Housing_EDA/EDA Housing dataset.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Les données du dataset housing concernent la médiane de prix, nombre de chambres, emplacement ... de chaque arrondissement dans Californie. De telle sorte qu'un arrondissement peut contenir de 600 jusqu'à 3000 habitants. Nous allons dans ce notebook explorer, visualiser et trouver des informations relevant à partir de nos données."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Se familiariser avec les données"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Importer les données et se familiariser avec leurs structures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "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>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "      <th>ocean_proximity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-122.23</td>\n",
       "      <td>37.88</td>\n",
       "      <td>41.0</td>\n",
       "      <td>880.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>322.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>8.3252</td>\n",
       "      <td>452600.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-122.22</td>\n",
       "      <td>37.86</td>\n",
       "      <td>21.0</td>\n",
       "      <td>7099.0</td>\n",
       "      <td>1106.0</td>\n",
       "      <td>2401.0</td>\n",
       "      <td>1138.0</td>\n",
       "      <td>8.3014</td>\n",
       "      <td>358500.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-122.24</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1467.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>496.0</td>\n",
       "      <td>177.0</td>\n",
       "      <td>7.2574</td>\n",
       "      <td>352100.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1274.0</td>\n",
       "      <td>235.0</td>\n",
       "      <td>558.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>5.6431</td>\n",
       "      <td>341300.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1627.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>259.0</td>\n",
       "      <td>3.8462</td>\n",
       "      <td>342200.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "0    -122.23     37.88                41.0        880.0           129.0   \n",
       "1    -122.22     37.86                21.0       7099.0          1106.0   \n",
       "2    -122.24     37.85                52.0       1467.0           190.0   \n",
       "3    -122.25     37.85                52.0       1274.0           235.0   \n",
       "4    -122.25     37.85                52.0       1627.0           280.0   \n",
       "\n",
       "   population  households  median_income  median_house_value ocean_proximity  \n",
       "0       322.0       126.0         8.3252            452600.0        NEAR BAY  \n",
       "1      2401.0      1138.0         8.3014            358500.0        NEAR BAY  \n",
       "2       496.0       177.0         7.2574            352100.0        NEAR BAY  \n",
       "3       558.0       219.0         5.6431            341300.0        NEAR BAY  \n",
       "4       565.0       259.0         3.8462            342200.0        NEAR BAY  "
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd \n",
    "\n",
    "housing = pd.read_csv('housing/housing.csv')\n",
    "housing.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['longitude', 'latitude', 'housing_median_age', 'total_rooms',\n",
       "       'total_bedrooms', 'population', 'households', 'median_income',\n",
       "       'median_house_value', 'ocean_proximity'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "NB:   \n",
    "- Chaque ligne représente un arrondissement (one district).\n",
    "- Nous avons 10 colonnes (['longitude', 'latitude', 'housing_median_age', 'total_rooms','total_bedrooms', 'population', 'households', 'median_income','median_house_value', 'ocean_proximity'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 20640 entries, 0 to 20639\n",
      "Data columns (total 10 columns):\n",
      "longitude             20640 non-null float64\n",
      "latitude              20640 non-null float64\n",
      "housing_median_age    20640 non-null float64\n",
      "total_rooms           20640 non-null float64\n",
      "total_bedrooms        20433 non-null float64\n",
      "population            20640 non-null float64\n",
      "households            20640 non-null float64\n",
      "median_income         20640 non-null float64\n",
      "median_house_value    20640 non-null float64\n",
      "ocean_proximity       20640 non-null object\n",
      "dtypes: float64(9), object(1)\n",
      "memory usage: 1.6+ MB\n"
     ]
    }
   ],
   "source": [
    "housing.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* La colonne `ocean_proximity` a besoin qu'on **change son type** par après (car elle est de type object qui est trop vague)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "      <th>ocean_proximity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>20635</th>\n",
       "      <td>-121.09</td>\n",
       "      <td>39.48</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1665.0</td>\n",
       "      <td>374.0</td>\n",
       "      <td>845.0</td>\n",
       "      <td>330.0</td>\n",
       "      <td>1.5603</td>\n",
       "      <td>78100.0</td>\n",
       "      <td>INLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20636</th>\n",
       "      <td>-121.21</td>\n",
       "      <td>39.49</td>\n",
       "      <td>18.0</td>\n",
       "      <td>697.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>114.0</td>\n",
       "      <td>2.5568</td>\n",
       "      <td>77100.0</td>\n",
       "      <td>INLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20637</th>\n",
       "      <td>-121.22</td>\n",
       "      <td>39.43</td>\n",
       "      <td>17.0</td>\n",
       "      <td>2254.0</td>\n",
       "      <td>485.0</td>\n",
       "      <td>1007.0</td>\n",
       "      <td>433.0</td>\n",
       "      <td>1.7000</td>\n",
       "      <td>92300.0</td>\n",
       "      <td>INLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20638</th>\n",
       "      <td>-121.32</td>\n",
       "      <td>39.43</td>\n",
       "      <td>18.0</td>\n",
       "      <td>1860.0</td>\n",
       "      <td>409.0</td>\n",
       "      <td>741.0</td>\n",
       "      <td>349.0</td>\n",
       "      <td>1.8672</td>\n",
       "      <td>84700.0</td>\n",
       "      <td>INLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20639</th>\n",
       "      <td>-121.24</td>\n",
       "      <td>39.37</td>\n",
       "      <td>16.0</td>\n",
       "      <td>2785.0</td>\n",
       "      <td>616.0</td>\n",
       "      <td>1387.0</td>\n",
       "      <td>530.0</td>\n",
       "      <td>2.3886</td>\n",
       "      <td>89400.0</td>\n",
       "      <td>INLAND</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "20635    -121.09     39.48                25.0       1665.0           374.0   \n",
       "20636    -121.21     39.49                18.0        697.0           150.0   \n",
       "20637    -121.22     39.43                17.0       2254.0           485.0   \n",
       "20638    -121.32     39.43                18.0       1860.0           409.0   \n",
       "20639    -121.24     39.37                16.0       2785.0           616.0   \n",
       "\n",
       "       population  households  median_income  median_house_value  \\\n",
       "20635       845.0       330.0         1.5603             78100.0   \n",
       "20636       356.0       114.0         2.5568             77100.0   \n",
       "20637      1007.0       433.0         1.7000             92300.0   \n",
       "20638       741.0       349.0         1.8672             84700.0   \n",
       "20639      1387.0       530.0         2.3886             89400.0   \n",
       "\n",
       "      ocean_proximity  \n",
       "20635          INLAND  \n",
       "20636          INLAND  \n",
       "20637          INLAND  \n",
       "20638          INLAND  \n",
       "20639          INLAND  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* On dirait que notre colonne `ocean_proximity` est une colonne qui contient des categories."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Découvrir le nombre de catégories qu'on a dans  ocean_proximity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<1H OCEAN     9136\n",
       "INLAND        6551\n",
       "NEAR OCEAN    2658\n",
       "NEAR BAY      2290\n",
       "ISLAND           5\n",
       "Name: ocean_proximity, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing['ocean_proximity'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Description statistique de nos données"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20433.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>-119.569704</td>\n",
       "      <td>35.631861</td>\n",
       "      <td>28.639486</td>\n",
       "      <td>2635.763081</td>\n",
       "      <td>537.870553</td>\n",
       "      <td>1425.476744</td>\n",
       "      <td>499.539680</td>\n",
       "      <td>3.870671</td>\n",
       "      <td>206855.816909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.003532</td>\n",
       "      <td>2.135952</td>\n",
       "      <td>12.585558</td>\n",
       "      <td>2181.615252</td>\n",
       "      <td>421.385070</td>\n",
       "      <td>1132.462122</td>\n",
       "      <td>382.329753</td>\n",
       "      <td>1.899822</td>\n",
       "      <td>115395.615874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-124.350000</td>\n",
       "      <td>32.540000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.499900</td>\n",
       "      <td>14999.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-121.800000</td>\n",
       "      <td>33.930000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>1447.750000</td>\n",
       "      <td>296.000000</td>\n",
       "      <td>787.000000</td>\n",
       "      <td>280.000000</td>\n",
       "      <td>2.563400</td>\n",
       "      <td>119600.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-118.490000</td>\n",
       "      <td>34.260000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>2127.000000</td>\n",
       "      <td>435.000000</td>\n",
       "      <td>1166.000000</td>\n",
       "      <td>409.000000</td>\n",
       "      <td>3.534800</td>\n",
       "      <td>179700.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>-118.010000</td>\n",
       "      <td>37.710000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>3148.000000</td>\n",
       "      <td>647.000000</td>\n",
       "      <td>1725.000000</td>\n",
       "      <td>605.000000</td>\n",
       "      <td>4.743250</td>\n",
       "      <td>264725.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>-114.310000</td>\n",
       "      <td>41.950000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>39320.000000</td>\n",
       "      <td>6445.000000</td>\n",
       "      <td>35682.000000</td>\n",
       "      <td>6082.000000</td>\n",
       "      <td>15.000100</td>\n",
       "      <td>500001.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          longitude      latitude  housing_median_age   total_rooms  \\\n",
       "count  20640.000000  20640.000000        20640.000000  20640.000000   \n",
       "mean    -119.569704     35.631861           28.639486   2635.763081   \n",
       "std        2.003532      2.135952           12.585558   2181.615252   \n",
       "min     -124.350000     32.540000            1.000000      2.000000   \n",
       "25%     -121.800000     33.930000           18.000000   1447.750000   \n",
       "50%     -118.490000     34.260000           29.000000   2127.000000   \n",
       "75%     -118.010000     37.710000           37.000000   3148.000000   \n",
       "max     -114.310000     41.950000           52.000000  39320.000000   \n",
       "\n",
       "       total_bedrooms    population    households  median_income  \\\n",
       "count    20433.000000  20640.000000  20640.000000   20640.000000   \n",
       "mean       537.870553   1425.476744    499.539680       3.870671   \n",
       "std        421.385070   1132.462122    382.329753       1.899822   \n",
       "min          1.000000      3.000000      1.000000       0.499900   \n",
       "25%        296.000000    787.000000    280.000000       2.563400   \n",
       "50%        435.000000   1166.000000    409.000000       3.534800   \n",
       "75%        647.000000   1725.000000    605.000000       4.743250   \n",
       "max       6445.000000  35682.000000   6082.000000      15.000100   \n",
       "\n",
       "       median_house_value  \n",
       "count        20640.000000  \n",
       "mean        206855.816909  \n",
       "std         115395.615874  \n",
       "min          14999.000000  \n",
       "25%         119600.000000  \n",
       "50%         179700.000000  \n",
       "75%         264725.000000  \n",
       "max         500001.000000  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* La colonne `total_bedrooms` n'a que **20433** valeurs alors qu'en tout nous avons **20640** ceci veut dire qu'elle contient des valeurs **NaN**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Remarques:  \n",
    "\n",
    "* Le prix minimum d'une maison est 14999.\n",
    "* Le prix maximum est 500001."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Une première visualisation de nos données"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline \n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "housing.hist(bins=50, figsize=(20,15))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualiser les données géographiques"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x28606b45c88>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Repérer les surfaces d'une densité importante (alpha=0.1)\n",
    "housing.plot(kind=\"scatter\", x=\"longitude\", y=\"latitude\", alpha=0.1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Le prix d'une maison et son emplacement"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Le rayon de chaque cercle représente la population de chaque arrondissement (option s), et la couleur représente le prix (la mediane des prix de maisons) (option c). \n",
    "> Une couleur prédéfinie a été utilisé qui est color map (option c) appelée `jet`, qui change du bleu (petite valeurs) au rouge (très grande valeur). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x28608aa9fd0>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing.plot(kind=\"scatter\", x=\"longitude\", y=\"latitude\", alpha=0.4,\n",
    "            s=housing[\"population\"]/100, label=\"population\",\n",
    "            c=\"median_house_value\", cmap=plt.get_cmap(\"jet\"), \n",
    "            colorbar=True )\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On peut remarquer qu'effectivement l'emplacement de la maison joue un role dans son prix. On peut prendre par exemple les maisons se trouvant à la position (longitude ~= 37 et latitude ~= 122 , categorisée NEAR BAY) ont un prix plus élevée. Nous avons aussi quelques emplacements NEAR OCEAN qui ont un prix élevé. Mais ceci ne nous permet pas de généraliser."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Correlations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "matrice_corr = housing.corr()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Questions: Y-a-t il une relation entre le prix d'une maison et**\n",
    "1. le salaire \n",
    "2. le nombre de chambres \n",
    "3. le nombre de pièces (rooms)\n",
    "4. son age  \n",
    "**?**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Prix et Salaire**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "median_house_value    1.000000\n",
       "median_income         0.688075\n",
       "total_rooms           0.134153\n",
       "housing_median_age    0.105623\n",
       "households            0.065843\n",
       "total_bedrooms        0.049686\n",
       "population           -0.024650\n",
       "longitude            -0.045967\n",
       "latitude             -0.144160\n",
       "Name: median_house_value, dtype: float64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matrice_corr['median_house_value'].sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A travers le resulat au-dessus on peut voir qu'il ya une correlation positive qui s'approche de ~ 1. On peut dire que le prix mediane des maisons augmente avec un bon salaire."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Rq:**\n",
    "* La méthode `corr()` ne mesure que les correlations lineaires et il se peut que pour nos données nous ayons des correlations non lineaires c'est pourquoi nous allons utiliser une méthode de Pandas appelée `scatter_matrix` qui va nous dessiner des graphes de chaque valeur numérique avec les valeurs numériques que nous lui fourniront."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\sarae\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:5: FutureWarning: 'pandas.tools.plotting.scatter_matrix' is deprecated, import 'pandas.plotting.scatter_matrix' instead.\n",
      "  \"\"\"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x0000028608FE4F28>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002860900D828>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000028608CB4EB8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000028608CE4550>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000028608D0DBE0>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x0000028608D0DC18>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000028608D65940>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000028608D8DFD0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000028608DBE6A0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000028608DE5D30>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x0000028608E18400>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x00000286091BEA58>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x00000286091EF128>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x00000286092187B8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002860923FE48>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x0000028606705978>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002860673FA58>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000028606784780>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002860728A550>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x00000286065B0438>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x00000286067F8860>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x00000286068297F0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x00000286068DA0F0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002860690BC18>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x00000286072D5B70>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 25 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pandas.tools.plotting import scatter_matrix\n",
    "\n",
    "attributes = [\"median_house_value\", \"median_income\", \"total_rooms\", \n",
    "              \"housing_median_age\", \"population\"]\n",
    "scatter_matrix(housing[attributes], figsize=(12, 8))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Interprétation des graphes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Le graphe qui paraît le plus intéressant est celui du salaire et la valeur médiane du prix de la maison. Voyons ceci un peu de plus près."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x286069c4208>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing.plot(kind='scatter', x=\"median_income\", y='median_house_value', alpha=0.1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Conclusion**: Nous pouvons remarquer qu'effectivement le prix d'une maison est haut si le salaire est haut."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Rq**: On peut voir qu'il y a des lignes horizontales aux alentours de ~360000 et ~280000 et d'autres valeurs, ceci nous pousse à faire un peu le ménage de nos données."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Création de nouvelles valeurs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "housing['rooms_per_household'] = housing['total_rooms']/housing['households']\n",
    "housing['bedrooms_per_room'] = housing['total_bedrooms']/housing['total_rooms']\n",
    "housing['population_per_househol'] = housing['population']/housing['households']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "      <th>ocean_proximity</th>\n",
       "      <th>rooms_per_household</th>\n",
       "      <th>bedrooms_per_household</th>\n",
       "      <th>population_per_househol</th>\n",
       "      <th>bedrooms_per_room</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-122.23</td>\n",
       "      <td>37.88</td>\n",
       "      <td>41.0</td>\n",
       "      <td>880.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>322.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>8.3252</td>\n",
       "      <td>452600.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>6.984127</td>\n",
       "      <td>1.023810</td>\n",
       "      <td>2.555556</td>\n",
       "      <td>0.146591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-122.22</td>\n",
       "      <td>37.86</td>\n",
       "      <td>21.0</td>\n",
       "      <td>7099.0</td>\n",
       "      <td>1106.0</td>\n",
       "      <td>2401.0</td>\n",
       "      <td>1138.0</td>\n",
       "      <td>8.3014</td>\n",
       "      <td>358500.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>6.238137</td>\n",
       "      <td>0.971880</td>\n",
       "      <td>2.109842</td>\n",
       "      <td>0.155797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-122.24</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1467.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>496.0</td>\n",
       "      <td>177.0</td>\n",
       "      <td>7.2574</td>\n",
       "      <td>352100.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>8.288136</td>\n",
       "      <td>1.073446</td>\n",
       "      <td>2.802260</td>\n",
       "      <td>0.129516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1274.0</td>\n",
       "      <td>235.0</td>\n",
       "      <td>558.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>5.6431</td>\n",
       "      <td>341300.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>5.817352</td>\n",
       "      <td>1.073059</td>\n",
       "      <td>2.547945</td>\n",
       "      <td>0.184458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1627.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>259.0</td>\n",
       "      <td>3.8462</td>\n",
       "      <td>342200.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>6.281853</td>\n",
       "      <td>1.081081</td>\n",
       "      <td>2.181467</td>\n",
       "      <td>0.172096</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "0    -122.23     37.88                41.0        880.0           129.0   \n",
       "1    -122.22     37.86                21.0       7099.0          1106.0   \n",
       "2    -122.24     37.85                52.0       1467.0           190.0   \n",
       "3    -122.25     37.85                52.0       1274.0           235.0   \n",
       "4    -122.25     37.85                52.0       1627.0           280.0   \n",
       "\n",
       "   population  households  median_income  median_house_value ocean_proximity  \\\n",
       "0       322.0       126.0         8.3252            452600.0        NEAR BAY   \n",
       "1      2401.0      1138.0         8.3014            358500.0        NEAR BAY   \n",
       "2       496.0       177.0         7.2574            352100.0        NEAR BAY   \n",
       "3       558.0       219.0         5.6431            341300.0        NEAR BAY   \n",
       "4       565.0       259.0         3.8462            342200.0        NEAR BAY   \n",
       "\n",
       "   rooms_per_household  bedrooms_per_household  population_per_househol  \\\n",
       "0             6.984127                1.023810                 2.555556   \n",
       "1             6.238137                0.971880                 2.109842   \n",
       "2             8.288136                1.073446                 2.802260   \n",
       "3             5.817352                1.073059                 2.547945   \n",
       "4             6.281853                1.081081                 2.181467   \n",
       "\n",
       "   bedrooms_per_room  \n",
       "0           0.146591  \n",
       "1           0.155797  \n",
       "2           0.129516  \n",
