Melbourne Housing Market.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Predcit Melbourne housing prices."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Run prediction with numerical columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from arcgis import GIS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "gis = GIS(\"https://www.arcgis.com\", \"arcgis_python\", \"P@ssword123\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "housing_data = gis.content.search('title: Melbourne Housing Market', 'Feature layer', outside_org=True)[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div class=\"item_container\" style=\"height: auto; overflow: hidden; border: 1px solid #cfcfcf; border-radius: 2px; background: #f6fafa; line-height: 1.21429em; padding: 10px;\">\n",
       "                    <div class=\"item_left\" style=\"width: 210px; float: left;\">\n",
       "                       <a href='https://geosaurus.maps.arcgis.com/home/item.html?id=90819038fe2c42de93d5344be090ebb4' target='_blank'>\n",
       "                        <img src='data:image/png;base64,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' width='200' height='133' class=\"itemThumbnail\">\n",
       "                       </a>\n",
       "                    </div>\n",
       "\n",
       "                    <div class=\"item_right\"     style=\"float: none; width: auto; overflow: hidden;\">\n",
       "                        <a href='https://geosaurus.maps.arcgis.com/home/item.html?id=90819038fe2c42de93d5344be090ebb4' target='_blank'><b>Melbourne Housing Market</b>\n",
       "                        </a>\n",
       "                        <br/><img src='https://geosaurus.maps.arcgis.com/home/js/jsapi/esri/css/images/item_type_icons/featureshosted16.png' style=\"vertical-align:middle;\">Feature Layer Collection by demo_deldev\n",
       "                        <br/>Last Modified: May 28, 2018\n",
       "                        <br/>0 comments, 4 views\n",
       "                    </div>\n",
       "                </div>\n",
       "                "
      ],
      "text/plain": [
       "<Item title:\"Melbourne Housing Market\" type:Feature Layer Collection owner:demo_deldev>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from arcgis.features import SpatialDataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "sdf = SpatialDataFrame.from_layer(housing_data.layers[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Address', 'Bathroom', 'Bedroom2', 'BuildingArea', 'Car', 'CouncilArea',\n",
       "       'Date', 'Distance', 'FID', 'Landsize', 'Lattitude', 'Longtitude',\n",
       "       'Method', 'Postcode', 'Price', 'Propertycount', 'Regionname', 'Rooms',\n",
       "       'SellerG', 'Suburb', 'Type', 'YearBuilt', 'SHAPE'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sdf.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(26881, 23)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sdf.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "sdf = sdf[sdf.Price.notnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(20993, 23)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sdf.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Address', 'Bathroom', 'Bedroom2', 'BuildingArea', 'Car', 'CouncilArea',\n",
       "       'Date', 'Distance', 'FID', 'Landsize', 'Lattitude', 'Longtitude',\n",
       "       'Method', 'Postcode', 'Price', 'Propertycount', 'Regionname', 'Rooms',\n",
       "       'SellerG', 'Suburb', 'Type', 'YearBuilt', 'SHAPE'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sdf.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>Bathroom</th>\n",
       "      <th>Bedroom2</th>\n",
       "      <th>Car</th>\n",
       "      <th>Distance</th>\n",
       "      <th>FID</th>\n",
       "      <th>Landsize</th>\n",
       "      <th>Lattitude</th>\n",
       "      <th>Longtitude</th>\n",
       "      <th>Postcode</th>\n",
       "      <th>Price</th>\n",
       "      <th>Propertycount</th>\n",
       "      <th>Rooms</th>\n",
       "      <th>YearBuilt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>20778.000000</td>\n",
       "      <td>20784.000000</td>\n",
       "      <td>20401.000000</td>\n",
       "      <td>20993.000000</td>\n",
       "      <td>20993.000000</td>\n",
       "      <td>17960.000000</td>\n",
       "      <td>20993.000000</td>\n",
       "      <td>20993.000000</td>\n",
       "      <td>20993.000000</td>\n",
       "      <td>2.099300e+04</td>\n",
       "      <td>20993.000000</td>\n",
       "      <td>20993.000000</td>\n",
       "      <td>12076.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.591298</td>\n",
       "      <td>3.046237</td>\n",
       "      <td>1.715259</td>\n",
       "      <td>11.359020</td>\n",
       "      <td>13443.965941</td>\n",
       "      <td>593.748719</td>\n",
       "      <td>-37.806963</td>\n",
       "      <td>144.996711</td>\n",
       "      <td>3114.630972</td>\n",
       "      <td>1.089746e+06</td>\n",
       "      <td>7516.751489</td>\n",
       "      <td>3.059163</td>\n",
       "      <td>1966.592001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.700844</td>\n",
       "      <td>0.954948</td>\n",
       "      <td>0.994518</td>\n",
       "      <td>6.891418</td>\n",
       "      <td>7730.711620</td>\n",
       "      <td>3759.538783</td>\n",
       "      <td>0.091619</td>\n",
       "      <td>0.120680</td>\n",
       "      <td>114.810599</td>\n",
       "      <td>6.530283e+05</td>\n",
       "      <td>4411.397778</td>\n",
       "      <td>0.949881</td>\n",
       "      <td>36.752058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-38.190430</td>\n",
       "      <td>144.423790</td>\n",
       "      <td>3000.000000</td>\n",
       "      <td>8.500000e+04</td>\n",
       "      <td>83.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1196.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.400000</td>\n",
       "      <td>6777.000000</td>\n",
       "      <td>219.000000</td>\n",
       "      <td>-37.860900</td>\n",
       "      <td>144.925300</td>\n",
       "      <td>3046.000000</td>\n",
       "      <td>6.570000e+05</td>\n",
       "      <td>4380.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1950.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>10.400000</td>\n",
       "      <td>13481.000000</td>\n",
       "      <td>512.000000</td>\n",
       "      <td>-37.800460</td>\n",
       "      <td>145.003200</td>\n",
       "      <td>3087.000000</td>\n",
       "      <td>9.100000e+05</td>\n",
       "      <td>6567.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1970.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>14.200000</td>\n",
       "      <td>20082.000000</td>\n",
       "      <td>664.000000</td>\n",
       "      <td>-37.748970</td>\n",
       "      <td>145.068770</td>\n",
       "      <td>3152.000000</td>\n",
       "      <td>1.335000e+06</td>\n",
