HDB_Linear_Regression_EDA.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#dataset: https://data.gov.sg/dataset/resale-flat-prices (hdb resale)\n",
    "#dataset: https://data.gov.sg/dataset/private-residential-property-price-index-by-type-of-property?view_id=a2f1ffe8-e7b1-4fbb-8c41-c6a26e0456d4&resource_id=947b5cbe-0b0a-4fdb-b06e-aca1e34d87fd (private property)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import python libraries\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "sns.set_theme()\n",
    "plt.rcParams['figure.figsize']=[10,8]\n",
    "import datetime\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>month</th>\n",
       "      <th>town</th>\n",
       "      <th>flat_type</th>\n",
       "      <th>block</th>\n",
       "      <th>street_name</th>\n",
       "      <th>storey_range</th>\n",
       "      <th>floor_area_sqm</th>\n",
       "      <th>flat_model</th>\n",
       "      <th>lease_commence_date</th>\n",
       "      <th>resale_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1990-01</td>\n",
       "      <td>ANG MO KIO</td>\n",
       "      <td>1 ROOM</td>\n",
       "      <td>309</td>\n",
       "      <td>ANG MO KIO AVE 1</td>\n",
       "      <td>10 TO 12</td>\n",
       "      <td>31.0</td>\n",
       "      <td>IMPROVED</td>\n",
       "      <td>1977</td>\n",
       "      <td>9000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1990-01</td>\n",
       "      <td>ANG MO KIO</td>\n",
       "      <td>1 ROOM</td>\n",
       "      <td>309</td>\n",
       "      <td>ANG MO KIO AVE 1</td>\n",
       "      <td>04 TO 06</td>\n",
       "      <td>31.0</td>\n",
       "      <td>IMPROVED</td>\n",
       "      <td>1977</td>\n",
       "      <td>6000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     month        town flat_type block       street_name storey_range  \\\n",
       "0  1990-01  ANG MO KIO    1 ROOM   309  ANG MO KIO AVE 1     10 TO 12   \n",
       "1  1990-01  ANG MO KIO    1 ROOM   309  ANG MO KIO AVE 1     04 TO 06   \n",
       "\n",
       "   floor_area_sqm flat_model  lease_commence_date  resale_price  \n",
       "0            31.0   IMPROVED                 1977          9000  \n",
       "1            31.0   IMPROVED                 1977          6000  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#load and read csv files\n",
    "\n",
    "yr1999 = pd.read_csv('resale-flat-prices-based-on-approval-date-1990-1999.csv')\n",
    "yr2012=pd.read_csv('resale-flat-prices-based-on-approval-date-2000-feb-2012.csv')\n",
    "yr2016=pd.read_csv('resale-flat-prices-based-on-registration-date-from-jan-2015-to-dec-2016.csv')\n",
    "yr2021=pd.read_csv('resale-flat-prices-based-on-registration-date-from-jan-2017-onwards.csv')\n",
    "yr2014=pd.read_csv('resale-flat-prices-based-on-registration-date-from-mar-2012-to-dec-2014.csv')\n",
    "yr1999.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# drop 'remaining_lease' column from yr2016 & yr2021 dataframes\n",
    "\n",
    "col =['remaining_lease']\n",
    "file_list = [yr2016,yr2021]\n",
    "for w in file_list:\n",
    "    for i in col:\n",
    "        w.drop(i,axis='columns',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# drop 'block', 'street_name', 'flat_model' and 'storey_range' columns from all dataframes (df : yr2021)\n",
    "\n",
    "col =['block','street_name','flat_model','storey_range']\n",
    "file_list = [yr1999,yr2012,yr2014,yr2016,yr2021]\n",
    "for w in file_list:\n",
    "    for i in col:\n",
    "        w.drop(i,axis='columns',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "#concatenate into 5 dataframes (yr1999 : yr2021) into 1 dataframe yr_combine\n",
    "\n",
    "file_list = [yr1999,yr2012,yr2014,yr2016,yr2021]\n",
    "yr_combine = pd.concat(file_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>month</th>\n",
       "      <th>town</th>\n",
       "      <th>flat_type</th>\n",
       "      <th>floor_area_sqm</th>\n",
       "      <th>lease_commence_date</th>\n",
       "      <th>resale_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1990-01</td>\n",
       "      <td>ANG MO KIO</td>\n",
       "      <td>1 ROOM</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1977</td>\n",
       "      <td>9000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1990-01</td>\n",
       "      <td>ANG MO KIO</td>\n",
       "      <td>1 ROOM</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1977</td>\n",
       "      <td>6000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1990-01</td>\n",
       "      <td>ANG MO KIO</td>\n",
       "      <td>1 ROOM</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1977</td>\n",
       "      <td>8000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1990-01</td>\n",
       "      <td>ANG MO KIO</td>\n",
       "      <td>1 ROOM</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1977</td>\n",
       "      <td>6000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1990-01</td>\n",
       "      <td>ANG MO KIO</td>\n",
       "      <td>3 ROOM</td>\n",
       "      <td>73.0</td>\n",
       "      <td>1976</td>\n",
       "      <td>47200.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     month        town flat_type  floor_area_sqm  lease_commence_date  \\\n",