       "3           0.184458  \n",
       "4           0.172096  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "median_house_value         1.000000\n",
       "median_income              0.688075\n",
       "rooms_per_household        0.151948\n",
       "total_rooms                0.134153\n",
       "housing_median_age         0.105623\n",
       "households                 0.065843\n",
       "total_bedrooms             0.049686\n",
       "population_per_househol   -0.023737\n",
       "population                -0.024650\n",
       "longitude                 -0.045967\n",
       "bedrooms_per_household    -0.046739\n",
       "latitude                  -0.144160\n",
       "bedrooms_per_room         -0.255880\n",
       "Name: median_house_value, dtype: float64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mat_corr = housing.corr()\n",
    "mat_corr['median_house_value'].sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Cc**: On dirait que le nombre de chambres à coucher dans une maison affecte négativement le prix d'une maison. En d'autres terme on peut dire qu'une maison avec un nombre faible de chambres à coucher/chambres est plus chère que les autres maisons. Le nombre de pièces aussi affecte positivement le prix d'une maison ce qui est normal puisque plus la maison est grande plus elle est chère.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "      <th>ocean_proximity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-122.23</td>\n",
       "      <td>37.88</td>\n",
       "      <td>41.0</td>\n",
       "      <td>880.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>322.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>8.3252</td>\n",
       "      <td>452600.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-122.22</td>\n",
       "      <td>37.86</td>\n",
       "      <td>21.0</td>\n",
       "      <td>7099.0</td>\n",
       "      <td>1106.0</td>\n",
       "      <td>2401.0</td>\n",
       "      <td>1138.0</td>\n",
       "      <td>8.3014</td>\n",
       "      <td>358500.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-122.24</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1467.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>496.0</td>\n",
       "      <td>177.0</td>\n",
       "      <td>7.2574</td>\n",
       "      <td>352100.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1274.0</td>\n",
       "      <td>235.0</td>\n",
       "      <td>558.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>5.6431</td>\n",
       "      <td>341300.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1627.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>259.0</td>\n",
       "      <td>3.8462</td>\n",
       "      <td>342200.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "0    -122.23     37.88                41.0        880.0           129.0   \n",
       "1    -122.22     37.86                21.0       7099.0          1106.0   \n",
       "2    -122.24     37.85                52.0       1467.0           190.0   \n",
       "3    -122.25     37.85                52.0       1274.0           235.0   \n",
       "4    -122.25     37.85                52.0       1627.0           280.0   \n",
       "\n",
       "   population  households  median_income  median_house_value ocean_proximity  \n",
       "0       322.0       126.0         8.3252            452600.0        NEAR BAY  \n",
       "1      2401.0      1138.0         8.3014            358500.0        NEAR BAY  \n",
       "2       496.0       177.0         7.2574            352100.0        NEAR BAY  \n",
       "3       558.0       219.0         5.6431            341300.0        NEAR BAY  \n",
       "4       565.0       259.0         3.8462            342200.0        NEAR BAY  "
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd \n",
    "\n",
    "housing = pd.read_csv('housing/housing.csv')\n",
    "housing.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "longitude             False\n",
       "latitude              False\n",
       "housing_median_age    False\n",
       "total_rooms           False\n",
       "total_bedrooms         True\n",
       "population            False\n",
       "households            False\n",
       "median_income         False\n",
       "median_house_value    False\n",
       "ocean_proximity       False\n",
       "dtype: bool"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing.isnull().any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Remplace les valeurs manquantes par la mediane\n",
    "median = housing[\"total_bedrooms\"].median()\n",
    "housing['total_bedrooms'] = housing[\"total_bedrooms\"].fillna(median)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>-119.569704</td>\n",
       "      <td>35.631861</td>\n",
       "      <td>28.639486</td>\n",
       "      <td>2635.763081</td>\n",
       "      <td>536.838857</td>\n",
       "      <td>1425.476744</td>\n",
       "      <td>499.539680</td>\n",
       "      <td>3.870671</td>\n",
       "      <td>206855.816909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.003532</td>\n",
       "      <td>2.135952</td>\n",
       "      <td>12.585558</td>\n",
       "      <td>2181.615252</td>\n",
       "      <td>419.391878</td>\n",
       "      <td>1132.462122</td>\n",
       "      <td>382.329753</td>\n",
       "      <td>1.899822</td>\n",
       "      <td>115395.615874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-124.350000</td>\n",
       "      <td>32.540000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.499900</td>\n",
       "      <td>14999.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-121.800000</td>\n",
       "      <td>33.930000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>1447.750000</td>\n",
       "      <td>297.000000</td>\n",
       "      <td>787.000000</td>\n",
       "      <td>280.000000</td>\n",
       "      <td>2.563400</td>\n",
       "      <td>119600.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-118.490000</td>\n",
       "      <td>34.260000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>2127.000000</td>\n",
       "      <td>435.000000</td>\n",
       "      <td>1166.000000</td>\n",
       "      <td>409.000000</td>\n",
       "      <td>3.534800</td>\n",
       "      <td>179700.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>-118.010000</td>\n",
       "      <td>37.710000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>3148.000000</td>\n",
       "      <td>643.250000</td>\n",
       "      <td>1725.000000</td>\n",
       "      <td>605.000000</td>\n",
       "      <td>4.743250</td>\n",
       "      <td>264725.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>-114.310000</td>\n",
       "      <td>41.950000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>39320.000000</td>\n",
       "      <td>6445.000000</td>\n",
       "      <td>35682.000000</td>\n",
       "      <td>6082.000000</td>\n",
       "      <td>15.000100</td>\n",
       "      <td>500001.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          longitude      latitude  housing_median_age   total_rooms  \\\n",
       "count  20640.000000  20640.000000        20640.000000  20640.000000   \n",
       "mean    -119.569704     35.631861           28.639486   2635.763081   \n",
       "std        2.003532      2.135952           12.585558   2181.615252   \n",
       "min     -124.350000     32.540000            1.000000      2.000000   \n",
       "25%     -121.800000     33.930000           18.000000   1447.750000   \n",
       "50%     -118.490000     34.260000           29.000000   2127.000000   \n",
       "75%     -118.010000     37.710000           37.000000   3148.000000   \n",
       "max     -114.310000     41.950000           52.000000  39320.000000   \n",
       "\n",
       "       total_bedrooms    population    households  median_income  \\\n",
       "count    20640.000000  20640.000000  20640.000000   20640.000000   \n",
       "mean       536.838857   1425.476744    499.539680       3.870671   \n",
       "std        419.391878   1132.462122    382.329753       1.899822   \n",
       "min          1.000000      3.000000      1.000000       0.499900   \n",
       "25%        297.000000    787.000000    280.000000       2.563400   \n",
       "50%        435.000000   1166.000000    409.000000       3.534800   \n",
       "75%        643.250000   1725.000000    605.000000       4.743250   \n",
       "max       6445.000000  35682.000000   6082.000000      15.000100   \n",
       "\n",
       "       median_house_value  \n",
       "count        20640.000000  \n",
       "mean        206855.816909  \n",
       "std         115395.615874  \n",
       "min          14999.000000  \n",
       "25%         119600.000000  \n",
       "50%         179700.000000  \n",
       "75%         264725.000000  \n",
       "max         500001.000000  "
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "housing['rooms_per_household'] = housing['total_rooms']/housing['households']\n",
    "housing['bedrooms_per_room'] = housing['total_bedrooms']/housing['total_rooms']\n",
    "housing['population_per_househol'] = housing['population']/housing['households']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "      <th>rooms_per_household</th>\n",
       "      <th>bedrooms_per_room</th>\n",
       "      <th>population_per_househol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>-119.569704</td>\n",
       "      <td>35.631861</td>\n",
       "      <td>28.639486</td>\n",
       "      <td>2635.763081</td>\n",
       "      <td>536.838857</td>\n",
       "      <td>1425.476744</td>\n",
       "      <td>499.539680</td>\n",
       "      <td>3.870671</td>\n",
       "      <td>206855.816909</td>\n",
       "      <td>5.429000</td>\n",
       "      <td>0.213794</td>\n",
       "      <td>3.070655</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.003532</td>\n",
       "      <td>2.135952</td>\n",
       "      <td>12.585558</td>\n",
       "      <td>2181.615252</td>\n",
       "      <td>419.391878</td>\n",
       "      <td>1132.462122</td>\n",
       "      <td>382.329753</td>\n",
       "      <td>1.899822</td>\n",
       "      <td>115395.615874</td>\n",
       "      <td>2.474173</td>\n",
       "      <td>0.065248</td>\n",
       "      <td>10.386050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-124.350000</td>\n",
       "      <td>32.540000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.499900</td>\n",
       "      <td>14999.000000</td>\n",
       "      <td>0.846154</td>\n",
       "      <td>0.037151</td>\n",
       "      <td>0.692308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-121.800000</td>\n",
       "      <td>33.930000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>1447.750000</td>\n",
       "      <td>297.000000</td>\n",
       "      <td>787.000000</td>\n",
       "      <td>280.000000</td>\n",
       "      <td>2.563400</td>\n",
       "      <td>119600.000000</td>\n",
       "      <td>4.440716</td>\n",
       "      <td>0.175225</td>\n",
       "      <td>2.429741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-118.490000</td>\n",
       "      <td>34.260000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>2127.000000</td>\n",
       "      <td>435.000000</td>\n",
       "      <td>1166.000000</td>\n",
       "      <td>409.000000</td>\n",
       "      <td>3.534800</td>\n",
       "      <td>179700.000000</td>\n",
       "      <td>5.229129</td>\n",
       "      <td>0.203159</td>\n",
       "      <td>2.818116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>-118.010000</td>\n",
       "      <td>37.710000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>3148.000000</td>\n",
       "      <td>643.250000</td>\n",
       "      <td>1725.000000</td>\n",
       "      <td>605.000000</td>\n",
       "      <td>4.743250</td>\n",
       "      <td>264725.000000</td>\n",
       "      <td>6.052381</td>\n",
       "      <td>0.240126</td>\n",
       "      <td>3.282261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>-114.310000</td>\n",
       "      <td>41.950000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>39320.000000</td>\n",
       "      <td>6445.000000</td>\n",
       "      <td>35682.000000</td>\n",
       "      <td>6082.000000</td>\n",
       "      <td>15.000100</td>\n",
       "      <td>500001.000000</td>\n",
       "      <td>141.909091</td>\n",
       "      <td>2.824675</td>\n",
       "      <td>1243.333333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          longitude      latitude  housing_median_age   total_rooms  \\\n",
       "count  20640.000000  20640.000000        20640.000000  20640.000000   \n",
       "mean    -119.569704     35.631861           28.639486   2635.763081   \n",
       "std        2.003532      2.135952           12.585558   2181.615252   \n",
       "min     -124.350000     32.540000            1.000000      2.000000   \n",
       "25%     -121.800000     33.930000           18.000000   1447.750000   \n",
       "50%     -118.490000     34.260000           29.000000   2127.000000   \n",
       "75%     -118.010000     37.710000           37.000000   3148.000000   \n",
       "max     -114.310000     41.950000           52.000000  39320.000000   \n",
       "\n",
       "       total_bedrooms    population    households  median_income  \\\n",
       "count    20640.000000  20640.000000  20640.000000   20640.000000   \n",
       "mean       536.838857   1425.476744    499.539680       3.870671   \n",
       "std        419.391878   1132.462122    382.329753       1.899822   \n",
       "min          1.000000      3.000000      1.000000       0.499900   \n",
       "25%        297.000000    787.000000    280.000000       2.563400   \n",
       "50%        435.000000   1166.000000    409.000000       3.534800   \n",
       "75%        643.250000   1725.000000    605.000000       4.743250   \n",
       "max       6445.000000  35682.000000   6082.000000      15.000100   \n",
       "\n",
       "       median_house_value  rooms_per_household  bedrooms_per_room  \\\n",
       "count        20640.000000         20640.000000       20640.000000   \n",
       "mean        206855.816909             5.429000           0.213794   \n",
       "std         115395.615874             2.474173           0.065248   \n",
       "min          14999.000000             0.846154           0.037151   \n",
       "25%         119600.000000             4.440716           0.175225   \n",
       "50%         179700.000000             5.229129           0.203159   \n",
       "75%         264725.000000             6.052381           0.240126   \n",
       "max         500001.000000           141.909091           2.824675   \n",
       "\n",
       "       population_per_househol  \n",
       "count             20640.000000  \n",
       "mean                  3.070655  \n",
       "std                  10.386050  \n",
       "min                   0.692308  \n",
       "25%                   2.429741  \n",
       "50%                   2.818116  \n",
       "75%                   3.282261  \n",
       "max                1243.333333  "
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing['total_bedrooms'].isnull().any()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2860a2ea208>"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing.plot(kind='box', figsize=(20,15))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Rq**: On dirait qu'il y a plusieurs outliers.\n",
    "Nous allons survoler ces outliers et voir comment s'en occuper."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2860692bc50>"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing.boxplot(column='median_house_value', figsize=(20,15))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "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>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "      <th>ocean_proximity</th>\n",
       "      <th>rooms_per_household</th>\n",
       "      <th>bedrooms_per_room</th>\n",
       "      <th>population_per_househol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>-122.27</td>\n",
       "      <td>37.80</td>\n",
       "      <td>52.0</td>\n",
       "      <td>249.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>396.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>1.2434</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>2.929412</td>\n",
       "      <td>0.313253</td>\n",
       "      <td>4.658824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>459</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.87</td>\n",
       "      <td>52.0</td>\n",
       "      <td>609.0</td>\n",
       "      <td>236.0</td>\n",
       "      <td>1349.0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>1.1696</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>2.436000</td>\n",
       "      <td>0.387521</td>\n",
       "      <td>5.396000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>-122.24</td>\n",
       "      <td>37.86</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1668.0</td>\n",
       "      <td>225.0</td>\n",
       "      <td>517.0</td>\n",
       "      <td>214.0</td>\n",
       "      <td>7.8521</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>7.794393</td>\n",
       "      <td>0.134892</td>\n",
       "      <td>2.415888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>494</th>\n",
       "      <td>-122.24</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>3726.0</td>\n",
       "      <td>474.0</td>\n",
       "      <td>1366.0</td>\n",
       "      <td>496.0</td>\n",
       "      <td>9.3959</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>7.512097</td>\n",
       "      <td>0.127214</td>\n",
       "      <td>2.754032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>509</th>\n",
       "      <td>-122.23</td>\n",
       "      <td>37.83</td>\n",
       "      <td>52.0</td>\n",
       "      <td>2990.0</td>\n",
       "      <td>379.0</td>\n",
       "      <td>947.0</td>\n",
       "      <td>361.0</td>\n",
       "      <td>7.8772</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>8.282548</td>\n",
       "      <td>0.126756</td>\n",
       "      <td>2.623269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>510</th>\n",
       "      <td>-122.22</td>\n",
       "      <td>37.82</td>\n",
       "      <td>39.0</td>\n",
       "      <td>2492.0</td>\n",
       "      <td>310.0</td>\n",
       "      <td>808.0</td>\n",
       "      <td>315.0</td>\n",
       "      <td>11.8603</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>7.911111</td>\n",
       "      <td>0.124398</td>\n",
       "      <td>2.565079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>511</th>\n",
       "      <td>-122.22</td>\n",
       "      <td>37.82</td>\n",
       "      <td>42.0</td>\n",
       "      <td>2991.0</td>\n",
       "      <td>335.0</td>\n",
       "      <td>1018.0</td>\n",
       "      <td>335.0</td>\n",
       "      <td>13.4990</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>8.928358</td>\n",
       "      <td>0.112003</td>\n",
       "      <td>3.038806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512</th>\n",
       "      <td>-122.23</td>\n",
       "      <td>37.82</td>\n",
       "      <td>52.0</td>\n",
       "      <td>3242.0</td>\n",
       "      <td>366.0</td>\n",
       "      <td>1001.0</td>\n",
       "      <td>352.0</td>\n",
       "      <td>12.2138</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>9.210227</td>\n",
       "      <td>0.112893</td>\n",
       "      <td>2.843750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>514</th>\n",
       "      <td>-122.23</td>\n",
       "      <td>37.82</td>\n",
       "      <td>52.0</td>\n",
       "      <td>3494.0</td>\n",
       "      <td>396.0</td>\n",
       "      <td>1192.0</td>\n",
       "      <td>383.0</td>\n",
       "      <td>12.3804</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>9.122715</td>\n",
       "      <td>0.113337</td>\n",
       "      <td>3.112272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>517</th>\n",
       "      <td>-122.23</td>\n",
       "      <td>37.82</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1611.0</td>\n",
       "      <td>203.0</td>\n",
       "      <td>556.0</td>\n",
       "      <td>179.0</td>\n",
       "      <td>8.7477</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>0.126009</td>\n",
       "      <td>3.106145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>923</th>\n",
       "      <td>-121.89</td>\n",
       "      <td>37.49</td>\n",
       "      <td>9.0</td>\n",
       "      <td>4909.0</td>\n",
       "      <td>577.0</td>\n",
       "      <td>1981.0</td>\n",
       "      <td>591.0</td>\n",
       "      <td>9.7194</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>8.306261</td>\n",
       "      <td>0.117539</td>\n",
       "      <td>3.351946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>955</th>\n",
       "      <td>-121.93</td>\n",
       "      <td>37.66</td>\n",
       "      <td>24.0</td>\n",
       "      <td>3166.0</td>\n",
       "      <td>424.0</td>\n",
       "      <td>1081.0</td>\n",
       "      <td>400.0</td>\n",
       "      <td>8.3337</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>7.915000</td>\n",
       "      <td>0.133923</td>\n",
       "      <td>2.702500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1574</th>\n",
       "      <td>-122.03</td>\n",
       "      <td>37.83</td>\n",
       "      <td>24.0</td>\n",
       "      <td>5948.0</td>\n",
       "      <td>738.0</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>710.0</td>\n",
       "      <td>9.8708</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>8.377465</td>\n",
       "      <td>0.124075</td>\n",
       "      <td>2.812676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1582</th>\n",
       "      <td>-122.00</td>\n",
       "      <td>37.86</td>\n",
       "      <td>18.0</td>\n",
       "      <td>8953.0</td>\n",
       "      <td>1074.0</td>\n",
       "      <td>3011.0</td>\n",
       "      <td>993.0</td>\n",
       "      <td>10.7372</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>9.016113</td>\n",
       "      <td>0.119960</td>\n",
       "      <td>3.032226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1583</th>\n",
       "      <td>-121.97</td>\n",
       "      <td>37.87</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1029.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>416.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>13.4883</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>8.434426</td>\n",
       "      <td>0.122449</td>\n",
       "      <td>3.409836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1585</th>\n",
       "      <td>-122.00</td>\n",
       "      <td>37.84</td>\n",
       "      <td>16.0</td>\n",
       "      <td>7681.0</td>\n",
       "      <td>946.0</td>\n",
       "      <td>2777.0</td>\n",
       "      <td>908.0</td>\n",
       "      <td>9.5271</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>8.459251</td>\n",
       "      <td>0.123161</td>\n",
       "      <td>3.058370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586</th>\n",
       "      <td>-121.96</td>\n",
       "      <td>37.85</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3209.0</td>\n",
       "      <td>379.0</td>\n",
       "      <td>1199.0</td>\n",
       "      <td>392.0</td>\n",
       "      <td>12.2478</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>8.186224</td>\n",
       "      <td>0.118105</td>\n",
       "      <td>3.058673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1591</th>\n",
       "      <td>-122.12</td>\n",
       "      <td>37.94</td>\n",
       "      <td>22.0</td>\n",
       "      <td>4949.0</td>\n",
       "      <td>626.0</td>\n",
       "      <td>1850.0</td>\n",
       "      <td>590.0</td>\n",
       "      <td>10.4549</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>8.388136</td>\n",
       "      <td>0.126490</td>\n",
       "      <td>3.135593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1593</th>\n",
       "      <td>-122.14</td>\n",
       "      <td>37.90</td>\n",
       "      <td>32.0</td>\n",
       "      <td>5738.0</td>\n",
       "      <td>746.0</td>\n",
       "      <td>2099.0</td>\n",
       "      <td>732.0</td>\n",
       "      <td>10.3224</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>7.838798</td>\n",
       "      <td>0.130010</td>\n",