       "      <td>10331.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>2000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>9.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>48.100000</td>\n",
       "      <td>26881.000000</td>\n",
       "      <td>433014.000000</td>\n",
       "      <td>-37.397800</td>\n",
       "      <td>145.526350</td>\n",
       "      <td>3978.000000</td>\n",
       "      <td>1.120000e+07</td>\n",
       "      <td>21650.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>2019.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Bathroom      Bedroom2           Car      Distance           FID  \\\n",
       "count  20778.000000  20784.000000  20401.000000  20993.000000  20993.000000   \n",
       "mean       1.591298      3.046237      1.715259     11.359020  13443.965941   \n",
       "std        0.700844      0.954948      0.994518      6.891418   7730.711620   \n",
       "min        0.000000      0.000000      0.000000      0.000000      2.000000   \n",
       "25%        1.000000      2.000000      1.000000      6.400000   6777.000000   \n",
       "50%        1.000000      3.000000      2.000000     10.400000  13481.000000   \n",
       "75%        2.000000      4.000000      2.000000     14.200000  20082.000000   \n",
       "max        9.000000     20.000000     18.000000     48.100000  26881.000000   \n",
       "\n",
       "            Landsize     Lattitude    Longtitude      Postcode         Price  \\\n",
       "count   17960.000000  20993.000000  20993.000000  20993.000000  2.099300e+04   \n",
       "mean      593.748719    -37.806963    144.996711   3114.630972  1.089746e+06   \n",
       "std      3759.538783      0.091619      0.120680    114.810599  6.530283e+05   \n",
       "min         0.000000    -38.190430    144.423790   3000.000000  8.500000e+04   \n",
       "25%       219.000000    -37.860900    144.925300   3046.000000  6.570000e+05   \n",
       "50%       512.000000    -37.800460    145.003200   3087.000000  9.100000e+05   \n",
       "75%       664.000000    -37.748970    145.068770   3152.000000  1.335000e+06   \n",
       "max    433014.000000    -37.397800    145.526350   3978.000000  1.120000e+07   \n",
       "\n",
       "       Propertycount         Rooms     YearBuilt  \n",
       "count   20993.000000  20993.000000  12076.000000  \n",
       "mean     7516.751489      3.059163   1966.592001  \n",
       "std      4411.397778      0.949881     36.752058  \n",
       "min        83.000000      1.000000   1196.000000  \n",
       "25%      4380.000000      2.000000   1950.000000  \n",
       "50%      6567.000000      3.000000   1970.000000  \n",
       "75%     10331.000000      4.000000   2000.000000  \n",
       "max     21650.000000     16.000000   2019.000000  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sdf.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dataset with continuous values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "cols = ['Bathroom', 'Bedroom2', 'BuildingArea', 'Distance', 'Landsize',\n",
    "        'Lattitude', 'Longtitude', 'Rooms', 'YearBuilt', 'Price']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = sdf[cols]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>Bathroom</th>\n",
       "      <th>Bedroom2</th>\n",
       "      <th>BuildingArea</th>\n",
       "      <th>Distance</th>\n",
       "      <th>Landsize</th>\n",
       "      <th>Lattitude</th>\n",
       "      <th>Longtitude</th>\n",
       "      <th>Rooms</th>\n",
       "      <th>YearBuilt</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>None</td>\n",
       "      <td>2.5</td>\n",
       "      <td>202.0</td>\n",
       "      <td>-37.7996</td>\n",
       "      <td>144.9984</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1480000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>79</td>\n",
       "      <td>2.5</td>\n",
       "      <td>156.0</td>\n",
       "      <td>-37.8079</td>\n",
       "      <td>144.9934</td>\n",
       "      <td>2</td>\n",
       "      <td>1900.0</td>\n",
       "      <td>1035000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>150</td>\n",
       "      <td>2.5</td>\n",
       "      <td>134.0</td>\n",
       "      <td>-37.8093</td>\n",
       "      <td>144.9944</td>\n",
       "      <td>3</td>\n",
       "      <td>1900.0</td>\n",
       "      <td>1465000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>None</td>\n",
       "      <td>2.5</td>\n",
       "      <td>94.0</td>\n",
       "      <td>-37.7969</td>\n",
       "      <td>144.9969</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>850000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>142</td>\n",
       "      <td>2.5</td>\n",
       "      <td>120.0</td>\n",
       "      <td>-37.8072</td>\n",
       "      <td>144.9941</td>\n",
       "      <td>4</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>1600000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Bathroom  Bedroom2 BuildingArea  Distance  Landsize  Lattitude  Longtitude  \\\n",
       "1       1.0       2.0         None       2.5     202.0   -37.7996    144.9984   \n",
       "2       1.0       2.0           79       2.5     156.0   -37.8079    144.9934   \n",
       "4       2.0       3.0          150       2.5     134.0   -37.8093    144.9944   \n",
       "5       2.0       3.0         None       2.5      94.0   -37.7969    144.9969   \n",
       "6       1.0       3.0          142       2.5     120.0   -37.8072    144.9941   \n",
       "\n",
       "   Rooms  YearBuilt      Price  \n",
       "1      2        NaN  1480000.0  \n",
       "2      2     1900.0  1035000.0  \n",
       "4      3     1900.0  1465000.0  \n",
       "5      3        NaN   850000.0  \n",
       "6      4     2014.0  1600000.0  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Deleting rows with nan price "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "sf = df[np.isfinite(df['Price'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(20993, 10)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sf.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dropping the target value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = sf.Price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "sf.drop('Price', inplace=True, axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Replacing nan values with the missing values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import Imputer\n",
    "\n",
    "imputer = Imputer(strategy=\"median\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Imputer(axis=0, copy=True, missing_values='NaN', strategy='median', verbose=0)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imputer.fit(sf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1.000000e+00,  3.000000e+00,  1.330000e+02,  1.040000e+01,\n",
       "        5.120000e+02, -3.780046e+01,  1.450032e+02,  3.000000e+00,\n",
       "        1.970000e+03])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sf.median().values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "transformed = imputer.transform(sf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = pd.DataFrame(transformed, columns=sf.columns,\n",