       "0  1990-01  ANG MO KIO    1 ROOM            31.0                 1977   \n",
       "1  1990-01  ANG MO KIO    1 ROOM            31.0                 1977   \n",
       "2  1990-01  ANG MO KIO    1 ROOM            31.0                 1977   \n",
       "3  1990-01  ANG MO KIO    1 ROOM            31.0                 1977   \n",
       "4  1990-01  ANG MO KIO    3 ROOM            73.0                 1976   \n",
       "\n",
       "   resale_price  \n",
       "0        9000.0  \n",
       "1        6000.0  \n",
       "2        8000.0  \n",
       "3        6000.0  \n",
       "4       47200.0  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# review yr_combine dataframe 1st 5 rows\n",
    "\n",
    "yr_combine.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#convert 'lease_commence_date' to datetime format\n",
    "\n",
    "from datetime import datetime\n",
    "\n",
    "date_format=[]\n",
    "date_list = yr_combine['lease_commence_date'].astype(str).values.tolist()\n",
    "for j in date_list:\n",
    "    date_obj = datetime.strptime(j, '%Y')\n",
    "    date_format.append(date_obj)\n",
    "yr_combine['lease_commence_date']=date_format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "#convert month to datetime format and assign to new column 'month_dt'\n",
    "\n",
    "from datetime import datetime\n",
    "\n",
    "date_format=[]\n",
    "date_list = yr_combine['month'].astype(str).values.tolist()\n",
    "for i in date_list:\n",
    "    date_obj = datetime.strptime(i, '%Y-%m')\n",
    "    date_format.append(date_obj)\n",
    "yr_combine['month_dt']=date_format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# compute days expired by subtracting 'month_dt' by 'lease_commence_date'.  This will give you the age of the flat.\n",
    "\n",
    "yr_combine['days_expired'] = yr_combine['month_dt']-yr_combine['lease_commence_date']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# compute remaining_lease by converting 'days_expired' into integer in years, subtracting it from 99 years.\n",
    "\n",
    "yr_combine['remaining_lease'] = (99-((pd.to_numeric(yr_combine['days_expired'].dt.days, downcast='integer'))/365)).round(decimals=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# convert 'month' format to integer, removing the month part of the string to become 'yyyy'\n",
    "\n",
    "yr_combine['month']= [int(i[:-3]) for i in yr_combine['month']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "#replace flat_type value of 'MULTI-GENERATION' and 'MULTI GENERATION' to 'MULTI_GENERATION'. \n",
    "\n",
    "yr_combine['flat_type'].replace('MULTI-GENERATION','MULTI_GENERATION',inplace=True)\n",
    "yr_combine['flat_type'].replace('MULTI GENERATION','MULTI_GENERATION',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>town</th>\n",
       "      <th>flat_type</th>\n",
       "      <th>floor_area_sqm</th>\n",
       "      <th>lease_commence_date</th>\n",
       "      <th>resale_price</th>\n",
       "      <th>month_dt</th>\n",
       "      <th>days_expired</th>\n",
       "      <th>remaining_lease</th>\n",
       "      <th>price_per_sqm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1990</td>\n",
       "      <td>ANG MO KIO</td>\n",
       "      <td>1 ROOM</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1977-01-01</td>\n",
       "      <td>9000.0</td>\n",
       "      <td>1990-01-01</td>\n",
       "      <td>4748 days</td>\n",
       "      <td>86.0</td>\n",
       "      <td>290.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1990</td>\n",
       "      <td>ANG MO KIO</td>\n",
       "      <td>1 ROOM</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1977-01-01</td>\n",
       "      <td>6000.0</td>\n",
       "      <td>1990-01-01</td>\n",
       "      <td>4748 days</td>\n",
       "      <td>86.0</td>\n",
       "      <td>194.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1990</td>\n",
       "      <td>ANG MO KIO</td>\n",
       "      <td>1 ROOM</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1977-01-01</td>\n",
       "      <td>8000.0</td>\n",
       "      <td>1990-01-01</td>\n",
       "      <td>4748 days</td>\n",
       "      <td>86.0</td>\n",
       "      <td>258.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1990</td>\n",
       "      <td>ANG MO KIO</td>\n",
       "      <td>1 ROOM</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1977-01-01</td>\n",
       "      <td>6000.0</td>\n",
       "      <td>1990-01-01</td>\n",
       "      <td>4748 days</td>\n",
       "      <td>86.0</td>\n",
       "      <td>194.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1990</td>\n",
       "      <td>ANG MO KIO</td>\n",
       "      <td>3 ROOM</td>\n",
       "      <td>73.0</td>\n",
       "      <td>1976-01-01</td>\n",
       "      <td>47200.0</td>\n",
       "      <td>1990-01-01</td>\n",
       "      <td>5114 days</td>\n",
       "      <td>85.0</td>\n",
       "      <td>647.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year        town flat_type  floor_area_sqm lease_commence_date  \\\n",
       "0  1990  ANG MO KIO    1 ROOM            31.0          1977-01-01   \n",
       "1  1990  ANG MO KIO    1 ROOM            31.0          1977-01-01   \n",
