DataPreparation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Final Dataset - Data Collection, Analysis, Wrangling, Feature Engineering"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Collection\n",
    "To collect data we programmed a web scraper that would go through each listing that can currently (3 Apr 2020) be found on PropertyFinder.qa. From each listing we collected the following data: Value, Type, Reference, Bedrooms, Bathrooms, Furnishing, Size, Amenities, Agency, Location. These were then saved into a csv file named \"PF_scrape_final.csv\", which we will use for the project. There were a total of 6700+ properties listed, but some were not of a type we wanted so we ended up with exactly 6688 properties as entries in our dataset. These \"bad\" types were listings that were of type \"Whole Building\" or \"Bulk Rent Units\"."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# Data ingestion\n",
    "data = pd.read_csv(\"PF_scrape_final.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Our training data contains 6688 records/rows, each with 10 fields/data attributes\n"
     ]
    }
   ],
   "source": [
    "# Data inspection\n",
    "(records, fields) = data.shape\n",
    "print('Our training data contains {} records/rows, each with {} fields/data attributes'.format(records, fields))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>Value</th>\n",
       "      <th>Type</th>\n",
       "      <th>Reference</th>\n",
       "      <th>Bedrooms</th>\n",
       "      <th>Bathrooms</th>\n",
       "      <th>Furnishing</th>\n",
       "      <th>Size</th>\n",
       "      <th>Amenities</th>\n",
       "      <th>Agency</th>\n",
       "      <th>Location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>6,500 QAR Monthly</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>AP2831</td>\n",
       "      <td>studio</td>\n",
       "      <td>1</td>\n",
       "      <td>Furnished</td>\n",
       "      <td>646 sq...</td>\n",
       "      <td>Central A/C - Concierge - Covered Parking - Ki...</td>\n",
       "      <td>Capstone Property</td>\n",
       "      <td>Marina Gate - Porto Arabia - The Pearl - Doha</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>7,000 QAR Monthly</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>AP2812</td>\n",
       "      <td>studio</td>\n",
       "      <td>1</td>\n",
       "      <td>Furnished</td>\n",
       "      <td>667 sq...</td>\n",
       "      <td>Central A/C - Concierge - Covered Parking - Ki...</td>\n",
       "      <td>Capstone Property</td>\n",
       "      <td>West Bay Villas - West Bay - West Bay - Doha</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>6,700 QAR Monthly</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>AP2820</td>\n",
       "      <td>studio</td>\n",
       "      <td>1</td>\n",
       "      <td>Furnished</td>\n",
       "      <td>646 sq...</td>\n",
       "      <td>Balcony - Central A/C - Concierge - Covered Pa...</td>\n",
       "      <td>Capstone Property</td>\n",
       "      <td>Imperial Diamond - Viva Bahriyah - The Pearl ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>6,500 QAR Monthly</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>AP2639B</td>\n",
       "      <td>studio</td>\n",
       "      <td>1</td>\n",
       "      <td>Partly furnished</td>\n",
       "      <td>657 sq...</td>\n",
       "      <td>Balcony - Built in Wardrobes - Central A/C - C...</td>\n",
       "      <td>Capstone Property</td>\n",
       "      <td>Viva West - Viva Bahriyah - The Pearl - Doha</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>7,500 QAR Monthly</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>403-WB-STU-FF</td>\n",
       "      <td>studio</td>\n",
       "      <td>1</td>\n",
       "      <td>Furnished</td>\n",
       "      <td>646 sq...</td>\n",
       "      <td>Built in Wardrobes - Central A/C - Concierge -...</td>\n",
       "      <td>ABHome Real Estate</td>\n",
       "      <td>West Bay Tower - West Bay - West Bay - Doha</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Value       Type      Reference Bedrooms Bathrooms  \\\n",
       "0  6,500 QAR Monthly  Apartment         AP2831   studio         1   \n",
       "1  7,000 QAR Monthly  Apartment         AP2812   studio         1   \n",
       "2  6,700 QAR Monthly  Apartment         AP2820   studio         1   \n",
       "3  6,500 QAR Monthly  Apartment        AP2639B   studio         1   \n",
       "4  7,500 QAR Monthly  Apartment  403-WB-STU-FF   studio         1   \n",
       "\n",
       "         Furnishing                                               Size  \\\n",
       "0         Furnished                                          646 sq...   \n",
       "1         Furnished                                          667 sq...   \n",
       "2         Furnished                                          646 sq...   \n",
       "3  Partly furnished                                          657 sq...   \n",
       "4         Furnished                                          646 sq...   \n",
       "\n",
       "                                           Amenities              Agency  \\\n",
       "0  Central A/C - Concierge - Covered Parking - Ki...   Capstone Property   \n",
       "1  Central A/C - Concierge - Covered Parking - Ki...   Capstone Property   \n",
       "2  Balcony - Central A/C - Concierge - Covered Pa...   Capstone Property   \n",
       "3  Balcony - Built in Wardrobes - Central A/C - C...   Capstone Property   \n",
       "4  Built in Wardrobes - Central A/C - Concierge -...  ABHome Real Estate   \n",
       "\n",
       "                                            Location  \n",
       "0      Marina Gate - Porto Arabia - The Pearl - Doha  \n",
       "1       West Bay Villas - West Bay - West Bay - Doha  \n",
       "2   Imperial Diamond - Viva Bahriyah - The Pearl ...  \n",
       "3       Viva West - Viva Bahriyah - The Pearl - Doha  \n",
       "4        West Bay Tower - West Bay - West Bay - Doha  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Our features have following titles:\n",
      " Value, Type, Reference, Bedrooms, Bathrooms, Furnishing, Size, Amenities, Agency, Location\n"
     ]
    }
   ],
   "source": [
    "dcols = data.columns\n",
    "print('Our features have following titles:\\n', \", \".join(dcols))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 6688 entries, 0 to 6687\n",
      "Data columns (total 10 columns):\n",
      "Value         6688 non-null object\n",
      "Type          6688 non-null object\n",
      "Reference     6688 non-null object\n",
      "Bedrooms      6688 non-null object\n",
      "Bathrooms     6688 non-null object\n",
      "Furnishing    6688 non-null object\n",
      "Size          6621 non-null object\n",
      "Amenities     6202 non-null object\n",
      "Agency        6688 non-null object\n",
      "Location      6620 non-null object\n",
      "dtypes: object(10)\n",
      "memory usage: 522.6+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>Value</th>\n",
       "      <th>Type</th>\n",
       "      <th>Reference</th>\n",
       "      <th>Bedrooms</th>\n",
       "      <th>Bathrooms</th>\n",
       "      <th>Furnishing</th>\n",
       "      <th>Size</th>\n",
       "      <th>Amenities</th>\n",
       "      <th>Agency</th>\n",
       "      <th>Location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>6688</td>\n",
       "      <td>6688</td>\n",
       "      <td>6688</td>\n",
       "      <td>6688</td>\n",
       "      <td>6688</td>\n",
       "      <td>6688</td>\n",
       "      <td>6621</td>\n",
       "      <td>6202</td>\n",
       "      <td>6688</td>\n",
       "      <td>6620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>unique</td>\n",
       "      <td>292</td>\n",
       "      <td>7</td>\n",
       "      <td>6456</td>\n",
       "      <td>18</td>\n",
       "      <td>11</td>\n",
       "      <td>40</td>\n",
       "      <td>378</td>\n",
       "      <td>2279</td>\n",
       "      <td>205</td>\n",
       "      <td>444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>top</td>\n",
       "      <td>10,000 QAR Monthly</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>tanweenproperties-1645513</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Furnished</td>\n",
       "      <td>1,292 ...</td>\n",
       "      <td>Balcony - Built in Wardrobes - Central A/C - C...</td>\n",
       "      <td>NelsonPark Property</td>\n",
       "      <td>Viva West - Viva Bahriyah - The Pearl - Doha</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>freq</td>\n",
       "      <td>363</td>\n",
       "      <td>4775</td>\n",
       "      <td>2</td>\n",
       "      <td>1941</td>\n",
       "      <td>2274</td>\n",
       "      <td>2783</td>\n",
       "      <td>310</td>\n",
       "      <td>135</td>\n",
       "      <td>600</td>\n",
       "      <td>384</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Value       Type                  Reference Bedrooms  \\\n",
       "count                 6688       6688                       6688     6688   \n",
       "unique                 292          7                       6456       18   \n",
       "top     10,000 QAR Monthly  Apartment  tanweenproperties-1645513        2   \n",
       "freq                   363       4775                          2     1941   \n",
       "\n",
       "       Bathrooms Furnishing  \\\n",
       "count       6688       6688   \n",
       "unique        11         40   \n",
       "top            2  Furnished   \n",
       "freq        2274       2783   \n",
       "\n",
       "                                                     Size  \\\n",
       "count                                                6621   \n",
       "unique                                                378   \n",
       "top                                             1,292 ...   \n",
       "freq                                                  310   \n",
       "\n",
       "                                                Amenities  \\\n",
       "count                                                6202   \n",
       "unique                                               2279   \n",
       "top     Balcony - Built in Wardrobes - Central A/C - C...   \n",
       "freq                                                  135   \n",
       "\n",
       "                      Agency                                       Location  \n",
       "count                   6688                                           6620  \n",
       "unique                   205                                            444  \n",
       "top     NelsonPark Property    Viva West - Viva Bahriyah - The Pearl - Doha  \n",
       "freq                     600                                            384  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\f",
      "Total number of missing entries: 621\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "total_nan = np.sum(np.sum(data.isnull()))\n",
    "print('\\fTotal number of missing entries: {}\\n'.format(total_nan))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Summary of info about the our dataset*\n",
    "\n",
    "This data set includes 6688 listings of properties to rent, including their value, type, reference, bedrooms, bathrooms, furnishing, size, agency, location and all the amenities they have.\n",
    "\n",
    "The dataset includes 621 NaN values due to the fact that some listings did not record the nr of bethrooms and our webscraper then kept listing the subsequent features normally. So, the subsequent features (furnishing, size, amenities, agency, location) are placed in the row but shifted to the left by one.\n",
    "\n",
    "\n",
    "The data reports:\n",
    "\n",
    "- Value: price to rent the property in QAR per month (i.e. QAR Monthly)\n",
    "- Type: description of the property (e.g. Apartment, Villa, Compound)\n",
    "- Reference: unique identifiert of the listing, usually used only by the agency\n",
    "- Bedrooms: number of bedrooms that are found in the property\n",
    "- Bathrooms: number of bathrooms that are found in the property\n",