    "                          index = list(sf.index.values))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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>Bathroom</th>\n",
       "      <th>Bedroom2</th>\n",
       "      <th>BuildingArea</th>\n",
       "      <th>Distance</th>\n",
       "      <th>Landsize</th>\n",
       "      <th>Lattitude</th>\n",
       "      <th>Longtitude</th>\n",
       "      <th>Rooms</th>\n",
       "      <th>YearBuilt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>133.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>202.0</td>\n",
       "      <td>-37.7996</td>\n",
       "      <td>144.9984</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1970.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>156.0</td>\n",
       "      <td>-37.8079</td>\n",
       "      <td>144.9934</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>134.0</td>\n",
       "      <td>-37.8093</td>\n",
       "      <td>144.9944</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>133.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>94.0</td>\n",
       "      <td>-37.7969</td>\n",
       "      <td>144.9969</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1970.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>120.0</td>\n",
       "      <td>-37.8072</td>\n",
       "      <td>144.9941</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2014.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Bathroom  Bedroom2  BuildingArea  Distance  Landsize  Lattitude  \\\n",
       "1       1.0       2.0         133.0       2.5     202.0   -37.7996   \n",
       "2       1.0       2.0          79.0       2.5     156.0   -37.8079   \n",
       "4       2.0       3.0         150.0       2.5     134.0   -37.8093   \n",
       "5       2.0       3.0         133.0       2.5      94.0   -37.7969   \n",
       "6       1.0       3.0         142.0       2.5     120.0   -37.8072   \n",
       "\n",
       "   Longtitude  Rooms  YearBuilt  \n",
       "1    144.9984    2.0     1970.0  \n",
       "2    144.9934    2.0     1900.0  \n",
       "4    144.9944    3.0     1900.0  \n",
       "5    144.9969    3.0     1970.0  \n",
       "6    144.9941    4.0     2014.0  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Feature scaling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_scaled = (x-x.min())/(x.max()-x.min())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Splittng train and test "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "train_X, test_X, train_y, test_y = train_test_split(x_scaled, y, random_state=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15744"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(train_X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15744"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(train_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5249"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(test_X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5249"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(test_y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Training and testing model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6814292905003134"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.tree import DecisionTreeRegressor\n",
    "from sklearn.metrics import r2_score\n",
    "\n",
    "model = DecisionTreeRegressor(max_leaf_nodes=500)\n",
    "model.fit(train_X, train_y)\n",
    "predicted = model.predict(test_X)\n",
    "r2_score(test_y, predicted)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "217740.1282340278"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# mean absolute error for decisiontreeclassifier\n",
    "from sklearn.metrics import mean_absolute_error\n",
    "mean_absolute_error(test_y, predicted)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7659181132222522"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "\n",
    "forest_reg = RandomForestRegressor()\n",
    "forest = forest_reg.fit(train_X, train_y)\n",
    "Predicted = forest.predict(test_X)\n",
    "r2_score(test_y, Predicted)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "182061.09502127388"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# mean absolute error for RandonForestRegressor\n",
    "from sklearn.metrics import mean_absolute_error\n",
    "mean_absolute_error(test_y, Predicted)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. Run prediction with categorical columns by making dummies."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "columns = ['Bathroom', 'Bedroom2', 'Distance', 'Landsize',\n",
    "        'Lattitude', 'Longtitude', 'Rooms', 'Price', 'Regionname', 'Method']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "dt = sdf[columns]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20993"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(dt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Bathroom       215\n",
       "Bedroom2       209\n",
       "Distance         0\n",
       "Landsize      3033\n",
       "Lattitude        0\n",
       "Longtitude       0\n",
       "Rooms            0\n",
       "Price            0\n",
       "Regionname       0\n",
       "Method           0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "dd = dt[np.isfinite(dt['Price'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(20993, 10)"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dd.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Distance     -0.235394\n",
       "Lattitude    -0.215607\n",
       "Landsize      0.032734\n",
       "Longtitude    0.197874\n",
       "Bathroom      0.430088\n",
       "Bedroom2      0.430289\n",
       "Rooms         0.446781\n",
       "Price         1.000000\n",
       "Name: Price, dtype: float64"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr_matrix = dd.corr()\n",
    "\n",
    "corr_matrix['Price'].sort_values()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# dropping target value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "Y = dd.Price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "dd.drop('Price', inplace=True, axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Replacing nan values with median"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "dd_num = dd.drop(['Method','Regionname'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import Imputer\n",
    "\n",
    "imputer = Imputer(strategy=\"median\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Imputer(axis=0, copy=True, missing_values='NaN', strategy='median', verbose=0)"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imputer.fit(dd_num)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "transformed = imputer.transform(dd_num)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_transfomed = pd.DataFrame(transformed, columns=dd_num.columns,\n",
