0</td>\n",
       "      <td>13.138237</td>\n",
       "      <td>7.664816</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    borough neighborhood building_class building_class_map building_category  \\\n",
       "0  Brooklyn   BATH BEACH            A9                   A  ONE FAMILY HOMES   \n",
       "1  Brooklyn   BATH BEACH            A1                   A  ONE FAMILY HOMES   \n",
       "2  Brooklyn   BATH BEACH            A9                   A  ONE FAMILY HOMES   \n",
       "\n",
       "  building_category_map building_type tax_class tax_class_map zipcode  \\\n",
       "0                FAMILY   RESIDENTIAL         1            1    11214   \n",
       "1                FAMILY   RESIDENTIAL         1            1    11214   \n",
       "2                FAMILY   RESIDENTIAL         1            1    11214   \n",
       "\n",
       "   total_units  gross_square_feet year_built  sale_date  sale_month  \\\n",
       "0            1               1492       1930 2013-06-06           6   \n",
       "1            1               1724       1930 2012-12-18          12   \n",
       "2            1               2132       1930 2012-08-24           8   \n",
       "\n",
       "   sale_year  sale_price  log_sale_price  log_gross_square_feet  \n",
       "0       2013    560000.0       13.235692               7.307873  \n",
       "1       2012    860000.0       13.664688               7.452402  \n",
       "2       2012    508000.0       13.138237               7.664816  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raw_data = pd.read_csv('dataset/housing/output_after_eda.csv', \\\n",
    "                      dtype={'borough': object, 'neighborhood': object, 'building_class': object,\n",
    "                             'building_class_map': object, 'building_category': object, \n",
    "                             'building_category_map': object, 'building_type': object, 'tax_class': object,\n",
    "                             'tax_class_map': object, 'zipcode': object, 'total_units': int, 'gross_square_feet': int,\n",
    "                             'year_built': object, 'sale_month': int, 'sale_year': int, 'sale_price': float,\n",
    "                             'log_sale_price': float, 'log_gross_square_feet': float}, \\\n",
    "                      parse_dates=['sale_date'], \\\n",
    "                      infer_datetime_format=True)\n",
    "\n",
    "raw_data.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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