    "- Furnishing: description of how much furniture is found in the property (e.g. Furnished, Partly furnished)\n",
    "- Size: area of the property in square feet and square meters (i.e. sqft / sqm)\n",
    "- Amenities: description of all the amenities that come with the property (e.g. Shared pool, Balcony, Security)\n",
    "- Agency: name of the company that listed the property for rent\n",
    "- Location: description of where the property is geographically found\n",
    "\n",
    "<u>The question we are going to answer with this database:</u> Given a property with some features, what price should you list it online?\n",
    "\n",
    "The values that are currently in the data set are all still string values that our webscraper copied from the site and wrote into the csv file, therefore it is not possible to make any type of graph or plot, so we will do this after we have wrangled our data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "matplotlib.rcParams['figure.dpi']= 100 # set the resolution to x dpi\n",
    "\n",
    "import itertools"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It seems like our data is too dirty to make any type of graph or plot, so we will do this after we have wrangled our data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Wrangling\n",
    "Overview of what is to come: \n",
    "- Handle any NaNs\n",
    "- Some entries did not have a bathroom number so the features after that got shifted to the left by one. We remove these entries.\n",
    "- We need to change the type of value to a simple int by getting rid of \"QAR Monthly\" and comma in number.\n",
    "- Clean Bedrooms column so that it contains a simple int with the total number of rooms\n",
    "- We need to clean Size column because the entries strings are weird and we just want an int here too.\n",
    "- The amenities column will be the hardest task. Because we need to get a list of all different posssible amenties and then we need to create a feature column for every single one of them and for every entry we need to either mark it true or false if that amenity was listed in their amenities or not. \n",
    "- Lastly, location will have to be cleaned up by simply turning the string of multiple locations into one single location, I think we should choose the second to last location because that is very general but more specific than Doha.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Imputing Missing Values\n",
    "\n",
    "First, we check our data for missing values. We follow a 'backfill' approach to our imputations, based on intuition about the data at hand."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The amount of missing values (NaN) in each feature column are the following:\n",
      " - Value: 0\n",
      " - Type: 0\n",
      " - Reference: 0\n",
      " - Bedrooms: 0\n",
      " - Bathrooms: 0\n",
      " - Furnishing: 0\n",
      " - Size: 67\n",
      " - Amenities: 486\n",
      " - Agency: 0\n",
      " - Location: 68\n",
      "\n",
      "Total: 621\n"
     ]
    }
   ],
   "source": [
    "print('The amount of missing values (NaN) in each feature column are the following:')\n",
    "for feature in data.columns:\n",
    "    nan = np.sum(np.sum(data[feature].isnull()))\n",
    "    print(f' - {feature}: {nan}')\n",
    "total_nan = np.sum(np.sum(data.isnull()))\n",
    "print(f'\\nTotal: {total_nan}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see that it is the **Ameneties**, **Size**, and **Location** columns that contain missing values.\n",
    "We use 'bfill' to assign their new values.\n",
    "In our dataset, we scraped the data on the site where they ordered the listings in ascending order by the \"Bedrooms\". So we assume that data in close proximity are somehow related, and therefore we use \"bfill\" as our method of imputation for missing values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total missing values: 0\n"
     ]
    }
   ],
   "source": [
    "data = data.fillna(method='bfill')\n",
    "\n",
    "total_nan = np.sum(np.sum(data.isnull()))\n",
    "print(f'Total missing values: {total_nan}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Cleaning Value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        6500\n",
       "1        7000\n",
       "2        6700\n",
       "3        6500\n",
       "4        7500\n",
       "        ...  \n",
       "6683    60000\n",
       "6684    80000\n",
       "6685    18000\n",
       "6686    22000\n",
       "6687    55000\n",
       "Name: Value, Length: 6688, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Let's start by converting all \"Value\" entries into a singular int\n",
    "# This will be the price in QAR Monthly\n",
    "\n",
    "def converted_values():\n",
    "    '''\n",
    "    We will use this function to return a list of all \n",
    "    values to be replaced\n",
    "    '''    \n",
    "    replacements = []\n",
    "    for entry in data.loc[:, \"Value\"]:\n",
    "        '''\n",
    "        Each entry in the Values column is of the form: _ QAR Monthly\n",
    "        So we split this string into a list of its contents, and select\n",
    "        the first element, which is our desired integer\n",
    "        '''\n",
    "        entry_list = str.split(entry)\n",
    "        value_str = entry_list[0] \n",
    "        # Remove the commas and convert to int\n",
    "        value_int = int(value_str.replace(',',''))\n",
    "        replacements.append(value_int)\n",
    "    return replacements\n",
    "\n",
    "data[\"Value\"] = converted_values()\n",
    "data[\"Value\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Cleaning Bathrooms\n",
    "Next, let us clean the **Bathrooms** entries.  \n",
    "\n",
    "Due to a quirk in the webscraper, some entries did not have a bathroom number so the features after that got shifted to the left by one. These integer entries were then replaced by string entries from the **Furnishing** feature column. \n",
    "This column contains the following possible entries: *'Furnished', 'Partly furnished', 'Unfurnished'*  \n",
    "\n",
    "*We will drop these entries*, as they are few enough not to make much of a difference on our results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        1\n",
       "1        1\n",
       "2        1\n",
       "3        1\n",
       "4        1\n",
       "        ..\n",
       "6683    7+\n",
       "6684    7+\n",
       "6685    7+\n",
       "6686    7+\n",
       "6687    7+\n",
       "Name: Bathrooms, Length: 6620, dtype: object"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dropped_rows = []\n",
    "indx = 0\n",
    "for entry in data.loc[:, 'Bathrooms']:\n",
    "    if entry in ['Furnished', 'Partly furnished', 'Unfurnished']:\n",
    "        dropped_rows.append(indx)\n",
    "    indx += 1\n",
    "        \n",
    "data = data.drop(dropped_rows)\n",
    "data.loc[:, \"Bathrooms\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that the Bathroom feature reflects accurate information, we also want it to contain simple integer values.\n",
    "We do this by converting all \"7+\" values into 8, and all other values into their integer counterparts."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       1\n",
       "1       1\n",
       "2       1\n",
       "3       1\n",
       "4       1\n",
       "       ..\n",
       "6683    8\n",
       "6684    8\n",
       "6685    8\n",
       "6686    8\n",
       "6687    8\n",
       "Name: Bathrooms, Length: 6620, dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# replacing '7+'\n",
    "data = data.replace({'Bathrooms':'7+'}, 8)\n",
    "# converting to integers\n",
    "data['Bathrooms'] = [int(x) for x in data['Bathrooms']]\n",
    "\n",
    "data['Bathrooms']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Cleaning Size\n",
    "\n",
    "We now move to the **Size** column. Each entry is of the form: \"x sqft / y sqm\".  \n",
    "We are really only interested in the square metrege, so if we *split* each entry and retrieve the *fourth element* only, this is what we obtain."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         60\n",
       "1         62\n",
       "2         60\n",
       "3         61\n",
       "4         60\n",
       "        ... \n",
       "6683    1250\n",
       "6684    1225\n",
       "6685     375\n",
       "6686     350\n",
       "6687    2000\n",
       "Name: Size, Length: 6620, dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# We also need to make sure to remove commas from y so that \n",
    "# it may be converted to an integer\n",
    "sqm_list = [int(y.split()[3].replace(\",\", \"\")) for y in data.loc[:, \"Size\"]]\n",
    "\n",
    "data[\"Size\"] = sqm_list\n",
    "data[\"Size\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Cleaning Location\n",
    "\n",
    "We now move to the **Location** feature. \n",
    "\n",
    "Each entry looks something like this: \"Street Number - Street Name - Province - Doha\" \n",
    "\n",
    "Some have less, but all have \"Doha\" at the end. The most general location that is less general than \"Doha\" is the one right before it, so that is the one we retain. This is the second-to-last entry of each."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        The Pearl\n",
       "1         West Bay\n",
       "2        The Pearl\n",
       "3        The Pearl\n",
       "4         West Bay\n",
       "           ...    \n",
       "6683      Al Dafna\n",
       "6684      Al Dafna\n",
       "6685      Al Hilal\n",
       "6686      Al Hilal\n",
       "6687    Ain Khaled\n",
       "Name: Location, Length: 6620, dtype: object"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prov_list = [location.split(\" - \")[-2].strip() for location in data.loc[:, 'Location']]\n",
    "\n",
    "data[\"Location\"] = prov_list\n",
    "data[\"Location\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Cleaning Bedrooms\n",
    "\n",
    "Next is **Bedrooms**.  \n",
    "Most are simple strings of a single number, but there more interesting values as well. These take one of the following forms: \n",
    "- \"studio\"\n",
    "- \"7+\"\n",
    "- \"x + Maids Room\"\n",
    "\n",
    "In the case of \"studio\", we simply change the entry to the integer 1.  \n",
    "In the case of \"7+\", we do as before and simply modify the value to the integer *8*.  \n",
    "In the case of some *x* (where *x* can be a number or one of the above cases) followed by \"+ Maids Room\", we take that *x* value and increase it by one."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                studio\n",
       "1                studio\n",
       "2                studio\n",
       "3                studio\n",
       "4                studio\n",
       "             ...       \n",
       "6683    7+ + Maids Room\n",
       "6684    7+ + Maids Room\n",
       "6685                 7+\n",
       "6686    7+ + Maids Room\n",
       "6687                 7+\n",
       "Name: Bedrooms, Length: 6620, dtype: object"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"Bedrooms\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       1\n",
       "1       1\n",
       "2       1\n",
       "3       1\n",
       "4       1\n",
       "       ..\n",
       "6683    9\n",
       "6684    9\n",
       "6685    8\n",
       "6686    9\n",
       "6687    8\n",
       "Name: Bedrooms, Length: 6620, dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Finding and changing \"studio\" to \"1\" and \"7+\" to \"8\",\n",
    "# as well as their \"+ Maids Room\" counterparts\n",
    "data = data.replace({'Bedrooms':'7+'}, '8')\n",
    "data = data.replace({'Bedrooms':'7+ + Maids Room'}, '9')\n",
    "data = data.replace({'Bedrooms':'studio'}, '1')\n",
    "data = data.replace({'Bedrooms':'studio + Maids Room'}, '2')\n",
    "\n",
    "# Converting the rest of the entries\n",
    "replacements = []\n",
    "for entry in data.loc[:, \"Bedrooms\"]:\n",
    "    # Only those entries longer than 1 contain \"+ Maids Room\"\n",
    "    if len(entry) > 1:\n",
    "        replacements.append(int(entry[0]) + 1)\n",
    "    else:\n",
    "        replacements.append(int(entry))\n",
    "\n",
    "data['Bedrooms'] = replacements\n",
    "data['Bedrooms']\n",