       "      <td>2.867486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1617</th>\n",
       "      <td>-122.08</td>\n",
       "      <td>37.84</td>\n",
       "      <td>17.0</td>\n",
       "      <td>1320.0</td>\n",
       "      <td>159.0</td>\n",
       "      <td>1722.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>11.7064</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>9.361702</td>\n",
       "      <td>0.120455</td>\n",
       "      <td>12.212766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1621</th>\n",
       "      <td>-122.08</td>\n",
       "      <td>37.82</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2045.0</td>\n",
       "      <td>237.0</td>\n",
       "      <td>830.0</td>\n",
       "      <td>252.0</td>\n",
       "      <td>11.3421</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>8.115079</td>\n",
       "      <td>0.115892</td>\n",
       "      <td>3.293651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1636</th>\n",
       "      <td>-122.18</td>\n",
       "      <td>37.91</td>\n",
       "      <td>31.0</td>\n",
       "      <td>7200.0</td>\n",
       "      <td>876.0</td>\n",
       "      <td>2428.0</td>\n",
       "      <td>843.0</td>\n",
       "      <td>10.9405</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>8.540925</td>\n",
       "      <td>0.121667</td>\n",
       "      <td>2.880190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1637</th>\n",
       "      <td>-122.20</td>\n",
       "      <td>37.90</td>\n",
       "      <td>36.0</td>\n",
       "      <td>2107.0</td>\n",
       "      <td>287.0</td>\n",
       "      <td>740.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>10.3416</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>7.525000</td>\n",
       "      <td>0.136213</td>\n",
       "      <td>2.642857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1638</th>\n",
       "      <td>-122.18</td>\n",
       "      <td>37.90</td>\n",
       "      <td>36.0</td>\n",
       "      <td>4760.0</td>\n",
       "      <td>610.0</td>\n",
       "      <td>1511.0</td>\n",
       "      <td>572.0</td>\n",
       "      <td>9.0064</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>8.321678</td>\n",
       "      <td>0.128151</td>\n",
       "      <td>2.641608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1644</th>\n",
       "      <td>-121.94</td>\n",
       "      <td>37.83</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2836.0</td>\n",
       "      <td>373.0</td>\n",
       "      <td>959.0</td>\n",
       "      <td>335.0</td>\n",
       "      <td>10.5815</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>8.465672</td>\n",
       "      <td>0.131523</td>\n",
       "      <td>2.862687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1645</th>\n",
       "      <td>-121.89</td>\n",
       "      <td>37.82</td>\n",
       "      <td>4.0</td>\n",
       "      <td>11444.0</td>\n",
       "      <td>1355.0</td>\n",
       "      <td>3898.0</td>\n",
       "      <td>1257.0</td>\n",
       "      <td>13.2949</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>9.104216</td>\n",
       "      <td>0.118403</td>\n",
       "      <td>3.101034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1646</th>\n",
       "      <td>-121.91</td>\n",
       "      <td>37.81</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3477.0</td>\n",
       "      <td>416.0</td>\n",
       "      <td>1216.0</td>\n",
       "      <td>395.0</td>\n",
       "      <td>13.1499</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>8.802532</td>\n",
       "      <td>0.119643</td>\n",
       "      <td>3.078481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1914</th>\n",
       "      <td>-120.10</td>\n",
       "      <td>38.91</td>\n",
       "      <td>33.0</td>\n",
       "      <td>1561.0</td>\n",
       "      <td>282.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1.8750</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>141.909091</td>\n",
       "      <td>0.180653</td>\n",
       "      <td>2.727273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3486</th>\n",
       "      <td>-118.54</td>\n",
       "      <td>34.28</td>\n",
       "      <td>10.0</td>\n",
       "      <td>7665.0</td>\n",
       "      <td>999.0</td>\n",
       "      <td>3517.0</td>\n",
       "      <td>998.0</td>\n",
       "      <td>10.8805</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>7.680361</td>\n",
       "      <td>0.130333</td>\n",
       "      <td>3.524048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3533</th>\n",
       "      <td>-118.54</td>\n",
       "      <td>34.26</td>\n",
       "      <td>23.0</td>\n",
       "      <td>4960.0</td>\n",
       "      <td>592.0</td>\n",
       "      <td>1929.0</td>\n",
       "      <td>586.0</td>\n",
       "      <td>10.9052</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>8.464164</td>\n",
       "      <td>0.119355</td>\n",
       "      <td>3.291809</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18361</th>\n",
       "      <td>-122.14</td>\n",
       "      <td>37.36</td>\n",
       "      <td>23.0</td>\n",
       "      <td>11294.0</td>\n",
       "      <td>1377.0</td>\n",
       "      <td>3840.0</td>\n",
       "      <td>1367.0</td>\n",
       "      <td>12.1387</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>8.261887</td>\n",
       "      <td>0.121923</td>\n",
       "      <td>2.809071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18362</th>\n",
       "      <td>-122.15</td>\n",
       "      <td>37.35</td>\n",
       "      <td>23.0</td>\n",
       "      <td>3814.0</td>\n",
       "      <td>485.0</td>\n",
       "      <td>1344.0</td>\n",
       "      <td>464.0</td>\n",
       "      <td>12.9792</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>8.219828</td>\n",
       "      <td>0.127163</td>\n",
       "      <td>2.896552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18363</th>\n",
       "      <td>-122.11</td>\n",
       "      <td>37.31</td>\n",
       "      <td>7.0</td>\n",
       "      <td>189.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>13.8093</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>6.517241</td>\n",
       "      <td>0.137566</td>\n",
       "      <td>2.896552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18364</th>\n",
       "      <td>-122.12</td>\n",
       "      <td>37.29</td>\n",
       "      <td>11.0</td>\n",
       "      <td>436.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>212.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>8.6196</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5.813333</td>\n",
       "      <td>0.160550</td>\n",
       "      <td>2.826667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18366</th>\n",
       "      <td>-122.08</td>\n",
       "      <td>37.24</td>\n",
       "      <td>21.0</td>\n",
       "      <td>427.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>182.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>11.3283</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>6.100000</td>\n",
       "      <td>0.147541</td>\n",
       "      <td>2.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18380</th>\n",
       "      <td>-121.86</td>\n",
       "      <td>37.21</td>\n",
       "      <td>23.0</td>\n",
       "      <td>2552.0</td>\n",
       "      <td>305.0</td>\n",
       "      <td>916.0</td>\n",
       "      <td>316.0</td>\n",
       "      <td>9.1974</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>8.075949</td>\n",
       "      <td>0.119514</td>\n",
       "      <td>2.898734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18381</th>\n",
       "      <td>-121.87</td>\n",
       "      <td>37.21</td>\n",
       "      <td>18.0</td>\n",
       "      <td>1080.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>382.0</td>\n",
       "      <td>121.0</td>\n",
       "      <td>9.0800</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>8.925620</td>\n",
       "      <td>0.112963</td>\n",
       "      <td>3.157025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18382</th>\n",
       "      <td>-121.83</td>\n",
       "      <td>37.23</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5389.0</td>\n",
       "      <td>903.0</td>\n",
       "      <td>2232.0</td>\n",
       "      <td>825.0</td>\n",
       "      <td>6.6659</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>6.532121</td>\n",
       "      <td>0.167564</td>\n",
       "      <td>2.705455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18461</th>\n",
       "      <td>-121.76</td>\n",
       "      <td>37.26</td>\n",
       "      <td>17.0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>4.6458</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>4.901961</td>\n",
       "      <td>0.208000</td>\n",
       "      <td>2.764706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18464</th>\n",
       "      <td>-121.74</td>\n",
       "      <td>37.19</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1290.0</td>\n",
       "      <td>197.0</td>\n",
       "      <td>881.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>4.2039</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>6.753927</td>\n",
       "      <td>0.152713</td>\n",
       "      <td>4.612565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18499</th>\n",
       "      <td>-121.74</td>\n",
       "      <td>37.35</td>\n",
       "      <td>34.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>217.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>5.2327</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>4.731183</td>\n",
       "      <td>0.204545</td>\n",
       "      <td>2.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18619</th>\n",
       "      <td>-122.02</td>\n",
       "      <td>37.01</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1005.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>345.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>10.0968</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>7.790698</td>\n",
       "      <td>0.137313</td>\n",
       "      <td>2.674419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20163</th>\n",
       "      <td>-119.31</td>\n",
       "      <td>34.44</td>\n",
       "      <td>5.0</td>\n",
       "      <td>403.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>208.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>12.6320</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>7.462963</td>\n",
       "      <td>0.119107</td>\n",
       "      <td>3.851852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20174</th>\n",
       "      <td>-119.17</td>\n",
       "      <td>34.31</td>\n",
       "      <td>21.0</td>\n",
       "      <td>259.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>5.2681</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>5.755556</td>\n",
       "      <td>0.146718</td>\n",
       "      <td>3.155556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20180</th>\n",
       "      <td>-119.39</td>\n",
       "      <td>34.32</td>\n",
       "      <td>19.0</td>\n",
       "      <td>3238.0</td>\n",
       "      <td>629.0</td>\n",
       "      <td>1195.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>4.8472</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>7.309255</td>\n",
       "      <td>0.194256</td>\n",
       "      <td>2.697517</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20233</th>\n",
       "      <td>-119.29</td>\n",
       "      <td>34.24</td>\n",
       "      <td>27.0</td>\n",
       "      <td>4742.0</td>\n",
       "      <td>775.0</td>\n",
       "      <td>1682.0</td>\n",
       "      <td>696.0</td>\n",
       "      <td>6.1940</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>6.813218</td>\n",
       "      <td>0.163433</td>\n",
       "      <td>2.416667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20272</th>\n",
       "      <td>-119.23</td>\n",
       "      <td>34.19</td>\n",
       "      <td>16.0</td>\n",
       "      <td>5297.0</td>\n",
       "      <td>810.0</td>\n",
       "      <td>1489.0</td>\n",
       "      <td>667.0</td>\n",
       "      <td>6.4522</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>7.941529</td>\n",
       "      <td>0.152917</td>\n",
       "      <td>2.232384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20273</th>\n",
       "      <td>-119.23</td>\n",
       "      <td>34.17</td>\n",
       "      <td>18.0</td>\n",
       "      <td>6171.0</td>\n",
       "      <td>1490.0</td>\n",
       "      <td>2164.0</td>\n",
       "      <td>1210.0</td>\n",
       "      <td>3.6875</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>5.100000</td>\n",
       "      <td>0.241452</td>\n",
       "      <td>1.788430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20322</th>\n",
       "      <td>-119.14</td>\n",
       "      <td>34.23</td>\n",
       "      <td>8.0</td>\n",
       "      <td>243.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>2.5714</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>3.037500</td>\n",
       "      <td>0.308642</td>\n",
       "      <td>1.275000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20325</th>\n",
       "      <td>-119.04</td>\n",
       "      <td>34.28</td>\n",
       "      <td>21.0</td>\n",
       "      <td>1856.0</td>\n",
       "      <td>276.0</td>\n",
       "      <td>863.0</td>\n",
       "      <td>255.0</td>\n",
       "      <td>4.5833</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>7.278431</td>\n",
       "      <td>0.148707</td>\n",
       "      <td>3.384314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20326</th>\n",
       "      <td>-118.96</td>\n",
       "      <td>34.30</td>\n",
       "      <td>16.0</td>\n",
       "      <td>3103.0</td>\n",
       "      <td>482.0</td>\n",
       "      <td>1567.0</td>\n",
       "      <td>467.0</td>\n",
       "      <td>6.9070</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>6.644540</td>\n",
       "      <td>0.155334</td>\n",
       "      <td>3.355460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20335</th>\n",
       "      <td>-118.94</td>\n",
       "      <td>34.24</td>\n",
       "      <td>5.0</td>\n",
       "      <td>10018.0</td>\n",
       "      <td>1233.0</td>\n",
       "      <td>4253.0</td>\n",
       "      <td>1120.0</td>\n",
       "      <td>8.9063</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>8.944643</td>\n",
       "      <td>0.123078</td>\n",
       "      <td>3.797321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20367</th>\n",
       "      <td>-118.94</td>\n",
       "      <td>34.16</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1170.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>493.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>8.0428</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>8.239437</td>\n",
       "      <td>0.126496</td>\n",
       "      <td>3.471831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20380</th>\n",
       "      <td>-118.83</td>\n",
       "      <td>34.14</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1316.0</td>\n",
       "      <td>194.0</td>\n",
       "      <td>450.0</td>\n",
       "      <td>173.0</td>\n",
       "      <td>10.1597</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>7.606936</td>\n",
       "      <td>0.147416</td>\n",
       "      <td>2.601156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20389</th>\n",
       "      <td>-118.90</td>\n",
       "      <td>34.19</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1582.0</td>\n",
       "      <td>196.0</td>\n",
       "      <td>573.0</td>\n",
       "      <td>182.0</td>\n",
       "      <td>10.0595</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>8.692308</td>\n",
       "      <td>0.123894</td>\n",
       "      <td>3.148352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20422</th>\n",
       "      <td>-118.90</td>\n",
       "      <td>34.14</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1503.0</td>\n",
       "      <td>263.0</td>\n",
       "      <td>576.0</td>\n",
       "      <td>216.0</td>\n",
       "      <td>5.1457</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>6.958333</td>\n",
       "      <td>0.174983</td>\n",
       "      <td>2.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20426</th>\n",
       "      <td>-118.69</td>\n",
       "      <td>34.18</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1177.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>415.0</td>\n",
       "      <td>119.0</td>\n",
       "      <td>10.0472</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>9.890756</td>\n",
       "      <td>0.117247</td>\n",
       "      <td>3.487395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20427</th>\n",
       "      <td>-118.80</td>\n",
       "      <td>34.19</td>\n",
       "      <td>4.0</td>\n",
       "      <td>15572.0</td>\n",
       "      <td>2222.0</td>\n",
       "      <td>5495.0</td>\n",
       "      <td>2152.0</td>\n",
       "      <td>8.6499</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>7.236059</td>\n",
       "      <td>0.142692</td>\n",
       "      <td>2.553439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20436</th>\n",
       "      <td>-118.69</td>\n",
       "      <td>34.21</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3663.0</td>\n",
       "      <td>409.0</td>\n",
       "      <td>1179.0</td>\n",
       "      <td>371.0</td>\n",
       "      <td>12.5420</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>9.873315</td>\n",
       "      <td>0.111657</td>\n",
       "      <td>3.177898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20443</th>\n",
       "      <td>-118.85</td>\n",
       "      <td>34.27</td>\n",
       "      <td>50.0</td>\n",
       "      <td>187.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>3.3438</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5.342857</td>\n",
       "      <td>0.176471</td>\n",
       "      <td>3.714286</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>965 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "89       -122.27     37.80                52.0        249.0            78.0   \n",
       "459      -122.25     37.87                52.0        609.0           236.0   \n",
       "493      -122.24     37.86                52.0       1668.0           225.0   \n",
       "494      -122.24     37.85                52.0       3726.0           474.0   \n",
       "509      -122.23     37.83                52.0       2990.0           379.0   \n",
       "510      -122.22     37.82                39.0       2492.0           310.0   \n",
       "511      -122.22     37.82                42.0       2991.0           335.0   \n",
       "512      -122.23     37.82                52.0       3242.0           366.0   \n",
       "514      -122.23     37.82                52.0       3494.0           396.0   \n",
       "517      -122.23     37.82                52.0       1611.0           203.0   \n",
       "923      -121.89     37.49                 9.0       4909.0           577.0   \n",
       "955      -121.93     37.66                24.0       3166.0           424.0   \n",
       "1574     -122.03     37.83                24.0       5948.0           738.0   \n",
       "1582     -122.00     37.86                18.0       8953.0          1074.0   \n",
       "1583     -121.97     37.87                 4.0       1029.0           126.0   \n",
       "1585     -122.00     37.84                16.0       7681.0           946.0   \n",
       "1586     -121.96     37.85                10.0       3209.0           379.0   \n",
       "1591     -122.12     37.94                22.0       4949.0           626.0   \n",
       "1593     -122.14     37.90                32.0       5738.0           746.0   \n",
       "1617     -122.08     37.84                17.0       1320.0           159.0   \n",
       "1621     -122.08     37.82                 4.0       2045.0           237.0   \n",
       "1636     -122.18     37.91                31.0       7200.0           876.0   \n",
       "1637     -122.20     37.90                36.0       2107.0           287.0   \n",
       "1638     -122.18     37.90                36.0       4760.0           610.0   \n",
       "1644     -121.94     37.83                11.0       2836.0           373.0   \n",
       "1645     -121.89     37.82                 4.0      11444.0          1355.0   \n",
       "1646     -121.91     37.81                 7.0       3477.0           416.0   \n",
       "1914     -120.10     38.91                33.0       1561.0           282.0   \n",
       "3486     -118.54     34.28                10.0       7665.0           999.0   \n",
       "3533     -118.54     34.26                23.0       4960.0           592.0   \n",
       "...          ...       ...                 ...          ...             ...   \n",
       "18361    -122.14     37.36                23.0      11294.0          1377.0   \n",
       "18362    -122.15     37.35                23.0       3814.0           485.0   \n",
       "18363    -122.11     37.31                 7.0        189.0            26.0   \n",
       "18364    -122.12     37.29                11.0        436.0            70.0   \n",
       "18366    -122.08     37.24                21.0        427.0            63.0   \n",
       "18380    -121.86     37.21                23.0       2552.0           305.0   \n",
       "18381    -121.87     37.21                18.0       1080.0           122.0   \n",
       "18382    -121.83     37.23                 7.0       5389.0           903.0   \n",
       "18461    -121.76     37.26                17.0        250.0            52.0   \n",
       "18464    -121.74     37.19                11.0       1290.0           197.0   \n",
       "18499    -121.74     37.35                34.0        440.0            90.0   \n",
       "18619    -122.02     37.01                20.0       1005.0           138.0   \n",
       "20163    -119.31     34.44                 5.0        403.0            48.0   \n",
       "20174    -119.17     34.31                21.0        259.0            38.0   \n",
       "20180    -119.39     34.32                19.0       3238.0           629.0   \n",
       "20233    -119.29     34.24                27.0       4742.0           775.0   \n",
       "20272    -119.23     34.19                16.0       5297.0           810.0   \n",
       "20273    -119.23     34.17                18.0       6171.0          1490.0   \n",
       "20322    -119.14     34.23                 8.0        243.0            75.0   \n",
       "20325    -119.04     34.28                21.0       1856.0           276.0   \n",
       "20326    -118.96     34.30                16.0       3103.0           482.0   \n",
       "20335    -118.94     34.24                 5.0      10018.0          1233.0   \n",
       "20367    -118.94     34.16                 3.0       1170.0           148.0   \n",
       "20380    -118.83     34.14                16.0       1316.0           194.0   \n",
       "20389    -118.90     34.19                26.0       1582.0           196.0   \n",
       "20422    -118.90     34.14                35.0       1503.0           263.0   \n",
       "20426    -118.69     34.18                11.0       1177.0           138.0   \n",
       "20427    -118.80     34.19                 4.0      15572.0          2222.0   \n",
       "20436    -118.69     34.21                10.0       3663.0           409.0   \n",
       "20443    -118.85     34.27                50.0        187.0            33.0   \n",
       "\n",
       "       population  households  median_income  median_house_value  \\\n",
       "89          396.0        85.0         1.2434            500001.0   \n",
       "459        1349.0       250.0         1.1696            500001.0   \n",
       "493         517.0       214.0         7.8521            500001.0   \n",
       "494        1366.0       496.0         9.3959            500001.0   \n",
       "509         947.0       361.0         7.8772            500001.0   \n",
       "510         808.0       315.0        11.8603            500001.0   \n",
       "511        1018.0       335.0        13.4990            500001.0   \n",
       "512        1001.0       352.0        12.2138            500001.0   \n",
       "514        1192.0       383.0        12.3804            500001.0   \n",