       "2  1990  ANG MO KIO    1 ROOM            31.0          1977-01-01   \n",
       "3  1990  ANG MO KIO    1 ROOM            31.0          1977-01-01   \n",
       "4  1990  ANG MO KIO    3 ROOM            73.0          1976-01-01   \n",
       "\n",
       "   resale_price   month_dt days_expired  remaining_lease  price_per_sqm  \n",
       "0        9000.0 1990-01-01    4748 days             86.0          290.0  \n",
       "1        6000.0 1990-01-01    4748 days             86.0          194.0  \n",
       "2        8000.0 1990-01-01    4748 days             86.0          258.0  \n",
       "3        6000.0 1990-01-01    4748 days             86.0          194.0  \n",
       "4       47200.0 1990-01-01    5114 days             85.0          647.0  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#create a new column \"price_per_sqm\"\n",
    "#rename column name 'month' to 'year'\n",
    "\n",
    "\n",
    "yr_combine['price_per_sqm']=round(yr_combine['resale_price']/yr_combine['floor_area_sqm'],0)\n",
    "yr_combine.rename(columns={'month':'year'}, inplace=True)\n",
    "yr_combine.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>year</th>\n",
       "      <th>town</th>\n",
       "      <th>flat_type</th>\n",
       "      <th>floor_area_sqm</th>\n",
       "      <th>lease_commence_date</th>\n",
       "      <th>resale_price</th>\n",
       "      <th>month_dt</th>\n",
       "      <th>days_expired</th>\n",
       "      <th>remaining_lease</th>\n",
       "      <th>price_per_sqm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>87591</th>\n",
       "      <td>2021</td>\n",
       "      <td>ANG MO KIO</td>\n",
       "      <td>2 ROOM</td>\n",
       "      <td>44.0</td>\n",
       "      <td>1978-01-01</td>\n",
       "      <td>218000.0</td>\n",
       "      <td>2021-04-01</td>\n",
       "      <td>15796 days</td>\n",
       "      <td>56.0</td>\n",
       "      <td>4955.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87592</th>\n",
       "      <td>2021</td>\n",
       "      <td>ANG MO KIO</td>\n",
       "      <td>2 ROOM</td>\n",
       "      <td>45.0</td>\n",
       "      <td>1986-01-01</td>\n",
       "      <td>225000.0</td>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>12784 days</td>\n",
       "      <td>64.0</td>\n",
       "      <td>5000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87593</th>\n",
       "      <td>2021</td>\n",
       "      <td>ANG MO KIO</td>\n",
       "      <td>2 ROOM</td>\n",
       "      <td>45.0</td>\n",
       "      <td>1986-01-01</td>\n",
       "      <td>211000.0</td>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>12784 days</td>\n",
       "      <td>64.0</td>\n",
       "      <td>4689.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87594</th>\n",
       "      <td>2021</td>\n",
       "      <td>ANG MO KIO</td>\n",
       "      <td>2 ROOM</td>\n",
       "      <td>45.0</td>\n",
       "      <td>1986-01-01</td>\n",
       "      <td>208500.0</td>\n",
       "      <td>2021-04-01</td>\n",
       "      <td>12874 days</td>\n",
       "      <td>64.0</td>\n",
       "      <td>4633.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87595</th>\n",
       "      <td>2021</td>\n",
       "      <td>ANG MO KIO</td>\n",
       "      <td>2 ROOM</td>\n",
       "      <td>44.0</td>\n",
       "      <td>1978-01-01</td>\n",
       "      <td>230000.0</td>\n",
       "      <td>2021-05-01</td>\n",
       "      <td>15826 days</td>\n",
       "      <td>56.0</td>\n",
       "      <td>5227.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       year        town flat_type  floor_area_sqm lease_commence_date  \\\n",
       "87591  2021  ANG MO KIO    2 ROOM            44.0          1978-01-01   \n",
       "87592  2021  ANG MO KIO    2 ROOM            45.0          1986-01-01   \n",
       "87593  2021  ANG MO KIO    2 ROOM            45.0          1986-01-01   \n",
       "87594  2021  ANG MO KIO    2 ROOM            45.0          1986-01-01   \n",
       "87595  2021  ANG MO KIO    2 ROOM            44.0          1978-01-01   \n",
       "\n",
       "       resale_price   month_dt days_expired  remaining_lease  price_per_sqm  \n",
       "87591      218000.0 2021-04-01   15796 days             56.0         4955.0  \n",
       "87592      225000.0 2021-01-01   12784 days             64.0         5000.0  \n",
       "87593      211000.0 2021-01-01   12784 days             64.0         4689.0  \n",
       "87594      208500.0 2021-04-01   12874 days             64.0         4633.0  \n",
       "87595      230000.0 2021-05-01   15826 days             56.0         5227.0  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "yr_grt2020 = yr_combine[yr_combine['year']>2020]\n",
    "yr_grt2020.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Which location should I consider?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# sort locations based on number of transactions\n",
    "\n",
    "yr_grt2020_trans = yr_grt2020.town.value_counts().reset_index().rename(columns={'index':'Location','town':'Transactions'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# compute the towns with the most transactions using barplot\n",
    "\n",