    "        "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Cleaning Amenities\n",
    "\n",
    "Lastly, we have **Amenities**.  \n",
    "\n",
    "First, we create a set of all possible amenities."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       Central A/C - Concierge - Covered Parking - Ki...\n",
       "1       Central A/C - Concierge - Covered Parking - Ki...\n",
       "2       Balcony - Central A/C - Concierge - Covered Pa...\n",
       "3       Balcony - Built in Wardrobes - Central A/C - C...\n",
       "4       Built in Wardrobes - Central A/C - Concierge -...\n",
       "                              ...                        \n",
       "6683    Balcony - Built in Wardrobes - Maid Service - ...\n",
       "6684    Balcony - Built in Wardrobes - Central A/C - C...\n",
       "6685    Balcony - Covered Parking - Maids Room - Pets ...\n",
       "6686    Balcony - Covered Parking - Maids Room - Pets ...\n",
       "6687                                         Pets Allowed\n",
       "Name: Amenities, Length: 6620, dtype: object"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.loc[:, \"Amenities\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Balcony',\n",
       " 'Barbecue Area',\n",
       " 'Built in Wardrobes',\n",
       " 'Central A/C',\n",
       " \"Children's Play Area\",\n",
       " \"Children's Pool\",\n",
       " 'Concierge',\n",
       " 'Covered Parking',\n",
       " 'Kitchen Appliances',\n",
       " 'Lobby in Building',\n",
       " 'MD Properties',\n",
       " 'Maid Service',\n",
       " 'Maids Room',\n",
       " 'Networked',\n",
       " 'Pets Allowed',\n",
       " 'Private Garden',\n",
       " 'Private Gym',\n",
       " 'Private Jacuzzi',\n",
       " 'Private Pool',\n",
       " 'Security',\n",
       " 'Shared Gym',\n",
       " 'Shared Pool',\n",
       " 'Shared Spa',\n",
       " 'Study',\n",
       " 'View of Landmark',\n",
       " 'View of Water',\n",
       " 'Walk-in Closet'}"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "amset = set()\n",
    "for entry in data.loc[:, \"Amenities\"]:\n",
    "    for amenity in entry.split(\" - \"):\n",
    "        amset.add(amenity)\n",
    "\n",
    "amset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we replace the string values in the **Amenities** column with a *list* of its amenities, so that it is easier to work with. And we add a new feature that represents the number of amenities the property has. We think this might be more useful than the individual amenities it has."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0       [Central A/C, Concierge, Covered Parking, Kitc...\n",
      "1       [Central A/C, Concierge, Covered Parking, Kitc...\n",
      "2       [Balcony, Central A/C, Concierge, Covered Park...\n",
      "3       [Balcony, Built in Wardrobes, Central A/C, Con...\n",
      "4       [Built in Wardrobes, Central A/C, Concierge, K...\n",
      "                              ...                        \n",
      "6683    [Balcony, Built in Wardrobes, Maid Service, Ma...\n",
      "6684    [Balcony, Built in Wardrobes, Central A/C, Cov...\n",
      "6685    [Balcony, Covered Parking, Maids Room, Pets Al...\n",
      "6686    [Balcony, Covered Parking, Maids Room, Pets Al...\n",
      "6687                                       [Pets Allowed]\n",
      "Name: Amenities, Length: 6620, dtype: object\n",
      "0        8\n",
      "1        8\n",
      "2        9\n",
      "3       10\n",
      "4       10\n",
      "        ..\n",
      "6683     5\n",
      "6684    10\n",
      "6685     5\n",
      "6686     5\n",
      "6687     1\n",
      "Name: Nr of amenities, Length: 6620, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "am_lists = [entry.split(\" - \") for entry in data.loc[:, \"Amenities\"]]\n",
    "nr_am_list = [len(am_l) for am_l in am_lists]\n",
    "            \n",
    "data['Amenities'] = am_lists\n",
    "data['Nr of amenities'] = nr_am_list\n",
    "print(data['Amenities'])\n",
    "print(data['Nr of amenities'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we binarize the amenities and delete the old amenities column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import MultiLabelBinarizer\n",
    "s = data['Amenities']\n",
    "mlb = MultiLabelBinarizer()\n",
    "df_amenities = pd.DataFrame(mlb.fit_transform(s),columns=mlb.classes_, index=data.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "del data['Amenities']\n",
    "data = pd.concat([data, df_amenities], axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this step we replaced the **Amenities** column with *multiple* columns depending on all the available amenities that can be found in the entry - these are of type boolean (1 or 0)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Our features have following titles now:\n",
      " Value, Type, Reference, Bedrooms, Bathrooms, Furnishing, Size, Agency, Location, Nr of amenities, Balcony, Barbecue Area, Built in Wardrobes, Central A/C, Children's Play Area, Children's Pool, Concierge, Covered Parking, Kitchen Appliances, Lobby in Building, MD Properties, Maid Service, Maids Room, Networked, Pets Allowed, Private Garden, Private Gym, Private Jacuzzi, Private Pool, Security, Shared Gym, Shared Pool, Shared Spa, Study, View of Landmark, View of Water, Walk-in Closet\n"
     ]
    }
   ],
   "source": [
    "dcols = data.columns\n",
    "print('Our features have following titles now:\\n', \", \".join(dcols))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>Value</th>\n",
       "      <th>Type</th>\n",
       "      <th>Reference</th>\n",
       "      <th>Bedrooms</th>\n",
       "      <th>Bathrooms</th>\n",
       "      <th>Furnishing</th>\n",
       "      <th>Size</th>\n",
       "      <th>Agency</th>\n",
       "      <th>Location</th>\n",
       "      <th>Nr of amenities</th>\n",
       "      <th>...</th>\n",
       "      <th>Private Jacuzzi</th>\n",
       "      <th>Private Pool</th>\n",
       "      <th>Security</th>\n",
       "      <th>Shared Gym</th>\n",
       "      <th>Shared Pool</th>\n",
       "      <th>Shared Spa</th>\n",
       "      <th>Study</th>\n",
       "      <th>View of Landmark</th>\n",
       "      <th>View of Water</th>\n",
       "      <th>Walk-in Closet</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>6500</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>AP2831</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Furnished</td>\n",
       "      <td>60</td>\n",
       "      <td>Capstone Property</td>\n",
       "      <td>The Pearl</td>\n",
       "      <td>8</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>7000</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>AP2812</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Furnished</td>\n",
       "      <td>62</td>\n",
       "      <td>Capstone Property</td>\n",
       "      <td>West Bay</td>\n",
       "      <td>8</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>6700</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>AP2820</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Furnished</td>\n",
       "      <td>60</td>\n",
       "      <td>Capstone Property</td>\n",
       "      <td>The Pearl</td>\n",
       "      <td>9</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>6500</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>AP2639B</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Partly furnished</td>\n",
       "      <td>61</td>\n",
       "      <td>Capstone Property</td>\n",
       "      <td>The Pearl</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>7500</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>403-WB-STU-FF</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Furnished</td>\n",
       "      <td>60</td>\n",
       "      <td>ABHome Real Estate</td>\n",
       "      <td>West Bay</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\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",
       "      <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",
       "      <td>6683</td>\n",
       "      <td>60000</td>\n",
       "      <td>Villa</td>\n",
       "      <td>j-L529148</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>Unfurnished</td>\n",
       "      <td>1250</td>\n",
       "      <td>Steps Real Estate</td>\n",
       "      <td>Al Dafna</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6684</td>\n",
       "      <td>80000</td>\n",
       "      <td>Villa</td>\n",
       "      <td>nelsonpark-1891392</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>Unfurnished</td>\n",
       "      <td>1225</td>\n",
       "      <td>NelsonPark Property</td>\n",
       "      <td>Al Dafna</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6685</td>\n",
       "      <td>18000</td>\n",
       "      <td>Villa</td>\n",
       "      <td>FBCM-M0221</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>Unfurnished</td>\n",
       "      <td>375</td>\n",
       "      <td>Future Business</td>\n",
       "      <td>Al Hilal</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6686</td>\n",
       "      <td>22000</td>\n",
       "      <td>Villa</td>\n",
       "      <td>545</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>Unfurnished</td>\n",
       "      <td>350</td>\n",
       "      <td>GOLDEN KEY LUXURY REAL ESTATE</td>\n",
       "      <td>Al Hilal</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6687</td>\n",
       "      <td>55000</td>\n",
       "      <td>Villa</td>\n",
       "      <td>binajlan-1894906</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>Unfurnished</td>\n",
       "      <td>2000</td>\n",
       "      <td>Bin Ajlan Real Estate Group</td>\n",
       "      <td>Ain Khaled</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6620 rows × 37 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Value       Type           Reference  Bedrooms  Bathrooms  \\\n",
       "0      6500  Apartment              AP2831         1          1   \n",
       "1      7000  Apartment              AP2812         1          1   \n",
       "2      6700  Apartment              AP2820         1          1   \n",
       "3      6500  Apartment             AP2639B         1          1   \n",
       "4      7500  Apartment       403-WB-STU-FF         1          1   \n",
       "...     ...        ...                 ...       ...        ...   \n",
       "6683  60000      Villa           j-L529148         9          8   \n",
       "6684  80000      Villa  nelsonpark-1891392         9          8   \n",
       "6685  18000      Villa          FBCM-M0221         8          8   \n",
       "6686  22000      Villa                 545         9          8   \n",
       "6687  55000      Villa    binajlan-1894906         8          8   \n",
       "\n",
       "            Furnishing  Size                          Agency    Location  \\\n",
       "0            Furnished    60               Capstone Property   The Pearl   \n",
       "1            Furnished    62               Capstone Property    West Bay   \n",
       "2            Furnished    60               Capstone Property   The Pearl   \n",
       "3     Partly furnished    61               Capstone Property   The Pearl   \n",
       "4            Furnished    60              ABHome Real Estate    West Bay   \n",
       "...                ...   ...                             ...         ...   \n",
       "6683       Unfurnished  1250               Steps Real Estate    Al Dafna   \n",
       "6684       Unfurnished  1225            NelsonPark Property     Al Dafna   \n",
       "6685       Unfurnished   375                Future Business     Al Hilal   \n",
       "6686       Unfurnished   350  GOLDEN KEY LUXURY REAL ESTATE     Al Hilal   \n",
       "6687       Unfurnished  2000    Bin Ajlan Real Estate Group   Ain Khaled   \n",
       "\n",
       "      Nr of amenities  ...  Private Jacuzzi  Private Pool  Security  \\\n",
       "0                   8  ...                0             0         1   \n",
       "1                   8  ...                0             0         1   \n",
       "2                   9  ...                0             0         1   \n",