       "517         556.0       179.0         8.7477            500001.0   \n",
       "923        1981.0       591.0         9.7194            500001.0   \n",
       "955        1081.0       400.0         8.3337            500001.0   \n",
       "1574       1997.0       710.0         9.8708            500001.0   \n",
       "1582       3011.0       993.0        10.7372            500001.0   \n",
       "1583        416.0       122.0        13.4883            500001.0   \n",
       "1585       2777.0       908.0         9.5271            500001.0   \n",
       "1586       1199.0       392.0        12.2478            500001.0   \n",
       "1591       1850.0       590.0        10.4549            500001.0   \n",
       "1593       2099.0       732.0        10.3224            500001.0   \n",
       "1617       1722.0       141.0        11.7064            500001.0   \n",
       "1621        830.0       252.0        11.3421            500001.0   \n",
       "1636       2428.0       843.0        10.9405            500001.0   \n",
       "1637        740.0       280.0        10.3416            500001.0   \n",
       "1638       1511.0       572.0         9.0064            500001.0   \n",
       "1644        959.0       335.0        10.5815            500001.0   \n",
       "1645       3898.0      1257.0        13.2949            500001.0   \n",
       "1646       1216.0       395.0        13.1499            500001.0   \n",
       "1914         30.0        11.0         1.8750            500001.0   \n",
       "3486       3517.0       998.0        10.8805            500001.0   \n",
       "3533       1929.0       586.0        10.9052            500001.0   \n",
       "...           ...         ...            ...                 ...   \n",
       "18361      3840.0      1367.0        12.1387            500001.0   \n",
       "18362      1344.0       464.0        12.9792            500001.0   \n",
       "18363        84.0        29.0        13.8093            500001.0   \n",
       "18364       212.0        75.0         8.6196            500001.0   \n",
       "18366       182.0        70.0        11.3283            500001.0   \n",
       "18380       916.0       316.0         9.1974            500001.0   \n",
       "18381       382.0       121.0         9.0800            500001.0   \n",
       "18382      2232.0       825.0         6.6659            500001.0   \n",
       "18461       141.0        51.0         4.6458            500001.0   \n",
       "18464       881.0       191.0         4.2039            500001.0   \n",
       "18499       217.0        93.0         5.2327            500001.0   \n",
       "18619       345.0       129.0        10.0968            500001.0   \n",
       "20163       208.0        54.0        12.6320            500001.0   \n",
       "20174       142.0        45.0         5.2681            500001.0   \n",
       "20180      1195.0       443.0         4.8472            500001.0   \n",
       "20233      1682.0       696.0         6.1940            500001.0   \n",
       "20272      1489.0       667.0         6.4522            500001.0   \n",
       "20273      2164.0      1210.0         3.6875            500001.0   \n",
       "20322       102.0        80.0         2.5714            500001.0   \n",
       "20325       863.0       255.0         4.5833            500001.0   \n",
       "20326      1567.0       467.0         6.9070            500001.0   \n",
       "20335      4253.0      1120.0         8.9063            500001.0   \n",
       "20367       493.0       142.0         8.0428            500001.0   \n",
       "20380       450.0       173.0        10.1597            500001.0   \n",
       "20389       573.0       182.0        10.0595            500001.0   \n",
       "20422       576.0       216.0         5.1457            500001.0   \n",
       "20426       415.0       119.0        10.0472            500001.0   \n",
       "20427      5495.0      2152.0         8.6499            500001.0   \n",
       "20436      1179.0       371.0        12.5420            500001.0   \n",
       "20443       130.0        35.0         3.3438            500001.0   \n",
       "\n",
       "      ocean_proximity  rooms_per_household  bedrooms_per_room  \\\n",
       "89           NEAR BAY             2.929412           0.313253   \n",
       "459          NEAR BAY             2.436000           0.387521   \n",
       "493          NEAR BAY             7.794393           0.134892   \n",
       "494          NEAR BAY             7.512097           0.127214   \n",
       "509          NEAR BAY             8.282548           0.126756   \n",
       "510          NEAR BAY             7.911111           0.124398   \n",
       "511          NEAR BAY             8.928358           0.112003   \n",
       "512          NEAR BAY             9.210227           0.112893   \n",
       "514          NEAR BAY             9.122715           0.113337   \n",
       "517          NEAR BAY             9.000000           0.126009   \n",
       "923         <1H OCEAN             8.306261           0.117539   \n",
       "955         <1H OCEAN             7.915000           0.133923   \n",
       "1574         NEAR BAY             8.377465           0.124075   \n",
       "1582        <1H OCEAN             9.016113           0.119960   \n",
       "1583           INLAND             8.434426           0.122449   \n",
       "1585        <1H OCEAN             8.459251           0.123161   \n",
       "1586           INLAND             8.186224           0.118105   \n",
       "1591         NEAR BAY             8.388136           0.126490   \n",
       "1593         NEAR BAY             7.838798           0.130010   \n",
       "1617         NEAR BAY             9.361702           0.120455   \n",
       "1621         NEAR BAY             8.115079           0.115892   \n",
       "1636         NEAR BAY             8.540925           0.121667   \n",
       "1637         NEAR BAY             7.525000           0.136213   \n",
       "1638         NEAR BAY             8.321678           0.128151   \n",
       "1644           INLAND             8.465672           0.131523   \n",
       "1645           INLAND             9.104216           0.118403   \n",
       "1646           INLAND             8.802532           0.119643   \n",
       "1914           INLAND           141.909091           0.180653   \n",
       "3486        <1H OCEAN             7.680361           0.130333   \n",
       "3533        <1H OCEAN             8.464164           0.119355   \n",
       "...               ...                  ...                ...   \n",
       "18361        NEAR BAY             8.261887           0.121923   \n",
       "18362        NEAR BAY             8.219828           0.127163   \n",
       "18363       <1H OCEAN             6.517241           0.137566   \n",
       "18364       <1H OCEAN             5.813333           0.160550   \n",
       "18366       <1H OCEAN             6.100000           0.147541   \n",
       "18380       <1H OCEAN             8.075949           0.119514   \n",
       "18381       <1H OCEAN             8.925620           0.112963   \n",
       "18382       <1H OCEAN             6.532121           0.167564   \n",
       "18461       <1H OCEAN             4.901961           0.208000   \n",
       "18464       <1H OCEAN             6.753927           0.152713   \n",
       "18499       <1H OCEAN             4.731183           0.204545   \n",
       "18619      NEAR OCEAN             7.790698           0.137313   \n",
       "20163      NEAR OCEAN             7.462963           0.119107   \n",
       "20174      NEAR OCEAN             5.755556           0.146718   \n",
       "20180      NEAR OCEAN             7.309255           0.194256   \n",
       "20233      NEAR OCEAN             6.813218           0.163433   \n",
       "20272      NEAR OCEAN             7.941529           0.152917   \n",
       "20273      NEAR OCEAN             5.100000           0.241452   \n",
       "20322      NEAR OCEAN             3.037500           0.308642   \n",
       "20325       <1H OCEAN             7.278431           0.148707   \n",
       "20326       <1H OCEAN             6.644540           0.155334   \n",
       "20335       <1H OCEAN             8.944643           0.123078   \n",
       "20367       <1H OCEAN             8.239437           0.126496   \n",
       "20380      NEAR OCEAN             7.606936           0.147416   \n",
       "20389       <1H OCEAN             8.692308           0.123894   \n",
       "20422       <1H OCEAN             6.958333           0.174983   \n",
       "20426       <1H OCEAN             9.890756           0.117247   \n",
       "20427       <1H OCEAN             7.236059           0.142692   \n",
       "20436       <1H OCEAN             9.873315           0.111657   \n",
       "20443       <1H OCEAN             5.342857           0.176471   \n",
       "\n",
       "       population_per_househol  \n",
       "89                    4.658824  \n",
       "459                   5.396000  \n",
       "493                   2.415888  \n",
       "494                   2.754032  \n",
       "509                   2.623269  \n",
       "510                   2.565079  \n",
       "511                   3.038806  \n",
       "512                   2.843750  \n",
       "514                   3.112272  \n",
       "517                   3.106145  \n",
       "923                   3.351946  \n",
       "955                   2.702500  \n",
       "1574                  2.812676  \n",
       "1582                  3.032226  \n",
       "1583                  3.409836  \n",
       "1585                  3.058370  \n",
       "1586                  3.058673  \n",
       "1591                  3.135593  \n",
       "1593                  2.867486  \n",
       "1617                 12.212766  \n",
       "1621                  3.293651  \n",
       "1636                  2.880190  \n",
       "1637                  2.642857  \n",
       "1638                  2.641608  \n",
       "1644                  2.862687  \n",
       "1645                  3.101034  \n",
       "1646                  3.078481  \n",
       "1914                  2.727273  \n",
       "3486                  3.524048  \n",
       "3533                  3.291809  \n",
       "...                        ...  \n",
       "18361                 2.809071  \n",
       "18362                 2.896552  \n",
       "18363                 2.896552  \n",
       "18364                 2.826667  \n",
       "18366                 2.600000  \n",
       "18380                 2.898734  \n",
       "18381                 3.157025  \n",
       "18382                 2.705455  \n",
       "18461                 2.764706  \n",
       "18464                 4.612565  \n",
       "18499                 2.333333  \n",
       "18619                 2.674419  \n",
       "20163                 3.851852  \n",
       "20174                 3.155556  \n",
       "20180                 2.697517  \n",
       "20233                 2.416667  \n",
       "20272                 2.232384  \n",
       "20273                 1.788430  \n",
       "20322                 1.275000  \n",
       "20325                 3.384314  \n",
       "20326                 3.355460  \n",
       "20335                 3.797321  \n",
       "20367                 3.471831  \n",
       "20380                 2.601156  \n",
       "20389                 3.148352  \n",
       "20422                 2.666667  \n",
       "20426                 3.487395  \n",
       "20427                 2.553439  \n",
       "20436                 3.177898  \n",
       "20443                 3.714286  \n",
       "\n",
       "[965 rows x 13 columns]"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing[housing['median_house_value'] > 500000]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On dirait que notre colonne `median_house_value` contient des outliers. L'outlier est sous forme du nombre **500001.0** qui est louche puisque cette médiane est commune à toute les arrondissements."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2860a6d6438>"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing.boxplot(column='total_rooms', figsize=(20,15))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "      <th>ocean_proximity</th>\n",
       "      <th>rooms_per_household</th>\n",
       "      <th>bedrooms_per_room</th>\n",
       "      <th>population_per_househol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-122.22</td>\n",
       "      <td>37.86</td>\n",
       "      <td>21.0</td>\n",
       "      <td>7099.0</td>\n",
       "      <td>1106.0</td>\n",
       "      <td>2401.0</td>\n",
       "      <td>1138.0</td>\n",
       "      <td>8.3014</td>\n",
       "      <td>358500.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>6.238137</td>\n",
       "      <td>0.155797</td>\n",
       "      <td>2.109842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>-122.26</td>\n",
       "      <td>37.80</td>\n",
       "      <td>36.0</td>\n",
       "      <td>5329.0</td>\n",
       "      <td>2477.0</td>\n",
       "      <td>3469.0</td>\n",
       "      <td>2323.0</td>\n",
       "      <td>2.0096</td>\n",
       "      <td>130000.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>2.294016</td>\n",
       "      <td>0.464815</td>\n",
       "      <td>1.493328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.81</td>\n",
       "      <td>28.0</td>\n",
       "      <td>5806.0</td>\n",
       "      <td>1603.0</td>\n",
       "      <td>2563.0</td>\n",
       "      <td>1497.0</td>\n",
       "      <td>3.2177</td>\n",
       "      <td>273400.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>3.878424</td>\n",
       "      <td>0.276094</td>\n",
       "      <td>1.712091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>-122.26</td>\n",
       "      <td>37.81</td>\n",
       "      <td>34.0</td>\n",
       "      <td>5871.0</td>\n",
       "      <td>1914.0</td>\n",
       "      <td>2689.0</td>\n",
       "      <td>1789.0</td>\n",
       "      <td>2.8406</td>\n",
       "      <td>335700.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>3.281722</td>\n",
       "      <td>0.326009</td>\n",
       "      <td>1.503074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.83</td>\n",
       "      <td>28.0</td>\n",
       "      <td>5022.0</td>\n",
       "      <td>1750.0</td>\n",
       "      <td>2558.0</td>\n",
       "      <td>1661.0</td>\n",
       "      <td>2.4234</td>\n",
       "      <td>218500.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>3.023480</td>\n",
       "      <td>0.348467</td>\n",
       "      <td>1.540036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>-122.22</td>\n",
       "      <td>37.85</td>\n",
       "      <td>28.0</td>\n",
       "      <td>5287.0</td>\n",
       "      <td>1048.0</td>\n",
       "      <td>2031.0</td>\n",
       "      <td>956.0</td>\n",
       "      <td>5.4570</td>\n",
       "      <td>337300.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>5.530335</td>\n",
       "      <td>0.198222</td>\n",
       "      <td>2.124477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>-122.21</td>\n",
       "      <td>37.83</td>\n",
       "      <td>34.0</td>\n",
       "      <td>5065.0</td>\n",
       "      <td>788.0</td>\n",
       "      <td>1627.0</td>\n",
       "      <td>766.0</td>\n",
       "      <td>6.8976</td>\n",
       "      <td>333300.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>6.612272</td>\n",
       "      <td>0.155577</td>\n",
       "      <td>2.124021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>-122.23</td>\n",
       "      <td>37.79</td>\n",
       "      <td>43.0</td>\n",
       "      <td>5963.0</td>\n",
       "      <td>1344.0</td>\n",
       "      <td>4367.0</td>\n",
       "      <td>1231.0</td>\n",
       "      <td>2.1917</td>\n",
       "      <td>112800.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>4.844029</td>\n",
       "      <td>0.225390</td>\n",
       "      <td>3.547522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>283</th>\n",
       "      <td>-122.16</td>\n",
       "      <td>37.79</td>\n",
       "      <td>22.0</td>\n",
       "      <td>12842.0</td>\n",
       "      <td>2048.0</td>\n",
       "      <td>4985.0</td>\n",
       "      <td>1967.0</td>\n",
       "      <td>5.9849</td>\n",
       "      <td>371000.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>6.528724</td>\n",
       "      <td>0.159477</td>\n",
       "      <td>2.534316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>391</th>\n",
       "      <td>-122.30</td>\n",
       "      <td>37.90</td>\n",
       "      <td>15.0</td>\n",
       "      <td>5083.0</td>\n",
       "      <td>1212.0</td>\n",
       "      <td>2420.0</td>\n",
       "      <td>1146.0</td>\n",
       "      <td>4.5824</td>\n",
       "      <td>256100.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>4.435428</td>\n",
       "      <td>0.238442</td>\n",
       "      <td>2.111693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>485</th>\n",
       "      <td>-122.26</td>\n",
       "      <td>37.86</td>\n",
       "      <td>35.0</td>\n",
       "      <td>5161.0</td>\n",
       "      <td>1744.0</td>\n",
       "      <td>3276.0</td>\n",
       "      <td>1742.0</td>\n",
       "      <td>1.6307</td>\n",
       "      <td>253600.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>2.962687</td>\n",
       "      <td>0.337919</td>\n",
       "      <td>1.880597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508</th>\n",
       "      <td>-122.30</td>\n",
       "      <td>37.84</td>\n",
       "      <td>14.0</td>\n",
       "      <td>7355.0</td>\n",
       "      <td>2408.0</td>\n",
       "      <td>3100.0</td>\n",
       "      <td>2051.0</td>\n",
       "      <td>4.0018</td>\n",
       "      <td>143800.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>3.586056</td>\n",
       "      <td>0.327396</td>\n",
       "      <td>1.511458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>538</th>\n",
       "      <td>-122.28</td>\n",
       "      <td>37.78</td>\n",
       "      <td>29.0</td>\n",
       "      <td>5154.0</td>\n",
       "      <td>435.0</td>\n",
       "      <td>3741.0</td>\n",
       "      <td>1273.0</td>\n",
       "      <td>2.5762</td>\n",
       "      <td>173400.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>4.048704</td>\n",
       "      <td>0.084400</td>\n",
       "      <td>2.938727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>568</th>\n",
       "      <td>-122.24</td>\n",
       "      <td>37.73</td>\n",
       "      <td>21.0</td>\n",
       "      <td>7031.0</td>\n",
       "      <td>1249.0</td>\n",
       "      <td>2930.0</td>\n",
       "      <td>1235.0</td>\n",
       "      <td>4.5213</td>\n",
       "      <td>228400.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>5.693117</td>\n",
       "      <td>0.177642</td>\n",
       "      <td>2.372470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>570</th>\n",
       "      <td>-122.24</td>\n",
       "      <td>37.72</td>\n",
       "      <td>5.0</td>\n",
       "      <td>18634.0</td>\n",
       "      <td>2885.0</td>\n",
       "      <td>7427.0</td>\n",
       "      <td>2718.0</td>\n",
       "      <td>7.6110</td>\n",
       "      <td>350700.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>6.855776</td>\n",
       "      <td>0.154825</td>\n",
       "      <td>2.732524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>571</th>\n",
       "      <td>-122.27</td>\n",
       "      <td>37.73</td>\n",
       "      <td>31.0</td>\n",
       "      <td>5785.0</td>\n",
       "      <td>1379.0</td>\n",
       "      <td>2973.0</td>\n",
       "      <td>1312.0</td>\n",
       "      <td>3.2689</td>\n",
       "      <td>231000.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>4.409299</td>\n",
       "      <td>0.238375</td>\n",
       "      <td>2.266006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>573</th>\n",
       "      <td>-122.27</td>\n",
       "      <td>37.74</td>\n",
       "      <td>28.0</td>\n",
       "      <td>6909.0</td>\n",
       "      <td>1554.0</td>\n",
       "      <td>2974.0</td>\n",
       "      <td>1484.0</td>\n",
       "      <td>3.6875</td>\n",
       "      <td>353900.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>4.655660</td>\n",
       "      <td>0.224924</td>\n",
       "      <td>2.004043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>574</th>\n",
       "      <td>-122.27</td>\n",
       "      <td>37.77</td>\n",
       "      <td>23.0</td>\n",
       "      <td>5679.0</td>\n",
       "      <td>1270.0</td>\n",
       "      <td>2690.0</td>\n",
       "      <td>1151.0</td>\n",
       "      <td>4.7695</td>\n",
       "      <td>291700.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>4.933970</td>\n",
       "      <td>0.223631</td>\n",
       "      <td>2.337098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>576</th>\n",
       "      <td>-122.06</td>\n",
       "      <td>37.77</td>\n",
       "      <td>12.0</td>\n",
       "      <td>14316.0</td>\n",
       "      <td>2045.0</td>\n",
       "      <td>5781.0</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>7.2634</td>\n",
       "      <td>341600.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>7.133034</td>\n",
       "      <td>0.142847</td>\n",
       "      <td>2.880419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>592</th>\n",
       "      <td>-122.10</td>\n",
       "      <td>37.71</td>\n",
       "      <td>27.0</td>\n",
       "      <td>6740.0</td>\n",
       "      <td>1073.0</td>\n",
       "      <td>2723.0</td>\n",
       "      <td>1035.0</td>\n",
       "      <td>5.2131</td>\n",
       "      <td>252500.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>6.512077</td>\n",
       "      <td>0.159199</td>\n",
       "      <td>2.630918</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>605</th>\n",
       "      <td>-122.07</td>\n",
       "      <td>37.69</td>\n",
       "      <td>31.0</td>\n",
       "      <td>5914.0</td>\n",
       "      <td>1309.0</td>\n",
       "      <td>2999.0</td>\n",
       "      <td>1295.0</td>\n",
       "      <td>3.0964</td>\n",
       "      <td>190500.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>4.566795</td>\n",
       "      <td>0.221339</td>\n",
       "      <td>2.315830</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>654</th>\n",
       "      <td>-122.15</td>\n",
       "      <td>37.71</td>\n",
       "      <td>18.0</td>\n",
       "      <td>5778.0</td>\n",
       "      <td>1526.0</td>\n",
       "      <td>2441.0</td>\n",
       "      <td>1352.0</td>\n",
       "      <td>3.1682</td>\n",
       "      <td>202700.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>4.273669</td>\n",
       "      <td>0.264105</td>\n",
       "      <td>1.805473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>706</th>\n",
       "      <td>-122.04</td>\n",
       "      <td>37.65</td>\n",
       "      <td>10.0</td>\n",
       "      <td>8299.0</td>\n",
       "      <td>1326.0</td>\n",
       "      <td>3827.0</td>\n",
       "      <td>1288.0</td>\n",
       "      <td>6.2579</td>\n",
       "      <td>315500.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>6.443323</td>\n",
       "      <td>0.159778</td>\n",
       "      <td>2.971273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>707</th>\n",
       "      <td>-122.05</td>\n",
       "      <td>37.68</td>\n",
       "      <td>23.0</td>\n",
       "      <td>7518.0</td>\n",
       "      <td>1279.0</td>\n",
       "      <td>3827.0</td>\n",
       "      <td>1294.0</td>\n",
       "      <td>5.1701</td>\n",
       "      <td>216800.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>5.809892</td>\n",
       "      <td>0.170125</td>\n",
       "      <td>2.957496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709</th>\n",
       "      <td>-122.06</td>\n",
       "      <td>37.68</td>\n",
       "      <td>30.0</td>\n",
       "      <td>5367.0</td>\n",
       "      <td>1207.0</td>\n",
       "      <td>2667.0</td>\n",
       "      <td>1047.0</td>\n",
       "      <td>3.1796</td>\n",
       "      <td>170300.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>5.126074</td>\n",
       "      <td>0.224893</td>\n",
       "      <td>2.547278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>758</th>\n",
       "      <td>-122.07</td>\n",