    "sns.barplot(data=yr_grt2020_trans, y='Location', x='Transactions');\n",
    "plt.title('Number of Transactions According to Location (2021)', fontsize=17)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Would you like to consider 4 rooms in the east part of island?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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>year</th>\n",
       "      <th>town</th>\n",
       "      <th>flat_type</th>\n",
       "      <th>floor_area_sqm</th>\n",
       "      <th>lease_commence_date</th>\n",
       "      <th>resale_price</th>\n",
       "      <th>month_dt</th>\n",
       "      <th>days_expired</th>\n",
       "      <th>remaining_lease</th>\n",
       "      <th>price_per_sqm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>97516</th>\n",
       "      <td>2021</td>\n",
       "      <td>TAMPINES</td>\n",
       "      <td>4 ROOM</td>\n",
       "      <td>94.0</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>680000.0</td>\n",
       "      <td>2021-02-01</td>\n",
       "      <td>3684 days</td>\n",
       "      <td>89.0</td>\n",
       "      <td>7234.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97517</th>\n",
       "      <td>2021</td>\n",
       "      <td>TAMPINES</td>\n",
       "      <td>4 ROOM</td>\n",
       "      <td>94.0</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>670000.0</td>\n",
       "      <td>2021-04-01</td>\n",
       "      <td>3743 days</td>\n",
       "      <td>89.0</td>\n",
       "      <td>7128.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97518</th>\n",
       "      <td>2021</td>\n",
       "      <td>TAMPINES</td>\n",
       "      <td>4 ROOM</td>\n",
       "      <td>94.0</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>660000.0</td>\n",
       "      <td>2021-04-01</td>\n",
       "      <td>3743 days</td>\n",
       "      <td>89.0</td>\n",
       "      <td>7021.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97519</th>\n",
       "      <td>2021</td>\n",
       "      <td>TAMPINES</td>\n",
       "      <td>4 ROOM</td>\n",
       "      <td>94.0</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>658000.0</td>\n",
       "      <td>2021-04-01</td>\n",
       "      <td>3743 days</td>\n",
       "      <td>89.0</td>\n",
       "      <td>7000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97520</th>\n",
       "      <td>2021</td>\n",
       "      <td>TAMPINES</td>\n",
       "      <td>4 ROOM</td>\n",
       "      <td>94.0</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>669000.0</td>\n",
       "      <td>2021-05-01</td>\n",
       "      <td>3773 days</td>\n",
       "      <td>89.0</td>\n",
       "      <td>7117.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       year      town flat_type  floor_area_sqm lease_commence_date  \\\n",
       "97516  2021  TAMPINES    4 ROOM            94.0          2011-01-01   \n",
       "97517  2021  TAMPINES    4 ROOM            94.0          2011-01-01   \n",
       "97518  2021  TAMPINES    4 ROOM            94.0          2011-01-01   \n",
       "97519  2021  TAMPINES    4 ROOM            94.0          2011-01-01   \n",
       "97520  2021  TAMPINES    4 ROOM            94.0          2011-01-01   \n",
       "\n",
       "       resale_price   month_dt days_expired  remaining_lease  price_per_sqm  \n",
       "97516      680000.0 2021-02-01    3684 days             89.0         7234.0  \n",
       "97517      670000.0 2021-04-01    3743 days             89.0         7128.0  \n",
       "97518      660000.0 2021-04-01    3743 days             89.0         7021.0  \n",
       "97519      658000.0 2021-04-01    3743 days             89.0         7000.0  \n",
       "97520      669000.0 2021-05-01    3773 days             89.0         7117.0  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# compute resale prices for 4 rooms for 5 locations in the East\n",
    "\n",
    "town = ['TAMPINES', 'BEDOK', 'MARINE PARADE', 'PASIR RIS','PUNGGOL']\n",
    "east_4rm=[]\n",
    "for i in town:\n",
    "    x = yr_grt2020.loc[(yr_grt2020['town']==i) & (yr_grt2020['flat_type']=='4 ROOM')] \n",
    "    east_4rm.append(x)\n",
    "east_4rm = pd.concat(east_4rm)\n",
    "east_4rm.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "east_4rm.groupby('town')['resale_price'].mean().sort_values().plot.bar();\n",
    "plt.xlabel('Location', fontsize=15);\n",
    "plt.ylabel('Resale Price', fontsize=15);\n",
    "plt.title('Mean Resale Price for 4 room flat In The East', fontsize=17);\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### May be with close to a sum of 500k, I can get a 5 room flat somewhere up north?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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>year</th>\n",
       "      <th>town</th>\n",
       "      <th>flat_type</th>\n",
       "      <th>floor_area_sqm</th>\n",
       "      <th>lease_commence_date</th>\n",
       "      <th>resale_price</th>\n",
       "      <th>month_dt</th>\n",
       "      <th>days_expired</th>\n",
       "      <th>remaining_lease</th>\n",
       "      <th>price_per_sqm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>99040</th>\n",
       "      <td>2021</td>\n",
       "      <td>WOODLANDS</td>\n",