       "3                  10  ...                0             0         1   \n",
       "4                  10  ...                0             0         1   \n",
       "...               ...  ...              ...           ...       ...   \n",
       "6683                5  ...                0             0         0   \n",
       "6684               10  ...                1             1         0   \n",
       "6685                5  ...                0             0         0   \n",
       "6686                5  ...                0             0         0   \n",
       "6687                1  ...                0             0         0   \n",
       "\n",
       "      Shared Gym  Shared Pool  Shared Spa  Study  View of Landmark  \\\n",
       "0              1            1           0      0                 0   \n",
       "1              1            1           0      0                 0   \n",
       "2              1            1           0      0                 0   \n",
       "3              1            1           0      0                 0   \n",
       "4              1            1           1      0                 0   \n",
       "...          ...          ...         ...    ...               ...   \n",
       "6683           0            0           0      0                 1   \n",
       "6684           0            0           1      0                 0   \n",
       "6685           0            0           0      0                 0   \n",
       "6686           0            0           0      0                 0   \n",
       "6687           0            0           0      0                 0   \n",
       "\n",
       "      View of Water  Walk-in Closet  \n",
       "0                 1               0  \n",
       "1                 1               0  \n",
       "2                 1               0  \n",
       "3                 1               0  \n",
       "4                 1               0  \n",
       "...             ...             ...  \n",
       "6683              0               0  \n",
       "6684              0               0  \n",
       "6685              0               0  \n",
       "6686              0               0  \n",
       "6687              0               0  \n",
       "\n",
       "[6620 rows x 37 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Back to Analysis\n",
    "\n",
    "Now that our code is clean, we are able to do some basic analysis. </br>\n",
    "First we will make some graphs combining all features that are numerical."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feature pairings: [(0, 1), (0, 2), (0, 3), (0, 4), (1, 2), (1, 3), (1, 4), (2, 3), (2, 4), (3, 4)]\n",
      "[[<matplotlib.axes._subplots.AxesSubplot object at 0x1a17f4ec90>\n",
      "  <matplotlib.axes._subplots.AxesSubplot object at 0x1a1818fcd0>]\n",
      " [<matplotlib.axes._subplots.AxesSubplot object at 0x1a181cf4d0>\n",
      "  <matplotlib.axes._subplots.AxesSubplot object at 0x1a1813f190>]\n",
      " [<matplotlib.axes._subplots.AxesSubplot object at 0x1a18a6c510>\n",
      "  <matplotlib.axes._subplots.AxesSubplot object at 0x1a18a9e1d0>]\n",
      " [<matplotlib.axes._subplots.AxesSubplot object at 0x1a18adf650>\n",
      "  <matplotlib.axes._subplots.AxesSubplot object at 0x1a18b14e50>]\n",
      " [<matplotlib.axes._subplots.AxesSubplot object at 0x1a18b49a50>\n",
      "  <matplotlib.axes._subplots.AxesSubplot object at 0x1a18b88dd0>]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x1872 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# all subsets of size 2 in the feature set: all possible pairings of features\n",
    "possible_features = [feat for feat in dcols if feat in ['Value', 'Bathrooms', 'Bedrooms', 'Size', 'Nr of amenities']]\n",
    "feature_pairings = list(itertools.combinations(range(len(possible_features)), 2))\n",
    "print(\"Feature pairings:\", feature_pairings)\n",
    "\n",
    "# we'll show the plots in a matrix of three columns\n",
    "ncols = 2\n",
    "nrows = int(len(feature_pairings) // ncols)\n",
    "\n",
    "figure, subplots = plt.subplots(nrows, ncols, figsize=(16, 26))\n",
    "\n",
    "print(subplots)\n",
    "k = 0 # iterates over the feature pairings\n",
    "for i in range(nrows):\n",
    "    for j in range(ncols):\n",
    "        \n",
    "        feature_x = feature_pairings[k][0]\n",
    "        feature_y = feature_pairings[k][1]\n",
    "        k += 1\n",
    "\n",
    "        subplots[i][j].set_xlabel(possible_features[feature_x])\n",
    "        subplots[i][j].set_ylabel(possible_features[feature_y])\n",
    "\n",
    "        subplots[i][j].scatter(data[possible_features[feature_x]], \n",
    "                               data[possible_features[feature_y]],\n",
    "                               facecolors='blue', linewidths=0.20, s=10)\n",
    "    \n",
    "plt.subplots_adjust(left=None, bottom=None, right=None, \n",
    "                    top=None, wspace=0.5, hspace=0.35)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "nrows = 2\n",
    "ncols = 2\n",
    "figure, subplots = plt.subplots(nrows, ncols, figsize=(12, 6))\n",
    "\n",
    "titles = [\"Value\", \"Size\", \"Bedrooms\", \"Bathrooms\"]\n",
    "\n",
    "for i in range(nrows):\n",
    "    for j in range(ncols):\n",
    "        subplots[i, j].hist(data[titles[(2*i)+j]], bins=60)\n",
    "        subplots[i, j].set_xlabel(titles[(2*i)+j])\n",
    "        subplots[i, j].set_ylabel('nr of examples')\n",
    "        subplots[i, j].set_title(titles[(2*i)+j])\n",
    "       \n",
    "plt.subplots_adjust(left=None, bottom=None, right=None, \n",
    "                    top=None, wspace=0.5, hspace=0.35)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By viewing some of these graphs and the histograms, we see that we have some outliers. These outliers are found in the Value and Size features."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Removing Outliers\n",
    "  \n",
    "We will do this using the parametric rule of thumb: 3$\\sigma$ cut-off only on the columns of Value and Size.\n",
    "\n",
    "- **Three standard deviations from the mean is a common cut-off in practice for identifying outliers in a Gaussian or Gaussian-like distribution.**<br><p> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# not specific assumption: mean and std are estimated from the data\n",
    "\n",
    "outlier_data = data[[\"Value\",\"Size\"]]\n",
    "\n",
    "data_mean, data_std = np.mean(outlier_data), np.std(outlier_data)\n",
    "\n",
    "cut_off = 3 * data_std \n",
    "\n",
    "lower, upper = data_mean - cut_off, data_mean + cut_off\n",
    "\n",
    "# print('lower cut-off: {:.3f} - upper cut-off: {:.3f}'.format(lower, upper))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of outliers in Values and Size columns: 40\n",
      "Outliers:       Value    Size\n",
      "0       NaN     NaN\n",
      "1       NaN     NaN\n",
      "2       NaN     NaN\n",
      "3       NaN     NaN\n",
      "4       NaN     NaN\n",
      "...     ...     ...\n",
      "6683    NaN  1250.0\n",
      "6684    NaN  1225.0\n",
      "6685    NaN     NaN\n",
      "6686    NaN     NaN\n",
      "6687    NaN  2000.0\n",
      "\n",
      "[6620 rows x 2 columns]\n"
     ]
    }
   ],
   "source": [
    "# identify outliers\n",
    "outliers = outlier_data[ (outlier_data < lower) | (outlier_data > upper) ]\n",
    "\n",
    "np.set_printoptions(precision=3)\n",
    "\n",
    "total_outlier_nan = (outliers.shape[0]*outliers.shape[1]) - np.sum(np.sum(outliers.isnull()))\n",
    "print(f'Total number of outliers in Values and Size columns: {total_outlier_nan}')\n",
    "\n",
    "print('Outliers:', outliers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "outlier_clean = outlier_data[ (outlier_data > lower) & (outlier_data < upper) ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 6620 entries, 0 to 6687\n",
      "Data columns (total 2 columns):\n",
      "Value    6616 non-null float64\n",
      "Size     6584 non-null float64\n",
      "dtypes: float64(2)\n",
      "memory usage: 155.2 KB\n"
     ]
    }
   ],
   "source": [
    "outlier_clean.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Type</th>\n",
       "      <th>Reference</th>\n",
       "      <th>Bedrooms</th>\n",
       "      <th>Bathrooms</th>\n",
       "      <th>Furnishing</th>\n",
       "      <th>Agency</th>\n",
       "      <th>Location</th>\n",
       "      <th>Nr of amenities</th>\n",
       "      <th>Balcony</th>\n",
       "      <th>Barbecue Area</th>\n",
       "      <th>...</th>\n",
       "      <th>Private Jacuzzi</th>\n",
       "      <th>Private Pool</th>\n",
       "      <th>Security</th>\n",
       "      <th>Shared Gym</th>\n",
       "      <th>Shared Pool</th>\n",
       "      <th>Shared Spa</th>\n",
       "      <th>Study</th>\n",
       "      <th>View of Landmark</th>\n",
       "      <th>View of Water</th>\n",
       "      <th>Walk-in Closet</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>AP2831</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Furnished</td>\n",
       "      <td>Capstone Property</td>\n",
       "      <td>The Pearl</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>AP2812</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Furnished</td>\n",
       "      <td>Capstone Property</td>\n",
       "      <td>West Bay</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>AP2820</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Furnished</td>\n",
       "      <td>Capstone Property</td>\n",
       "      <td>The Pearl</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>AP2639B</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Partly furnished</td>\n",
       "      <td>Capstone Property</td>\n",
       "      <td>The Pearl</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>403-WB-STU-FF</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Furnished</td>\n",
       "      <td>ABHome Real Estate</td>\n",
       "      <td>West Bay</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\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",
       "      <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",
       "      <td>6683</td>\n",
       "      <td>Villa</td>\n",
       "      <td>j-L529148</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>Unfurnished</td>\n",
       "      <td>Steps Real Estate</td>\n",
       "      <td>Al Dafna</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6684</td>\n",
       "      <td>Villa</td>\n",
       "      <td>nelsonpark-1891392</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>Unfurnished</td>\n",
       "      <td>NelsonPark Property</td>\n",
       "      <td>Al Dafna</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6685</td>\n",
       "      <td>Villa</td>\n",
       "      <td>FBCM-M0221</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>Unfurnished</td>\n",
       "      <td>Future Business</td>\n",
       "      <td>Al Hilal</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6686</td>\n",
       "      <td>Villa</td>\n",
       "      <td>545</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>Unfurnished</td>\n",
       "      <td>GOLDEN KEY LUXURY REAL ESTATE</td>\n",
       "      <td>Al Hilal</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6687</td>\n",
       "      <td>Villa</td>\n",
       "      <td>binajlan-1894906</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>Unfurnished</td>\n",
       "      <td>Bin Ajlan Real Estate Group</td>\n",
       "      <td>Ain Khaled</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6620 rows × 35 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Type           Reference  Bedrooms  Bathrooms        Furnishing  \\\n",
       "0     Apartment              AP2831         1          1         Furnished   \n",
       "1     Apartment              AP2812         1          1         Furnished   \n",
       "2     Apartment              AP2820         1          1         Furnished   \n",
       "3     Apartment             AP2639B         1          1  Partly furnished   \n",
       "4     Apartment       403-WB-STU-FF         1          1         Furnished   \n",