       "      <td>37.66</td>\n",
       "      <td>21.0</td>\n",
       "      <td>5031.0</td>\n",
       "      <td>1168.0</td>\n",
       "      <td>2461.0</td>\n",
       "      <td>1042.0</td>\n",
       "      <td>3.8750</td>\n",
       "      <td>179300.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>4.828215</td>\n",
       "      <td>0.232161</td>\n",
       "      <td>2.361804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>761</th>\n",
       "      <td>-122.08</td>\n",
       "      <td>37.65</td>\n",
       "      <td>17.0</td>\n",
       "      <td>5018.0</td>\n",
       "      <td>1439.0</td>\n",
       "      <td>3069.0</td>\n",
       "      <td>1299.0</td>\n",
       "      <td>2.7694</td>\n",
       "      <td>161900.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>3.862972</td>\n",
       "      <td>0.286768</td>\n",
       "      <td>2.362587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>780</th>\n",
       "      <td>-122.10</td>\n",
       "      <td>37.63</td>\n",
       "      <td>18.0</td>\n",
       "      <td>9963.0</td>\n",
       "      <td>2031.0</td>\n",
       "      <td>5613.0</td>\n",
       "      <td>1946.0</td>\n",
       "      <td>3.8171</td>\n",
       "      <td>187200.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>5.119733</td>\n",
       "      <td>0.203854</td>\n",
       "      <td>2.884378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>794</th>\n",
       "      <td>-122.08</td>\n",
       "      <td>37.64</td>\n",
       "      <td>30.0</td>\n",
       "      <td>5267.0</td>\n",
       "      <td>1253.0</td>\n",
       "      <td>4065.0</td>\n",
       "      <td>1113.0</td>\n",
       "      <td>3.3479</td>\n",
       "      <td>182100.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>4.732255</td>\n",
       "      <td>0.237896</td>\n",
       "      <td>3.652291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>799</th>\n",
       "      <td>-122.07</td>\n",
       "      <td>37.64</td>\n",
       "      <td>22.0</td>\n",
       "      <td>5861.0</td>\n",
       "      <td>1516.0</td>\n",
       "      <td>5436.0</td>\n",
       "      <td>1463.0</td>\n",
       "      <td>2.5158</td>\n",
       "      <td>134900.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>4.006152</td>\n",
       "      <td>0.258659</td>\n",
       "      <td>3.715653</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20424</th>\n",
       "      <td>-118.75</td>\n",
       "      <td>34.18</td>\n",
       "      <td>4.0</td>\n",
       "      <td>16704.0</td>\n",
       "      <td>2704.0</td>\n",
       "      <td>6187.0</td>\n",
       "      <td>2207.0</td>\n",
       "      <td>6.6122</td>\n",
       "      <td>357600.0</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>7.568645</td>\n",
       "      <td>0.161877</td>\n",
       "      <td>2.803353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20425</th>\n",
       "      <td>-118.75</td>\n",
       "      <td>34.17</td>\n",
       "      <td>18.0</td>\n",
       "      <td>6217.0</td>\n",
       "      <td>858.0</td>\n",
       "      <td>2703.0</td>\n",
       "      <td>834.0</td>\n",
       "      <td>6.8075</td>\n",
       "      <td>325900.0</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>7.454436</td>\n",
       "      <td>0.138009</td>\n",
       "      <td>3.241007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20427</th>\n",
       "      <td>-118.80</td>\n",
       "      <td>34.19</td>\n",
       "      <td>4.0</td>\n",
       "      <td>15572.0</td>\n",
       "      <td>2222.0</td>\n",
       "      <td>5495.0</td>\n",
       "      <td>2152.0</td>\n",
       "      <td>8.6499</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>7.236059</td>\n",
       "      <td>0.142692</td>\n",
       "      <td>2.553439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20428</th>\n",
       "      <td>-118.83</td>\n",
       "      <td>34.23</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8803.0</td>\n",
       "      <td>1114.0</td>\n",
       "      <td>3385.0</td>\n",
       "      <td>1010.0</td>\n",
       "      <td>8.7288</td>\n",
       "      <td>425800.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>8.715842</td>\n",
       "      <td>0.126548</td>\n",
       "      <td>3.351485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20437</th>\n",
       "      <td>-118.81</td>\n",
       "      <td>34.25</td>\n",
       "      <td>4.0</td>\n",
       "      <td>9147.0</td>\n",
       "      <td>1827.0</td>\n",
       "      <td>3950.0</td>\n",
       "      <td>1661.0</td>\n",
       "      <td>5.7160</td>\n",
       "      <td>320800.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5.506924</td>\n",
       "      <td>0.199738</td>\n",
       "      <td>2.378085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20440</th>\n",
       "      <td>-118.77</td>\n",
       "      <td>34.24</td>\n",
       "      <td>6.0</td>\n",
       "      <td>16222.0</td>\n",
       "      <td>2309.0</td>\n",
       "      <td>6700.0</td>\n",
       "      <td>2080.0</td>\n",
       "      <td>6.4963</td>\n",
       "      <td>308100.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>7.799038</td>\n",
       "      <td>0.142338</td>\n",
       "      <td>3.221154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20444</th>\n",
       "      <td>-118.90</td>\n",
       "      <td>34.30</td>\n",
       "      <td>13.0</td>\n",
       "      <td>5591.0</td>\n",
       "      <td>1013.0</td>\n",
       "      <td>3188.0</td>\n",
       "      <td>971.0</td>\n",
       "      <td>5.5925</td>\n",
       "      <td>208600.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5.757981</td>\n",
       "      <td>0.181184</td>\n",
       "      <td>3.283213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20445</th>\n",
       "      <td>-118.83</td>\n",
       "      <td>34.33</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6679.0</td>\n",
       "      <td>1164.0</td>\n",
       "      <td>3196.0</td>\n",
       "      <td>1157.0</td>\n",
       "      <td>5.4493</td>\n",
       "      <td>242600.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5.772688</td>\n",
       "      <td>0.174278</td>\n",
       "      <td>2.762316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20450</th>\n",
       "      <td>-118.91</td>\n",
       "      <td>34.28</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6106.0</td>\n",
       "      <td>1134.0</td>\n",
       "      <td>3246.0</td>\n",
       "      <td>1062.0</td>\n",
       "      <td>5.2206</td>\n",
       "      <td>280200.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5.749529</td>\n",
       "      <td>0.185719</td>\n",
       "      <td>3.056497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20451</th>\n",
       "      <td>-118.90</td>\n",
       "      <td>34.26</td>\n",
       "      <td>5.0</td>\n",
       "      <td>25187.0</td>\n",
       "      <td>3521.0</td>\n",
       "      <td>11956.0</td>\n",
       "      <td>3478.0</td>\n",
       "      <td>6.9712</td>\n",
       "      <td>321300.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>7.241806</td>\n",
       "      <td>0.139794</td>\n",
       "      <td>3.437608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20460</th>\n",
       "      <td>-118.75</td>\n",
       "      <td>34.29</td>\n",
       "      <td>17.0</td>\n",
       "      <td>5512.0</td>\n",
       "      <td>435.0</td>\n",
       "      <td>2734.0</td>\n",
       "      <td>814.0</td>\n",
       "      <td>6.6073</td>\n",
       "      <td>258100.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>6.771499</td>\n",
       "      <td>0.078919</td>\n",
       "      <td>3.358722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20486</th>\n",
       "      <td>-118.68</td>\n",
       "      <td>34.28</td>\n",
       "      <td>17.0</td>\n",
       "      <td>6488.0</td>\n",
       "      <td>1102.0</td>\n",
       "      <td>3199.0</td>\n",
       "      <td>1070.0</td>\n",
       "      <td>5.0962</td>\n",
       "      <td>238000.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>6.063551</td>\n",
       "      <td>0.169852</td>\n",
       "      <td>2.989720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20487</th>\n",
       "      <td>-118.67</td>\n",
       "      <td>34.30</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6123.0</td>\n",
       "      <td>825.0</td>\n",
       "      <td>2440.0</td>\n",
       "      <td>736.0</td>\n",
       "      <td>7.9013</td>\n",
       "      <td>393000.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>8.319293</td>\n",
       "      <td>0.134738</td>\n",
       "      <td>3.315217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20488</th>\n",
       "      <td>-118.68</td>\n",
       "      <td>34.28</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6150.0</td>\n",
       "      <td>1265.0</td>\n",
       "      <td>3188.0</td>\n",
       "      <td>1266.0</td>\n",
       "      <td>4.7034</td>\n",
       "      <td>223000.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>4.857820</td>\n",
       "      <td>0.205691</td>\n",
       "      <td>2.518167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20504</th>\n",
       "      <td>-118.73</td>\n",
       "      <td>34.29</td>\n",
       "      <td>11.0</td>\n",
       "      <td>5451.0</td>\n",
       "      <td>736.0</td>\n",
       "      <td>2526.0</td>\n",
       "      <td>752.0</td>\n",
       "      <td>7.3550</td>\n",
       "      <td>343900.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>7.248670</td>\n",
       "      <td>0.135021</td>\n",
       "      <td>3.359043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20507</th>\n",
       "      <td>-121.52</td>\n",
       "      <td>38.59</td>\n",
       "      <td>35.0</td>\n",
       "      <td>6418.0</td>\n",
       "      <td>1545.0</td>\n",
       "      <td>3814.0</td>\n",
       "      <td>1496.0</td>\n",
       "      <td>1.6647</td>\n",
       "      <td>69100.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>4.290107</td>\n",
       "      <td>0.240729</td>\n",
       "      <td>2.549465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20509</th>\n",
       "      <td>-121.53</td>\n",
       "      <td>38.60</td>\n",
       "      <td>25.0</td>\n",
       "      <td>5154.0</td>\n",
       "      <td>1105.0</td>\n",
       "      <td>3196.0</td>\n",
       "      <td>1073.0</td>\n",
       "      <td>2.7566</td>\n",
       "      <td>80200.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>4.803355</td>\n",
       "      <td>0.214397</td>\n",
       "      <td>2.978565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20524</th>\n",
       "      <td>-121.55</td>\n",
       "      <td>38.55</td>\n",
       "      <td>10.0</td>\n",
       "      <td>6227.0</td>\n",
       "      <td>1164.0</td>\n",
       "      <td>2909.0</td>\n",
       "      <td>1077.0</td>\n",
       "      <td>4.1060</td>\n",
       "      <td>115900.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>5.781801</td>\n",
       "      <td>0.186928</td>\n",
       "      <td>2.701021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20528</th>\n",
       "      <td>-121.80</td>\n",
       "      <td>38.55</td>\n",
       "      <td>11.0</td>\n",
       "      <td>5121.0</td>\n",
       "      <td>899.0</td>\n",
       "      <td>2258.0</td>\n",
       "      <td>901.0</td>\n",
       "      <td>4.7168</td>\n",
       "      <td>223200.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>5.683685</td>\n",
       "      <td>0.175552</td>\n",
       "      <td>2.506104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20529</th>\n",
       "      <td>-121.78</td>\n",
       "      <td>38.55</td>\n",
       "      <td>12.0</td>\n",
       "      <td>10509.0</td>\n",
       "      <td>2186.0</td>\n",
       "      <td>5633.0</td>\n",
       "      <td>2138.0</td>\n",
       "      <td>2.9605</td>\n",
       "      <td>204300.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>4.915341</td>\n",
       "      <td>0.208012</td>\n",
       "      <td>2.634705</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20530</th>\n",
       "      <td>-121.76</td>\n",
       "      <td>38.57</td>\n",
       "      <td>11.0</td>\n",
       "      <td>15018.0</td>\n",
       "      <td>3008.0</td>\n",
       "      <td>7984.0</td>\n",
       "      <td>2962.0</td>\n",
       "      <td>3.1371</td>\n",
       "      <td>201800.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>5.070223</td>\n",
       "      <td>0.200293</td>\n",
       "      <td>2.695476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20533</th>\n",
       "      <td>-121.67</td>\n",
       "      <td>38.54</td>\n",
       "      <td>13.0</td>\n",
       "      <td>6141.0</td>\n",
       "      <td>1019.0</td>\n",
       "      <td>2553.0</td>\n",
       "      <td>967.0</td>\n",
       "      <td>4.2432</td>\n",
       "      <td>326500.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>6.350569</td>\n",
       "      <td>0.165934</td>\n",
       "      <td>2.640124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20539</th>\n",
       "      <td>-121.71</td>\n",
       "      <td>38.56</td>\n",
       "      <td>20.0</td>\n",
       "      <td>8627.0</td>\n",
       "      <td>1516.0</td>\n",
       "      <td>4071.0</td>\n",
       "      <td>1466.0</td>\n",
       "      <td>4.2198</td>\n",
       "      <td>164100.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>5.884720</td>\n",
       "      <td>0.175727</td>\n",
       "      <td>2.776944</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20541</th>\n",
       "      <td>-121.70</td>\n",
       "      <td>38.54</td>\n",
       "      <td>13.0</td>\n",
       "      <td>6819.0</td>\n",
       "      <td>1158.0</td>\n",
       "      <td>2828.0</td>\n",
       "      <td>1115.0</td>\n",
       "      <td>4.6225</td>\n",
       "      <td>226500.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>6.115695</td>\n",
       "      <td>0.169820</td>\n",
       "      <td>2.536323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20543</th>\n",
       "      <td>-121.74</td>\n",
       "      <td>38.55</td>\n",
       "      <td>33.0</td>\n",
       "      <td>6861.0</td>\n",
       "      <td>1820.0</td>\n",
       "      <td>3717.0</td>\n",
       "      <td>1767.0</td>\n",
       "      <td>1.7311</td>\n",
       "      <td>182600.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>3.882852</td>\n",
       "      <td>0.265267</td>\n",
       "      <td>2.103565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20544</th>\n",
       "      <td>-121.76</td>\n",
       "      <td>38.55</td>\n",
       "      <td>23.0</td>\n",
       "      <td>8800.0</td>\n",
       "      <td>1857.0</td>\n",
       "      <td>6330.0</td>\n",
       "      <td>1832.0</td>\n",
       "      <td>2.0650</td>\n",
       "      <td>219400.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>4.803493</td>\n",
       "      <td>0.211023</td>\n",
       "      <td>3.455240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20563</th>\n",
       "      <td>-121.75</td>\n",
       "      <td>38.67</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12139.0</td>\n",
       "      <td>2640.0</td>\n",
       "      <td>6837.0</td>\n",
       "      <td>2358.0</td>\n",
       "      <td>3.1250</td>\n",
       "      <td>132500.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>5.148007</td>\n",
       "      <td>0.217481</td>\n",
       "      <td>2.899491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20567</th>\n",
       "      <td>-121.79</td>\n",
       "      <td>38.66</td>\n",
       "      <td>15.0</td>\n",
       "      <td>6809.0</td>\n",
       "      <td>1052.0</td>\n",
       "      <td>3060.0</td>\n",
       "      <td>1060.0</td>\n",
       "      <td>5.3064</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>6.423585</td>\n",
       "      <td>0.154501</td>\n",
       "      <td>2.886792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20569</th>\n",
       "      <td>-121.76</td>\n",
       "      <td>38.66</td>\n",
       "      <td>17.0</td>\n",
       "      <td>5320.0</td>\n",
       "      <td>984.0</td>\n",
       "      <td>2866.0</td>\n",
       "      <td>928.0</td>\n",
       "      <td>4.1997</td>\n",
       "      <td>133400.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>5.732759</td>\n",
       "      <td>0.184962</td>\n",
       "      <td>3.088362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20629</th>\n",
       "      <td>-121.39</td>\n",
       "      <td>39.12</td>\n",
       "      <td>28.0</td>\n",
       "      <td>10035.0</td>\n",
       "      <td>1856.0</td>\n",
       "      <td>6912.0</td>\n",
       "      <td>1818.0</td>\n",
       "      <td>2.0943</td>\n",
       "      <td>108300.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>5.519802</td>\n",
       "      <td>0.184953</td>\n",
       "      <td>3.801980</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1758 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "1        -122.22     37.86                21.0       7099.0          1106.0   \n",
       "95       -122.26     37.80                36.0       5329.0          2477.0   \n",
       "101      -122.25     37.81                28.0       5806.0          1603.0   \n",
       "104      -122.26     37.81                34.0       5871.0          1914.0   \n",
       "116      -122.25     37.83                28.0       5022.0          1750.0   \n",
       "125      -122.22     37.85                28.0       5287.0          1048.0   \n",
       "133      -122.21     37.83                34.0       5065.0           788.0   \n",
       "185      -122.23     37.79                43.0       5963.0          1344.0   \n",
       "283      -122.16     37.79                22.0      12842.0          2048.0   \n",
       "391      -122.30     37.90                15.0       5083.0          1212.0   \n",
       "485      -122.26     37.86                35.0       5161.0          1744.0   \n",
       "508      -122.30     37.84                14.0       7355.0          2408.0   \n",
       "538      -122.28     37.78                29.0       5154.0           435.0   \n",
       "568      -122.24     37.73                21.0       7031.0          1249.0   \n",
       "570      -122.24     37.72                 5.0      18634.0          2885.0   \n",
       "571      -122.27     37.73                31.0       5785.0          1379.0   \n",
       "573      -122.27     37.74                28.0       6909.0          1554.0   \n",
       "574      -122.27     37.77                23.0       5679.0          1270.0   \n",
       "576      -122.06     37.77                12.0      14316.0          2045.0   \n",
       "592      -122.10     37.71                27.0       6740.0          1073.0   \n",
       "605      -122.07     37.69                31.0       5914.0          1309.0   \n",
       "654      -122.15     37.71                18.0       5778.0          1526.0   \n",
       "706      -122.04     37.65                10.0       8299.0          1326.0   \n",
       "707      -122.05     37.68                23.0       7518.0          1279.0   \n",
       "709      -122.06     37.68                30.0       5367.0          1207.0   \n",
       "758      -122.07     37.66                21.0       5031.0          1168.0   \n",
       "761      -122.08     37.65                17.0       5018.0          1439.0   \n",
       "780      -122.10     37.63                18.0       9963.0          2031.0   \n",
       "794      -122.08     37.64                30.0       5267.0          1253.0   \n",
       "799      -122.07     37.64                22.0       5861.0          1516.0   \n",
       "...          ...       ...                 ...          ...             ...   \n",
       "20424    -118.75     34.18                 4.0      16704.0          2704.0   \n",
       "20425    -118.75     34.17                18.0       6217.0           858.0   \n",
       "20427    -118.80     34.19                 4.0      15572.0          2222.0   \n",
       "20428    -118.83     34.23                 6.0       8803.0          1114.0   \n",
       "20437    -118.81     34.25                 4.0       9147.0          1827.0   \n",
       "20440    -118.77     34.24                 6.0      16222.0          2309.0   \n",
       "20444    -118.90     34.30                13.0       5591.0          1013.0   \n",
       "20445    -118.83     34.33                 6.0       6679.0          1164.0   \n",
       "20450    -118.91     34.28                 6.0       6106.0          1134.0   \n",
       "20451    -118.90     34.26                 5.0      25187.0          3521.0   \n",
       "20460    -118.75     34.29                17.0       5512.0           435.0   \n",
       "20486    -118.68     34.28                17.0       6488.0          1102.0   \n",
       "20487    -118.67     34.30                 5.0       6123.0           825.0   \n",
       "20488    -118.68     34.28                 5.0       6150.0          1265.0   \n",
       "20504    -118.73     34.29                11.0       5451.0           736.0   \n",
       "20507    -121.52     38.59                35.0       6418.0          1545.0   \n",
       "20509    -121.53     38.60                25.0       5154.0          1105.0   \n",
       "20524    -121.55     38.55                10.0       6227.0          1164.0   \n",
       "20528    -121.80     38.55                11.0       5121.0           899.0   \n",
       "20529    -121.78     38.55                12.0      10509.0          2186.0   \n",
       "20530    -121.76     38.57                11.0      15018.0          3008.0   \n",
       "20533    -121.67     38.54                13.0       6141.0          1019.0   \n",
       "20539    -121.71     38.56                20.0       8627.0          1516.0   \n",
       "20541    -121.70     38.54                13.0       6819.0          1158.0   \n",
       "20543    -121.74     38.55                33.0       6861.0          1820.0   \n",
       "20544    -121.76     38.55                23.0       8800.0          1857.0   \n",
       "20563    -121.75     38.67                 9.0      12139.0          2640.0   \n",
       "20567    -121.79     38.66                15.0       6809.0          1052.0   \n",
       "20569    -121.76     38.66                17.0       5320.0           984.0   \n",
       "20629    -121.39     39.12                28.0      10035.0          1856.0   \n",
       "\n",
       "       population  households  median_income  median_house_value  \\\n",
       "1          2401.0      1138.0         8.3014            358500.0   \n",
       "95         3469.0      2323.0         2.0096            130000.0   \n",
       "101        2563.0      1497.0         3.2177            273400.0   \n",
       "104        2689.0      1789.0         2.8406            335700.0   \n",
       "116        2558.0      1661.0         2.4234            218500.0   \n",
       "125        2031.0       956.0         5.4570            337300.0   \n",
       "133        1627.0       766.0         6.8976            333300.0   \n",
       "185        4367.0      1231.0         2.1917            112800.0   \n",
       "283        4985.0      1967.0         5.9849            371000.0   \n",
       "391        2420.0      1146.0         4.5824            256100.0   \n",
       "485        3276.0      1742.0         1.6307            253600.0   \n",
       "508        3100.0      2051.0         4.0018            143800.0   \n",
       "538        3741.0      1273.0         2.5762            173400.0   \n",
       "568        2930.0      1235.0         4.5213            228400.0   \n",
       "570        7427.0      2718.0         7.6110            350700.0   \n",
       "571        2973.0      1312.0         3.2689            231000.0   \n",
       "573        2974.0      1484.0         3.6875            353900.0   \n",
       "574        2690.0      1151.0         4.7695            291700.0   \n",
       "576        5781.0      2007.0         7.2634            341600.0   \n",
       "592        2723.0      1035.0         5.2131            252500.0   \n",
       "605        2999.0      1295.0         3.0964            190500.0   \n",
       "654        2441.0      1352.0         3.1682            202700.0   \n",