    "                          index = list(dd_num.index.values))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = pd.concat([X_transfomed, dd[['Method','Regionname']]], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Bathroom      0\n",
       "Bedroom2      0\n",
       "Distance      0\n",
       "Landsize      0\n",
       "Lattitude     0\n",
       "Longtitude    0\n",
       "Rooms         0\n",
       "Method        0\n",
       "Regionname    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dummies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_dummy = pd.get_dummies(X)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# scaling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_scaled = (X_dummy-X_dummy.min())/(X_dummy.max()-X_dummy.min())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Splitting train and test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "x_train, x_test, y_train, y_test = train_test_split(X_scaled, y, random_state=42)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# training and testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6458052436684913"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.tree import DecisionTreeRegressor\n",
    "from sklearn.metrics import r2_score\n",
    "\n",
    "model = DecisionTreeRegressor(max_leaf_nodes=500)\n",
    "model.fit(x_train, y_train)\n",
    "predicted = model.predict(x_test)\n",
    "r2_score(y_test, predicted)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "618940.6649457039"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# mean_absolute_error for DecissiontreeRegressor\n",
    "from sklearn.metrics import mean_absolute_error\n",
    "mean_absolute_error(y_test, Predicted)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7431406088585124"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "\n",
    "forest_reg = RandomForestRegressor()\n",
    "forest = forest_reg.fit(x_train, y_train)\n",
    "Predicted = forest.predict(x_test)\n",
    "r2_score(y_test, Predicted)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "189131.15439675582"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# mean_absolute_error for RandomForestRegressor\n",
    "from sklearn.metrics import mean_absolute_error\n",
    "mean_absolute_error(y_test, Predicted)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. Visualization on orignal data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "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>Address</th>\n",
       "      <th>Bathroom</th>\n",
       "      <th>Bedroom2</th>\n",
       "      <th>BuildingArea</th>\n",
       "      <th>Car</th>\n",
       "      <th>CouncilArea</th>\n",
       "      <th>Date</th>\n",
       "      <th>Distance</th>\n",
       "      <th>FID</th>\n",
       "      <th>Landsize</th>\n",
       "      <th>...</th>\n",
       "      <th>Postcode</th>\n",
       "      <th>Price</th>\n",
       "      <th>Propertycount</th>\n",
       "      <th>Regionname</th>\n",
       "      <th>Rooms</th>\n",
       "      <th>SellerG</th>\n",
       "      <th>Suburb</th>\n",
       "      <th>Type</th>\n",
       "      <th>YearBuilt</th>\n",
       "      <th>SHAPE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>85 Turner St</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>None</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Yarra City Council</td>\n",
       "      <td>03-12-2016</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2</td>\n",
       "      <td>202.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3067</td>\n",
       "      <td>1480000.0</td>\n",
       "      <td>4019</td>\n",
       "      <td>Northern Metropolitan</td>\n",
       "      <td>2</td>\n",
       "      <td>Biggin</td>\n",
       "      <td>Abbotsford</td>\n",
       "      <td>h</td>\n",
       "      <td>NaN</td>\n",
       "      <td>{'x': 16141148.053839399, 'y': -4551154.566602...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Address  Bathroom  Bedroom2 BuildingArea  Car         CouncilArea  \\\n",
       "1  85 Turner St       1.0       2.0         None  1.0  Yarra City Council   \n",
       "\n",
       "         Date  Distance  FID  Landsize  \\\n",
       "1  03-12-2016       2.5    2     202.0   \n",
       "\n",
       "                         ...                          Postcode      Price  \\\n",
       "1                        ...                              3067  1480000.0   \n",
       "\n",
       "  Propertycount             Regionname  Rooms  SellerG      Suburb  Type  \\\n",
       "1          4019  Northern Metropolitan      2   Biggin  Abbotsford     h   \n",
       "\n",
       "  YearBuilt                                              SHAPE  \n",
       "1       NaN  {'x': 16141148.053839399, 'y': -4551154.566602...  \n",
       "\n",
       "[1 rows x 23 columns]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sdf.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x23097839c88>"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x23097839588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "sdf.plot(kind=\"scatter\", x=\"Longtitude\", y=\"Lattitude\", alpha=0.5, s=sdf[\"Price\"]/10000,\n",
    "         c=\"Landsize\", cmap=plt.get_cmap(\"jet\"))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\priyanka\\Anaconda3\\lib\\site-packages\\statsmodels\\nonparametric\\kde.py:454: RuntimeWarning: invalid value encountered in greater\n",
      "  X = X[np.logical_and(X>clip[0], X<clip[1])] # won't work for two columns.\n",
      "C:\\Users\\priyanka\\Anaconda3\\lib\\site-packages\\statsmodels\\nonparametric\\kde.py:454: RuntimeWarning: invalid value encountered in less\n",
      "  X = X[np.logical_and(X>clip[0], X<clip[1])] # won't work for two columns.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x1d64bdf07f0>"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1d64bde8940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(X, diag_kind=\"kde\", size= 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2309718fc50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.jointplot(x=sdf.Rooms, y=sdf.Price, data=df, kind=\"kde\", color=\"m\")\n",
    "g.plot_joint(plt.scatter, c=\"w\", s=30, linewidth=1, marker=\"+\")\n",
    "g.ax_joint.collections[0].set_alpha(0)\n",
    "g.set_axis_labels(\"$X$\", \"$Y$\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Northern Metropolitan', 'Western Metropolitan',\n",
       "       'Southern Metropolitan', 'Eastern Metropolitan',\n",
       "       'South-Eastern Metropolitan', 'Eastern Victoria',\n",
       "       'Northern Victoria', 'Western Victoria'], dtype=object)"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sdf['Regionname'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0,0,'Northern Metropolitan'),\n",
       " Text(0,0,'Western Metropolitan'),\n",
       " Text(0,0,'Southern Metropolitan'),\n",
       " Text(0,0,'Eastern Metropolitan'),\n",
       " Text(0,0,'South-Eastern Metropolitan'),\n",
       " Text(0,0,'Eastern Victoria'),\n",
       " Text(0,0,'Northern Victoria'),\n",