       "...         ...                 ...       ...        ...               ...   \n",
       "6683      Villa           j-L529148         9          8       Unfurnished   \n",
       "6684      Villa  nelsonpark-1891392         9          8       Unfurnished   \n",
       "6685      Villa          FBCM-M0221         8          8       Unfurnished   \n",
       "6686      Villa                 545         9          8       Unfurnished   \n",
       "6687      Villa    binajlan-1894906         8          8       Unfurnished   \n",
       "\n",
       "                              Agency    Location  Nr of amenities  Balcony  \\\n",
       "0                  Capstone Property   The Pearl                8        0   \n",
       "1                  Capstone Property    West Bay                8        0   \n",
       "2                  Capstone Property   The Pearl                9        1   \n",
       "3                  Capstone Property   The Pearl               10        1   \n",
       "4                 ABHome Real Estate    West Bay               10        0   \n",
       "...                              ...         ...              ...      ...   \n",
       "6683               Steps Real Estate    Al Dafna                5        1   \n",
       "6684            NelsonPark Property     Al Dafna               10        1   \n",
       "6685                Future Business     Al Hilal                5        1   \n",
       "6686  GOLDEN KEY LUXURY REAL ESTATE     Al Hilal                5        1   \n",
       "6687    Bin Ajlan Real Estate Group   Ain Khaled                1        0   \n",
       "\n",
       "      Barbecue Area  ...  Private Jacuzzi  Private Pool  Security  Shared Gym  \\\n",
       "0                 0  ...                0             0         1           1   \n",
       "1                 0  ...                0             0         1           1   \n",
       "2                 0  ...                0             0         1           1   \n",
       "3                 0  ...                0             0         1           1   \n",
       "4                 0  ...                0             0         1           1   \n",
       "...             ...  ...              ...           ...       ...         ...   \n",
       "6683              0  ...                0             0         0           0   \n",
       "6684              0  ...                1             1         0           0   \n",
       "6685              0  ...                0             0         0           0   \n",
       "6686              0  ...                0             0         0           0   \n",
       "6687              0  ...                0             0         0           0   \n",
       "\n",
       "      Shared Pool  Shared Spa  Study  View of Landmark  View of Water  \\\n",
       "0               1           0      0                 0              1   \n",
       "1               1           0      0                 0              1   \n",
       "2               1           0      0                 0              1   \n",
       "3               1           0      0                 0              1   \n",
       "4               1           1      0                 0              1   \n",
       "...           ...         ...    ...               ...            ...   \n",
       "6683            0           0      0                 1              0   \n",
       "6684            0           1      0                 0              0   \n",
       "6685            0           0      0                 0              0   \n",
       "6686            0           0      0                 0              0   \n",
       "6687            0           0      0                 0              0   \n",
       "\n",
       "      Walk-in Closet  \n",
       "0                  0  \n",
       "1                  0  \n",
       "2                  0  \n",
       "3                  0  \n",
       "4                  0  \n",
       "...              ...  \n",
       "6683               0  \n",
       "6684               0  \n",
       "6685               0  \n",
       "6686               0  \n",
       "6687               0  \n",
       "\n",
       "[6620 rows x 35 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "del data['Value']\n",
    "del data['Size']\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Value</th>\n",
       "      <th>Size</th>\n",
       "      <th>Type</th>\n",
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       "  <tbody>\n",
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       "      <td>0</td>\n",
       "      <td>6500.0</td>\n",
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       "      <td>Apartment</td>\n",
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       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>7000.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>AP2812</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Furnished</td>\n",
       "      <td>Capstone Property</td>\n",
       "      <td>West Bay</td>\n",
       "      <td>8</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>6700.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>AP2820</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Furnished</td>\n",
       "      <td>Capstone Property</td>\n",
       "      <td>The Pearl</td>\n",
       "      <td>9</td>\n",
       "      <td>...</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>6500.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>AP2639B</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Partly furnished</td>\n",
       "      <td>Capstone Property</td>\n",
       "      <td>The Pearl</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>7500.0</td>\n",
       "      <td>60.0</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6680</td>\n",
       "      <td>35000.0</td>\n",
       "      <td>700.0</td>\n",
       "      <td>Villa</td>\n",
       "      <td>j-L529080</td>\n",
       "      <td>9</td>\n",
       "      <td>7</td>\n",
       "      <td>Unfurnished</td>\n",
       "      <td>Steps Real Estate</td>\n",
       "      <td>Al Duhail</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6681</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>680.0</td>\n",
       "      <td>Villa</td>\n",
       "      <td>W1-L509006</td>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>Unfurnished</td>\n",
       "      <td>Steps Real Estate</td>\n",
       "      <td>Ain Khaled</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6682</td>\n",
       "      <td>15000.0</td>\n",
       "      <td>400.0</td>\n",
       "      <td>Villa</td>\n",
       "      <td>N1-L498991</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>Unfurnished</td>\n",
       "      <td>Steps Real Estate</td>\n",
       "      <td>Al Gharrafa</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6685</td>\n",
       "      <td>18000.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>Villa</td>\n",
       "      <td>FBCM-M0221</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>Unfurnished</td>\n",
       "      <td>Future Business</td>\n",
       "      <td>Al Hilal</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6686</td>\n",
       "      <td>22000.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>Villa</td>\n",
       "      <td>545</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>Unfurnished</td>\n",
       "      <td>GOLDEN KEY LUXURY REAL ESTATE</td>\n",
       "      <td>Al Hilal</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6580 rows × 37 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Value   Size       Type      Reference  Bedrooms  Bathrooms  \\\n",
       "0      6500.0   60.0  Apartment         AP2831         1          1   \n",
       "1      7000.0   62.0  Apartment         AP2812         1          1   \n",
       "2      6700.0   60.0  Apartment         AP2820         1          1   \n",
       "3      6500.0   61.0  Apartment        AP2639B         1          1   \n",
       "4      7500.0   60.0  Apartment  403-WB-STU-FF         1          1   \n",
       "...       ...    ...        ...            ...       ...        ...   \n",
       "6680  35000.0  700.0      Villa      j-L529080         9          7   \n",
       "6681  30000.0  680.0      Villa     W1-L509006         8          6   \n",
       "6682  15000.0  400.0      Villa     N1-L498991         8          7   \n",
       "6685  18000.0  375.0      Villa     FBCM-M0221         8          8   \n",
       "6686  22000.0  350.0      Villa            545         9          8   \n",
       "\n",
       "            Furnishing                          Agency     Location  \\\n",
       "0            Furnished               Capstone Property    The Pearl   \n",
       "1            Furnished               Capstone Property     West Bay   \n",
       "2            Furnished               Capstone Property    The Pearl   \n",
       "3     Partly furnished               Capstone Property    The Pearl   \n",
       "4            Furnished              ABHome Real Estate     West Bay   \n",
       "...                ...                             ...          ...   \n",
       "6680       Unfurnished               Steps Real Estate    Al Duhail   \n",
       "6681       Unfurnished               Steps Real Estate   Ain Khaled   \n",
       "6682       Unfurnished               Steps Real Estate  Al Gharrafa   \n",
       "6685       Unfurnished                Future Business      Al Hilal   \n",
       "6686       Unfurnished  GOLDEN KEY LUXURY REAL ESTATE      Al Hilal   \n",
       "\n",
       "      Nr of amenities  ...  Private Jacuzzi  Private Pool  Security  \\\n",
       "0                   8  ...                0             0         1   \n",
       "1                   8  ...                0             0         1   \n",
       "2                   9  ...                0             0         1   \n",
       "3                  10  ...                0             0         1   \n",
       "4                  10  ...                0             0         1   \n",
       "...               ...  ...              ...           ...       ...   \n",
       "6680                1  ...                0             0         0   \n",
       "6681                2  ...                0             0         0   \n",
       "6682                5  ...                0             0         0   \n",
       "6685                5  ...                0             0         0   \n",
       "6686                5  ...                0             0         0   \n",
       "\n",
       "      Shared Gym  Shared Pool  Shared Spa  Study  View of Landmark  \\\n",
       "0              1            1           0      0                 0   \n",
       "1              1            1           0      0                 0   \n",
       "2              1            1           0      0                 0   \n",
       "3              1            1           0      0                 0   \n",
       "4              1            1           1      0                 0   \n",
       "...          ...          ...         ...    ...               ...   \n",
       "6680           0            0           0      0                 0   \n",
       "6681           0            0           0      0                 0   \n",
       "6682           0            0           0      0                 1   \n",
       "6685           0            0           0      0                 0   \n",
       "6686           0            0           0      0                 0   \n",
       "\n",
       "      View of Water  Walk-in Closet  \n",
       "0                 1               0  \n",
       "1                 1               0  \n",
       "2                 1               0  \n",
       "3                 1               0  \n",
       "4                 1               0  \n",
       "...             ...             ...  \n",
       "6680              0               0  \n",
       "6681              0               0  \n",
       "6682              0               0  \n",
       "6685              0               0  \n",
       "6686              0               0  \n",
       "\n",