       "      <td>5 ROOM</td>\n",
       "      <td>117.0</td>\n",
       "      <td>1976-01-01</td>\n",
       "      <td>350000.0</td>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>16437 days</td>\n",
       "      <td>54.0</td>\n",
       "      <td>2991.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99041</th>\n",
       "      <td>2021</td>\n",
       "      <td>WOODLANDS</td>\n",
       "      <td>5 ROOM</td>\n",
       "      <td>126.0</td>\n",
       "      <td>1976-01-01</td>\n",
       "      <td>370000.0</td>\n",
       "      <td>2021-03-01</td>\n",
       "      <td>16496 days</td>\n",
       "      <td>54.0</td>\n",
       "      <td>2937.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99042</th>\n",
       "      <td>2021</td>\n",
       "      <td>WOODLANDS</td>\n",
       "      <td>5 ROOM</td>\n",
       "      <td>115.0</td>\n",
       "      <td>1977-01-01</td>\n",
       "      <td>382000.0</td>\n",
       "      <td>2021-04-01</td>\n",
       "      <td>16161 days</td>\n",
       "      <td>55.0</td>\n",
       "      <td>3322.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99043</th>\n",
       "      <td>2021</td>\n",
       "      <td>WOODLANDS</td>\n",
       "      <td>5 ROOM</td>\n",
       "      <td>124.0</td>\n",
       "      <td>1978-01-01</td>\n",
       "      <td>418000.0</td>\n",
       "      <td>2021-05-01</td>\n",
       "      <td>15826 days</td>\n",
       "      <td>56.0</td>\n",
       "      <td>3371.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99044</th>\n",
       "      <td>2021</td>\n",
       "      <td>WOODLANDS</td>\n",
       "      <td>5 ROOM</td>\n",
       "      <td>124.0</td>\n",
       "      <td>1978-01-01</td>\n",
       "      <td>515000.0</td>\n",
       "      <td>2021-05-01</td>\n",
       "      <td>15826 days</td>\n",
       "      <td>56.0</td>\n",
       "      <td>4153.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       year       town flat_type  floor_area_sqm lease_commence_date  \\\n",
       "99040  2021  WOODLANDS    5 ROOM           117.0          1976-01-01   \n",
       "99041  2021  WOODLANDS    5 ROOM           126.0          1976-01-01   \n",
       "99042  2021  WOODLANDS    5 ROOM           115.0          1977-01-01   \n",
       "99043  2021  WOODLANDS    5 ROOM           124.0          1978-01-01   \n",
       "99044  2021  WOODLANDS    5 ROOM           124.0          1978-01-01   \n",
       "\n",
       "       resale_price   month_dt days_expired  remaining_lease  price_per_sqm  \n",
       "99040      350000.0 2021-01-01   16437 days             54.0         2991.0  \n",
       "99041      370000.0 2021-03-01   16496 days             54.0         2937.0  \n",
       "99042      382000.0 2021-04-01   16161 days             55.0         3322.0  \n",
       "99043      418000.0 2021-05-01   15826 days             56.0         3371.0  \n",
       "99044      515000.0 2021-05-01   15826 days             56.0         4153.0  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# compute resale prices for 5 rooms for 5 locations in the North\n",
    "\n",
    "town = ['WOODLANDS', 'YISHUN', 'SEMBAWANG']\n",
    "north_5rm=[]\n",
    "for i in town:\n",
    "    x = yr_grt2020.loc[(yr_grt2020['town']==i) & (yr_grt2020['flat_type']=='5 ROOM')] \n",
    "    north_5rm.append(x)\n",
    "north_5rm = pd.concat(north_5rm)\n",
    "north_5rm.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "north_5rm.groupby('town')['resale_price'].mean().sort_values().plot.bar();\n",
    "plt.xlabel('Location');\n",
    "plt.ylabel('Resale Price');\n",
    "plt.title('Mean Resale Price for 5 room flat In The North', fontsize=17);\n",
    "plt.show()"
   ]
  },
  {
   "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>year</th>\n",
       "      <th>town</th>\n",
       "      <th>flat_type</th>\n",
       "      <th>floor_area_sqm</th>\n",
       "      <th>lease_commence_date</th>\n",
       "      <th>resale_price</th>\n",
       "      <th>month_dt</th>\n",
       "      <th>days_expired</th>\n",
       "      <th>remaining_lease</th>\n",
       "      <th>price_per_sqm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>99040</th>\n",
       "      <td>2021</td>\n",
       "      <td>WOODLANDS</td>\n",
       "      <td>5 ROOM</td>\n",
       "      <td>117.0</td>\n",
       "      <td>1976-01-01</td>\n",
       "      <td>350000.0</td>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>16437 days</td>\n",
       "      <td>54.0</td>\n",
       "      <td>2991.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99041</th>\n",
       "      <td>2021</td>\n",
       "      <td>WOODLANDS</td>\n",
       "      <td>5 ROOM</td>\n",
       "      <td>126.0</td>\n",
       "      <td>1976-01-01</td>\n",
       "      <td>370000.0</td>\n",
       "      <td>2021-03-01</td>\n",
       "      <td>16496 days</td>\n",
       "      <td>54.0</td>\n",
       "      <td>2937.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99042</th>\n",
       "      <td>2021</td>\n",
       "      <td>WOODLANDS</td>\n",
       "      <td>5 ROOM</td>\n",
       "      <td>115.0</td>\n",
       "      <td>1977-01-01</td>\n",
       "      <td>382000.0</td>\n",
       "      <td>2021-04-01</td>\n",