       "706        3827.0      1288.0         6.2579            315500.0   \n",
       "707        3827.0      1294.0         5.1701            216800.0   \n",
       "709        2667.0      1047.0         3.1796            170300.0   \n",
       "758        2461.0      1042.0         3.8750            179300.0   \n",
       "761        3069.0      1299.0         2.7694            161900.0   \n",
       "780        5613.0      1946.0         3.8171            187200.0   \n",
       "794        4065.0      1113.0         3.3479            182100.0   \n",
       "799        5436.0      1463.0         2.5158            134900.0   \n",
       "...           ...         ...            ...                 ...   \n",
       "20424      6187.0      2207.0         6.6122            357600.0   \n",
       "20425      2703.0       834.0         6.8075            325900.0   \n",
       "20427      5495.0      2152.0         8.6499            500001.0   \n",
       "20428      3385.0      1010.0         8.7288            425800.0   \n",
       "20437      3950.0      1661.0         5.7160            320800.0   \n",
       "20440      6700.0      2080.0         6.4963            308100.0   \n",
       "20444      3188.0       971.0         5.5925            208600.0   \n",
       "20445      3196.0      1157.0         5.4493            242600.0   \n",
       "20450      3246.0      1062.0         5.2206            280200.0   \n",
       "20451     11956.0      3478.0         6.9712            321300.0   \n",
       "20460      2734.0       814.0         6.6073            258100.0   \n",
       "20486      3199.0      1070.0         5.0962            238000.0   \n",
       "20487      2440.0       736.0         7.9013            393000.0   \n",
       "20488      3188.0      1266.0         4.7034            223000.0   \n",
       "20504      2526.0       752.0         7.3550            343900.0   \n",
       "20507      3814.0      1496.0         1.6647             69100.0   \n",
       "20509      3196.0      1073.0         2.7566             80200.0   \n",
       "20524      2909.0      1077.0         4.1060            115900.0   \n",
       "20528      2258.0       901.0         4.7168            223200.0   \n",
       "20529      5633.0      2138.0         2.9605            204300.0   \n",
       "20530      7984.0      2962.0         3.1371            201800.0   \n",
       "20533      2553.0       967.0         4.2432            326500.0   \n",
       "20539      4071.0      1466.0         4.2198            164100.0   \n",
       "20541      2828.0      1115.0         4.6225            226500.0   \n",
       "20543      3717.0      1767.0         1.7311            182600.0   \n",
       "20544      6330.0      1832.0         2.0650            219400.0   \n",
       "20563      6837.0      2358.0         3.1250            132500.0   \n",
       "20567      3060.0      1060.0         5.3064            165000.0   \n",
       "20569      2866.0       928.0         4.1997            133400.0   \n",
       "20629      6912.0      1818.0         2.0943            108300.0   \n",
       "\n",
       "      ocean_proximity  rooms_per_household  bedrooms_per_room  \\\n",
       "1            NEAR BAY             6.238137           0.155797   \n",
       "95           NEAR BAY             2.294016           0.464815   \n",
       "101          NEAR BAY             3.878424           0.276094   \n",
       "104          NEAR BAY             3.281722           0.326009   \n",
       "116          NEAR BAY             3.023480           0.348467   \n",
       "125          NEAR BAY             5.530335           0.198222   \n",
       "133          NEAR BAY             6.612272           0.155577   \n",
       "185          NEAR BAY             4.844029           0.225390   \n",
       "283          NEAR BAY             6.528724           0.159477   \n",
       "391          NEAR BAY             4.435428           0.238442   \n",
       "485          NEAR BAY             2.962687           0.337919   \n",
       "508          NEAR BAY             3.586056           0.327396   \n",
       "538          NEAR BAY             4.048704           0.084400   \n",
       "568          NEAR BAY             5.693117           0.177642   \n",
       "570          NEAR BAY             6.855776           0.154825   \n",
       "571          NEAR BAY             4.409299           0.238375   \n",
       "573          NEAR BAY             4.655660           0.224924   \n",
       "574          NEAR BAY             4.933970           0.223631   \n",
       "576          NEAR BAY             7.133034           0.142847   \n",
       "592          NEAR BAY             6.512077           0.159199   \n",
       "605          NEAR BAY             4.566795           0.221339   \n",
       "654          NEAR BAY             4.273669           0.264105   \n",
       "706          NEAR BAY             6.443323           0.159778   \n",
       "707          NEAR BAY             5.809892           0.170125   \n",
       "709          NEAR BAY             5.126074           0.224893   \n",
       "758          NEAR BAY             4.828215           0.232161   \n",
       "761          NEAR BAY             3.862972           0.286768   \n",
       "780          NEAR BAY             5.119733           0.203854   \n",
       "794          NEAR BAY             4.732255           0.237896   \n",
       "799          NEAR BAY             4.006152           0.258659   \n",
       "...               ...                  ...                ...   \n",
       "20424      NEAR OCEAN             7.568645           0.161877   \n",
       "20425      NEAR OCEAN             7.454436           0.138009   \n",
       "20427       <1H OCEAN             7.236059           0.142692   \n",
       "20428       <1H OCEAN             8.715842           0.126548   \n",
       "20437       <1H OCEAN             5.506924           0.199738   \n",
       "20440       <1H OCEAN             7.799038           0.142338   \n",
       "20444       <1H OCEAN             5.757981           0.181184   \n",
       "20445       <1H OCEAN             5.772688           0.174278   \n",
       "20450       <1H OCEAN             5.749529           0.185719   \n",
       "20451       <1H OCEAN             7.241806           0.139794   \n",
       "20460       <1H OCEAN             6.771499           0.078919   \n",
       "20486       <1H OCEAN             6.063551           0.169852   \n",
       "20487       <1H OCEAN             8.319293           0.134738   \n",
       "20488       <1H OCEAN             4.857820           0.205691   \n",
       "20504       <1H OCEAN             7.248670           0.135021   \n",
       "20507          INLAND             4.290107           0.240729   \n",
       "20509          INLAND             4.803355           0.214397   \n",
       "20524          INLAND             5.781801           0.186928   \n",
       "20528          INLAND             5.683685           0.175552   \n",
       "20529          INLAND             4.915341           0.208012   \n",
       "20530          INLAND             5.070223           0.200293   \n",
       "20533          INLAND             6.350569           0.165934   \n",
       "20539          INLAND             5.884720           0.175727   \n",
       "20541          INLAND             6.115695           0.169820   \n",
       "20543          INLAND             3.882852           0.265267   \n",
       "20544          INLAND             4.803493           0.211023   \n",
       "20563          INLAND             5.148007           0.217481   \n",
       "20567          INLAND             6.423585           0.154501   \n",
       "20569          INLAND             5.732759           0.184962   \n",
       "20629          INLAND             5.519802           0.184953   \n",
       "\n",
       "       population_per_househol  \n",
       "1                     2.109842  \n",
       "95                    1.493328  \n",
       "101                   1.712091  \n",
       "104                   1.503074  \n",
       "116                   1.540036  \n",
       "125                   2.124477  \n",
       "133                   2.124021  \n",
       "185                   3.547522  \n",
       "283                   2.534316  \n",
       "391                   2.111693  \n",
       "485                   1.880597  \n",
       "508                   1.511458  \n",
       "538                   2.938727  \n",
       "568                   2.372470  \n",
       "570                   2.732524  \n",
       "571                   2.266006  \n",
       "573                   2.004043  \n",
       "574                   2.337098  \n",
       "576                   2.880419  \n",
       "592                   2.630918  \n",
       "605                   2.315830  \n",
       "654                   1.805473  \n",
       "706                   2.971273  \n",
       "707                   2.957496  \n",
       "709                   2.547278  \n",
       "758                   2.361804  \n",
       "761                   2.362587  \n",
       "780                   2.884378  \n",
       "794                   3.652291  \n",
       "799                   3.715653  \n",
       "...                        ...  \n",
       "20424                 2.803353  \n",
       "20425                 3.241007  \n",
       "20427                 2.553439  \n",
       "20428                 3.351485  \n",
       "20437                 2.378085  \n",
       "20440                 3.221154  \n",
       "20444                 3.283213  \n",
       "20445                 2.762316  \n",
       "20450                 3.056497  \n",
       "20451                 3.437608  \n",
       "20460                 3.358722  \n",
       "20486                 2.989720  \n",
       "20487                 3.315217  \n",
       "20488                 2.518167  \n",
       "20504                 3.359043  \n",
       "20507                 2.549465  \n",
       "20509                 2.978565  \n",
       "20524                 2.701021  \n",
       "20528                 2.506104  \n",
       "20529                 2.634705  \n",
       "20530                 2.695476  \n",
       "20533                 2.640124  \n",
       "20539                 2.776944  \n",
       "20541                 2.536323  \n",
       "20543                 2.103565  \n",
       "20544                 3.455240  \n",
       "20563                 2.899491  \n",
       "20567                 2.886792  \n",
       "20569                 3.088362  \n",
       "20629                 3.801980  \n",
       "\n",
       "[1758 rows x 13 columns]"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing[housing['total_rooms'] > 5000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2860a736cc0>"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing.boxplot(column='population', figsize=(20,15))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "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>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "      <th>ocean_proximity</th>\n",
       "      <th>rooms_per_household</th>\n",
       "      <th>bedrooms_per_room</th>\n",
       "      <th>population_per_househol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6057</th>\n",
       "      <td>-117.78</td>\n",
       "      <td>34.03</td>\n",
       "      <td>8.0</td>\n",
       "      <td>32054.0</td>\n",
       "      <td>5290.0</td>\n",
       "      <td>15507.0</td>\n",
       "      <td>5050.0</td>\n",
       "      <td>6.0191</td>\n",
       "      <td>253900.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>6.347327</td>\n",
       "      <td>0.165034</td>\n",
       "      <td>3.070693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6066</th>\n",
       "      <td>-117.87</td>\n",
       "      <td>34.04</td>\n",
       "      <td>7.0</td>\n",
       "      <td>27700.0</td>\n",
       "      <td>4179.0</td>\n",
       "      <td>15037.0</td>\n",
       "      <td>4072.0</td>\n",
       "      <td>6.6288</td>\n",
       "      <td>339700.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>6.802554</td>\n",
       "      <td>0.150866</td>\n",
       "      <td>3.692780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9880</th>\n",
       "      <td>-121.79</td>\n",
       "      <td>36.64</td>\n",
       "      <td>11.0</td>\n",
       "      <td>32627.0</td>\n",
       "      <td>6445.0</td>\n",
       "      <td>28566.0</td>\n",
       "      <td>6082.0</td>\n",
       "      <td>2.3087</td>\n",
       "      <td>118800.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5.364518</td>\n",
       "      <td>0.197536</td>\n",
       "      <td>4.696810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10309</th>\n",
       "      <td>-117.74</td>\n",
       "      <td>33.89</td>\n",
       "      <td>4.0</td>\n",
       "      <td>37937.0</td>\n",
       "      <td>5471.0</td>\n",
       "      <td>16122.0</td>\n",
       "      <td>5189.0</td>\n",
       "      <td>7.4947</td>\n",
       "      <td>366300.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>7.311043</td>\n",
       "      <td>0.144213</td>\n",
       "      <td>3.106957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13139</th>\n",
       "      <td>-121.44</td>\n",
       "      <td>38.43</td>\n",
       "      <td>3.0</td>\n",
       "      <td>39320.0</td>\n",
       "      <td>6210.0</td>\n",
       "      <td>16305.0</td>\n",
       "      <td>5358.0</td>\n",
       "      <td>4.9516</td>\n",
       "      <td>153700.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>7.338559</td>\n",
       "      <td>0.157935</td>\n",
       "      <td>3.043113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15360</th>\n",
       "      <td>-117.42</td>\n",
       "      <td>33.35</td>\n",
       "      <td>14.0</td>\n",
       "      <td>25135.0</td>\n",
       "      <td>4819.0</td>\n",
       "      <td>35682.0</td>\n",
       "      <td>4769.0</td>\n",
       "      <td>2.5729</td>\n",
       "      <td>134400.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5.270497</td>\n",
       "      <td>0.191725</td>\n",
       "      <td>7.482072</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "6057     -117.78     34.03                 8.0      32054.0          5290.0   \n",
       "6066     -117.87     34.04                 7.0      27700.0          4179.0   \n",
       "9880     -121.79     36.64                11.0      32627.0          6445.0   \n",
       "10309    -117.74     33.89                 4.0      37937.0          5471.0   \n",
       "13139    -121.44     38.43                 3.0      39320.0          6210.0   \n",
       "15360    -117.42     33.35                14.0      25135.0          4819.0   \n",
       "\n",
       "       population  households  median_income  median_house_value  \\\n",
       "6057      15507.0      5050.0         6.0191            253900.0   \n",
       "6066      15037.0      4072.0         6.6288            339700.0   \n",
       "9880      28566.0      6082.0         2.3087            118800.0   \n",
       "10309     16122.0      5189.0         7.4947            366300.0   \n",
       "13139     16305.0      5358.0         4.9516            153700.0   \n",
       "15360     35682.0      4769.0         2.5729            134400.0   \n",
       "\n",
       "      ocean_proximity  rooms_per_household  bedrooms_per_room  \\\n",
       "6057        <1H OCEAN             6.347327           0.165034   \n",
       "6066        <1H OCEAN             6.802554           0.150866   \n",
       "9880        <1H OCEAN             5.364518           0.197536   \n",
       "10309       <1H OCEAN             7.311043           0.144213   \n",
       "13139          INLAND             7.338559           0.157935   \n",
       "15360       <1H OCEAN             5.270497           0.191725   \n",
       "\n",
       "       population_per_househol  \n",
       "6057                  3.070693  \n",
       "6066                  3.692780  \n",
       "9880                  4.696810  \n",
       "10309                 3.106957  \n",
       "13139                 3.043113  \n",
       "15360                 7.482072  "
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing[housing['population'] > 15000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2860a7964e0>"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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0MhwOMxgM6o4GADAXiiMAgBlNJpO02+2L1trtdiaTSU2JAADmS3EEADCjZrOZ9fX1i9bW19fTbDZrSgQAMF+KIwCAGfX7/XS73YzH42xubmY8Hqfb7abf79cdDQBgLgzHBgCY0YUB2L1eL5PJJM1mM4PBwGBsAGDXKMqyrDvDs1pcXCw3NjbqjgEAcElra2tZWlqqOwYAwCUVRfFgWZaL29nrqhoAAAAAlRRHAAAAAFRSHAEAAABQSXEEALADo9EorVYry8vLabVaGY1GdUcCAJgbT1UDAJjRaDRKv9/PcDjMdDpNo9FIt9tNEk9WAwB2BSeOAABmNBgMMhwO0+l0srCwkE6nk+FwmMFgUHc0AIC5UBwBAMxoMpmk3W5ftNZutzOZTGpKBAAwX4ojAIAZNZvNrK+vX7S2vr6eZrNZUyIAgPlSHAEAzKjf76fb7WY8HmdzczPj8Tjdbjf9fr/uaAAAc2E4NgDAjC4MwO71eplMJmk2mxkMBgZjAwC7RlGWZd0ZntXi4mK5sbFRdwwAgEtaW1vL0tJS3TEAAC6pKIoHy7Jc3M5eV9UAAAAAqKQ4AgAAAKCS4ggAAACASoojAAAAACopjgAAAACopDgCAAAAoJLiCAAAAIBKiiMAAAAAKimOAAAAAKikOAIAAACgkuIIAGAHRqNRWq1WlpeX02q1MhqN6o4EADA3C3UHAAC4XI1Go/T7/QyHw0yn0zQajXS73STJyspKzekAAHbOiSMAgBkNBoMMh8N0Op0sLCyk0+lkOBxmMBjUHQ0AYC4URwAAM5pMJmm32xettdvtTCaTmhIBAMyX4ggAYEbNZjPr6+sXra2vr6fZbNaUCABgvhRHAAAz6vf76Xa7GY/H2dzczHg8TrfbTb/frzsaAMBcGI4NADCjCwOwe71eJpNJms1mBoOBwdgAwK5RlGVZd4Zntbi4WG5sbNQdAwDgktbW1rK0tFR3DACASyqK4sGyLBe3s9dVNQAAAAAqKY4AAAAAqKQ4AgAAAKCS4ggAAACASoojAAAAACopjgAAAACopDgCAAAAoJLiCAAAAIBKiiMAgB0YjUZptVpZXl5Oq9XKaDSqOxIAwNws1B0AAOByNRqN0u/3MxwOM51O02g00u12kyQrKys1pwMA2DknjgAAZjQYDDIcDtPpdLKwsJBOp5PhcJjBYFB3NACAuVAcAQDMaDKZpN1uX7TWbrczmUxqSgQAMF+KIwCAGTWbzayvr1+0tr6+nmazWVMiAID5UhwBAMyo3++n2+1mPB5nc3Mz4/E43W43/X6/7mgAAHNhODYAwIwuDMDu9XqZTCZpNpsZDAYGYwMAu0ZRlmXdGZ7V4uJiubGxUXcMAIBLWltby9LSUt0xAAAuqSiKB8uyXNzOXlfVAAAAAKikOAIAAACgkuIIAAAAgEqKIwAAAAAqKY4AAAAAqKQ4AgAAAKCS4ggAYAdGo1FarVaWl5fTarUyGo3qjgQAMDcLdQcAALhcjUaj9Pv9DIfDTKfTNBqNdLvdJMnKykrN6QAAds6JIwCAGQ0GgwyHw3Q6nSwsLKTT6WQ4HGYwGNQdDQBgLhRHAAAzmkwmabfbF6212+1MJpOaEgEAzJeragAAM2o2m7njjjty/PjxTCaTNJvNHDlyJM1ms+5oAABzoTgCAJhRp9PJ0aNHc/To0Rw+fDgnT57M6upqbr311rqjAQDMheIIAGBG4/E4q6urOXbs2NMnjlZXV3P8+PG6owEAzEVRlmXdGZ7V4uJiubGxUXcMAIBKjUYj3/ve97J3796sra1laWkp586dy/79+zOdTuuOBwBQqSiKB8uyXNzOXsOxAQBm1Gw2s76+ftHa+vq6GUcAwK6hOAIAmFG/30+32814PM7m5mbG43G63W76/X7d0QAA5sKMIwCAGa2srCRJer3e0zOOBoPB0+sAAJc7M44AAObgwowjAIDnOzOOAAAAANgxxREAAAAAlRRHAAAAAFRSHAEAAABQSXEEAAAAQCXFEQAAAACVFEcAAAAAVFIcAQAAAFBJcQQAsAOj0SitVivLy8tptVoZjUZ1RwIAmJuFugMAAFyuRqNR+v1+hsNhptNpGo1Gut1ukmRlZaXmdAAAO+fEEQDAjAaDQYbDYTqdThYWFtLpdDIcDjMYDOqOBgAwF4ojAIAZTSaTtNvti9ba7XYmk0lNiQAA5stVNQCAGTWbzdxxxx05fvx4JpNJms1mjhw5kmazWXc0AIC5UBwBAMyo0+nk6NGjOXr0aA4fPpyTJ09mdXU1t956a93RAADmQnEEADCj8Xic1dXVHDt27OkTR6urqzl+/Hjd0QAA5qIoy7LuDM9qcXGx3NjYqDsGAEClRqOR733ve9m7d2/W1taytLSUc+fOZf/+/ZlOp3XHAwCoVBTFg2VZLm5nr+HYAAAzajabWV9fv2htfX3djCMAYNdQHAEAzKjf76fb7WY8HmdzczPj8Tjdbjf9fr/uaAAAc2HGEQDAjFZWVpIkvV7v6RlHg8Hg6XUAgMudGUcAAHNwYcYRAMDznRlHAAAAAOyY4ggAAACASoojAAAAACopjgAAAACopDgCANiB0WiUVquV5eXltFqtjEajuiMBAMzNQt0BAAAuV6PRKP1+P8PhMNPpNI1GI91uN0mysrJSczoAgJ1z4ggAYEaDwSDD4TCdTicLCwvpdDoZDocZDAZ1RwMAmAvFEQDAjCaTSdrt9kVr7XY7k8mkpkQAAPOlOAIAmFGz2cz6+vpFa+vr62k2mzUlAgCYL8URAMCM+v1+ut1uxuNxNjc3Mx6P0+120+/3644GADAXhmMDAMzowgDsXq+XyWSSZrOZwWBgMDYAsGsUZVnWneFZLS4ulhsbG3XHAAC4pLW1tSwtLdUdAwDgkoqieLAsy8Xt7HVVDQBgB0ajUVqtVpaXl9NqtTIajeqOBAAwN9u+qlYURSPJRpK/Lcvyl4qi+OdJfj/JVUn+Msm/Kcvy+0VR7Evye0l+Msk/JHlDWZZf3fodtyfpJpkmeWtZln86zw8DAPBcGo1G6ff7GQ6HmU6naTQa6Xa7SeK6GgCwK/wwJ47eluSZz5Y9muR3yrJ8eZLH8lQhlK2vj5Vl+bIkv7O1L0VRHE7ya0n+RZJfSPLBrTIKAOCyNBgMMhwO0+l0srCwkE6nk+FwmMFgUHc0AIC52FZxVBTFoSSvSfIft94XSX42ySe3ttyd5MjW69duvc/W95e39r82ye+XZflkWZYPJflKkp+ax4cAAKjDZDJJu92+aK3dbmcymTzLTwAAXF62e1Xt/0hyW5If2Xr/Y0keL8tyc+v9qSTXbL2+JsnXkqQsy82iKL61tf+aJH/2jN/5zJ95WlEUb07y5iQ5cOBA1tbWtvtZAACeU9dee20+8IEP5Cd+4idy5syZrK2t5ctf/nKuvfZaf8MAALvCJYujoih+Kck3y7J8sCiKpQvLFVvLS3zvB/3MPy6U5UeSfCR56qlqnk4CADxfvfvd7356xtH+/ftTlmXuuuuuvPvd7/aENQBgV9jOiaN/neSXi6L4xST7k7wwT51AurIoioWtU0eHkjy6tf9UkpckOVUUxUKSH01y+hnrFzzzZwAALjsrKyv50pe+lFe/+tV58skns2/fvtxyyy0GYwMAu8YlZxyVZXl7WZaHyrJ8aZ4abv1AWZY3JRkn+ZWtbTcn+dTW609vvc/W9x8oy7LcWv+1oij2bT2R7eVJ/tPcPgkAwHNsNBrlvvvuy+c+97l8/vOfz+c+97ncd999GY1GdUcDAJiLH+apav/UapK3F0XxlTw1w2i4tT5M8mNb629P8s4kKcvyvyT5gyQnk/xJkt8oy3K6g38fAKBWnqoGAOx22x2OnSQpy3ItydrW679JxVPRyrL8XpLXP8vPD5L4SwoA2BUmk0lOnTqVVquVyWSSZrOZ1dVVT1UDAHaNnZw4AgD4H9rBgwfT6/Vy9uzZlGWZs2fPptfr5eDBg3VHAwCYC8URAMCMnnjiiZw5cya9Xi+f/exn0+v1cubMmTzxxBN1RwMAmAvFEQDAjE6fPp3bbrstx44dy2te85ocO3Yst912W06fPl13NACAuVAcAQDsQKfTyYkTJ3L//ffnxIkT6XQ6dUcCAJgbxREAwIwOHTqUm2++OePxOJubmxmPx7n55ptz6NChuqMBAMzFD/VUNQAA/tGdd96Zt7zlLfn5n//5nDt3Lnv37s3+/fvzu7/7u3VHAwCYCyeOAAB2YP/+/bnmmmtSFEWuueaa7N+/v+5IAABzozgCAJjRYDDIvffem4ceeigPPPBAHnroodx7770ZDAZ1RwMAmAvFEQDAjCaTSdrt9kVr7XY7k8mkpkQAAPOlOAIAmFGz2cz6+vpFa+vr62k2mzUlAgCYL8URAMCM+v1+ut3uRU9V63a76ff7dUcDAJgLT1UDAJjRyspKkqTX62UymaTZbGYwGDy9DgBwuXPiCAAAAIBKThwBAMxoNBql3+9nOBxmOp2m0Wik2+0miVNHAMCu4MQRAMCMBoNBhsNhOp1OFhYW0ul0MhwOMxgM6o4GADAXiiMAgBlNJpO02+2L1trtdiaTSU2JAADmS3EEADCjZrOZ9fX1i9bW19fTbDZrSgQAMF9mHAEAzKjf7+cNb3hDrrjiijz88MO57rrrcvbs2bzvfe+rOxoAwFw4cQQAMAdFUdQdAQBg7hRHAAAzGgwGuffee/PQQw/l/vvvz0MPPZR7773XcGwAYNdQHAEAzMhwbABgt1McAQDMyHBsAGC3MxwbAGBGzxyO/cgjj+Taa681HBsA2FWcOAIAmIOyLOuOAAAwd4ojAIAZPXM49gMPPGA4NgCw6yiOAABmZDg2ALDbKY4AAGZkODYAsNspjgAAZtTv99PtdjMej7O5uZnxeJxut5t+v193NACAufBUNQCAGa2srORLX/pSXv3qV+fJJ5/Mvn37csstt2RlZaXuaAAAc6E4AgCY0Wg0yn333ZfPfe5zmU6naTQa6Xa7edWrXqU8AgB2BVfVAABmNBgMMhwO0+l0srCwkE6nk+Fw6KlqAMCuoTgCAJjRZDLJqVOn0mq1sry8nFarlVOnTnmqGgCwa7iqBgAwo4MHD2Z1dTX33HPP01fVbrrpphw8eLDuaAAAc+HEEQDADpRl+QPfAwBczpw4AgCY0aOPPpqPfexj6fV6mUwmaTabufPOO/PGN76x7mgAAHPhxBEAwIyazWYOHTqUEydO5P7778+JEydy6NChNJvNuqMBAMyF4ggAYEb9fj/dbjfj8Tibm5sZj8fpdrvp9/t1RwMAmAtX1QAAZrSyspIkF11VGwwGT68DAFzuiufzAMfFxcVyY2Oj7hgAAJe0traWpaWlumMAAFxSURQPlmW5uJ29rqoBAAAAUElxBAAAAEAlxREAwA70er3s378/nU4n+/fvT6/XqzsSAMDcGI4NADCjXq+XD3/4wzl69GgOHz6ckydPZnV1NUly11131ZwOAGDnnDgCAJjRRz/60Rw9ejRvf/vbs3///rz97W/P0aNH89GPfrTuaAAAc6E4AgCY0ZNPPplbb731orVbb701Tz75ZE2JAADmS3EEADCjffv25cMf/vBFax/+8Iezb9++mhIBAMyXGUcAADO65ZZbnp5pdPjw4fz2b/92VldX/5tTSAAAlyvFEQDAjC4MwH7Xu96VJ598Mvv27cutt95qMDYAsGsUZVnWneFZLS4ulhsbG3XHAAC4pLW1tSwtLdUdAwDgkoqieLAsy8Xt7DXjCAAAAIBKiiMAgB0YjUZptVpZXl5Oq9XKaDSqOxIAwNwojgAAZjQajfK2t70tZ8+eTZKcPXs2b3vb25RHAMCuYcYRAMCMXvKSl2Q6neaee+7JdDpNo9HITTfdlEajka997Wt1xwMAqGTGEQDAc+DUqVO5++670+l0srCwkE6nk7vvvjunTp2qOxoAwFwojgAAAACotFB3AACAy9WhQ4fy+te/Pi960YvyyCOP5Nprr81jjz2WQ4cO1R0NAGAunDgCAJjRkSNH8p3vfCff/e53c/78+Xz3u9/Nd77znRw5cqTuaAAAc6E4AgCY0Xg8zu23354Xv/jF2bNnT1784hfn9ttvz3g8rjsaAMBceKoaAMCMGo1Gvvd/mEfcAAAgAElEQVS972Xv3r1ZW1vL0tJSzp07l/3792c6ndYdDwCg0g/zVDUzjgAAZtRsNnPHHXfk+PHjmUwmaTabOXLkSJrNZt3RAADmQnEEADCjTqeTo0eP5ujRozl8+HBOnjyZ1dXV3HrrrXVHAwCYC8URAMCMxuNxVldXc+zYsadPHK2urub48eN1RwMAmAszjgAAZmTGEQBwOfphZhx5qhoAwIyazWbW19cvWltfXzfjCADYNVxVAwCYUb/fzxve8IZcccUVefjhh3Pdddfl7Nmzed/73ld3NACAuXDiCABgDoqiqDsCAMDcKY4AAGY0GAxy77335qGHHsr999+fhx56KPfee28Gg0Hd0QAA5kJxBAAwo8lkkna7fdFau93OZDKpKREAwHwpjgAAZmQ4NgCw2xmODQAwo2cOx37kkUdy7bXXGo4NAOwqThwBAMxBWZZ1RwAAmDvFEQDAjJ45HPuBBx4wHBsA2HUURwAAMzIcGwDY7cw4AgCYUbPZzB133JHjx49nMpmk2WzmyJEjhmMDALuG4ggAYEadTidHjx7N0aNHc/jw4Zw8eTKrq6u59dZb644GADAXiiMAgBmNx+Osrq7m2LFjT584Wl1dzfHjx+uOBgAwF2YcAQDMaDKZ5BWveMVFa694xSvMOAIAdg3FEQDAjA4ePJher5ezZ8+mLMucPXs2vV4vBw8erDsaAMBcKI4AAGb0xBNP5MyZM+n1evnsZz+bXq+XM2fO5Iknnqg7GgDAXCiOAABmdPr06dx22205duxYXvOa1+TYsWO57bbbcvr06bqjAQDMheIIAGAHOp1OTpw4kfvvvz8nTpxIp9OpOxIAwNx4qhoAwIwOHTqUX/3VX82VV16Zhx9+ONddd10ef/zxHDp0qO5oAABz4cQRAMCMjhw5kscffzxf/epXU5ZlvvrVr+bxxx/PkSNH6o4GADAXiiMAgBl94hOfyJ49e3LgwIEkyYEDB7Jnz5584hOfqDkZAMB8KI4AAGZ0+vTpvOc978k3vvGNjMfjfOMb38h73vMew7EBgF1DcQQAsANf/OIXs3///nQ6nezfvz9f/OIX644EADA3iiMAgBkVRZHPfOYzedOb3pQ//uM/zpve9KZ85jOfSVEUdUcDAJgLT1UDAJjRhYLoD//wD/OhD30oBw4cSFEUiiMAYNdw4ggAYEbnz5/PLbfckscffzxJ8vjjj+eWW27J+fPna04GADAfiiMAgBnt27cvZ8+ezcte9rLs2bMnL3vZy3L27Nns27ev7mgAAHOhOAIAmNGNN96Ye+65JzfccEM+9alP5YYbbsg999yTG2+8se5oAABzYcYRAMCM/vZv/zZHjhzJsWPH8qEPfSj79u3LkSNH8td//dd1RwMAmAsnjgAAZjSZTPK6173uoqtqr3vd6zKZTOqOBgAwF04cAQDM6ODBg1ldXc0999yT6XSaRqORm266KQcPHqw7GgDAXDhxBACwA2VZ/sD3AACXMyeOAABm9Oijj+ZjH/tYer1eJpNJms1m7rzzzrzxjW+sOxoAwFw4cQQAMKNms5lDhw7lxIkTuf/++3PixIkcOnQozWaz7mgAAHOhOAIAmFG/30+32814PM7m5mbG43G63W76/X7d0QAA5sJVNQCAGa2srCTJRVfVBoPB0+sAAJe74vk8wHFxcbHc2NioOwYAwCWtra1laWmp7hgAAJdUFMWDZVkubmevq2oAADswGo3SarWyvLycVquV0WhUdyQAgLlxVQ0AYEaj0Sj9fj/D4TDT6TSNRiPdbjdJXFcDAHYFJ44AAGY0GAwyHA7T6XSysLCQTqeT4XCYwWBQdzQAgLlQHAEAzGgymeTUqVMXXVU7depUJpNJ3dEAAOZCcQQAMKODBw/mrW99a86ePZuyLHP27Nm89a1vzcGDB+uOBgAwF4ojAIAZPfHEE/n2t7+dXq+Xz372s+n1evn2t