       "[6580 rows x 37 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = pd.concat([outlier_clean, data], axis=1, sort=False)\n",
    "result = result[result['Value'].notna()]\n",
    "result = result[result['Size'].notna()]\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feature pairings: [(0, 1), (0, 2), (0, 3), (0, 4), (1, 2), (1, 3), (1, 4), (2, 3), (2, 4), (3, 4)]\n",
      "[[<matplotlib.axes._subplots.AxesSubplot object at 0x1a1a72ac90>\n",
      "  <matplotlib.axes._subplots.AxesSubplot object at 0x1a1a71df10>]\n",
      " [<matplotlib.axes._subplots.AxesSubplot object at 0x114ffe1d0>\n",
      "  <matplotlib.axes._subplots.AxesSubplot object at 0x1a1927a9d0>]\n",
      " [<matplotlib.axes._subplots.AxesSubplot object at 0x1a192bc210>\n",
      "  <matplotlib.axes._subplots.AxesSubplot object at 0x1a192eda10>]\n",
      " [<matplotlib.axes._subplots.AxesSubplot object at 0x1a1932f350>\n",
      "  <matplotlib.axes._subplots.AxesSubplot object at 0x1a19363b50>]\n",
      " [<matplotlib.axes._subplots.AxesSubplot object at 0x1a1939a750>\n",
      "  <matplotlib.axes._subplots.AxesSubplot object at 0x1a193cdf50>]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x1872 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# all subsets of size 2 in the feature set: all possible pairings of features\n",
    "possible_features = [feat for feat in dcols if feat in ['Value', 'Bathrooms', 'Bedrooms', 'Size', 'Nr of amenities']]\n",
    "feature_pairings = list(itertools.combinations(range(len(possible_features)), 2))\n",
    "print(\"Feature pairings:\", feature_pairings)\n",
    "\n",
    "# we'll show the plots in a matrix of three columns\n",
    "ncols = 2\n",
    "nrows = int(len(feature_pairings) // ncols)\n",
    "\n",
    "figure, subplots = plt.subplots(nrows, ncols, figsize=(16, 26))\n",
    "\n",
    "print(subplots)\n",
    "k = 0 # iterates over the feature pairings\n",
    "for i in range(nrows):\n",
    "    for j in range(ncols):\n",
    "        \n",
    "        feature_x = feature_pairings[k][0]\n",
    "        feature_y = feature_pairings[k][1]\n",
    "        k += 1\n",
    "\n",
    "        subplots[i][j].set_xlabel(possible_features[feature_x])\n",
    "        subplots[i][j].set_ylabel(possible_features[feature_y])\n",
    "\n",
    "        subplots[i][j].scatter(result[possible_features[feature_x]], \n",
    "                               result[possible_features[feature_y]],\n",
    "                               facecolors='blue', linewidths=0.20, s=10)\n",
    "    \n",
    "plt.subplots_adjust(left=None, bottom=None, right=None, \n",
    "                    top=None, wspace=0.5, hspace=0.35)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "nrows = 2\n",
    "ncols = 2\n",
    "figure, subplots = plt.subplots(nrows, ncols, figsize=(12, 6))\n",
    "\n",
    "titles = [\"Value\", \"Size\", \"Bedrooms\", \"Bathrooms\"]\n",
    "\n",
    "for i in range(nrows):\n",
    "    for j in range(ncols):\n",
    "        subplots[i, j].hist(result[titles[(2*i)+j]], bins=60)\n",
    "        subplots[i, j].set_xlabel(titles[(2*i)+j])\n",
    "        subplots[i, j].set_ylabel('nr of examples')\n",
    "        subplots[i, j].set_title(titles[(2*i)+j])\n",
    "       \n",
    "plt.subplots_adjust(left=None, bottom=None, right=None, \n",
    "                    top=None, wspace=0.5, hspace=0.35)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you see, the data without outliers seems better, so we will use this new data from now on."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = result"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Feature Engineering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Value                   float64\n",
       "Size                    float64\n",
       "Type                     object\n",
       "Reference                object\n",
       "Bedrooms                  int64\n",
       "Bathrooms                 int64\n",
       "Furnishing               object\n",
       "Agency                   object\n",
       "Location                 object\n",
       "Nr of amenities           int64\n",
       "Balcony                   int64\n",
       "Barbecue Area             int64\n",
       "Built in Wardrobes        int64\n",
       "Central A/C               int64\n",
       "Children's Play Area      int64\n",
       "Children's Pool           int64\n",
       "Concierge                 int64\n",
       "Covered Parking           int64\n",
       "Kitchen Appliances        int64\n",
       "Lobby in Building         int64\n",
       "MD Properties             int64\n",
       "Maid Service              int64\n",
       "Maids Room                int64\n",
       "Networked                 int64\n",
       "Pets Allowed              int64\n",
       "Private Garden            int64\n",
       "Private Gym               int64\n",
       "Private Jacuzzi           int64\n",
       "Private Pool              int64\n",
       "Security                  int64\n",
       "Shared Gym                int64\n",
       "Shared Pool               int64\n",
       "Shared Spa                int64\n",
       "Study                     int64\n",
       "View of Landmark          int64\n",
       "View of Water             int64\n",
       "Walk-in Closet            int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# A look at our data currently\n",
    "data.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our targets will be the **Value** feature, as this is the measure which relates to the answer of our *QuAM*."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "targets = data['Value']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We start by changing some features into category types.\n",
    "These are: *Type, Furnishing, Agency*, and *Location* and make a df excluding the targets and Reference."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>Size</th>\n",
       "      <th>Type</th>\n",
       "      <th>Bedrooms</th>\n",
       "      <th>Bathrooms</th>\n",
       "      <th>Furnishing</th>\n",
       "      <th>Agency</th>\n",
       "      <th>Location</th>\n",
       "      <th>Nr of amenities</th>\n",
       "      <th>Balcony</th>\n",
       "      <th>Barbecue Area</th>\n",
       "      <th>...</th>\n",
       "      <th>Private Jacuzzi</th>\n",
       "      <th>Private Pool</th>\n",
       "      <th>Security</th>\n",
       "      <th>Shared Gym</th>\n",
       "      <th>Shared Pool</th>\n",
       "      <th>Shared Spa</th>\n",
       "      <th>Study</th>\n",
       "      <th>View of Landmark</th>\n",
       "      <th>View of Water</th>\n",
       "      <th>Walk-in Closet</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Furnished</td>\n",
       "      <td>Capstone Property</td>\n",
       "      <td>The Pearl</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>62.0</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Furnished</td>\n",
       "      <td>Capstone Property</td>\n",
       "      <td>West Bay</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>60.0</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Furnished</td>\n",
       "      <td>Capstone Property</td>\n",
       "      <td>The Pearl</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>61.0</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Partly furnished</td>\n",
       "      <td>Capstone Property</td>\n",
       "      <td>The Pearl</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>60.0</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Furnished</td>\n",
       "      <td>ABHome Real Estate</td>\n",
       "      <td>West Bay</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\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",
       "      <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",
       "      <td>6680</td>\n",
       "      <td>700.0</td>\n",
       "      <td>Villa</td>\n",
       "      <td>9</td>\n",
       "      <td>7</td>\n",
       "      <td>Unfurnished</td>\n",
       "      <td>Steps Real Estate</td>\n",
       "      <td>Al Duhail</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6681</td>\n",
       "      <td>680.0</td>\n",
       "      <td>Villa</td>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>Unfurnished</td>\n",
       "      <td>Steps Real Estate</td>\n",
       "      <td>Ain Khaled</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6682</td>\n",
       "      <td>400.0</td>\n",
       "      <td>Villa</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>Unfurnished</td>\n",
       "      <td>Steps Real Estate</td>\n",
       "      <td>Al Gharrafa</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6685</td>\n",
       "      <td>375.0</td>\n",
       "      <td>Villa</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>Unfurnished</td>\n",
       "      <td>Future Business</td>\n",
       "      <td>Al Hilal</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6686</td>\n",
       "      <td>350.0</td>\n",
       "      <td>Villa</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>Unfurnished</td>\n",
       "      <td>GOLDEN KEY LUXURY REAL ESTATE</td>\n",
       "      <td>Al Hilal</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6580 rows × 35 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Size       Type  Bedrooms  Bathrooms        Furnishing  \\\n",
       "0      60.0  Apartment         1          1         Furnished   \n",
       "1      62.0  Apartment         1          1         Furnished   \n",
       "2      60.0  Apartment         1          1         Furnished   \n",
       "3      61.0  Apartment         1          1  Partly furnished   \n",
       "4      60.0  Apartment         1          1         Furnished   \n",
       "...     ...        ...       ...        ...               ...   \n",
       "6680  700.0      Villa         9          7       Unfurnished   \n",
       "6681  680.0      Villa         8          6       Unfurnished   \n",
       "6682  400.0      Villa         8          7       Unfurnished   \n",
       "6685  375.0      Villa         8          8       Unfurnished   \n",
       "6686  350.0      Villa         9          8       Unfurnished   \n",
       "\n",
       "                              Agency     Location  Nr of amenities  Balcony  \\\n",
       "0                  Capstone Property    The Pearl                8        0   \n",
       "1                  Capstone Property     West Bay                8        0   \n",
       "2                  Capstone Property    The Pearl                9        1   \n",
       "3                  Capstone Property    The Pearl               10        1   \n",
       "4                 ABHome Real Estate     West Bay               10        0   \n",
       "...                              ...          ...              ...      ...   \n",
       "6680               Steps Real Estate    Al Duhail                1        0   \n",
       "6681               Steps Real Estate   Ain Khaled                2        1   \n",
       "6682               Steps Real Estate  Al Gharrafa                5        1   \n",
       "6685                Future Business      Al Hilal                5        1   \n",
       "6686  GOLDEN KEY LUXURY REAL ESTATE      Al Hilal                5        1   \n",
       "\n",
       "      Barbecue Area  ...  Private Jacuzzi  Private Pool  Security  Shared Gym  \\\n",
       "0                 0  ...                0             0         1           1   \n",
       "1                 0  ...                0             0         1           1   \n",
       "2                 0  ...                0             0         1           1   \n",
       "3                 0  ...                0             0         1           1   \n",
       "4                 0  ...                0             0         1           1   \n",
       "...             ...  ...              ...           ...       ...         ...   \n",
       "6680              0  ...                0             0         0           0   \n",
       "6681              0  ...                0             0         0           0   \n",
       "6682              0  ...                0             0         0           0   \n",