       "      <td>16161 days</td>\n",
       "      <td>55.0</td>\n",
       "      <td>3322.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99043</th>\n",
       "      <td>2021</td>\n",
       "      <td>WOODLANDS</td>\n",
       "      <td>5 ROOM</td>\n",
       "      <td>124.0</td>\n",
       "      <td>1978-01-01</td>\n",
       "      <td>418000.0</td>\n",
       "      <td>2021-05-01</td>\n",
       "      <td>15826 days</td>\n",
       "      <td>56.0</td>\n",
       "      <td>3371.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99044</th>\n",
       "      <td>2021</td>\n",
       "      <td>WOODLANDS</td>\n",
       "      <td>5 ROOM</td>\n",
       "      <td>124.0</td>\n",
       "      <td>1978-01-01</td>\n",
       "      <td>515000.0</td>\n",
       "      <td>2021-05-01</td>\n",
       "      <td>15826 days</td>\n",
       "      <td>56.0</td>\n",
       "      <td>4153.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       year       town flat_type  floor_area_sqm lease_commence_date  \\\n",
       "99040  2021  WOODLANDS    5 ROOM           117.0          1976-01-01   \n",
       "99041  2021  WOODLANDS    5 ROOM           126.0          1976-01-01   \n",
       "99042  2021  WOODLANDS    5 ROOM           115.0          1977-01-01   \n",
       "99043  2021  WOODLANDS    5 ROOM           124.0          1978-01-01   \n",
       "99044  2021  WOODLANDS    5 ROOM           124.0          1978-01-01   \n",
       "\n",
       "       resale_price   month_dt days_expired  remaining_lease  price_per_sqm  \n",
       "99040      350000.0 2021-01-01   16437 days             54.0         2991.0  \n",
       "99041      370000.0 2021-03-01   16496 days             54.0         2937.0  \n",
       "99042      382000.0 2021-04-01   16161 days             55.0         3322.0  \n",
       "99043      418000.0 2021-05-01   15826 days             56.0         3371.0  \n",
       "99044      515000.0 2021-05-01   15826 days             56.0         4153.0  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "north_5rm.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### May we have the price trend for 5 room flats in the north?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# price trend for north\n",
    "\n",
    "town = ['WOODLANDS', 'YISHUN', 'SEMBAWANG']\n",
    "north_5rm=[]\n",
    "for i in town:\n",
    "    x = yr_combine.loc[(yr_combine['town']==i) & (yr_combine['flat_type']=='5 ROOM')] \n",
    "    north_5rm.append(x)\n",
    "north_5rm = pd.concat(north_5rm)\n",
    "north_5rm.head()\n",
    "\n",
    "fig=plt.gcf()\n",
    "fig.set_size_inches(12,8)\n",
    "sns.lineplot(data=north_5rm, x='year', y='resale_price', hue='town', palette='bright', ci=None);\n",
    "plt.title('Price Trend for 5 Room Resale Flat In These 3 Locations', fontsize=17);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Let's narrow down our choice to Yishun, remaining lease of at lease 70years, price of < 500k, and must be 5 room and floor area must be greater than 110sqm.  Find the location."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# list down all the requirements of the client and assign to 'requirement'\n",
    "\n",
    "requirement =(yr_grt2020['town']=='YISHUN') & (yr_grt2020['remaining_lease']>70) & (yr_grt2020['resale_price']<500000) &\\\n",
    "               (yr_grt2020['flat_type']=='5 ROOM') & (yr_grt2020['floor_area_sqm']>110)\n",
    "\n",
    "choice=yr_grt2020.loc[requirement]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>town</th>\n",
       "      <th>flat_type</th>\n",
       "      <th>floor_area_sqm</th>\n",
       "      <th>lease_commence_date</th>\n",
       "      <th>resale_price</th>\n",
       "      <th>month_dt</th>\n",
       "      <th>days_expired</th>\n",
       "      <th>remaining_lease</th>\n",
       "      <th>price_per_sqm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>99845</th>\n",
       "      <td>2021</td>\n",
       "      <td>YISHUN</td>\n",
       "      <td>5 ROOM</td>\n",
       "      <td>133.0</td>\n",
       "      <td>1993-01-01</td>\n",
       "      <td>478000.0</td>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>10227 days</td>\n",
       "      <td>71.0</td>\n",
       "      <td>3594.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99888</th>\n",
       "      <td>2021</td>\n",
       "      <td>YISHUN</td>\n",
       "      <td>5 ROOM</td>\n",
       "      <td>135.0</td>\n",
       "      <td>1993-01-01</td>\n",
       "      <td>452000.0</td>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>10227 days</td>\n",
       "      <td>71.0</td>\n",
       "      <td>3348.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99895</th>\n",
       "      <td>2021</td>\n",
       "      <td>YISHUN</td>\n",
       "      <td>5 ROOM</td>\n",
       "      <td>123.0</td>\n",
       "      <td>1993-01-01</td>\n",
       "      <td>457000.0</td>\n",
       "      <td>2021-02-01</td>\n",
       "      <td>10258 days</td>\n",
       "      <td>71.0</td>\n",
       "      <td>3715.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99917</th>\n",
       "      <td>2021</td>\n",
       "      <td>YISHUN</td>\n",
       "      <td>5 ROOM</td>\n",
       "      <td>111.0</td>\n",