7+dJ554ou5oAABzYTg2AMCMTp8+nV/+5V/Ou971rjz55JPZt29ffumXfimf/vSn644GADAXThwBAOzA2tparr766uzZsydXX3111tbW6o4EADA3iiMAgBnt2bMnZ86cSa/Xy3333Zder5czZ85kzx5/YgEAu4OragAAMzp//nx+9Ed/NHfddVceeeSRXHvttfmRH/mRfOtb36o7GgDAXPjfYQAAO3DjjTfm61//es6fP5+vf/3rufHGG+uOBAAwN04cAQDM6KqrrspnPvOZvPe9783hw4dz8uTJvOMd78hVV11VdzQAgLm4ZHFUFMX+JF9Msm9r/yfLsvzNoij+eZLfT3JVkr9M8m/Ksvx+URT7kvxekp9M8g9J3lCW5Ve3ftftSbpJpkneWpbln87/IwEAPDde8IIX5Pz587nrrrvy8MMP57rrrssLX/jCvOAFL6g7GgDAXGznqtqTSX62LMvrk/zLJL9QFMXPJDma5HfKsnx5ksfyVCGUra+PlWX5siS/s7UvRVEcTvJrSf5Fkl9I8sGiKBrz/DAAAM+lRx99NO9///tzxRVXpCiKXHHFFXn/+9+fRx99tO5oAABzccniqHzKma23e7f+K5P8bJJPbq3fneTI1uvXbr3P1veXi6IottZ/vyzLJ8uyfCjJV5L81Fw+BQBADZrNZg4dOpQTJ07k/vvvz4kTJ3Lo0KE0m826owEAzMW2hmMXRdEoiuI/J/lmks8n+X+TPF6W5ebWllNJrtl6fU2SryXJ1ve/leTHnrle8TMAAJedfr+fbreb8Xiczc3NjMfjdLvd9Pv9uqMBAMzFtoZjl2U5TfIvi6K4MskfJan632jl1tfiWb73bOsXKYrizUnenCQHDhzI2tradiICADznrr766tx0001505velEceeSTXXnttfv3Xfz1XX321v2EAgF3hh3qqWlmWjxdFsZbkZ5JcWRTFwtapokNJLlzmP5XkJUlOFUWxkORHk5x+xvoFz/yZZ/4bH0nykSRZXFwsl5aWfpiIAADPqaWlpfzWb/1W1tbW4u8WAGC3ueRVtaIofnzrpFGKovifk/xvSSZJxkl+ZWvbzUk+tfX601vvs/X9B8qyLLfWf60oin1bT2R7eZL/NK8PAgBQh16vl/3796fT6WT//v3p9Xp1RwIAmJvtnDi6OsndW09A25PkD8qy/ExRFCeT/H5RFP8hyZeTDLf2D5P8X0VRfCVPnTT6tSQpy/K/FEXxB0lOJtlM8htbV+AAAC5LvV4vH/zgB/PjP/7j+eY3v5krr7wyH/zgB5Mkd911V83pAAB2rnjqMNDz0+LiYrmxsVF3DACASnv37s0LX/jCfPKTn8x0Ok2j0civ/Mqv5Nvf/nbOnTtXdzwAgEpFUTxYluXidvZu66lqAAD8tzY3N/Pxj388nU4nCwsL6XQ6+fjHP57Nzc1L/zAAwGVAcQQAsAMnTpz4ge8BAC5nP9RT1QAA+EdXXXVVbr/99jQajRw+fDi//du/ndtvvz1XXXVV3dEAAOZCcQQAMKMPfOADectb3pJ3vvOdOXfuXPbu3ZsXvOAF+cAHPlB3NACAuXBVDQBgRisrK3nlK1/59Eyjzc3NvPKVr8zKykrNyQAA5kNxBAAwo16vly984Qs5cOBA9uzZkwMHDuQLX/hCer1e3dEAAOaiKMuy7gzPanFxsdzY2Kg7BgBApb1796bRaOT8+fNPX1Xbs2dPptNpzp07V3c8AIBKRVE8WJbl4nb2mnEEADCjzc3NnD9/Pu9973tz+PDhnDx5Mu94xzty/vz5uqMBAMyF4ggAYAeuv/76HDt2LJPJJM1mM9dff32+/OUv1x0LAGAuzDgCANiBL3/5y7nhhhvyqU99KjfccIPSCADYVcw4AgCYUVEU2bt3b5I8PePowuvn899YAMD/2Mw4AgB4DhRFkXPnzqXRaCRJzp8/n+l0mqIoak4GADAfrqoBAMzommuuSaPRyHQ6TZJMp9M0Go1cc801NScDAJgPxREAwIwee+yxp0ujC6bTaR577LGaEgEAzJfiCABgRmfPnk2SvOhFL7ro64V1AIDLneIIAGAHrr/++hw8eDB79uzJwYMHc/3119cdCQBgbgzHBgDYgb/6q7/KgQMHUpZl/v7v/z5/93d/V3ckAIC5ceIIAGCHvv/976csy3z/+9+vOwoAwFwpjgAAdujCMGxDsQGA3UZxBACwA41G4we+BwC4nCmOAABm1Gg0Mp1Oc+DAgSTJgQMHMp1OlUcAwK6hOAIAmNF0Ok2SFEWRPXv2pCiKi9YBAC53iiMAgB141atelcceeyznz5/PY489lle96lV1RwIAmJuFugMAAFzO/vzP/zx33nlnDh8+nJMnT+a2226rOxIAwNwojgAAZrSwsJBGo5F3vvOdOXfuXPbu3ZuFhYWnr6wBAFzuFEcAADPa3NzMdDrNnj1P3f4/f/58Njc3U5ZlzckAAOZDcQQAMKMLJ47Onz//dIG0sLBgODYAsGsojgAAZrS5uZnNzc2n3587d67GNAAA8+epagAAO3ThqtqFr/D/t3e/IZbe532Hv/fs7FqjVWSNcL0Y2/U0RRQ5VHGTwXGUVKwbUOws1IEmJCFxhAkWBZu00JosoaDUoaCiUqjdoFamamWRqFi0RqayI4uVp6Eobi0Xx4kRlYUlRZLVOEUbNbW1Ws3Ory/2rDyzurU7mjPaM3t0XbA85/zmmfPco1fHHz9/AGBe+HYDADCFqsott9ySL3zhC7nlllvcGBsAmCsuVQMAmML+/fu3PFVt//79OXny5KzHAgDYFcIRAMAUTp48mX379iXJSzfJBgCYFy5VAwCY0sbGxpYtAMC8EI4AAKY0xtiyBQCYF8IRAMAUzn6SmierAQDzxDcbAIApbGxsZHl5OVWV5eVll6sBAHNFOAIAmEJV5cCBA0mSAwcOpKpmPBEAwO4RjgAApnDppZdmaWkpVZWlpaVceumlsx4JAGDXCEcAAFM4+4bYbpANAMyTxVkPAABwsbryyivz7LPP5vHHH0+Sl7ZXXnnl7IYCANhFzjgCANih1dXVV7UOAHCxEY4AAHbogQceyMGDB7OyspKFhYWsrKzk4MGDeeCBB2Y9GgDArhCOAAB2aH19PXfffXcee+yxHDt2LI899ljuvvvurK+vz3o0AIBd4R5HAABTuPPOO/Oxj30sDz/8cK6++upcc801sx4JAGDXOOMIAGCHDh48mLvuuivXXXdd7rnnnlx33XW56667cvDgwVmPBgCwK5xxBACwQ8vLyzl58mRuvfXW3HrrrUmS/fv3Z3l5ecaTAQDsDmccAQDs0NNPP50rrrgiKysrqaqsrKzkiiuuyNNPPz3r0QAAdoVwBACwQwcOHMjy8nKeeOKJjDHyxBNPZHl5OQcOHJj1aAAAu0I4AgDYoRdeeCGPPPJILrvssiwsLOSyyy7LI488khdeeGHWowEA7ArhCABgCouLizlx4kQ2NjZy4sSJLC66hSQAMD+EIwCAKayvr2djYyNJsrGxkfX19RlPBACwe4QjAAAAAFrCEQDAlI4cOZLPfvazOXLkyKxHAQDYVTXGmPUMr2h1dXU89NBDsx4DAKBVVVlYWHjpUrUkL73fy9+xAIDXt6r66hhjdTv7OuMIAGAKGxsb2bdvX5Jk3759WyISAMDFTjgCANihqkqSXH755VlYWMjll1++ZR0A4GInHAEA7NAYIwcOHMjx48ezsbGR48eP58CBAy5TAwDmhnAEADCFpaWlrKysZGFhISsrK1laWpr1SAAAu0Y4AgDYocXFxayvr29ZW19fz+Li4owmAgDYXb7VAADs0KlTp/Ld7343J06cyMbGRp588smcOnXKPY4AgLnhjCMAgB3at29fqiqnTp1Kkpei0ZmnrAEAXOyEIwCAHVpfX88Y46UzjKoqY4yXXb4GAHCxEo4AAKZ05ilqnqYGAMwb4QgAYEqbzzgCAJgnwhEAwJSccQQAzCvhCAAAAICWcAQAAABASzgCAAAAoCUcAQAAANASjgAApuSpagDAvBKOAACm5KlqAMC8Eo4AAAAAaAlHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBLOAIAmNLCwsKWLQDAvPDtBgAAAICWcAQAMKWNjY0tWwCAeSEcAQBM6ZJLLtmyBQCYF8IRAMCUTpw4sWULADAvhCMAAAAAWsIRAMCUlpeXs7CwkOXl5VmPAgCwqxZnPQAAwMXu+PHjW7YAAPPCGUcAAFNaXFzcsgUAmBfCEQDAlMYYW7YAAPNCOAIAmNKpU6e2bAEA5oVwBAAwpYWFhS1bAIB54dsNAMCUNjY2tmwBAOaFcAQAAABASzgCAJjStddem7vvvjvXXnvtrEcBANhVnhkLADClBx98MA8++OCsxwAA2HXOOAIAAACgJRwBAExpaWkpVZWlpaVZjwIAsKtcqgYAMKXnn39+yxYAYF444wgAAACAlnAEAAAAQEs4AgCY0iWXXLJlCwAwL4QjAIApnThxYssWAGBeCEcAAAAAtIQjAAAAAFrCEQAAAAAt4QgAAACAlnAEAAAAQEs4AgAAAKAlHAEAAADQEo4AAAAAaAlHAAAAALSEIwAAAABawhEAAAAALeEIAGAKVZX9+/cnSfbv35+qmvFEAAC7RzgCAJjCGCOnTp1Kkpw6dSpjjBlPBACwe84bjqrq7VX1pap6uKq+UVX/YLJ+ZVXdX1XfnGyXJ+tVVZ+oqker6utV9SObPuuGyf7frKobXrs/CwDgwtnY2NiyBQCYF9s542g9yT8aY1yd5D1JPlJV70xyNMmxMcZVSY5N3ifJ+5NcNfl3Y5Jbk9OhKclNSX4sybuT3HQmNgEAAACw95w3HI0xnhlj/M/J679M8nCStyb5QJI7JrvdkeRnJ68/kOTT47QvJ7miqt6S5KeT3D/GeHaMcTzJ/Unet6t/DQAAAAC75lXd46iqVpL8rST/PcmhMcYzyem4lOTNk93emuTJTb/21GTtldYBAAAA2IMWt7tjVV2W5D8l+YdjjP97jieGdD8Y51g/+zg35vQlbjl06FDW1ta2OyIAwJ7hOwwAMA+2FY6qan9OR6PfHWP858nyn1XVW8YYz0wuRfvOZP2pJG/f9OtvS/Ltyfrhs9bXzj7WGOO2JLclyerq6jh8+PDZuwAA7Hm+wwAA82A7T1WrJP8uycNjjH+56UefS3LmyWg3JLln0/qvTp6u9p4kz00uZbsvyfVVtTy5Kfb1kzUAAAAA9qDtnHH0E0k+mOSPq+prk7XfTHJzks9U1a8l+dMkPz/52eeT/EySR5N8L8mHkmSM8WxV/XaSr0z2+/gY49ld+SsAAAAA2HU1xstuM7RnrK6ujoceemjWYwAAtM5xz8fs5e9YAMDrW1V9dYyxup19X9VT1QAAeLkzAelcIQkA4GIkHAEATOnM2UXOMgIA5o1wBAAAAEBLOAIAAACgJRwBAAAA0BKOAAAAAGgJRwAAAAC0hCMAAAAAWsIRAAAAAC3hCAAAAICWcAQAAABASzgCAAAAoCUcAQAAANASjgAAAABoCUcAAAAAtIQjAAAAAFrCEQAAAAAt4QgAAACAlnAEAAAAQEs4AgAAAKAlHAEAAADQEo4AAAAAaAlHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBLOAIAAACgJRwBAAAA0BKOAAAAAGgJRwAAAAC0hCMAAAAAWsIRAAAAAC3hCAAAAICWcAQAAABASzgCAAAAoCUcAQAAANASjgAAAABoCUcAAAAAtIQjAAAAAFrCEQAAAAAt4QgAAACAlnAEAAAAQEs4AgAAAKAlHAEAAADQEo4AAAAAaAlHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBLOAIAAACgJRwBAAAA0BKOAAAAAGgJRwAAAAC0hCMAAAAAWsIRAAAAAC3hCAAAAICWcAQAAABASzgCAAAAoCUcAQAAANASjgAAAABoCUcAAAAAtIQjAAAAAFrCEQAAAAAt4QgAAACAlnAEAAAAQEs4AgAAAKAlHAEAAADQEo4AAAAAaAlHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBLOAIAAACgJRwBAAAA0BKOAAAAAGgJRwAAAAC0hCMAAAAAWsIRAAAAAC3hCAAAAICWcAQAAABASzgCAAAAoCUcAQAAANASjgAAAABoCUcAAAAAtIQjAAAAAFrCEQAAAAAt4QgAAACAlnAEAAAAQEs4AgAAAKAlHAEAAADQEo4AAAAAaAlHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBLOAIAAACgJRwBAAAA0BKOAAAAAGgJRwAAAAC0hCMAAAAAWsIRAAAAAC3hCAAAAIDW4qwHAAA4l6qa9Qg7spfnHmPMegQA4CIhHAEAe9pejhznikN7eW4AgO1yqRoAwA599KMffVXrAAAXG2ccAQDs0Cc/+ckkyac+9am88MILecMb3pAPf/jDL60DAFzsai+fRr26ujoeeuihWY8BAHBeK0fvzeM3H5n1GAAA51VVXx1jrG5nX5eqAQAAANASjgAAAABonTccVdXtVfWdqvqTTWtXVtX9VfXNyXZ5sl5V9YmqerSqvl5VP7Lpd26Y7P/NqrrhtflzAAAAANgt2znj6D8ked9Za0eTHBtjXJXk2OR9krw/yVWTfzcmuTU5HZqS3JTkx5K8O8lNZ2ITAAAAAHvTecPRGOMPkjx71vIHktwxeX1Hkp/dtP7pcdqXk1xRVW9J8tNJ7h9jPDvGOJ7k/rw8RgEAAACwh+z0HkeHxhjPJMlk++bJ+luTPLlpv6cma6+0DgAAAMAetbjLn1fN2jjH+ss/oOrGnL7MLYcOHcra2tquDQcA8FryvQUAmDc7DUd/VlVvGWM8M7kU7TuT9aeSvH3Tfm9L8u3J+uGz1te6Dx5j3JbktiRZXV0dhw8f7nYDANhbfv/e+N4CAMybnV6q9rkkZ56MdkOSezat/+rk6WrvSfLc5FK2+5JcX1XLk5tiXz9ZAwAAAGCPOu8ZR1V1V06fLfSmqnoqp5+OdnOSz1TVryX50yQ/P9n980l+JsmjSb6X5ENJMsZ4tqp+O8lXJvt9fIxx9g23AQAAANhDzhuOxhi/9Ao/+qlm35HkI6/wObcnuf1VTQcAAADAzOz0UjUAAAAA5pxwBAAAAEBLOAIAAACgJRwBAAAA0BKOAAAAAGgJRwAAAAC0hCMAAAAAWsIRAAAAAC3hCAAAAICWcAQAAABASzgCAAAAoCUcAQAAANASjgAAAABoCUcAAAAAtIQjAAAAAFrCEQAAAAAt4QgAAACAlnAEAAAAQEs4AgAAAKAlHAEAAADQEo4AAAAAaAlHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBLOAIAAACgJRwBAAAA0BKOAAAAAGgJRwAAAAC0hCMAAAAAWsIRAAAAAC3hCAAAAICWcAQAAABASzgCAAAAoCUcAQAAANASjgAAAABoCUcAAAAAtIQjAAAAAFrCEQAAAAAt4QgAAACAlnAEAAAAQEs4AgAAAKC1OOsBAIDZ+eF/+sU89/yLsx5jbqwcvXfWI8yNNy7tzx/ddP2sxwCA1z3hCABex557/sU8fvORWY8xF9bW1nL48OFZjzE3RDgA2BtcqgYAAABASzgCAAAAoCUcAQAAANASjgAAAABoCUcAAAAAtIQjAAAAAFrCEQAAAAAt4QgAAACAlnAEAAAAQEs4AgAAAKAlHAEAAADQEo4AAAAAaAlHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBLOAIAAACgJRwBAAAA0BKOAAAAAGgJRwAAAAC0hCMAAAAAWouzHgAAmJ0fuPpo/uYdR2c9xvy4Y9YDzI8fuDpJjsx6DAB43ROOAOB17C8fvjmP3+x/nO+GtbW1HD58eNZjzI2Vo/fOegQAIC5VAwAAAOAVCEcAAAAAtIQjAAAAAFrCEQAAAAAt4QgAAACAlnAEAAAAQEs4AgAAAKAlHAEAAADQEo4AAAAAaAlHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBrcdYDAACztXL03lmPMD9+33/L3fLGpf2zHgEAiHAEAK9rj998ZNYjzI2Vo/f67wkAzB2XqgEAAADQEo4AAAAAaAlHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBLOAIAAACgJRwBAAAA0BKOAAAAAGgJRwAAAAC0hCMAAAAAWsIRAAAAAC3hCAAAAICWcAQAAABASzgCAAAAoCUcAQAAANASjgAAAABoCUcAAAAAtIQjAAAAAFrCEQAAAAAt4QgAAACAlnAEAAAAQEs4AgAAAKAlHAEAAADQEo4AAAAAaAlHAAAAALSEIwAAAABaFzwcVdX7qup/VdWjVXX0Qh8fAAAAgO25oOGoqvYl+Z0k70/yziS/VFXvvJAzAAAAALA9F/qMo3cneXSM8a0xxskk/zHJBy7wDAAAAABsw4UOR29N8uSm909N1gAAAADYYxYv8PGqWRtbdqi6McmNSXLo0KGsra1dgLEAgL3qve9976xH2Lb657OeYHu+9KUvzXoEAOAicaHD0VNJ3r7p/duSfHvzDmOM25LcliSrq6vj8OHDF2w4AGDvGWOcf6c9YG1tLb63AADz5kJfqvaVJFdV1V+rqgNJfjHJ5y7wDAAAAABswwU942iMsV5VH01yX5J9SW4fY3zjQs4AAAAAwPZc6EvVMsb4fJLPX+jjAgAAAPDqXOhL1QAAAAC4SAhHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBLOAIAAACgJRwBAAAA0BKOAAAAAGgJRwAAAAC0hCMAAAAAWsIRAAAAAC3hCAAAAICWcAQAAABASzgCAAAAoCUcAQAAANASjgAAAABoCUcAAAAAtIQjAAAAAEcDdsIAAANmSURBVFrCEQAAAAAt4QgAAACAlnAEAAAAQEs4AgAAAKAlHAEAAADQEo4AAAAAaAlHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBLOAIAAACgJRwBAAAA0KoxxqxneEVV9edJnpj1HAAA2/CmJP9n1kMAAGzDO8YYf2U7O+7pcAQAcLGoqofGGKuzngMAYDe5VA0AAACAlnAEAAAAQEs4AgDYHbfNegAAgN3mHkcAAAAAtJxxBAAAAEBLOAIA5lZVrVTVn8zguP/vVe7/W1X1j5v1mcwPAHCGcAQAAABASzgCAObdvqr6VFV9o6q+WFVLVfWuqvpyVX29qj5bVctJUlVrVbU6ef2mqnp88vqHqup/VNXXJr9z1WT9Vzat/9uq2nfmoFX1z6rqjybHOTRZe0dVHZt8xrGq+qtnD1tVPzr5vT9M8pFN6+0MAACvJeEIAJh3VyX5nTHGDyX5iyR/L8mnk/zGGOOaJH+c5KbzfMbfT/KvxhjvSrKa5KmqujrJLyT5icn6qSS/PNn/YJIvjzF+OMkfJPnwZP1fJ/n05Li/m+QTzbH+fZJfH2P8+Plm2NZfDwAwBeEIAJh3j40xvjZ5/dUkfz3JFWOM/zpZuyPJdef5jD9M8ptV9RtJ3jHGeD7JTyX50SRfqaqvTd7/4GT/k0n+y6Zjrkxe/3iS35u8vjPJT24+SFW98azZ7jzPDAAArynhCACYdy9sen0qyRXn2Hc93/9+dMmZxTHG7yX5u0meT3JfVf2dJJXkjjHGuyb//sYY47cmv/LiGGNsOubiKxxvnPW+mrVzzQAA8JoSjgCA15vnkhyvqr89ef/BJGfO8Hk8p88iSpKfO/MLVfWDSb41xvhEks8luSbJsSQ/V1VvnuxzZVW94zzHfjDJL05e/3KS/7b5h2OMv0jyXFX95KZ9zjUDAMBr6pX+3y8AgHl2Q5J/U1WXJvlWkg9N1v9Fks9U1QeTPLBp/19I8itV9WKS/53k42OMZ6vqnyT5YlUtJHkxp29m/cQ5jvvrSW6vqo8l+fNNx93sQ5N9vpfkvnPN8Kr+YgCAHajvn0UNAAAAAN/nUjUAAAAAWsIRAAAAAC3hCAAAAICWcAQAAABASzgCAAAAoCUcAQAAANASjgAAAABoCUcAAAAAtP4/zwjJ2/V0QrcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1440x1080 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing.boxplot(column='households', figsize=(20,15))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "      <th>ocean_proximity</th>\n",
       "      <th>rooms_per_household</th>\n",
       "      <th>bedrooms_per_room</th>\n",
       "      <th>population_per_househol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>922</th>\n",
       "      <td>-121.92</td>\n",
       "      <td>37.53</td>\n",
       "      <td>7.0</td>\n",
       "      <td>28258.0</td>\n",
       "      <td>3864.0</td>\n",
       "      <td>12203.0</td>\n",
       "      <td>3701.0</td>\n",
       "      <td>8.4045</td>\n",
       "      <td>451100.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>7.635234</td>\n",
       "      <td>0.136740</td>\n",
       "      <td>3.297217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1010</th>\n",
       "      <td>-121.73</td>\n",
       "      <td>37.68</td>\n",
       "      <td>17.0</td>\n",
       "      <td>20354.0</td>\n",
       "      <td>3493.0</td>\n",
       "      <td>8768.0</td>\n",
       "      <td>3293.0</td>\n",
       "      <td>5.4496</td>\n",
       "      <td>238900.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>6.180990</td>\n",
       "      <td>0.171612</td>\n",
       "      <td>2.662618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1060</th>\n",
       "      <td>-121.88</td>\n",
       "      <td>39.74</td>\n",
       "      <td>12.0</td>\n",
       "      <td>14631.0</td>\n",
       "      <td>3298.0</td>\n",
       "      <td>7517.0</td>\n",
       "      <td>3262.0</td>\n",
       "      <td>1.6785</td>\n",
       "      <td>153100.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>4.485285</td>\n",
       "      <td>0.225412</td>\n",
       "      <td>2.304414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3981</th>\n",
       "      <td>-118.60</td>\n",
       "      <td>34.19</td>\n",
       "      <td>16.0</td>\n",
       "      <td>14912.0</td>\n",
       "      <td>4183.0</td>\n",
       "      <td>5105.0</td>\n",
       "      <td>3302.0</td>\n",
       "      <td>2.8312</td>\n",
       "      <td>213900.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>4.516051</td>\n",
       "      <td>0.280512</td>\n",
       "      <td>1.546033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4035</th>\n",
       "      <td>-118.52</td>\n",
       "      <td>34.17</td>\n",
       "      <td>20.0</td>\n",
       "      <td>17377.0</td>\n",
       "      <td>4457.0</td>\n",
       "      <td>7450.0</td>\n",
       "      <td>4204.0</td>\n",
       "      <td>3.2154</td>\n",
       "      <td>259600.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>4.133444</td>\n",
       "      <td>0.256488</td>\n",
       "      <td>1.772122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5540</th>\n",
       "      <td>-118.43</td>\n",
       "      <td>33.96</td>\n",
       "      <td>16.0</td>\n",
       "      <td>14891.0</td>\n",
       "      <td>3984.0</td>\n",
       "      <td>6270.0</td>\n",
       "      <td>3595.0</td>\n",
       "      <td>5.1064</td>\n",
       "      <td>283200.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>4.142142</td>\n",
       "      <td>0.267544</td>\n",
       "      <td>1.744089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6057</th>\n",
       "      <td>-117.78</td>\n",
       "      <td>34.03</td>\n",
       "      <td>8.0</td>\n",
       "      <td>32054.0</td>\n",
       "      <td>5290.0</td>\n",
       "      <td>15507.0</td>\n",
       "      <td>5050.0</td>\n",
       "      <td>6.0191</td>\n",
       "      <td>253900.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>6.347327</td>\n",
       "      <td>0.165034</td>\n",
       "      <td>3.070693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6066</th>\n",
       "      <td>-117.87</td>\n",
       "      <td>34.04</td>\n",
       "      <td>7.0</td>\n",
       "      <td>27700.0</td>\n",
       "      <td>4179.0</td>\n",
       "      <td>15037.0</td>\n",
       "      <td>4072.0</td>\n",
       "      <td>6.6288</td>\n",
       "      <td>339700.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>6.802554</td>\n",
       "      <td>0.150866</td>\n",
       "      <td>3.692780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6338</th>\n",
       "      <td>-117.88</td>\n",
       "      <td>33.96</td>\n",
       "      <td>16.0</td>\n",
       "      <td>19059.0</td>\n",
       "      <td>3079.0</td>\n",
       "      <td>10988.0</td>\n",
       "      <td>3061.0</td>\n",
       "      <td>5.5469</td>\n",
       "      <td>265200.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>6.226397</td>\n",
       "      <td>0.161551</td>\n",
       "      <td>3.589677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8467</th>\n",
       "      <td>-118.34</td>\n",
       "      <td>33.91</td>\n",
       "      <td>12.0</td>\n",
       "      <td>9975.0</td>\n",
       "      <td>3638.0</td>\n",
       "      <td>7429.0</td>\n",
       "      <td>3405.0</td>\n",
       "      <td>2.6689</td>\n",
       "      <td>192300.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>2.929515</td>\n",
       "      <td>0.364712</td>\n",
       "      <td>2.181791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8468</th>\n",
       "      <td>-118.33</td>\n",
       "      <td>33.91</td>\n",
       "      <td>8.0</td>\n",
       "      <td>10731.0</td>\n",
       "      <td>3335.0</td>\n",
       "      <td>7211.0</td>\n",
       "      <td>3028.0</td>\n",
       "      <td>2.4550</td>\n",
       "      <td>192700.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>3.543923</td>\n",
       "      <td>0.310782</td>\n",
       "      <td>2.381440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8716</th>\n",
       "      <td>-118.35</td>\n",
       "      <td>33.84</td>\n",
       "      <td>22.0</td>\n",
       "      <td>13133.0</td>\n",
       "      <td>3680.0</td>\n",
       "      <td>7180.0</td>\n",
       "      <td>3522.0</td>\n",
       "      <td>3.5414</td>\n",
       "      <td>354700.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>3.728847</td>\n",
       "      <td>0.280210</td>\n",
       "      <td>2.038614</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8985</th>\n",
       "      <td>-118.44</td>\n",
       "      <td>33.98</td>\n",
       "      <td>21.0</td>\n",
       "      <td>18132.0</td>\n",
       "      <td>5419.0</td>\n",
       "      <td>7431.0</td>\n",
       "      <td>4930.0</td>\n",
       "      <td>5.3359</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>3.677890</td>\n",
       "      <td>0.298864</td>\n",
       "      <td>1.507302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9018</th>\n",
       "      <td>-118.72</td>\n",
       "      <td>34.14</td>\n",
       "      <td>7.0</td>\n",
       "      <td>23866.0</td>\n",
       "      <td>4407.0</td>\n",
       "      <td>9873.0</td>\n",
       "      <td>4012.0</td>\n",
       "      <td>5.4032</td>\n",
       "      <td>318500.0</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>5.948654</td>\n",
       "      <td>0.184656</td>\n",
       "      <td>2.460867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9019</th>\n",
       "      <td>-118.78</td>\n",
       "      <td>34.16</td>\n",
       "      <td>9.0</td>\n",
       "      <td>30405.0</td>\n",
       "      <td>4093.0</td>\n",
       "      <td>12873.0</td>\n",
       "      <td>3931.0</td>\n",
       "      <td>8.0137</td>\n",
       "      <td>399200.0</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>7.734673</td>\n",
       "      <td>0.134616</td>\n",
       "      <td>3.274739</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9040</th>\n",
       "      <td>-118.09</td>\n",
       "      <td>34.68</td>\n",
       "      <td>4.0</td>\n",
       "      <td>23386.0</td>\n",
       "      <td>4171.0</td>\n",
       "      <td>10493.0</td>\n",
       "      <td>3671.0</td>\n",
       "      <td>4.0211</td>\n",
       "      <td>144000.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>6.370471</td>\n",
       "      <td>0.178355</td>\n",
       "      <td>2.858349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9122</th>\n",
       "      <td>-118.10</td>\n",
       "      <td>34.57</td>\n",
       "      <td>7.0</td>\n",
       "      <td>20377.0</td>\n",
       "      <td>4335.0</td>\n",
       "      <td>11973.0</td>\n",
       "      <td>3933.0</td>\n",
       "      <td>3.3086</td>\n",
       "      <td>138100.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>5.181032</td>\n",
       "      <td>0.212740</td>\n",
       "      <td>3.044241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9145</th>\n",
       "      <td>-118.46</td>\n",
       "      <td>34.40</td>\n",
       "      <td>12.0</td>\n",
       "      <td>25957.0</td>\n",
       "      <td>4798.0</td>\n",
       "      <td>10475.0</td>\n",
       "      <td>4490.0</td>\n",
       "      <td>4.5420</td>\n",
       "      <td>195300.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5.781069</td>\n",
       "      <td>0.184844</td>\n",
       "      <td>2.332962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9166</th>\n",
       "      <td>-118.43</td>\n",
       "      <td>34.43</td>\n",
       "      <td>5.0</td>\n",
       "      <td>21113.0</td>\n",
       "      <td>4386.0</td>\n",
       "      <td>9842.0</td>\n",
       "      <td>3886.0</td>\n",
       "      <td>4.2037</td>\n",
       "      <td>194600.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5.433093</td>\n",
       "      <td>0.207739</td>\n",
       "      <td>2.532681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9183</th>\n",
       "      <td>-118.55</td>\n",
       "      <td>34.41</td>\n",
       "      <td>8.0</td>\n",
       "      <td>21086.0</td>\n",
       "      <td>3945.0</td>\n",
       "      <td>9936.0</td>\n",
       "      <td>3790.0</td>\n",
       "      <td>5.8602</td>\n",
       "      <td>265100.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5.563588</td>\n",
       "      <td>0.187091</td>\n",
       "      <td>2.621636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9744</th>\n",
       "      <td>-121.68</td>\n",
       "      <td>36.72</td>\n",
       "      <td>12.0</td>\n",
       "      <td>19234.0</td>\n",
       "      <td>4492.0</td>\n",
       "      <td>12153.0</td>\n",
       "      <td>4372.0</td>\n",
       "      <td>3.2652</td>\n",
       "      <td>152800.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>4.399360</td>\n",
       "      <td>0.233545</td>\n",
       "      <td>2.779735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9880</th>\n",
       "      <td>-121.79</td>\n",
       "      <td>36.64</td>\n",
       "      <td>11.0</td>\n",
       "      <td>32627.0</td>\n",
       "      <td>6445.0</td>\n",
       "      <td>28566.0</td>\n",
       "      <td>6082.0</td>\n",
       "      <td>2.3087</td>\n",
       "      <td>118800.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5.364518</td>\n",
       "      <td>0.197536</td>\n",
       "      <td>4.696810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10309</th>\n",
       "      <td>-117.74</td>\n",
       "      <td>33.89</td>\n",
       "      <td>4.0</td>\n",
       "      <td>37937.0</td>\n",
       "      <td>5471.0</td>\n",
       "      <td>16122.0</td>\n",
       "      <td>5189.0</td>\n",
       "      <td>7.4947</td>\n",
       "      <td>366300.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>7.311043</td>\n",
       "      <td>0.144213</td>\n",
       "      <td>3.106957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11775</th>\n",
       "      <td>-121.33</td>\n",
       "      <td>38.77</td>\n",
       "      <td>3.0</td>\n",
       "      <td>20214.0</td>\n",
       "      <td>3559.0</td>\n",
       "      <td>8361.0</td>\n",
       "      <td>3112.0</td>\n",
       "      <td>4.2259</td>\n",
       "      <td>169300.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>6.495501</td>\n",
       "      <td>0.176066</td>\n",
       "      <td>2.686697</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12106</th>\n",
       "      <td>-117.34</td>\n",
       "      <td>33.98</td>\n",
       "      <td>10.0</td>\n",
       "      <td>17286.0</td>\n",
       "      <td>4952.0</td>\n",
       "      <td>9851.0</td>\n",
       "      <td>4616.0</td>\n",
       "      <td>1.7579</td>\n",
       "      <td>103400.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>3.744801</td>\n",
       "      <td>0.286475</td>\n",
       "      <td>2.134099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12152</th>\n",
       "      <td>-117.27</td>\n",
       "      <td>33.68</td>\n",
       "      <td>8.0</td>\n",
       "      <td>26322.0</td>\n",
       "      <td>4072.0</td>\n",
       "      <td>9360.0</td>\n",
       "      <td>3361.0</td>\n",
       "      <td>5.3238</td>\n",
       "      <td>228900.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>7.831598</td>\n",
       "      <td>0.154699</td>\n",
       "      <td>2.784885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12201</th>\n",
       "      <td>-117.20</td>\n",
       "      <td>33.58</td>\n",
       "      <td>2.0</td>\n",
       "      <td>30450.0</td>\n",
       "      <td>5033.0</td>\n",
       "      <td>9419.0</td>\n",
       "      <td>3197.0</td>\n",
       "      <td>4.5936</td>\n",
       "      <td>174300.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>9.524554</td>\n",
       "      <td>0.165287</td>\n",
       "      <td>2.946200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12214</th>\n",
       "      <td>-117.12</td>\n",
       "      <td>33.49</td>\n",
       "      <td>4.0</td>\n",
       "      <td>21988.0</td>\n",
       "      <td>4055.0</td>\n",
       "      <td>8824.0</td>\n",
       "      <td>3252.0</td>\n",
       "      <td>3.9963</td>\n",
       "      <td>191100.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>6.761378</td>\n",
       "      <td>0.184419</td>\n",
       "      <td>2.713407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12215</th>\n",
       "      <td>-117.12</td>\n",
       "      <td>33.52</td>\n",