       "6685              0  ...                0             0         0           0   \n",
       "6686              0  ...                0             0         0           0   \n",
       "\n",
       "      Shared Pool  Shared Spa  Study  View of Landmark  View of Water  \\\n",
       "0               1           0      0                 0              1   \n",
       "1               1           0      0                 0              1   \n",
       "2               1           0      0                 0              1   \n",
       "3               1           0      0                 0              1   \n",
       "4               1           1      0                 0              1   \n",
       "...           ...         ...    ...               ...            ...   \n",
       "6680            0           0      0                 0              0   \n",
       "6681            0           0      0                 0              0   \n",
       "6682            0           0      0                 1              0   \n",
       "6685            0           0      0                 0              0   \n",
       "6686            0           0      0                 0              0   \n",
       "\n",
       "      Walk-in Closet  \n",
       "0                  0  \n",
       "1                  0  \n",
       "2                  0  \n",
       "3                  0  \n",
       "4                  0  \n",
       "...              ...  \n",
       "6680               0  \n",
       "6681               0  \n",
       "6682               0  \n",
       "6685               0  \n",
       "6686               0  \n",
       "\n",
       "[6580 rows x 35 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = data.astype( {'Type':'category', 'Furnishing':'category', \n",
    "                   'Agency':'category', 'Location':'category'})\n",
    "features = data.drop(['Value', 'Reference'], 1)\n",
    "features"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Numerical features\n",
    "We want to select the features most relevant to our question, and disregard those that are redundant. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1a00ba90>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x1296 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sn\n",
    "plt.figure(figsize = (18,18))\n",
    "correlation_matrix = data.corr()\n",
    "plt.ylim(data.shape[1]+1,0)\n",
    "# plt.text(j, i, format(cm[i, j], '.1f'),\n",
    "# annot = True to print the values inside the square\n",
    "sn.heatmap(data=correlation_matrix, annot=True, fmt='.1g')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our first remark is that there are many features that have very little correlation with the target, therefore we decide to only keep features who's correlation with the target is above a certain threshold of: 0.2 - we know that this threshold is low but we believe that the combination of these features actually have a proper target correlation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, 3, 4, 5, 7, 17, 20]\n"
     ]
    }
   ],
   "source": [
    "import math\n",
    "#Loop through features, calculate the correlation coefficient with target and keep if >0.2\n",
    "good_features = []\n",
    "\n",
    "corr = data.corr().iloc[1:,0]\n",
    "index = 1\n",
    "for c in corr:\n",
    "    if math.fabs(c) > 0.2:\n",
    "        good_features.append(index)\n",
    "    index += 1\n",
    "print(good_features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "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>Size</th>\n",
       "      <th>Bedrooms</th>\n",
       "      <th>Bathrooms</th>\n",
       "      <th>Nr of amenities</th>\n",
       "      <th>Balcony</th>\n",
       "      <th>Built in Wardrobes</th>\n",
       "      <th>Maids Room</th>\n",
       "      <th>Private Garden</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>62.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>60.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>61.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>60.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\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",
       "      <td>6680</td>\n",
       "      <td>700.0</td>\n",
       "      <td>9</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6681</td>\n",
       "      <td>680.0</td>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6682</td>\n",
       "      <td>400.0</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6685</td>\n",
       "      <td>375.0</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6686</td>\n",
       "      <td>350.0</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6580 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Size  Bedrooms  Bathrooms  Nr of amenities  Balcony  \\\n",
       "0      60.0         1          1                8        0   \n",
       "1      62.0         1          1                8        0   \n",
       "2      60.0         1          1                9        1   \n",
       "3      61.0         1          1               10        1   \n",
       "4      60.0         1          1               10        0   \n",
       "...     ...       ...        ...              ...      ...   \n",
       "6680  700.0         9          7                1        0   \n",
       "6681  680.0         8          6                2        1   \n",
       "6682  400.0         8          7                5        1   \n",
       "6685  375.0         8          8                5        1   \n",
       "6686  350.0         9          8                5        1   \n",
       "\n",
       "      Built in Wardrobes  Maids Room  Private Garden  \n",
       "0                      0           0               0  \n",
       "1                      0           0               0  \n",
       "2                      0           0               0  \n",
       "3                      1           0               0  \n",
       "4                      1           0               0  \n",
       "...                  ...         ...             ...  \n",
       "6680                   0           1               0  \n",
       "6681                   0           0               0  \n",
       "6682                   1           1               0  \n",
       "6685                   0           1               1  \n",
       "6686                   0           1               1  \n",
       "\n",
       "[6580 rows x 8 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numerics = ['int16', 'int32', 'int64', 'float16', 'float32', 'float64']\n",
    "numeric_data = data.select_dtypes(include=numerics)\n",
    "\n",
    "main_num_features = numeric_data.iloc[:,good_features]\n",
    "main_num_features"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Categorical features\n",
    "We have now extracted the important numeric features, so the next step is to binarize the categorical features in order to be able to carry out the rest of the tests on them. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Type', 'Furnishing', 'Location'], dtype='object') \n",
      "\n"
     ]
    },
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Type_Apartment</th>\n",
       "      <th>Type_Compound</th>\n",
       "      <th>Type_Duplex</th>\n",
       "      <th>Type_Hotel Apartments</th>\n",
       "      <th>Type_Penthouse</th>\n",
       "      <th>Type_Townhouse</th>\n",
       "      <th>Type_Villa</th>\n",
       "      <th>Furnishing_Furnished</th>\n",
       "      <th>Furnishing_Partly furnished</th>\n",
       "      <th>Furnishing_Unfurnished</th>\n",
       "      <th>...</th>\n",
       "      <th>Location_Salata</th>\n",
       "      <th>Location_Salwa Road</th>\n",
       "      <th>Location_The Pearl</th>\n",
       "      <th>Location_Umm Al Seneem</th>\n",
       "      <th>Location_Umm Ghuwailina</th>\n",
       "      <th>Location_Umm Salal Ali</th>\n",
       "      <th>Location_Umm Salal Mohammad</th>\n",
       "      <th>Location_Wadi Al Sail</th>\n",
       "      <th>Location_West Bay</th>\n",
       "      <th>Location_West Bay Lagoon</th>\n",
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       "      <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",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>6680</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>6681</td>\n",
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       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <td>6682</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <td>6686</td>\n",
       "      <td>0</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6580 rows × 80 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Type_Apartment  Type_Compound  Type_Duplex  Type_Hotel Apartments  \\\n",
       "0                  1              0            0                      0   \n",
       "1                  1              0            0                      0   \n",
       "2                  1              0            0                      0   \n",
       "3                  1              0            0                      0   \n",
       "4                  1              0            0                      0   \n",
       "...              ...            ...          ...                    ...   \n",
       "6680               0              0            0                      0   \n",
       "6681               0              0            0                      0   \n",
       "6682               0              0            0                      0   \n",
       "6685               0              0            0                      0   \n",
       "6686               0              0            0                      0   \n",
       "\n",
       "      Type_Penthouse  Type_Townhouse  Type_Villa  Furnishing_Furnished  \\\n",
       "0                  0               0           0                     1   \n",
       "1                  0               0           0                     1   \n",
       "2                  0               0           0                     1   \n",
       "3                  0               0           0                     0   \n",
       "4                  0               0           0                     1   \n",
       "...              ...             ...         ...                   ...   \n",
       "6680               0               0           1                     0   \n",
       "6681               0               0           1                     0   \n",
       "6682               0               0           1                     0   \n",
       "6685               0               0           1                     0   \n",
       "6686               0               0           1                     0   \n",
       "\n",
       "      Furnishing_Partly furnished  Furnishing_Unfurnished  ...  \\\n",
       "0                               0                       0  ...   \n",
       "1                               0                       0  ...   \n",
       "2                               0                       0  ...   \n",
       "3                               1                       0  ...   \n",
       "4                               0                       0  ...   \n",
       "...                           ...                     ...  ...   \n",
       "6680                            0                       1  ...   \n",
       "6681                            0                       1  ...   \n",
       "6682                            0                       1  ...   \n",
       "6685                            0                       1  ...   \n",
       "6686                            0                       1  ...   \n",
       "\n",
       "      Location_Salata  Location_Salwa Road  Location_The Pearl  \\\n",
       "0                   0                    0                   1   \n",
       "1                   0                    0                   0   \n",
       "2                   0                    0                   1   \n",
       "3                   0                    0                   1   \n",
       "4                   0                    0                   0   \n",