       "      <td>2000-01-01</td>\n",
       "      <td>490000.0</td>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>7671 days</td>\n",
       "      <td>78.0</td>\n",
       "      <td>4414.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99937</th>\n",
       "      <td>2021</td>\n",
       "      <td>YISHUN</td>\n",
       "      <td>5 ROOM</td>\n",
       "      <td>112.0</td>\n",
       "      <td>2016-01-01</td>\n",
       "      <td>495000.0</td>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>1827 days</td>\n",
       "      <td>94.0</td>\n",
       "      <td>4420.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       year    town flat_type  floor_area_sqm lease_commence_date  \\\n",
       "99845  2021  YISHUN    5 ROOM           133.0          1993-01-01   \n",
       "99888  2021  YISHUN    5 ROOM           135.0          1993-01-01   \n",
       "99895  2021  YISHUN    5 ROOM           123.0          1993-01-01   \n",
       "99917  2021  YISHUN    5 ROOM           111.0          2000-01-01   \n",
       "99937  2021  YISHUN    5 ROOM           112.0          2016-01-01   \n",
       "\n",
       "       resale_price   month_dt days_expired  remaining_lease  price_per_sqm  \n",
       "99845      478000.0 2021-01-01   10227 days             71.0         3594.0  \n",
       "99888      452000.0 2021-01-01   10227 days             71.0         3348.0  \n",
       "99895      457000.0 2021-02-01   10258 days             71.0         3715.0  \n",
       "99917      490000.0 2021-01-01    7671 days             78.0         4414.0  \n",
       "99937      495000.0 2021-01-01    1827 days             94.0         4420.0  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "choice"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "myindex=choice.index.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[99845, 99888, 99895, 99917, 99937]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "myindex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "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>month</th>\n",
       "      <th>town</th>\n",
       "      <th>flat_type</th>\n",
       "      <th>block</th>\n",
       "      <th>street_name</th>\n",
       "      <th>storey_range</th>\n",
       "      <th>floor_area_sqm</th>\n",
       "      <th>flat_model</th>\n",
       "      <th>lease_commence_date</th>\n",
       "      <th>remaining_lease</th>\n",
       "      <th>resale_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>99845</th>\n",
       "      <td>2021-01</td>\n",
       "      <td>YISHUN</td>\n",
       "      <td>5 ROOM</td>\n",
       "      <td>419</td>\n",
       "      <td>YISHUN AVE 11</td>\n",
       "      <td>01 TO 03</td>\n",
       "      <td>133.0</td>\n",
       "      <td>Model A</td>\n",
       "      <td>1993</td>\n",
       "      <td>70 years 11 months</td>\n",
       "      <td>478000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99888</th>\n",
       "      <td>2021-01</td>\n",
       "      <td>YISHUN</td>\n",
       "      <td>5 ROOM</td>\n",
       "      <td>413</td>\n",
       "      <td>YISHUN RING RD</td>\n",
       "      <td>01 TO 03</td>\n",
       "      <td>135.0</td>\n",
       "      <td>Model A</td>\n",
       "      <td>1993</td>\n",
       "      <td>71 years 02 months</td>\n",
       "      <td>452000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99895</th>\n",
       "      <td>2021-02</td>\n",
       "      <td>YISHUN</td>\n",
       "      <td>5 ROOM</td>\n",
       "      <td>413</td>\n",
       "      <td>YISHUN RING RD</td>\n",
       "      <td>01 TO 03</td>\n",
       "      <td>123.0</td>\n",
       "      <td>Improved</td>\n",
       "      <td>1993</td>\n",
       "      <td>71 years</td>\n",
       "      <td>457000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99917</th>\n",
       "      <td>2021-01</td>\n",
       "      <td>YISHUN</td>\n",
       "      <td>5 ROOM</td>\n",
       "      <td>299</td>\n",
       "      <td>YISHUN ST 20</td>\n",
       "      <td>10 TO 12</td>\n",
       "      <td>111.0</td>\n",
       "      <td>Improved</td>\n",
       "      <td>2000</td>\n",
       "      <td>78 years 11 months</td>\n",
       "      <td>490000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99937</th>\n",
       "      <td>2021-01</td>\n",
       "      <td>YISHUN</td>\n",
       "      <td>5 ROOM</td>\n",
       "      <td>504C</td>\n",
       "      <td>YISHUN ST 51</td>\n",
       "      <td>01 TO 03</td>\n",
       "      <td>112.0</td>\n",
       "      <td>Improved</td>\n",
       "      <td>2016</td>\n",
       "      <td>94 years 02 months</td>\n",
       "      <td>495000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         month    town flat_type block     street_name storey_range  \\\n",
       "99845  2021-01  YISHUN    5 ROOM   419   YISHUN AVE 11     01 TO 03   \n",
       "99888  2021-01  YISHUN    5 ROOM   413  YISHUN RING RD     01 TO 03   \n",
       "99895  2021-02  YISHUN    5 ROOM   413  YISHUN RING RD     01 TO 03   \n",
       "99917  2021-01  YISHUN    5 ROOM   299    YISHUN ST 20     10 TO 12   \n",
       "99937  2021-01  YISHUN    5 ROOM  504C    YISHUN ST 51     01 TO 03   \n",
       "\n",