       "      <td>4.0</td>\n",
       "      <td>30401.0</td>\n",
       "      <td>4957.0</td>\n",
       "      <td>13251.0</td>\n",
       "      <td>4339.0</td>\n",
       "      <td>4.5841</td>\n",
       "      <td>212300.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>7.006453</td>\n",
       "      <td>0.163054</td>\n",
       "      <td>3.053929</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12227</th>\n",
       "      <td>-116.99</td>\n",
       "      <td>33.73</td>\n",
       "      <td>13.0</td>\n",
       "      <td>16148.0</td>\n",
       "      <td>3474.0</td>\n",
       "      <td>6159.0</td>\n",
       "      <td>3232.0</td>\n",
       "      <td>1.9961</td>\n",
       "      <td>97800.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>4.996287</td>\n",
       "      <td>0.215135</td>\n",
       "      <td>1.905631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12623</th>\n",
       "      <td>-121.53</td>\n",
       "      <td>38.48</td>\n",
       "      <td>5.0</td>\n",
       "      <td>27870.0</td>\n",
       "      <td>5027.0</td>\n",
       "      <td>11935.0</td>\n",
       "      <td>4855.0</td>\n",
       "      <td>4.8811</td>\n",
       "      <td>212200.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>5.740474</td>\n",
       "      <td>0.180373</td>\n",
       "      <td>2.458290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12703</th>\n",
       "      <td>-121.41</td>\n",
       "      <td>38.59</td>\n",
       "      <td>17.0</td>\n",
       "      <td>12355.0</td>\n",
       "      <td>3630.0</td>\n",
       "      <td>5692.0</td>\n",
       "      <td>3073.0</td>\n",
       "      <td>2.5245</td>\n",
       "      <td>99100.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>4.020501</td>\n",
       "      <td>0.293808</td>\n",
       "      <td>1.852262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12814</th>\n",
       "      <td>-121.50</td>\n",
       "      <td>38.62</td>\n",
       "      <td>8.0</td>\n",
       "      <td>16679.0</td>\n",
       "      <td>3457.0</td>\n",
       "      <td>7919.0</td>\n",
       "      <td>3329.0</td>\n",
       "      <td>3.7188</td>\n",
       "      <td>134500.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>5.010213</td>\n",
       "      <td>0.207267</td>\n",
       "      <td>2.378792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13080</th>\n",
       "      <td>-121.35</td>\n",
       "      <td>38.54</td>\n",
       "      <td>12.0</td>\n",
       "      <td>16239.0</td>\n",
       "      <td>3358.0</td>\n",
       "      <td>8656.0</td>\n",
       "      <td>3234.0</td>\n",
       "      <td>3.5691</td>\n",
       "      <td>116300.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>5.021336</td>\n",
       "      <td>0.206786</td>\n",
       "      <td>2.676562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13098</th>\n",
       "      <td>-121.40</td>\n",
       "      <td>38.47</td>\n",
       "      <td>4.0</td>\n",
       "      <td>20982.0</td>\n",
       "      <td>3392.0</td>\n",
       "      <td>10329.0</td>\n",
       "      <td>3086.0</td>\n",
       "      <td>4.3658</td>\n",
       "      <td>130600.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>6.799093</td>\n",
       "      <td>0.161662</td>\n",
       "      <td>3.347051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13139</th>\n",
       "      <td>-121.44</td>\n",
       "      <td>38.43</td>\n",
       "      <td>3.0</td>\n",
       "      <td>39320.0</td>\n",
       "      <td>6210.0</td>\n",
       "      <td>16305.0</td>\n",
       "      <td>5358.0</td>\n",
       "      <td>4.9516</td>\n",
       "      <td>153700.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>7.338559</td>\n",
       "      <td>0.157935</td>\n",
       "      <td>3.043113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13176</th>\n",
       "      <td>-117.75</td>\n",
       "      <td>34.01</td>\n",
       "      <td>4.0</td>\n",
       "      <td>22128.0</td>\n",
       "      <td>3522.0</td>\n",
       "      <td>10450.0</td>\n",
       "      <td>3258.0</td>\n",
       "      <td>6.1287</td>\n",
       "      <td>289600.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>6.791897</td>\n",
       "      <td>0.159165</td>\n",
       "      <td>3.207489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13382</th>\n",
       "      <td>-117.59</td>\n",
       "      <td>34.13</td>\n",
       "      <td>10.0</td>\n",
       "      <td>20263.0</td>\n",
       "      <td>3915.0</td>\n",
       "      <td>9716.0</td>\n",
       "      <td>3744.0</td>\n",
       "      <td>3.8505</td>\n",
       "      <td>169600.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>5.412126</td>\n",
       "      <td>0.193209</td>\n",
       "      <td>2.595085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13387</th>\n",
       "      <td>-117.61</td>\n",
       "      <td>34.10</td>\n",
       "      <td>9.0</td>\n",
       "      <td>18956.0</td>\n",
       "      <td>4095.0</td>\n",
       "      <td>10323.0</td>\n",
       "      <td>3832.0</td>\n",
       "      <td>3.6033</td>\n",
       "      <td>132600.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>4.946764</td>\n",
       "      <td>0.216027</td>\n",
       "      <td>2.693894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14505</th>\n",
       "      <td>-117.22</td>\n",
       "      <td>32.86</td>\n",
       "      <td>4.0</td>\n",
       "      <td>16289.0</td>\n",
       "      <td>4585.0</td>\n",
       "      <td>7604.0</td>\n",
       "      <td>4176.0</td>\n",
       "      <td>3.6287</td>\n",
       "      <td>280800.0</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>3.900623</td>\n",
       "      <td>0.281478</td>\n",
       "      <td>1.820881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15105</th>\n",
       "      <td>-117.01</td>\n",
       "      <td>32.83</td>\n",
       "      <td>17.0</td>\n",
       "      <td>15401.0</td>\n",
       "      <td>3280.0</td>\n",
       "      <td>7302.0</td>\n",
       "      <td>3176.0</td>\n",
       "      <td>3.3067</td>\n",
       "      <td>121900.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>4.849181</td>\n",
       "      <td>0.212973</td>\n",
       "      <td>2.299118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15337</th>\n",
       "      <td>-117.31</td>\n",
       "      <td>33.19</td>\n",
       "      <td>11.0</td>\n",
       "      <td>20944.0</td>\n",
       "      <td>3753.0</td>\n",
       "      <td>8738.0</td>\n",
       "      <td>3441.0</td>\n",
       "      <td>4.3762</td>\n",
       "      <td>215500.0</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>6.086603</td>\n",
       "      <td>0.179192</td>\n",
       "      <td>2.539378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15360</th>\n",
       "      <td>-117.42</td>\n",
       "      <td>33.35</td>\n",
       "      <td>14.0</td>\n",
       "      <td>25135.0</td>\n",
       "      <td>4819.0</td>\n",
       "      <td>35682.0</td>\n",
       "      <td>4769.0</td>\n",
       "      <td>2.5729</td>\n",
       "      <td>134400.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5.270497</td>\n",
       "      <td>0.191725</td>\n",
       "      <td>7.482072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15413</th>\n",
       "      <td>-117.27</td>\n",
       "      <td>33.23</td>\n",
       "      <td>5.0</td>\n",
       "      <td>20908.0</td>\n",
       "      <td>3933.0</td>\n",
       "      <td>9690.0</td>\n",
       "      <td>3510.0</td>\n",
       "      <td>4.1405</td>\n",
       "      <td>198500.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5.956695</td>\n",
       "      <td>0.188110</td>\n",
       "      <td>2.760684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15459</th>\n",
       "      <td>-117.27</td>\n",
       "      <td>33.15</td>\n",
       "      <td>4.0</td>\n",
       "      <td>23915.0</td>\n",
       "      <td>4135.0</td>\n",
       "      <td>10877.0</td>\n",
       "      <td>3958.0</td>\n",
       "      <td>4.6357</td>\n",
       "      <td>244900.0</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>6.042193</td>\n",
       "      <td>0.172904</td>\n",
       "      <td>2.748105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18209</th>\n",
       "      <td>-122.06</td>\n",
       "      <td>37.40</td>\n",
       "      <td>21.0</td>\n",
       "      <td>12855.0</td>\n",
       "      <td>3226.0</td>\n",
       "      <td>7273.0</td>\n",
       "      <td>3052.0</td>\n",
       "      <td>4.3351</td>\n",
       "      <td>267400.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>4.211992</td>\n",
       "      <td>0.250953</td>\n",
       "      <td>2.383028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18346</th>\n",
       "      <td>-122.15</td>\n",
       "      <td>37.43</td>\n",
       "      <td>20.0</td>\n",
       "      <td>11709.0</td>\n",
       "      <td>435.0</td>\n",
       "      <td>7604.0</td>\n",
       "      <td>3589.0</td>\n",
       "      <td>1.9045</td>\n",
       "      <td>375000.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>3.262469</td>\n",
       "      <td>0.037151</td>\n",
       "      <td>2.118696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20451</th>\n",
       "      <td>-118.90</td>\n",
       "      <td>34.26</td>\n",
       "      <td>5.0</td>\n",
       "      <td>25187.0</td>\n",
       "      <td>3521.0</td>\n",
       "      <td>11956.0</td>\n",
       "      <td>3478.0</td>\n",
       "      <td>6.9712</td>\n",
       "      <td>321300.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>7.241806</td>\n",
       "      <td>0.139794</td>\n",
       "      <td>3.437608</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "922      -121.92     37.53                 7.0      28258.0          3864.0   \n",
       "1010     -121.73     37.68                17.0      20354.0          3493.0   \n",
       "1060     -121.88     39.74                12.0      14631.0          3298.0   \n",
       "3981     -118.60     34.19                16.0      14912.0          4183.0   \n",
       "4035     -118.52     34.17                20.0      17377.0          4457.0   \n",
       "5540     -118.43     33.96                16.0      14891.0          3984.0   \n",
       "6057     -117.78     34.03                 8.0      32054.0          5290.0   \n",
       "6066     -117.87     34.04                 7.0      27700.0          4179.0   \n",
       "6338     -117.88     33.96                16.0      19059.0          3079.0   \n",
       "8467     -118.34     33.91                12.0       9975.0          3638.0   \n",
       "8468     -118.33     33.91                 8.0      10731.0          3335.0   \n",
       "8716     -118.35     33.84                22.0      13133.0          3680.0   \n",
       "8985     -118.44     33.98                21.0      18132.0          5419.0   \n",
       "9018     -118.72     34.14                 7.0      23866.0          4407.0   \n",
       "9019     -118.78     34.16                 9.0      30405.0          4093.0   \n",
       "9040     -118.09     34.68                 4.0      23386.0          4171.0   \n",
       "9122     -118.10     34.57                 7.0      20377.0          4335.0   \n",
       "9145     -118.46     34.40                12.0      25957.0          4798.0   \n",
       "9166     -118.43     34.43                 5.0      21113.0          4386.0   \n",
       "9183     -118.55     34.41                 8.0      21086.0          3945.0   \n",
       "9744     -121.68     36.72                12.0      19234.0          4492.0   \n",
       "9880     -121.79     36.64                11.0      32627.0          6445.0   \n",
       "10309    -117.74     33.89                 4.0      37937.0          5471.0   \n",
       "11775    -121.33     38.77                 3.0      20214.0          3559.0   \n",
       "12106    -117.34     33.98                10.0      17286.0          4952.0   \n",
       "12152    -117.27     33.68                 8.0      26322.0          4072.0   \n",
       "12201    -117.20     33.58                 2.0      30450.0          5033.0   \n",
       "12214    -117.12     33.49                 4.0      21988.0          4055.0   \n",
       "12215    -117.12     33.52                 4.0      30401.0          4957.0   \n",
       "12227    -116.99     33.73                13.0      16148.0          3474.0   \n",
       "12623    -121.53     38.48                 5.0      27870.0          5027.0   \n",
       "12703    -121.41     38.59                17.0      12355.0          3630.0   \n",
       "12814    -121.50     38.62                 8.0      16679.0          3457.0   \n",
       "13080    -121.35     38.54                12.0      16239.0          3358.0   \n",
       "13098    -121.40     38.47                 4.0      20982.0          3392.0   \n",
       "13139    -121.44     38.43                 3.0      39320.0          6210.0   \n",
       "13176    -117.75     34.01                 4.0      22128.0          3522.0   \n",
       "13382    -117.59     34.13                10.0      20263.0          3915.0   \n",
       "13387    -117.61     34.10                 9.0      18956.0          4095.0   \n",
       "14505    -117.22     32.86                 4.0      16289.0          4585.0   \n",
       "15105    -117.01     32.83                17.0      15401.0          3280.0   \n",
       "15337    -117.31     33.19                11.0      20944.0          3753.0   \n",
       "15360    -117.42     33.35                14.0      25135.0          4819.0   \n",
       "15413    -117.27     33.23                 5.0      20908.0          3933.0   \n",
       "15459    -117.27     33.15                 4.0      23915.0          4135.0   \n",
       "18209    -122.06     37.40                21.0      12855.0          3226.0   \n",
       "18346    -122.15     37.43                20.0      11709.0           435.0   \n",
       "20451    -118.90     34.26                 5.0      25187.0          3521.0   \n",
       "\n",
       "       population  households  median_income  median_house_value  \\\n",
       "922       12203.0      3701.0         8.4045            451100.0   \n",
       "1010       8768.0      3293.0         5.4496            238900.0   \n",
       "1060       7517.0      3262.0         1.6785            153100.0   \n",
       "3981       5105.0      3302.0         2.8312            213900.0   \n",
       "4035       7450.0      4204.0         3.2154            259600.0   \n",
       "5540       6270.0      3595.0         5.1064            283200.0   \n",
       "6057      15507.0      5050.0         6.0191            253900.0   \n",
       "6066      15037.0      4072.0         6.6288            339700.0   \n",
       "6338      10988.0      3061.0         5.5469            265200.0   \n",
       "8467       7429.0      3405.0         2.6689            192300.0   \n",
       "8468       7211.0      3028.0         2.4550            192700.0   \n",
       "8716       7180.0      3522.0         3.5414            354700.0   \n",
       "8985       7431.0      4930.0         5.3359            500001.0   \n",
       "9018       9873.0      4012.0         5.4032            318500.0   \n",
       "9019      12873.0      3931.0         8.0137            399200.0   \n",
       "9040      10493.0      3671.0         4.0211            144000.0   \n",
       "9122      11973.0      3933.0         3.3086            138100.0   \n",
       "9145      10475.0      4490.0         4.5420            195300.0   \n",
       "9166       9842.0      3886.0         4.2037            194600.0   \n",
       "9183       9936.0      3790.0         5.8602            265100.0   \n",
       "9744      12153.0      4372.0         3.2652            152800.0   \n",
       "9880      28566.0      6082.0         2.3087            118800.0   \n",
       "10309     16122.0      5189.0         7.4947            366300.0   \n",
       "11775      8361.0      3112.0         4.2259            169300.0   \n",
       "12106      9851.0      4616.0         1.7579            103400.0   \n",
       "12152      9360.0      3361.0         5.3238            228900.0   \n",
       "12201      9419.0      3197.0         4.5936            174300.0   \n",
       "12214      8824.0      3252.0         3.9963            191100.0   \n",
       "12215     13251.0      4339.0         4.5841            212300.0   \n",
       "12227      6159.0      3232.0         1.9961             97800.0   \n",
       "12623     11935.0      4855.0         4.8811            212200.0   \n",
       "12703      5692.0      3073.0         2.5245             99100.0   \n",
       "12814      7919.0      3329.0         3.7188            134500.0   \n",
       "13080      8656.0      3234.0         3.5691            116300.0   \n",
       "13098     10329.0      3086.0         4.3658            130600.0   \n",
       "13139     16305.0      5358.0         4.9516            153700.0   \n",
       "13176     10450.0      3258.0         6.1287            289600.0   \n",
       "13382      9716.0      3744.0         3.8505            169600.0   \n",
       "13387     10323.0      3832.0         3.6033            132600.0   \n",
       "14505      7604.0      4176.0         3.6287            280800.0   \n",
       "15105      7302.0      3176.0         3.3067            121900.0   \n",
       "15337      8738.0      3441.0         4.3762            215500.0   \n",
       "15360     35682.0      4769.0         2.5729            134400.0   \n",
       "15413      9690.0      3510.0         4.1405            198500.0   \n",
       "15459     10877.0      3958.0         4.6357            244900.0   \n",
       "18209      7273.0      3052.0         4.3351            267400.0   \n",
       "18346      7604.0      3589.0         1.9045            375000.0   \n",
       "20451     11956.0      3478.0         6.9712            321300.0   \n",
       "\n",
       "      ocean_proximity  rooms_per_household  bedrooms_per_room  \\\n",
       "922         <1H OCEAN             7.635234           0.136740   \n",
       "1010           INLAND             6.180990           0.171612   \n",
       "1060           INLAND             4.485285           0.225412   \n",
       "3981        <1H OCEAN             4.516051           0.280512   \n",
       "4035        <1H OCEAN             4.133444           0.256488   \n",
       "5540        <1H OCEAN             4.142142           0.267544   \n",
       "6057        <1H OCEAN             6.347327           0.165034   \n",
       "6066        <1H OCEAN             6.802554           0.150866   \n",
       "6338        <1H OCEAN             6.226397           0.161551   \n",
       "8467        <1H OCEAN             2.929515           0.364712   \n",
       "8468        <1H OCEAN             3.543923           0.310782   \n",
       "8716        <1H OCEAN             3.728847           0.280210   \n",
       "8985        <1H OCEAN             3.677890           0.298864   \n",
       "9018       NEAR OCEAN             5.948654           0.184656   \n",
       "9019       NEAR OCEAN             7.734673           0.134616   \n",
       "9040           INLAND             6.370471           0.178355   \n",
       "9122           INLAND             5.181032           0.212740   \n",
       "9145        <1H OCEAN             5.781069           0.184844   \n",
       "9166        <1H OCEAN             5.433093           0.207739   \n",
       "9183        <1H OCEAN             5.563588           0.187091   \n",
       "9744        <1H OCEAN             4.399360           0.233545   \n",
       "9880        <1H OCEAN             5.364518           0.197536   \n",
       "10309       <1H OCEAN             7.311043           0.144213   \n",
       "11775          INLAND             6.495501           0.176066   \n",
       "12106          INLAND             3.744801           0.286475   \n",
       "12152       <1H OCEAN             7.831598           0.154699   \n",
       "12201       <1H OCEAN             9.524554           0.165287   \n",
       "12214       <1H OCEAN             6.761378           0.184419   \n",
       "12215       <1H OCEAN             7.006453           0.163054   \n",
       "12227          INLAND             4.996287           0.215135   \n",
       "12623          INLAND             5.740474           0.180373   \n",
       "12703          INLAND             4.020501           0.293808   \n",
       "12814          INLAND             5.010213           0.207267   \n",
       "13080          INLAND             5.021336           0.206786   \n",
       "13098          INLAND             6.799093           0.161662   \n",
       "13139          INLAND             7.338559           0.157935   \n",
       "13176       <1H OCEAN             6.791897           0.159165   \n",
       "13382          INLAND             5.412126           0.193209   \n",
       "13387          INLAND             4.946764           0.216027   \n",
       "14505      NEAR OCEAN             3.900623           0.281478   \n",
       "15105       <1H OCEAN             4.849181           0.212973   \n",
       "15337      NEAR OCEAN             6.086603           0.179192   \n",
       "15360       <1H OCEAN             5.270497           0.191725   \n",
       "15413       <1H OCEAN             5.956695           0.188110   \n",
       "15459      NEAR OCEAN             6.042193           0.172904   \n",
       "18209        NEAR BAY             4.211992           0.250953   \n",
       "18346        NEAR BAY             3.262469           0.037151   \n",
       "20451       <1H OCEAN             7.241806           0.139794   \n",
       "\n",
       "       population_per_househol  \n",
       "922                   3.297217  \n",
       "1010                  2.662618  \n",
       "1060                  2.304414  \n",
       "3981                  1.546033  \n",
       "4035                  1.772122  \n",
       "5540                  1.744089  \n",
       "6057                  3.070693  \n",
       "6066                  3.692780  \n",
       "6338                  3.589677  \n",
       "8467                  2.181791  \n",
       "8468                  2.381440  \n",
       "8716                  2.038614  \n",
       "8985                  1.507302  \n",
       "9018                  2.460867  \n",
       "9019                  3.274739  \n",
       "9040                  2.858349  \n",
       "9122                  3.044241  \n",
       "9145                  2.332962  \n",
       "9166                  2.532681  \n",
       "9183                  2.621636  \n",
       "9744                  2.779735  \n",
       "9880                  4.696810  \n",
       "10309                 3.106957  \n",
       "11775                 2.686697  \n",
       "12106                 2.134099  \n",
       "12152                 2.784885  \n",
       "12201                 2.946200  \n",
       "12214                 2.713407  \n",
       "12215                 3.053929  \n",
       "12227                 1.905631  \n",
       "12623                 2.458290  \n",
       "12703                 1.852262  \n",
       "12814                 2.378792  \n",
       "13080                 2.676562  \n",
       "13098                 3.347051  \n",
       "13139                 3.043113  \n",
       "13176                 3.207489  \n",
       "13382                 2.595085  \n",
       "13387                 2.693894  \n",
       "14505                 1.820881  \n",
       "15105                 2.299118  \n",
       "15337                 2.539378  \n",
       "15360                 7.482072  \n",
       "15413                 2.760684  \n",
       "15459                 2.748105  \n",
       "18209                 2.383028  \n",
       "18346                 2.118696  \n",
       "20451                 3.437608  "
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing[housing['households'] > 3000]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Prenons par exemple la valeur de la ligne 8985 (voir image ci-dessous), on peut remarquer que la maison (household and not estate) est plutôt très chère pour une maison âgée de 21 an et avec comme nombre de chambre approximativement 4. Peut-être est-ce le problème??!!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"outlier1.PNG\">"
   ]
  }
 ],
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