       " Text(0,0,'Western Victoria')]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x230978fe898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.violinplot(x=sdf.Regionname, y=df.Price, data=sdf, bw='silverman', width=1,  palette=\"Set2\", size=8);\n",
    "\n",
    "\n",
    "g.set_xticklabels(['Northern Metropolitan', 'Western Metropolitan',\n",
    "       'Southern Metropolitan', 'Eastern Metropolitan',\n",
    "       'South-Eastern Metropolitan', 'Eastern Victoria',\n",
    "       'Northern Victoria', 'Western Victoria'],rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1d651a4d588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot(x=df.Rooms, y=df.Price, data=sdf);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1d651dbcbe0>"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1d64c25a5c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='Price', hue='Method', data=sdf)\n",
    "plt.legend(bbox_to_anchor=(1,1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x23097e854a8>"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x23096dd68d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "g = sns.countplot(x='Regionname', hue='Method', data=sdf)\n",
    "\n",
    "g.set_xticklabels(['Northern Metropolitan', 'Western Metropolitan',\n",
    "       'Southern Metropolitan', 'Eastern Metropolitan',\n",
    "       'South-Eastern Metropolitan', 'Eastern Victoria',\n",
    "       'Northern Victoria', 'Western Victoria'],rotation=90)\n",
    "plt.legend(bbox_to_anchor=(1,1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAagAAAEYCAYAAAAJeGK1AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAIABJREFUeJztnXeYHNWZ7t+v0+QcFGaEskAiSAghEDmDgTUYG4wDZm24rG3MYmxfX3bXe7mOa5s1LKzX9rIGgzEmGBuDjQ0SAkwQKIIQGqVRnFGYnEOHqnP/qHMqdfVMT/fM1Ejz/Z5Hz3RXVzhdMzpvffGQEAIMwzAMM9EI+D0AhmEYhvGCBYphGIaZkLBAMQzDMBMSFiiGYRhmQsICxTAMw0xIWKAYhmGYCQkLFMMwDDMhYYFiGIZhJiQsUAzDMMyEJOT3AIaisrJSzJo1y+9hMAzDMKPIxo0bW4UQVcPtN6EFatasWdiwYYPfw2AYhmFGESLan85+7OJjGIZhJiQsUAzDMMyEhAWKYRiGmZCwQDEMwzATEhYohmEYZkLCAsUwDMNMSFigGIZhmAkJCxSTkvrmXkQTmt/DYBhmksICxXgyENNw5YNv4o/vHfR7KAzDTFJYoBhPYgkdsYSOroG430NhGGaSwgLFeCIgAAC68HkgDMNMWligGE+EFCaNFYphGJ9ggWI8UbKks0AxDOMTLFDMkGiCBYphGH9ggWI8EYJjUAzD+AsLFOMJu/gYhvEbFijGEzNJgl18DMP4BAsU44mVZs4CxTCMP7BAMd5IXWIXH8MwfsECxXiiZEnTfR0GwzCTGBYoxhPl2WMXH8MwfjGsQBHRI0TUTEQf2raVE9EqItolf5bJ7UREDxJRPRF9QERLbcfcLPffRUQ3j83XYUYLjkExDOM36VhQjwK4wrXtbgCrhRDzAayW7wHgIwDmy3+3Afg5YAgagHsAnAFgOYB7lKgxExtudcQwjF8MK1BCiDcAtLs2XwPgMfn6MQDX2rb/Whi8C6CUiKYBuBzAKiFEuxCiA8AqJIseM4FgFx/DMH6TaQxqihDiMADIn9Vyew2ABtt+jXJbqu1JENFtRLSBiDa0tLRkODwmW6xCXV+HwTDMJGa0kyTIY5sYYnvyRiEeEkIsE0Isq6qqGtXBMemjWh1xoS7DMH6RqUA1Sdcd5M9mub0RwAzbfrUADg2xnZmgCK6DYhjGZzIVqBcAqEy8mwE8b9v+OZnNdyaALukCfBnAZURUJpMjLpPbmAkOW1AMw/hFaLgdiOhJABcAqCSiRhjZeD8E8AwR3QLgAIDr5e5/AXAlgHoA/QA+DwBCiHYi+i6A9XK/7wgh3IkXzATCSpLwdxwMw0xehhUoIcSnUnx0sce+AsDtKc7zCIBHRjQ6xjfMOihWKIZhfII7STCe8JLvDMP4DQsU44mZZs4xKIZhfIIFihkSFiiGYfyCBYrxxKyDYhcfwzA+wQLFeGIut8H6xDCMT7BAMZ4oz55gFx/DMD7BAsWkgF18DMP4CwsU4wmnmTMM4zcsUIwnnGbOMIzfsEAxnnCrI4Zh/IYFivFEcAyKYRifYYFihoRdfAzD+AULFOMJL/nOMIzfsEAxnlhZfP6Og2GYyQsLFOMJL7fBMIzfsEAxnpgWFLv4GIbxCRYoZkg4BsUwjF+wQDGemEkS7OJjGMYnWKAYT8w6KLagGIbxCRYoxhPLgvJ3HAzDTF5YoJgh4RgUwzB+wQLFeGIuWMgxKIZhfIIFivFELVTIFhTDMH7BAsV4Yi234eswGIaZxLBAMZ7wgoUMw/gNCxSTAm51xDCMv7BAMZ5wN3OGYfyGBYrxxMziY4FiGMYnWKAYT7hQl2EYv2GBYoaELSiGYfwiK4EioruIaCsRfUhETxJRLhHNJqK1RLSLiJ4moojcN0e+r5efzxqNL8CMDVwHxTCM32QsUERUA+AfASwTQpwEIAjgRgA/AnC/EGI+gA4At8hDbgHQIYSYB+B+uR8zQVGyJIQlVgzDMONJti6+EIA8IgoByAdwGMBFAJ6Vnz8G4Fr5+hr5HvLzi4mIsrw+M0bYNYlroRiG8YOMBUoIcRDAvwM4AEOYugBsBNAphEjI3RoB1MjXNQAa5LEJuX+F+7xEdBsRbSCiDS0tLZkOj8kSAUuUWJ8YhvGDbFx8ZTCsotkApgMoAPARj13V9OZlLSVNfUKIh4QQy4QQy6qqqjIdHpMttt8Mx6EYhvGDbFx8lwDYK4RoEULEAfwBwFkASqXLDwBqARySrxsBzAAA+XkJgPYsrs+MIXZJYhcfwzB+kI1AHQBwJhHly1jSxQDqALwG4BNyn5sBPC9fvyDfQ37+quDo+4TFEYPiXxPDMD6QTQxqLYxkh00AtshzPQTg/wD4GhHVw4gxPSwPeRhAhdz+NQB3ZzFuZoyxx6AEF+syDOMDoeF3SY0Q4h4A97g27wGw3GPfQQDXZ3M9xh/YgmIYxg+4kwTjCaeZMwzjNyxQjCd2SeJQIcMwfsACxXhiFyV28TEM4wcsUIwnnGbOMIzfsEAx3tgLdTmLj2EYH2CBYjxxtjpiC4phmPGHBYrxhAt1GYbxGxYoxhPhcPGxQDEMM/6wQDGe2CWJ9YlhGD9ggWKGhbP4GIbxAxYoxhN7HRQnSTAM4wcsUIwnXAfFMIzfsEAxnjiSJNiCYhjGB1igmBSwi49hGH9hgWI8cXYz928cDMNMXligGE+caeZsQTEMM/6wQDGecKEuwzB+wwLFeGLvxcetjhiG8QMWKGZYOM2cYRg/YIFiPLEbTWxAMQzjByxQjCdcqMswjN+wQDGe8JLvDMP4DQsUMyyCBYphGB9ggWI84UJdhmH8hgWK8YTTzBmG8RsWKMYTLtRlGMZvWKAYT7ibOcMwfsMCxQwLp5kzDOMHLFCMJ9wslmEYv2GBYjxxLvnu40AYhpm0ZCVQRFRKRM8S0XYi2kZEK4ionIhWEdEu+bNM7ktE9CAR1RPRB0S0dHS+AjMWcCcJhmH8JlsL6gEALwkhTgCwGMA2AHcDWC2EmA9gtXwPAB8BMF/+uw3Az7O8NjOWcJIEwzA+k7FAEVExgPMAPAwAQoiYEKITwDUAHpO7PQbgWvn6GgC/FgbvAiglomkZj5wZUxx1UGxBMQzjA9lYUHMAtAD4FRG9R0S/JKICAFOEEIcBQP6slvvXAGiwHd8otzkgotuIaAMRbWhpaclieEw2ONPM/RsHwzCTl2wEKgRgKYCfCyFOBdAHy53nBXlsS5r6hBAPCSGWCSGWVVVVZTE8JhscWXysUAzD+EA2AtUIoFEIsVa+fxaGYDUp15382Wzbf4bt+FoAh7K4PjOGOHrxcQyKYRgfyFighBBHADQQ0fFy08UA6gC8AOBmue1mAM/L1y8A+JzM5jsTQJdyBTITG06SYBjGD0JZHn8HgCeIKAJgD4DPwxC9Z4joFgAHAFwv9/0LgCsB1APol/syExR7kgS7+BiG8YOsBEoI8T6AZR4fXeyxrwBwezbXY8YPXm6DYRi/4U4SjCeOQl128TEM4wMsUIw3NlHiFXUZhvEDFijGE251xDCM37BAMZ5wmjnDMH7DAsV4IhwuPh8HwjDMpIUFivGEXXwMw/gNCxTjiTPNnAWKYZjxhwWKGRIi7iTBMIw/sEAd4zR1D+K8H7+G/W19IzpOSVKQiAWKYRhfYIE6xnnh/UM40N6Px9/ZP6LjVJJEMEDcSYJhGF9ggWIAANGE5tlzLxQg7sXHMIwvsEAdxfRGE6PS5SGh6Tj+Wy/hey9uM7ep0wYC7OJjGMYfWKCOUva39eGke17Gb9cdyPpcMenD++06yw2oupmHAsSFugzD+AIL1FHK7pZeAMCquqasz6X0h2yLHqttwUCAXXwMw/gCC9RRiumCI0tUbn1sPR5+a++Iz6VceLZTWVl8AUBjfWIYxgeyXbCQ8QndFChr2/sNnSjLj4z8XDJLz3YqUwBDgUDWMaiG9n509MdwSm1pVudhGGZywQJ1lGKJhiUrsYSeUbxIMy0oSvosEMh+Rd1zf/waAGDfD6/K6jwMw0wu2MV3lGLGjWyaEtdERm2J1DEOC8pMkghwqyOGYXyBBeqoxRCNgEOg9IzExMuFJ2wuRNYnhmH8gAXqKEV3JUnoukBCFxnFi0xRS/bwjUoMKhVCCGw60DEm52YY5uiHBeooxZ15p2qZsnHx2TMCna2ORkeg3EXFv9vYiOt+tgZ/3XJ4VM7PMMyxBQvUGNMXTWAwro36ed21S3FToEZ+LjMGZU8zN+ugRq+TRMw1OFXLtXeEjWwZhpkcsECNMV/8zUbc8/zWUT+vmcMnRSUui5UycvEJryQJg9EUqME4d51lGCZ9OM18jGnujo7JeZW7TLnl4lm4+HTTgkruJBEaRRdfNKEBCI/KuRiGOfZhC2qMSeg6BmKWi+9I1yDe3dOW/Xk1VwwqYQjU6FlQVgxKHyXDJ8oWFMMwI4AFaoxJ6AIDthjUI2/vxRd/szHr87oTG7KxoLxiUIrRdPEZFhTDMEx6sECNMQnNKVCDcQ390ewn6rg0a5SmqBhUZi4+9cqrWezodTN3x6DIK6+dYRhGwgI1xmi6cLi2ErpATNOzXsfJcvE5LaisXHwezWIDNHoLFkYT7OJjGCZ9WKDGGLeLT5PC4k65HilKkEazDsphz9jroEbLxZci3Z6Xm2IYxgsWqDFGcyVJJKQYxLNcw8KKQRnv44kssvhSWFBEstVRloaPGiNbUAzDjISsBYqIgkT0HhH9Wb6fTURriWgXET1NRBG5PUe+r5efz8r22kcDyoJSLj1NzvaxLCfrRFKShDx/BuaIchcGXGnmJLdlmyQRDhp/ZmNRsMwwzLHLaFhQdwLYZnv/IwD3CyHmA+gAcIvcfguADiHEPAD3y/2OeZRFo6wHZThlK1BuF182nST0FGnmRDQqrY4iUqDcFpRX1iDDMIwiK4EioloAVwH4pXxPAC4C8Kzc5TEA18rX18j3kJ9fTF4LEB1jKEtHWQ+jZkGpzhHyNCoGlUlCg5aiUJcABEYhzTwcUgLFFhTDMOmTrQX1HwC+CUDNthUAOoUQCfm+EUCNfF0DoAEA5Oddcn8HRHQbEW0gog0tLS1ZDs9/1OSvEiUSo5QkoYRPufRMCyqLLD47VgyKsl5uIxw0hI9bHTEMMxIyFigiuhpAsxDCXnXqZRElL/2a/Jm1QYiHhBDLhBDLqqqqMh3ehEAIawFBlSih3mdvQTktpngWFpSeolCXQAhSZokXdkIBtqAYhhk52fTiOxvAR4noSgC5AIphWFSlRBSSVlItgENy/0YAMwA0ElEIQAmA9iyuP+GxT+ymBaWPkQWVyDxJImU3czJcfFnHoJSLjy0ohmFGQMYWlBDin4QQtUKIWQBuBPCqEOIzAF4D8Am5280AnpevX5DvIT9/VWRbrTrBSdgmdisG5bR4MsXd2iiaTbNYM0nCFoMyV+ylrIuK1VkHXRbUMR+AZBgmK8aiDur/APgaEdXDiDE9LLc/DKBCbv8agLvH4NoTCs0hUIaAJEYpSUKd2xS8hLeLTyR7UT3OZfwkZxofCECQsi/UVQLIMSiGYUbCqCy3IYR4HcDr8vUeAMs99hkEcP1oXO9owW5BqRiUmXWXdZq5S6BSJEmkoy2p1oMi