       "...               ...                  ...                 ...   \n",
       "6680                0                    0                   0   \n",
       "6681                0                    0                   0   \n",
       "6682                0                    0                   0   \n",
       "6685                0                    0                   0   \n",
       "6686                0                    0                   0   \n",
       "\n",
       "      Location_Umm Al Seneem  Location_Umm Ghuwailina  Location_Umm Salal Ali  \\\n",
       "0                          0                        0                       0   \n",
       "1                          0                        0                       0   \n",
       "2                          0                        0                       0   \n",
       "3                          0                        0                       0   \n",
       "4                          0                        0                       0   \n",
       "...                      ...                      ...                     ...   \n",
       "6680                       0                        0                       0   \n",
       "6681                       0                        0                       0   \n",
       "6682                       0                        0                       0   \n",
       "6685                       0                        0                       0   \n",
       "6686                       0                        0                       0   \n",
       "\n",
       "      Location_Umm Salal Mohammad  Location_Wadi Al Sail  Location_West Bay  \\\n",
       "0                               0                      0                  0   \n",
       "1                               0                      0                  1   \n",
       "2                               0                      0                  0   \n",
       "3                               0                      0                  0   \n",
       "4                               0                      0                  1   \n",
       "...                           ...                    ...                ...   \n",
       "6680                            0                      0                  0   \n",
       "6681                            0                      0                  0   \n",
       "6682                            0                      0                  0   \n",
       "6685                            0                      0                  0   \n",
       "6686                            0                      0                  0   \n",
       "\n",
       "      Location_West Bay Lagoon  \n",
       "0                            0  \n",
       "1                            0  \n",
       "2                            0  \n",
       "3                            0  \n",
       "4                            0  \n",
       "...                        ...  \n",
       "6680                         0  \n",
       "6681                         0  \n",
       "6682                         0  \n",
       "6685                         0  \n",
       "6686                         0  \n",
       "\n",
       "[6580 rows x 80 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# First, we drop the Agency column as it carries little relevant information to the question at hand\n",
    "features = features.drop('Agency', axis=1)\n",
    "\n",
    "# Next, we carry out the binarization\n",
    "category_features = features.select_dtypes(include='category')\n",
    "print(category_features.columns, '\\n')\n",
    "main_category_features = pd.get_dummies(category_features)\n",
    "main_category_features"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we have all our important features sorted out, we combine them into one feature dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Size</th>\n",
       "      <th>Bedrooms</th>\n",
       "      <th>Bathrooms</th>\n",
       "      <th>Nr of amenities</th>\n",
       "      <th>Balcony</th>\n",
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       "      <th>Location_Umm Ghuwailina</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
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       "      <td>count</td>\n",
       "      <td>6580.000000</td>\n",
       "      <td>6580.000000</td>\n",
       "      <td>6580.000000</td>\n",
       "      <td>6580.000000</td>\n",
       "      <td>6580.000000</td>\n",
       "      <td>6580.000000</td>\n",
       "      <td>6580.00000</td>\n",
       "      <td>6580.000000</td>\n",
       "      <td>6580.000000</td>\n",
       "      <td>6580.000000</td>\n",
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       "      <td>6580.000000</td>\n",
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       "      <td>6580.000000</td>\n",
       "      <td>6580.000000</td>\n",
       "      <td>6580.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>mean</td>\n",
       "      <td>184.125380</td>\n",
       "      <td>2.564134</td>\n",
       "      <td>2.756839</td>\n",
       "      <td>7.201216</td>\n",
       "      <td>0.511246</td>\n",
       "      <td>0.599696</td>\n",
       "      <td>0.19772</td>\n",
       "      <td>0.078267</td>\n",
       "      <td>0.718541</td>\n",
       "      <td>0.084498</td>\n",
       "      <td>...</td>\n",
       "      <td>0.005623</td>\n",
       "      <td>0.001216</td>\n",
       "      <td>0.383131</td>\n",
       "      <td>0.000152</td>\n",
       "      <td>0.012006</td>\n",
       "      <td>0.002432</td>\n",
       "      <td>0.019149</td>\n",
       "      <td>0.000152</td>\n",
       "      <td>0.086474</td>\n",
       "      <td>0.020517</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>std</td>\n",
       "      <td>127.516507</td>\n",
       "      <td>1.565994</td>\n",
       "      <td>1.413942</td>\n",
       "      <td>3.638088</td>\n",
       "      <td>0.499911</td>\n",
       "      <td>0.489997</td>\n",
       "      <td>0.39831</td>\n",
       "      <td>0.268612</td>\n",
       "      <td>0.449745</td>\n",
       "      <td>0.278155</td>\n",
       "      <td>...</td>\n",
       "      <td>0.074782</td>\n",
       "      <td>0.034850</td>\n",
       "      <td>0.486187</td>\n",
       "      <td>0.012328</td>\n",
       "      <td>0.108921</td>\n",
       "      <td>0.049255</td>\n",
       "      <td>0.137059</td>\n",
       "      <td>0.012328</td>\n",
       "      <td>0.281084</td>\n",
       "      <td>0.141770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>min</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25%</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50%</td>\n",
       "      <td>140.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75%</td>\n",
       "      <td>232.250000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>max</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 88 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Size     Bedrooms    Bathrooms  Nr of amenities      Balcony  \\\n",
       "count  6580.000000  6580.000000  6580.000000      6580.000000  6580.000000   \n",
       "mean    184.125380     2.564134     2.756839         7.201216     0.511246   \n",
       "std     127.516507     1.565994     1.413942         3.638088     0.499911   \n",
       "min       1.000000     1.000000     1.000000         1.000000     0.000000   \n",
       "25%     100.000000     1.000000     2.000000         4.000000     0.000000   \n",
       "50%     140.000000     2.000000     2.000000         7.000000     1.000000   \n",
       "75%     232.250000     3.000000     3.000000        10.000000     1.000000   \n",
       "max    1000.000000     9.000000     8.000000        24.000000     1.000000   \n",
       "\n",
       "       Built in Wardrobes  Maids Room  Private Garden  Type_Apartment  \\\n",
       "count         6580.000000  6580.00000     6580.000000     6580.000000   \n",
       "mean             0.599696     0.19772        0.078267        0.718541   \n",
       "std              0.489997     0.39831        0.268612        0.449745   \n",
       "min              0.000000     0.00000        0.000000        0.000000   \n",
       "25%              0.000000     0.00000        0.000000        0.000000   \n",
       "50%              1.000000     0.00000        0.000000        1.000000   \n",
       "75%              1.000000     0.00000        0.000000        1.000000   \n",
       "max              1.000000     1.00000        1.000000        1.000000   \n",
       "\n",
       "       Type_Compound  ...  Location_Salata  Location_Salwa Road  \\\n",
       "count    6580.000000  ...      6580.000000          6580.000000   \n",
       "mean        0.084498  ...         0.005623             0.001216   \n",
       "std         0.278155  ...         0.074782             0.034850   \n",
       "min         0.000000  ...         0.000000             0.000000   \n",
       "25%         0.000000  ...         0.000000             0.000000   \n",
       "50%         0.000000  ...         0.000000             0.000000   \n",
       "75%         0.000000  ...         0.000000             0.000000   \n",
       "max         1.000000  ...         1.000000             1.000000   \n",
       "\n",
       "       Location_The Pearl  Location_Umm Al Seneem  Location_Umm Ghuwailina  \\\n",
       "count         6580.000000             6580.000000              6580.000000   \n",
       "mean             0.383131                0.000152                 0.012006   \n",
       "std              0.486187                0.012328                 0.108921   \n",
       "min              0.000000                0.000000                 0.000000   \n",
       "25%              0.000000                0.000000                 0.000000   \n",
       "50%              0.000000                0.000000                 0.000000   \n",
       "75%              1.000000                0.000000                 0.000000   \n",
       "max              1.000000                1.000000                 1.000000   \n",
       "\n",
       "       Location_Umm Salal Ali  Location_Umm Salal Mohammad  \\\n",
       "count             6580.000000                  6580.000000   \n",
       "mean                 0.002432                     0.019149   \n",
       "std                  0.049255                     0.137059   \n",
       "min                  0.000000                     0.000000   \n",
       "25%                  0.000000                     0.000000   \n",
       "50%                  0.000000                     0.000000   \n",
       "75%                  0.000000                     0.000000   \n",
       "max                  1.000000                     1.000000   \n",
       "\n",
       "       Location_Wadi Al Sail  Location_West Bay  Location_West Bay Lagoon  \n",
       "count            6580.000000        6580.000000               6580.000000  \n",
       "mean                0.000152           0.086474                  0.020517  \n",
       "std                 0.012328           0.281084                  0.141770  \n",
       "min                 0.000000           0.000000                  0.000000  \n",
       "25%                 0.000000           0.000000                  0.000000  \n",
       "50%                 0.000000           0.000000                  0.000000  \n",
       "75%                 0.000000           0.000000                  0.000000  \n",
       "max                 1.000000           1.000000                  1.000000  \n",
       "\n",
       "[8 rows x 88 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "main_features = pd.concat([main_num_features, main_category_features],axis=1)\n",
    "main_features.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As a final step, we merge these features with our targets and create a new csv file containing our cleaned data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_clean = pd.concat([main_features, targets],axis=1)\n",
    "\n",
    "data_clean.to_csv('data_clean.csv', index=False)"
   ]
  }
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