08WX1VDN83f2x7M7EcMwkwruJDGGeMegjNk+264K6jy6O4vPddp0PH7e60EJI0kikLxU+0hRotzUPZjVeRiGmVzwgoVjSMLWI2hglGJQmi6wqq4pKQYVMy0q53nTqWFSlp7DghJWmvloufgOdw14fn6MhyIZhskQFqgxJKHZY1CuLL4MLaj1+9rxxd9sRFGu8atTl0i1HlQ6k78Zt3L34oMUqCyz+NTxTWO0ujDDMMcm7OIbQ7QhsvhSpZkLIXD/qp3Y19rn+bmyxHoGjVpo3Z0k4dISU3uGSJnzjEEJmK2Osl1uQx3eG02gZ9CKQx37fUQYhskGFqgxxJkkoTu2pbKgGjsG8MDqXfiHx71X3dVcXdCVGzGVBZWOi8+z1RGEtKDSi2MNhS6EafFxHIphmHRhgRpDNI8YlLvzgxszVpVCWBJuATJ78XkX6qrd1eath7rw7p421z4e60HJDYFRWA9KFwLTS/IAsJuPYZj0YYEaQ7wKddW2VFl8qttCTsj7V+O2kNy9+JLqoOTnavMDr+zCd/5U53nOpE4SMOqgsnXxabpASX4YgOWadI4xq9MzDHOMwgI1htiTJNLtxae6LaQUKNdsPlwdlG4KlNW01m29WSvqOm0owuisqKvrAsXSxdcfSxao0Vqxl2GYYwsWqDHEkSSRcNZBpUqS6I8pgQqmOKd3GrkSHSGcmXuWi88SxlQi5rSgjPWgiCjpnCNFF0BRrmFB9dlWF1anzNZCYxjm2IQFagzx6iThbk3kpi9qWBi5Ye9fTcKdJKGW70hY2zVdoLl7EAlNt1lQxmcxTU8SBC+tVJ0kglK1stEQzZYkob6f/ZwjPfdATMP5976GNfWtmQ+KYZgJDwvUGJJJN3M1gae2oLytH7vbrnMgjuU/WI3v/rnOslLSsqCSFyyUi+FmVQslhEB+JAQioN8hUN6JHcPRORDD/rZ+rNt3TDfDZ5hJDwvUGKLcecEAWXVQmiUUXpgClcqCkkKRFzYEzKszRdeAUWu0sq7JtJZMCyqhw+UlNK0wryXfybSgMhcoTRcIBQj54aDDxWeNbWTnVt/5UKd3ZwqGYY4NWKDGEDWRFuaEzE7eylrwsqCEEOgeVBaU969GTea/uOk0LK4tScriA5wTf1IMStNTZgK6s/hUkoT9upmgCyNdvSAn5EiSMF18I7TOlMAeZIFimGMaFqgxJGETqCQXn4cF9dNX63Hfqp0ALGFIOqe0dpbUlmJWZQH2tPThD5sazToowOp0rovkLD5PF58ck32zOwaVqYtPnTtAQEFOCH1RmwXlio+lixr/oU4u+mWYYxkWqDS5b9VObDrQMaJjlDuvMCeUVpr57zY2mq/dyRDmOeXxwSCZ4vG1ZzY7zqcyBu3Zd04Xn7cFlWwlEQLKgkqjdaCui6R7pM4dJEJ+JOhKkhCO75Quav+DnQOcAcgwxzAsUGny4OpduO5na8z3ui5w8j0v46l1B1IeY1pQuSEMxjUIIYbsxTe1ONd8nWrSVucMBSzxAJwuPlXsK2wuvhFbUPK1ukQ6Lr5H3t6L6362Bm/bsuvUcYEAoSASQp/NxadlGIOyf5e2vtiIjmUY5uiBBSoNvGqAYpqOnmgC//r8hymP01wuPrvo2AWluWcQdYe6MaXEEqh4CoHSbIkXQUohUMqCgjWZq68Q9YpBeQqFMFx8UqHSybTbcaQHANDY0W9uU5ZXgAgFOUGzzsu4nvqZmQUFjE8cqrGjf8gHEYZhxgYWqDRw978D0nNPqSw+I0lCc5zH7pL72Wu78flH1yHXlhjhLsh1jyVILgsqYRcoazFDuwgIIdJ28akkiYDK4kvDlab2teuNOmcwAOTnhBwuPmHew2FP7RyvbSzjkcn3/PuHcPcftpiZmAzDjA8sUGngJUIJ0+pIfVzCFoPSBRwTnF2g+qIJNPdEHe6vVDEoXRfmUuwhm0DFNIGIFDhToHThiEHFUzWUTeHiUwsW2r/nW7tacfy3/prUzw8AAvKvyX5P1LUCRCiIBB1JEpp53cxcfABwsGPsBUr9rrJdBZlhmJHBApUGXp3H3cteeGG6+GQXBXujVPtkp+kCQgAHOwdRXZSDmtI8h7V1x5Pv4fsvGoKQkDVFgDPTL67ppgUWjVtJEvYsvpjZUNY1Ti8LCtaS7/Z96g53IZrQ8fLWI0nf16tmSthcfPmuGJT6ipkmSQDj4+JTlrBynTIMMz6wQKXBUBbUUNjTzAFjwT6FXfTUfgc7BlBTlofKohzH+bcd7kbd4W5zLF4p6HFNR64s3h30cPEp9x7g1XAWcn9rW5IFJT/s7DeKgL0Kick81jqRZUHBjEEJlyCONBHPYUGlEKivP7MZs+5+cWQnTkFimOJqhmHGBhaoNIh7WEvpPPWrOJLqQ2cXKHsWnzpXa28UuaEgwgFyxKBiCR29UauOKhRwuvKMMVoCZVpQsImAbk2wyUkSlqApBJyFuuqYTtmlQtMFegbj2N9mrfzrdgfajwvKQl1NF44Ymfu6gNEJo6G9H6lQty4nFEgZg/r9JiNlP5smt4rhlkhhGGZsYIFKAy8xslshqVw/Q1lQ9qfxhE2McsMBBAPkEMVYQjeTC+wWlP26cU2YDWbVRGrUQRmf6zYLCnAmPagJPzkGRTbRURaUkdad0ASu/8U7OP/e181jlGFnFwX1mshIMwesju2pXHwPrt6FGx96F6lQ+88ozx/WxafaPmVDQt4glb7PMMz4wAKVBsPFoI7/1kuex7ljUL22NkZ2AbJP0HmRIEJBcmyLabp5rFOgnONyW1CGi89yo8U0W4KCY0mO1PVIgYBboCwLartMK1eQlwUlLAsqP2KMT4ltql58Hf0xHOwcSCn8av/jyvPR2R93ZAa6ae3NfgXfuGlBcQyKYcYTFqg08I5BDf80ncqCyo8EXRaUdf7cUBChQCApJV1Nwgm7QLme6HNlB3S7BWWPQbkTM9yv3UkSgL3VkbFdCZRXDM5tbRmvYZ6nQN4HlSiRShjVvWlOsTy8aUGVGcvID5Vq3tKTfSHvcA1+GYYZG1ig0sBrMk4vBmXs414LKT8Sckx29nPlhIMIBch0KwEyBhVLyE4UupnF5+5GkeNy8TktKJeLzyORwfGVzCQJ5/7KZeYl0Kpu2P59lJVEshefcR+cbZ/cp1IWa1O3d689Nd4Z5fkAgEYPgVIp96NjQXGaOcP4QcjvARwNeE3GaWXxmXVQxmqyKs08NxxATNPNVWvtNU954aCxzLqtRkgJUX9Mc1hQ7sJR08WXsFx89jqoVKKo266lEIBZbwUAO5t6sGF/BzpkDMru4jRX35XvvYQwGDDqoIzvoSwoOZYUFtSRFAKlxqsEysuCKpBWamtvFEII7G/rR01ZHsLBkT+Tqd8PCxTDjC8sUGngVTTrtqASmo6Qa/LTdB1ESIq95MtkgbgmEAk540254QDCQcvFZ7eSPvnQO/jwYDdmVRgTc6oYlFraQxeWdWKvgwKM7c3dg1j+g9We30kIWQclzaI7n3rf+X3tAieAIAFqi1eGoqqDst8HJYjuTDsVnzvSlcKCkuecVpKLUIA8i3WVBfXsxkY88vZeNLQP4McfPwU3nD7D85xDMVSDX4Zhxg528aWBl7Xk3ub1dB2XRbVKOFQMSi02qCZyZxafYUEpF599UvzwoFELFTBjUC4LyuwkkbykhXBbUEKYtVXWvtZrZUF51VwV54YcYqbG7zVmR7PYHCXUmjkGIFnszRhUj7d7Tp0zFAhgWmmupwWlRHr7kR7MqigAkNoiGw7lcuQkicwYjVR/ZnLCApUGXn3xUk2qdhKajnAwgDxpQfVIgcqV773qkvJUDGqIp3YzBpUyi88uEOqnSHLxucXHqxcfJesTKgtzzLiMffxxD6tPXT9AluWY7OJznj8qj09tQRk/gwHC9JI8z1TzgZiG60+rxbp/vhiP33IGckIBRxeLkcB1UJlz08Nr8cOXtvs9DOYoJWOBIqIZRPQaEW0joq1EdKfcXk5Eq4hol/xZJrcTET1IRPVE9AERLR2tLzHWpFOo62lBadKCkpaNShXPDzsFKuFy8dnTzL2W5QjKQt3bL5zn2O6ugwLg6NrgFA7DhWcnecFC8rSgKgtzHPuq8XtZUGahLpGZzaiWffeKfQFW49tUFo+9O0VNWV7SwoUJTUdM0zGjPB8VhTkA1GKJ2QkUu/hGzr62Pmxp7PJ7GMxRSjYWVALA14UQCwGcCeB2IloE4G4Aq4UQ8wGslu8B4CMA5st/twH4eRbXHlfSSTP3mrzimo5IKIBQMIBIMGCLQQXNz93nzwkHEQxYdVJDWVAfP60WX790gbndnSRhjNNKknCnmQ+4XIROC0oYnSQ8TKjKoojzOFOgksdsd/HlhgMgAvqjzjTzJGt0mCw+c5XeAKGmNA9HugcdWY/98nup+6xe90czc9El2MWXMQlNZOxaZZiMBUoIcVgIsUm+7gGwDUANgGsAPCZ3ewzAtfL1NQB+LQzeBVBKRNMyHvk44lmom2RBJU9ecU032xLlhANmDEq5+KI2C6qiwJj0lYtPuRW9BMpu1diX3LAEymNtKA8XX7/L5ZVUqEtW8a2dioIcx/vEUC4+W7NY1U1CtW0arg7qSNegZ/zCbpXVlOZB0wWabPGqQWmh5dkEqjAnlLmLT2XxcSeJEZPQRcp6NoYZjlGJQRHRLACnAlgLYIoQ4jBgiBiAarlbDYAG22GNcpv7XLcR0QYi2tDS0jIaw8uadJrFern4EppAKGhM8HnhoJlm7nbxabrAounFOKmmGIumFyMUNGJQy7//Cn700o6k89q9biEvgbJNpPaMPrdADcTcFpT1Wr1M5eKzo7lcfHEt2YJSCY75kaAVg1IZhinqoKIJ3bNVkb07xfRSo1jXnsmnWiklWVCxDC0o9bAw0oWrGGi6QG804WjzxTDpkrVAEVEhgN8D+KoQonuoXT22Jc38QoiHhBDLhBDLqqqqsh3eqOAZg9KGF6iYpiMiZ+a8SBDdcrJVrY8eemM3fvnmHiR0HVWFOfjzHediblWhLNQVaO6J4pVtTcnXtimJXUBUdqDddTdoa3vkSP8WyS4+4QpCGc1indcOBwnFec7qBDNJwsPFp8REWWKGJTO8BVWWb9SOebmHhM1tWOPRTUIJkbofgBGDynSS5CSJzIkPk/DCMEORlUARURiGOD0hhPiD3NykXHfyZ7Pc3gjAXoRSC+BQNtcfL4ZrFgukyuJzWVByglTJAn98/xC+9+I2aJozoy4YCAzZSimRQqBUGrfdUrC6SrhiQ7pw7JcTCrgsKOFoFqsoyYt41HtJC8qj44Juc8cBhjgroTbTzN33UiY4AMbE1tEXw/2rdprnMrP4yMjiA5zLbgzEZTp/xBLSbGJQcdPFxzGokaL+Npo5DsVkQDZZfATgYQDbhBD32T56AcDN8vXNAJ63bf+czOY7E0CXcgVOZPqiCfzlw+RhphODSui62bkgx/Y0X5wbdu0AUdSpAAAgAElEQVRnCRlgWCleVpvXtb0sqEEPCyopBiWcLr6KgsiQS74rSvPDDreiGj+QKknC+KnOU14QQXtfzPGZezn5WMISqKbuQfzr8x/igdW78PbuVnPsgLGCb14kiIqCiFOgYsb17S6+gqxiUOziyxT1t8GJEkwmZGNBnQ3gJgAXEdH78t+VAH4I4FIi2gXgUvkeAP4CYA+AegD/A+DLWVx73Pjn57bgxQ8sgVLuJXcMysuCimnCtDbybAv8KRcfYMRz3DVJXnEfO/YYj9OCctYZAZa7L8nF57KgygsjcnkOq7DXq1C3LD+ctE1zxWg8O0kErO+r+uPZ2zApVGunWum6O9IVNWN3Vu8+p1U2vTTPFYNyFkQDQEEklHEMSl2XkyRGjsYCxWRBxq2OhBBvwTuuBAAXe+wvANye6fX8Yn+bc+G8hC4QDjoXFASMJqr1zT2YV11k7avpCAcsF59CufgAw7XWG02Y2X4AkiwUNw4Xn83CUVlr9gnfXHtJd7v4LFcYAJTLzDzVfkkt+e62oI4rL0A46BYo6/sa59AxENNwsLPfFCE1zsrCHLT1xmTj2+Q0c00XEAIojIRQURDBke5BK1Xd7KxuJUkAQE1pHna39JrnUKJsz+LLzwlmHIPiZrGZYf8dcyYfkwncScLGgG05coU7y1q5sdz9+X79zn5c9eBbpqvvlbom7GruNV189slS9YkDDGvDbUG5YzyA0V7IPQbAZUFFkp83YmYMyrXchsvFV5pnuB0XfOuvAGxLvtuG8sXz5+J7155kFgqb41GtjmwFrd/43WZcct8bpiiodPjKwghimo7uwYSjy4X9fgBAOBTAlOJcNHUPJgmSvbYKAKaW5DqC8F5ZfAWyg7xXycBwcLPYzLA/SHGSBJMJLFCSwbiGM37wCp5776Bju9uCUE/T7hhUU/egkRYt10u69dcb0NITNWNLuTYLal51IYpyQ5hdWYBYQkfCtoQG4G1BlRdYxbGpYlD2CdlNUi8+t4uvwFl8a6aZ275/VVGOsaBikosvOYtv7d42ADC7nwdsFhRgLIPhtWChGmMkGDCFJ3mJeqdVVpYfQU80YVpwSnjzw5ZgW+7Pkbv5rCw+TpIYCfbfG7v4mExggZL0RRPoHkxg/b4Ox3a3VKg2PO4YlOoS0TkQdwT9VZq5XaAqCiLY8v8uxyULqxFLJFtQXjEou4CkyuIbSqDcMaiWnkEMxDWcMLUIL3zlbFQXW7VN9mXaAx5JGMkxqORWR8pibOtTAiW/e6HxPVp7oo7VfhVqjBGbBaX2U5/Z66AAmGnvKlbl5eIrcHWUHwkJzdvFJ4TAr97eOyprTh2L2K1VzuJjMoEFSqImv93NvY7tbgsq4Xrq//IFcwFY/eU6++OObDF7mjlgTLyqJigSMtaFSsiu59Yxyb8Wp0B5J0nk21x89jiXGm/MZgF88TebsGFfB8oLIjilttTxPaMJ3TOLLy9ijCs5BuVMHOmPa6b10ipXtA0G3BZUzBIoPYUFVZyLtr6YWWysHg7MVkdybCXSPamKevtjCQQD5BhnvkcCSbp4ZScCwK7mXnz7T3X40+ajolpi3FF/F/mRIJp7oknZmgwzHCxQknjC+M9T3+IUKLcJZTZ4lZPWLefMdnze2R8zl5MAYMWgpEDl2OJPkWDQTAoIDpMkUZZvEyhbDMq+b04oYFoqRblOgXK7+ADD0lBWl/2ShhvM6UYzvoNxzuQYlHLxGefvGoibq/u29UXl+WVCQ1ke8sJB/Pjl7djd0gfAWQel3ISRUABTSwwxU+4h04KydTMHrLT97kElUBryw0FHmybLgvJ20x3pGsQ7u9s8P0tVqLuryfhbaesdfln5jfvb8fVnNk+qSVrdt5rSPCR0gda+iW9ptvfF8PlfrcPhruQO+cz4wwIliWnGxNXeF0ObzWXj1gr1n049HebI9ZsUXQNxR7aYO0nCIVC21/Y6qOFdfHYLyjhHKGC445T15WlBuRIEggEy++rZLaW+aMIzSUJ9h1QxKCWcdjFs73PGoIpzw/jNrWeYnd3V2BSmBSVdfADQIvvsxV0uPjWMknynBTUY1xzuPcC23LyHBSWEwJ1PvYebH1nnaWFZBchOcdvV3APAcmMOxVu72vD7TY2miE4G1N+D6vZxNGTybdjXjtd2tDhKSxj/YIGS2J+O65t78fT6A7jo319P2k/FI5RQhQJkxpmAZIFSk3muaUF5Z/PZRcntQgsFCMV5VnGvM0lCHWO8UGMpdFlQ+9r6sfVQt7kkBwA8cesZ+JerFwJwNoXtj2meCxYqaytlDErXTWFU97O1N5Z0zGkzy3D+AquNlT1jXwlUWCZJ2InZXHwBWyPbZBeflhSPKzBX8022oN6ub8Pave2IaTrW7ml3fCaESNlZfpd0B7enYRmoB6CO/kkkUPIXW1OqatomfhyqQdbTpbKmmfGFBUpi79xQ39KL+uZe7GntQ6drQlFp4aoOKkBkurMAGYOyW1AhlSQhBSSFBWV3peWGnJNrcV7YdFG5x6osKCVq6qe7W4Uam70ea0Z5vrmfXXP6YglzyXdHDEoemyoGFdcEqousLD0ApjXqNgrtLkivNPNIyIhB2YlpVmsku+CZLr4B4773xzRHUgpg1EEZnzktJCEE7l25A9NLcpETCuDNXa2Oz+0eObeLr34ELj71O2tPw9o6VlB/F8qCauo5CgSq3ah7XLe33bGEC+MPLFCSmMuCUoF5d3psc3cUJ93zMt6qNyayUIAcbrskF5+rUNe+b07Q24JSLitFUW4I58yvxMUnVMNN0Ey4kO43W8zLfi2FXaDsn9uFqD9qWVABj0LgVDGohKajUgqUyqhTQhVwKVRRrrdFaE+SKMkLO8botKBs98tlQQ2MwIJ6ZVszNjd04s5L5mP57HK8ucvZQd+eiWbvxRfXdOxpVRbU8KKjxt7ZP3kESony1OJcBAhoOgosqMYOQ6B6oglsPTRU72tmPGCBkqgJhEgJlJWVZ2dHUw8G4hr2tPTJGA05LKHOgbgjvuJOkkhlQdljUCV5ToHKCwcxr7oI/33TaUnjVsIWCaqflsXmjsMA1lpU7usnW1Cqm3myBeUVg9q4vx19MQ1VRc6lOJT2uAVjeAvKWD/K7uazL/BoH1duOIBwkMz4jpH84XRxFnhYULou8JOVOzCrIh/XLa3FufMrsau51+GKSuhWvMsew9vf1o+4JlCcG0orzVwdO5lcfGacNhREVVHOUVELdaC9H0uPKwUArGE3n++wQEnU5LdwajHW7mlP+ce5v83IPOuLJsyJ2h5X6uyPudLMpWAMkyRhn3BL851Fs8pdpc5lT5hQxylXohK6nFDQYS0pUllQ9hjUr9/Zh7/tbIEunMI1VAzq4z9/xxh7XrJr0TjWKRiFDoGytlsWlHGtKTY3n0oz14RwuESJCCV5YUcMyi3O6vp26/bFLYex/UgP7rp0AcLBAM6db8TF7FaUWlalIBKS6fcy21MmSCyfXYHuwcSwHSrU2DsmkYtPxaCCAZI1bRM7SUIIgYb2ASyZUYb51YV4Zw8LlN+wQElUfOFbVy1EOEiO7th2VGp0X0yzWS/WbexOyuJLroNS2I+zWyVuC8qe2PDzzyzF87efbb43BSoYcPzMDQeS4jDGdpsFFfR28b1d3ya/Y8JzxV53DMqeVXiwcyDpcwCOGBqQ2sWnYlblsqDXHodSVoiuiySXYXFu2FzGYyCWSBLnoFxyXnWSSGg67n9lJxZMKcTVp0wHAJwwtQiVhTmOOJTqHFKQE4IQltuqXiZILJ9dBmB44bEsqPQESteFmb3ohRACn3roXTy17kBa5/MDlcUXDpJZdD2RaeuLYSCuYUZ5Hs6aW4H1e9s9m0Az4wcLlERNINXFOUkWjJ09tjop+3Luis2NXfixbRXcsKuThF0UnBaU9do9mdtF5SMnTzOXojCOcwqUadWFg54CZRcPclghSbtiMKaZlgqRZXG5Y1CHOgdxwlSjSe7/vvx4R80WYBznLj52uPhsAnW4axBEMJMtptg6XNg7SbituGKXBeXVVaMgEjITWJ577yD2tPTha5ceb56LiHDu/Eq8Xd9qjklNsirJQqWaN/dEUZIXxowy43fROkyiRHyELr7H392P8378WsrOFwfa+/HOnjZ8cLArrfP5gXKPGhbUxHfxqQSJGWX5WDG3AgNxDR80dvo8qskNC5QkbnMtDdUyyD4RqTky4tH5QeHuJJEqzdxuQZFLLbxcde7jIkGnUOWEAg7LS+G1+GKq7XYr0V746o5B/eil7dh+pAdXnTwNJ04vSRIod00W4Gx+2x+3mvQe6RpEVWGO+T3sLj71NKvpyR0+ivNsFpRHHRRgWEH9MQ2xhI4HVu/CyTUluPzEKY59ls0qQ1tfDIdkoaYSFpVkocbQ0R9HWX7YdLcOlygRk4Xg6SZJvLD5EAbiGppTWFEqHX4wwyVExgPNLMUwMjI7++OOtcomGirFfEZ5Ps6YXQEiTjf3GxYoidVFm8y2OMOhrIKcIQREWSDDJUkMtQaUlyWkUBN12CWSuWHvGFSqhRC9Umr7YwnTsrJP+KnGqizJUlcWorI+7BTmOF18yvV2uHsQ02yJEfYkiQNt/eiPJaDrImkp+pK8MLpVL74UFlR+xFhy4+kNDWjsGMDXL1uQ9DBwnLRO1fpSapItMC0oKxuvND9i9hZsG6YWSv19pZPx19wziE0HOuT+3ud9VzbjHZjAE75y/Yakiw+Y2MW6yoKqLctDWUEEC6cWc6KEz7BASezpzfkpBMFtkXjFoBSq55zqepAbsSwbRaoY1HDXtRNyWU5W5pR3DCpVMN9rtdi4ZiUj2AUq5BFjMsZp7KOsCjX3hwLJ43e3YlJp6Yc7BxyiZI9Brd7ejPtX7UxKkgCAkrwQugbisju88BTngpwQ2vti+Omru7DMVSysqJUuu0YpUGqSVRZU1NYho7wgYnbiGK4WKm4K2/AuvlfqmqESG1O5DpUFlekijOOBco+GApZATWQ3X0N7PyoLI2bXkRVzK7DxQMeEtvqOdVigJHFbgWiBxxM/4HzqB+zxHudtDAcJNyyrBWDFV7wsqJw0LSg1CXphWlDyXCplOyeFBeVex0qRyrJS47Kfy0twAKvAWMXw1Ljda2wBXgJlTNxHugYxrSTP3D7FVay7uaFryCQJtdRGnsfaWPmRIDYd6EBTdxS3njs7yXoCgOmlxvWUQCnXnLKqYzahKc0PoyTPWGF4OAsqPoIkiZV1R8z742VxNXb0m0k8E9mCsq/jpR46JnKiRENHv/mAAgAr5lQgltDx3gGOQ/kFC5QkausBpya3IjkpffqM47DqrvOSJlU1eSuhKTB71QXMz5RhMlyrI7dVYk86+MpF81KO2x2DsltQlYXJyR5xPYUFlSJbiUwLyvruqcRUWXpl0sWnru8V9nIvrtgTTeBw1wB6ognMrLAmiemleabYA8D2I92eSRIleWFHQ1IvF1+hzMQDkFSvpcgJBTGlOMcs2FQr9c6tKgBgJUl09MdQlh9BIEAoy48MH4OyCZSXYCt6BuNYU9+Ga5fUAPAWKGU9TSvJTfl0L4RRm+bnGlYqSSIcDGBK0VEgUO0DjgSk5XPKESDgnd2tQxzFjCUsUBKzB1wgYArNrEpjUppbVYj5U4qSgv0hl0CpLgqhoNUiSLn4wsEAinJCjhTyVFl8APD8V87G1m9fjtsvnDdkDMqdxacsqNxwEPOmFCUfkGJu9HLx2a+RFx7eHanEV7n4VHxGeFw0ECA8cOMS3HfDYgCGi2+NTG8/c06F49o//sRi8151DyZwsGMgycWnehWqbgXeMSjr95cXTh1nrCnNMy2o9xs6kRMKYHGtUbwZTegYjGvoj2nW9yyImC4+TRf47doDaHa19VF/X3FNmEuzePH6jhbENB0fXTIdBZGgp+tw7d42lOaHsbi21LEqsp2H39qLj//8HbxS15zyWmONimsGA4TivBByw4EJ249P0wUOdQ5gRpllvRfnhnFyTQnXQ/kIC5QkrukIB42O4CreMr+6EAGyLAK3QFkWlLF/lYw7hYOWBWVPof7dl1bg8+fMMt8PFYPKCQVNX/hQJAuUOj6A+dWFjn0vP3EK7vvkEs/zxIeo9wgSOV18KWNQKknC7eLzPu81S2pwUk0JAMNyeHt3K8oLIjjeQ1jtFl7d4e4kF58S/sNyAvQSdbvrdqhMzfKCiJmy/n5DJ06qKTF/F7GEbsaRVDJIRWHE7Gi+Zncr/vm5LfjCo+sd4mF/ABiqZmplXRMqCyNYelwZygsjnkkSa/e24/RZ5cjPCXq6+P62swU/+Ms2AOk1sh0r7A2ViQhTi3PRNERtl58c7hpAQhcOCwoAzpxbgfcbOjNaR4zJHhYoSSyhm4KhJuPa8nz86Y5zzEJONUkp15WZJBFyTswqLgE41zo6YWqxo4lrull8Q+EWKLuLzy1Q992wBHOkq8rNUBZUIOC0PlLGoOR9K7NN3MOh3KY9gwm8s7sNK+ZUJImPm35bfZZC3VcVhB/OghpKoApyQuiT2YLbDnfj5JoS83cVTWhmHEml05cXWC6+V+qaEA4Sth7qxv9+drPpzotruvldU8WhogkNr21vxiULpyAYIJQX5CQt5XGkaxD72/pxxuxy5IWDSS6+3S29+MpvN2FulfG778lgBeFUjNQ9Z6aZy7/N6uLcCduPr6FdppiXOQXqrLmViGsCG1wrbTPjAwuUJKbpVrsgOUEGCDhxujU5qQlGPWUpt5xy8dWW5eHLF8zFL29eZrr4hlqgzh6PGiqLbygskXTGoHLDQVQUOuMseeFg0sSuUEF8d5wNMBIx7BZJqqGaMSjp+lKZjEOEXMyOEh80duFw1yBWzK1IvTOsQuNUFtSRIVx8hTYLyqtOSpEfCaEvquFQ1wD6YxrmTyk0f8fRuG5aQGX5louvtTcKIQRe2daM8xdU4ZuXn4A/f3AYP321HoCxIKZK+EhVrPvO7jb0RhO4TNZmza7Ix9ZD3Y4SgLV7LTdoXjjosNK6+uO49bENiAQD+NXnT0coQI6+kNnw5q4WnPlvq81WX+mg/qbU3/bU4twJm8XXIGOOM8rzHNuXzSxDKEDs5vMJFihJXLMsqICHew4wXHyhAGG6zDKzEhQsofrmFSdgblUhFk0vBgCcKF1YXoyKBUXOMZhZfPLce35wJdb988V47AvLEQhQyut85KRpAIBLF01J+iwYIMeErxInql2JBkrETppegv917mwzjXuopICCSBABAl7eegQAcPa8yqG+LpbMKJVjcm6vKctDTiiAx9/dD8A7xuS0oFK7TwtzguiLJsx2RvOri8z7GdN0U2DKCpSlmIOewQQ+PNiNg50DuGThFHzx/Dn42Kk1+MmqnXjpwyOIabrZFSNVse7KuiYURII4a65xD644aSra+2JYu9dao+rdPe0oyg1h4bRi5EUMF5+6v997sQ6NHf34xU2nobYs37AER8mC2rCvA0IgZQswL+xZfIBR09bUPTjk34NfNLT3I0BGUo6dgpwQFs8o5YJdn2CBkkQTuikYpvXj+n90w7IZuOfvFplP30rIVJq5PTZz/oIqvP6NC/DRxdOHvK7K1nOvNZQuwRR1UEosAgFCdXGuKRbuDgyK8xZUYd8Pr8KJ05MF9e6PnIAbls1wbPvtrWfgz/94jmObsggjoQD+5apFOGFqEc6dX4n7U8S9AEPsCmV90rSSXMyqyE+5LwAsPc7ofUdwfo/yggi+ecUJ5nvvThLW+IZ6IMiPhDAQ17DjiNEQdl51oeXii+ueLj4AeGZDAwDgohOqQUT4t+tOxsk1Jfj2n7YintDNTDavxAddF1hV14QLjq82f3fnL6hGXjiIv2wxVnd9pa4Jz25swPkLqmRvwSB0Ya1RtmpbE/5u8XScPqscgPFAtXZvu1n0mw3bjxhLT6huHelgxqCC1gNNNKGb8b2JREN7P6aV5CUVvAPAWXMrsOVgl1kKwYwfk16gXqlrQn1zjyMG5RU/AoCTa0tw04pZpiurSsZY1HHuP26VBTgUP/vMUlxwfBVOlBbXSAmmqoPyWAsKGN5S82r0+pkzZuLkWqdwnTWvEtVFzhold0FxKBjA47ecgTPmDO22U26+FXMqPGuT7Kj0cC/LoMb29DtUDGqo+BNgJcN8cLALFQURlBdETPGNJjTTxVfqSqd//v2DWFxbgmrpyssNB3HlydNwuGsQvbEEKotyEA4SWjyW53ivoRMtPVHTvQcYInvRwmq8vPUIHn93P770xEYsml6CH1x3svG5FLKBmIath7rQ2R93FB8X5Yaw/UgPvvDo+qwtqe1SrEciLgnTxWf8XVi1UKOXKBFL6Pjun+uwpj67VPCGjoEk955ixZwKaLrA+n3tnp8zY8ekFqi1e9rwvx7fgAdW1xsCJSd1NUemih+ppSBmVRgCpFodeT19DcecqkI8+vnlju7eIyFVkkSq1PThPImhIZrWDsdQ6fBDcdOKmQC83YuKz555HOZUFphxrU6PibLM1mLJy4JSwpOqU4hCtWba3NCJuTLRpDAnhAAZE1lHfxwFkaAtrd4YU/dgApcsdH6H2ZWGRSiE8dBQXWQkCgzGNcff18q6IwgFCBcc71yU8qOLp6O1N4Z//eOHOGFqMX79heVmQoj6jgNxzezAbneRqqSezv44nsyi63lvNIH9bUaMRq1anA4Jl4tvLLpJ/OJvu/HwW3tx0yPr8Mz6hozP09Den5QgoVg6swyRYMAsg2DGj/Sazh2DdA/G8bVnNkMIYHdzL6YU55gCpWJLqTzlnQPGE7SykCwLKrM4UjaEgwFUFEQwXT6d2rP4vBjOQlHf4epTpuHeTywe0VhSXXM4vnj+XNywbIZjnSs337vWsBre2Gms1eQVxymzHe/VRUNZTkMlSACWkDV2DJgWSV4kiEsWTsGzGxuxYk6Fo+O9PVvxYpdA2a3oSDAgi4AHcPFP/oYbT5+BOy6eDyEEVm5twoq5FUlLrVy2aApW3XUeogkdC6YUOeKWdgvqjZ0tOHF6sSng9u8BAP/z5h7ctGKmIzEnXZSrExiZBaWZhbpWkgSQ/cq6cU1HQhM42NmPn75aj8tPnILmnijuf2Unbjh9xvAncDEom/K6U8wVueEgls4s5UQJH5i0FtS3X6jDke5BLJ9Vjr2tfUYMSgrNp8+YietOrcGXzp/reazKFKuVRX0qBpWJBZUtwQDhjW9eiOtljEg9lLuXt3Bz3dIaz+1XnzId1y2twf+9etGwE7mbTC0oAEOKk9d+XsatvYu61+9CWRRDJUgAzi4X9lT9z62Yhfa+GFbVNTnGWyFf15TmYeE0Zw3XzHJLoMKhAKYU52L9/nYc7Bww3Wb1zb3Y29qHy06cmjQWIsL8KUU4yZbqrlD3u7U3hk0HOswFFxXKcjlrbgWauqP4w6aDnt/3SNcgXt3ehK4U2YXbDhvxpwDBXLU4HdwWVLVMEsm2m8R9q3ZiyXdW4guPbkBeJIjvXXsyzp5bieaeaMpu/UPRaHYx93bxAcCKOZWoO9yddjf6iUosoeO1Hc3Y19o3IZNV3ExKC+qvWw7j95sa8Y8Xz0dVUQ7W7WvH/rZ+s5N1YU4oZUGr+hyw0s3VU6kfAgXAUdD7/Y+dhB/+dbvnEheK7d+9IuVY8yJB3HdD6u8+FNkIVLoMVVvl7qLuJl0Lyt59fV61JThnz6vAnKoC7Gnpc1yrODeMwpwQLjtxSvJSKZEgppXk4nDXoLSgcs20e+XqWlnXBAC4dGFqF+dQ3+f1Hc2IawLnzXdmQKoU9I+dWoO+aAK/+NtuXH9arfnwMhjX8D9v7MHPXt+NgbiGAAHLZ5fjp59e6rDEth/pRlFOCGW2AmYvEpqO+1btxMq6Jjz7xRW2ZrEqyzWIsvzwiFx8Qgjc8tgGTC3JxfevPQlEhA8PdoHISA3/yfWLUVWUg6kludB0gdbeaFL/xuFQKebHpbCgAKNx7P2vGFmUV5yU/CBxNDAQ0/DF32zE36QXYlpJLlbMrcBZcyuxYm6FI4Y7UZg0ApXQdBxo78eu5l7803NbcEptCe64aB7WyxTeg50DOGuYGhzFv113Mq46ZZpZDKmebP1w8bm5ZkkNrlnibR0pxkpIMq3lGglDWVrDPSCYMag0XXwAMH+KZUEREW46cya+/ac6h7UWCBCe+/JZSSnKilkVBTjcNWhaUAplia/cegRLZpQ6uringxLalz48gtxwAKfNKnN83i+LeKuLc/HlC+fhHx7fiBe3HMZHF0/HqromfPfFOjS0D+AjJ03FjcuPw8Z97XjozT249bENeOq2M82/k+2He3DCtCIMxvWUWXxN3YO448n3sE7+f1pV1wRN10HkTMwZ6cq6f9vZgle3G+2aakrzcPuF83CgvR+XLJyCH338FPPhTLkPD3cNegpUz2Acr+1owctbj2BNfSvOnFOBb129CDWleY6FClOxZEYpcsMBvLunLSOB0nUBouFd7CM957MbG/HnLYdxycJqfHxpbcruMz2Dcdzy2Aas39eOb121ELnhIN7Z3YbXd7SYlvXMinysmFOBFXONf+4kKD8Yd4EioisAPAAgCOCXQogfjtW11tS34tfv7Mfull7sa+szO3YX54Zw/yeXIBwMYOE0K3vu+Kkeves8qCjMcYhATsg/F99EItMY1Miukbm45qcpUPm2ZsHuWq+Pn1aL+1buTBKj+V59DyWzqwrwzp42RIJkJk2cO78S7+xuw8HOAWxu7MI3rzh+xN9njoxv7WntwwXHVyXdmwHZnqeiIIJF04oxv7oQD67ehWc3NuLNXa2YX12IJ249w0ysOH9BFRZNL8aXntiEu55+H//16aUAjAy+65bWYE9Ln6cF9dauVtz51Hvoj2m4/5OLce9LO/Dy1iYsmFKY9NBiCFT6WXw/e303ppXk4rSZZbj35R2YW1WAQ50DuPLkaY7JWIn7ka5BQIahWnqiWHcblSgAAA1OSURBVFXXhJV1R7Cmvg0xTUdlYQRnza3E6u1NeG1HM75y4Ty09ESREwqkbCAMGA+hp88qT7seSgiB3S29eGNnK97Y1YJ397RBCCMLtbooR/7M9XxfWRgZ1kW/6UAH/t8LW/FBYxeqinLwxs4W/PvLO/CpM47DzStmOf4+O/pi+PtfrcPWQ9144MZTzdKXz545E7ousLO5B2vq27Bmdxte3HIYT8lkk8W1JfjV55en7X4fC8ZVoIgoCOC/AFwKoBHAeiJ6QQhRNxbX6xyIY2dTD+ZWF+LihVMwt6oA86qdjV/tgfUFQ0wyQxFhgcLDNy8z06snKiqpYKhGsYBlQc2bUpj0xFucG8ZLd52H0rz0sy5ny2zPSCiASxdNxStfOx9v17fizV2teFpm1122aORP5RWFOZhRnoeG9oGk+BMAzK4swM6mXpQXGF3Xv3zhXNz19GY090Rxz98twmfPnJn0N3vFSdPwL1cuxPde3IYfvbQdnz1zJnqjCZwwtRitvVE0dPSjayCOkrwwNF3gP1/dhQdW78K8qkI8ddtSzJ9ShM0NXXhy3QFMLclJKmuYXVmANbtb8dx7jfjYqbWOzzY3dGLb4W4sn12O2ZUF2HSgA+v2tuP/Xr0Inz7jODS09+Mfn3wfcU0kWTtKoN5r6MCB9j6s3NqEjQeM4uLjyvNx81kzcfmJU3HqcWUIBggHOwfwvT/X4d9X7gRgdKsfzro5c04F7n15B5q7Bz3/1rv643irvhVv7mrBGztbcEhayHMqC3D9aTOQFwmiuXsQLb1R7Gnpw9q97Z7rgxEB5fkRQ7SKc1FVmIPq4hxcsKAKs6sK8KO/7sDvNzWiuigH//HJJbhmyXRsOtCJh9/ag/95Yw9++eZeXHnyNNxyzmxML8nFTQ+vw962Pvzis6fhElembCBAOGFqMU6YWowvnDMbmi6w9VAX3tzVip+s3IG7f/8Bzp1faSyAGjGW8CkriJj1iGPNeFtQywHUCyH2AAARPQXgGgBjIlBXnjwNV548bdj9akrzcLBzIG0Lyo1avjzVOlLHOjWleUnZa2PJP5w/J6W/fMWcipSNPVVHjGEtqByrWbAXI/XVq0w+1UR4XnWh2aXiV2v2mQ9OmbC4thQN7QNJ8ScAuPf6xfjU8g7zafqaxTUIBQI4a25FUhssO7ecMxv72/rx32/swcb9RpHvwmlF2NXcg79sOYLF316JKcU5KMwJYXdLH647tQbf+9hJpuV52YlT8OiafXhu08Ekq+7Oi+dj+5Fu3PX0Zqypb0NtWT4EBN7Z3ebomFFTmodwkFCWH8aNy2cgNxzEQ59bho/+9C00dUeTEhrK8yOIBAP477/tAQCcOL0YX714AS4/aQqOn1KUJD41pXn4+WdPwxs7W/D9F7dh+ezyYe/12fMqce/LO7D8B6tREAmiJC+MkvwISvPC6I9r2NLYCV0Y9Wdnz63EVy6qwrnzK1NmBwJGXV1rb8wQrp4omnuijp8tPYOob+pBS28UD7+1F5FgALGEji9dMBe3XzjPfJg6bWYZTpt5Ghra+/HYmn14en0D/rT5EAoiQQgAj/796ThrmC4tgPF/5JTaUpxSW4r2vhgefmuvGSNVLJxWjL/eee6w5xoNaDwzOYjoEwCuEELcKt/fBOAMIcRXbPvcBuA2ADjuuONO279//5iPa29rH1Zva8It53gvYpcOr25vwnnzq4Y1zY81uvrjCIdo2My4icLvNjTgxOklZisqL3Rd4MoH38TtF87D3w3TCSQdmrsH8bGfrcHDf78MJ0w1rtvQ3o+P/vQtzK0qxFcvWYBzPAQmHd7Y2YIXNh/CvZ84ZVTjGwlNx7f++CFe2daMcJDw6tcvAGB0a9/V3ItdTb1o6OjHx5fW4IZlMxzXTmg6rv7Pt5AfCeLLF8xLemqPazq+86c6PLF2v5mNOb0kF184ZzbOW1CFtXvb8ebOFqzd2447LpqHW8+dYx67pbELP1m1Aw/ceGpSSv6T6w6gP6bhskVThhSFTBFC4I/vH0Rj+wA6B+Lo7I+jayCOroEYiAgr5lTgvAWVWFxbOurzQFtvFNf/4h3MrizAt65ehNnDNAHojSbwzPoGrKprwjcuPx6nzczM4umLJjAQ1zAQ08xlZoIBMlchyBQi2iiEWDbsfuMsUNcDuNwlUMuFEHd47b9s2TKxYcOGcRsfwzDJCCFGVfwU9kLl0U4gYCY26QrUeD/2NsIMYQIAagEcGucxMAwzAsZKOIZbVoVhxtsftR7AfCKaTUQRADcCeGGcx8AwDMMcBYyrBSWESBDRVwC8DCPN/BEhxNbxHAPDMAxzdDDukW0hxF8A/GW8r8swDMMcXUyulDOGYRjmqIEFimEYhpmQsEAxDMMwExIWKIZhGGZCwgLFMAzDTEjGtZPESCGiFgDZ9jqqBNA6CsM5FuF7kxq+N6nhe5Mavjepsd+bmUKI5A7HLia0QI0GRLQhnZYakxG+N6nhe5Mavjep4XuTmkzuDbv4GIZhmAkJCxTDMAwzIZkMAvWQ3wOYwPC9SQ3fm9TwvUkN35vUjPjeHPMxKIZhGOboZDJYUAzDMMxRCAsUwzAMMyE5pgWKiK4goh1EVE9Ed/s9Hj8hokeIqJmIPrRtKyeiVUS0S/7MbF3ooxgimkFErxHRNiLaSkR3yu18b4hyiWgdEW2W9+bbcvtsIlor783Tcm23SQkRBYnoPSL6s3zP9wYAEe0joi1E9D4RbZDbRvx/6pgVKCIKAvgvAB8BsAjAp4hokb+j8pVHAVzh2nY3gNVCiPkAVsv3k40EgK8LIRYCOBPA7fLvhO8NEAVwkRBiMYAlAK4gojMB/AjA/fLedAC4xccx+s2dALbZ3vO9sbhQCLHEVvs04v9Tx6xAAVgOoF4IsUcIEQPwFIBrfB6Tbwgh3gDQ7tp8DYDH5OvHAFw7roOaAAghDgshNsnXPTAmmxrwvYEw6JVvw/KfAHARgGfl9kl5bwCAiGoBXAXgl/I9ge/NUIz4/9SxLFA1ABps7xvlNsZiihDiMGBM1ACqfR6PrxDRLACnAlgLvjcATBfW+wCaAawCsBtApxAiIXeZzP+v/gPANwHo8n0F+N4oBICVRLSRiG6T20b8f2rcV9QdR8hjG+fUM54QUSGA3wP4qhCi23gYZoQQGoAlRFQK4DkAC712G99R+Q8RXQ2gWQixkYguUJs9dp1090ZythDiEBFVA1hFRNszOcmxbEE1Aphhe18L4JBPY5moNBHRNACQP5t9Ho8vEFEYhjg9IYT4g9zM98aGEKITwOsw4nSlRKQebifr/6uzAXyUiPbBCB9cBMOi4nsDQAhxSP5shvFgsxwZ/J86lgVqPYD5MqsmAuBGAC/4PKaJxgsAbpavbwbwvI9j8QUZN3gYwDYhxH22j/jeEFVJywlElAfgEhgxutcAfELuNinvjRDin4QQtUKIWTDmlleFEJ8B3xsQUQERFanXAC4D8CEy+D91THeSIKIrYTzVBAE8IoT4vs9D8g0iehLABTBa3jcBuAfAHwE8A+A4AAcAXC+EcCdSHNMQ0TkA3gSwBVYs4Z9hxKEm+705BUYwOwjjYfYZIcR3iGgODKuhHMB7AD4rhIj6N1J/kS6+bwghruZ7A8h78Jx8GwLwWyHE94moAiP8P3VMCxTDMAxz9HIsu/gYhmGYoxgWKIZhGGZCwgLFMAzDTEhYoBiGYZgJCQsUwzAMMyFhgWKYDCAiTXZq3iq7fX+NiALys2VE9OAQx84iok+P32gZ5uiE08wZJgOIqFcIUShfVwP4LYC3hRD3pHHsBZB1M2M7SoY5umELimGyRLZzuQ3AV8jgAtv6QOdLS+t9uW5QEYAfAjhXbrtLWlRvEtEm+e8seewFRPQ6ET1LRNuJ6AnZ+QJEdDoRrZHW2zoiKpKNXe8lovVE9AER/YNf94RhRoNjuVksw4wbQog90sXn7tD8DQC3CyHelg1pB2Gsg2NaUESUD+BSIcQgEc0H8CQAtYbOqQBOhNHT7W0AZxPROgBPA/ikEGI9ERUDGICx9lCXEOJ0IsoB8DYRrRRC7B3L784wYwULFMOMHl7drN8GcB8RPQHgD0KIRo9O6WEAPyWiJQA0AAtsn60TQjQCgFz2YhaALgCHhRDrAUAI0S0/vwzAKUSkesGVAJgPgAWKOSphgWKYUUD2H9NgdGg2l6QQQvyQiF4EcCWAd4noEo/D74LRH3ExDLf7oO0zex83Dcb/WYL3Mg4E4A4hxMtZfBWGmTBwDIphsoSIqgD8AsBPhSvriIjmCiG2CCF+BGADgBMA9AAosu1WAsMi0gHcBKM561BsBzCdiE6X1yiSSzy8DOBLcvkQENEC2U2aYY5K2IJimMzIky63MIAEgMcB3Oex31eJ6EIY1k8dgL/C6JqeIKLNAB4F8DMAvyei62Es19A31IWFEDEi+iSA/5TLYAzAWArjlzBcgJtkMkULeMlx5iiG08wZhmGYCQm7+BiGYZgJCQsUwzAMMyFhgWIYhmEmJCxQDMMwzISEBYphGIaZkLBAMQzDMBMSFiiGYRhmQvL/AcSh/5MNJz4GAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1d659530ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sdf.groupby(by='Distance').count()['Lattitude'].plot()\n",
    "plt.tight_layout()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}