       "       floor_area_sqm flat_model  lease_commence_date     remaining_lease  \\\n",
       "99845           133.0    Model A                 1993  70 years 11 months   \n",
       "99888           135.0    Model A                 1993  71 years 02 months   \n",
       "99895           123.0   Improved                 1993            71 years   \n",
       "99917           111.0   Improved                 2000  78 years 11 months   \n",
       "99937           112.0   Improved                 2016  94 years 02 months   \n",
       "\n",
       "       resale_price  \n",
       "99845      478000.0  \n",
       "99888      452000.0  \n",
       "99895      457000.0  \n",
       "99917      490000.0  \n",
       "99937      495000.0  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "yr2021=pd.read_csv('resale-flat-prices-based-on-registration-date-from-jan-2017-onwards.csv')\n",
    "yr2021.loc[yr2021.index.isin(myindex)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### May I know the trend of  HDB this year?  Will the price drop? Should I wait?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "#find average HDB price by year and standardize the data\n",
    "\n",
    "avg_price = yr_combine.groupby('year')['price_per_sqm'].agg(np.mean).to_frame().reset_index()\n",
    "scaler = StandardScaler()\n",
    "x=avg_price['price_per_sqm'].values.reshape(-1,1)\n",
    "avg_price['price_per_sqm_sc']=scaler.fit_transform(x)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "#find the total amount of resale by year and standardize the data\n",
    "\n",
    "total_resale_amt = yr_combine.groupby('year')['resale_price'].agg(np.sum).reset_index()\n",
    "scaler = StandardScaler()\n",
    "x=total_resale_amt['resale_price'].values.reshape(-1,1)\n",
    "total_resale_amt['resale_price_sc']=scaler.fit_transform(x)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# plot a regression line for price per sqm\n",
    "from scipy import stats\n",
    "\n",
    "x=np.array(avg_price['year'])\n",
    "y=np.array(avg_price['price_per_sqm_sc'])\n",
    "\n",
    "slope, intercept, r, p, stderr = stats.linregress(x,y)\n",
    "\n",
    "func = lambda x: slope*x + intercept\n",
    "\n",
    "x1=np.array([1990,2021])\n",
    "y1=np.array([func(1990), func(2021)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "# plot a regression line for total resale volume\n",
    "from scipy import stats\n",
    "\n",
    "x2=np.array(total_resale_amt['year'])\n",
    "y2=np.array(total_resale_amt['resale_price_sc'])\n",
    "\n",
    "slope, intercept, r, p, stderr = stats.linregress(x2,y2)\n",
    "\n",
    "func = lambda x: slope*x + intercept\n",
    "\n",
    "x3=np.array([1990,2021])\n",
    "y3=np.array([func(1990), func(2021)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(32,)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x792 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plot price per sqm and total resale amount and regression line for price per sqm\n",
    "\n",
    "plt.plot(avg_price['year'],avg_price['price_per_sqm_sc'], linestyle='--',linewidth=4);\n",
    "plt.plot(x1,y1, linestyle='--',linewidth=4)\n",
    "plt.plot(total_resale_amt['year'], total_resale_amt['resale_price_sc']);\n",
    "\n",
    "plt.plot(x3,y3)\n",
    "\n",
    "fig=plt.gcf();\n",
    "fig.set_size_inches(15,11);\n",
    "plt.xlabel('Year');\n",
    "plt.ylabel('Trend');\n",
    "plt.title('Total Resale Amount VS Price Per Sqm Based on Year', fontsize=15);\n",
    "plt.legend(['Price Per Sqm','Prediction For Price Per Sqm','Total Resale Amount','Prediction For Total Resale Amount'],\\\n",
    "           fontsize=15, loc='lower right');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Can we compare the trend of private properties vs HDB in resale prices?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "private2020 = pd.read_csv('private-residential-property-price-index-base-quarter-2009-q1-100.csv')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "# format year column\n",
    "\n",
    "private2020['year']=[i[:-3] for i in private2020['quarter']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "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>year</th>\n",
       "      <th>quarter</th>\n",
       "      <th>level_1</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1975</td>\n",
       "      <td>1975-Q1</td>\n",
       "      <td>Residential Properties</td>\n",
       "      <td>8.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1975</td>\n",
       "      <td>1975-Q2</td>\n",
       "      <td>Residential Properties</td>\n",
       "      <td>9.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1975</td>\n",
       "      <td>1975-Q3</td>\n",
       "      <td>Residential Properties</td>\n",
       "      <td>9.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1975</td>\n",
       "      <td>1975-Q4</td>\n",
       "      <td>Residential Properties</td>\n",
       "      <td>9.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1976</td>\n",
       "      <td>1976-Q1</td>\n",
       "      <td>Residential Properties</td>\n",
       "      <td>9.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>2019</td>\n",
       "      <td>2019-Q1</td>\n",
       "      <td>Residential Properties</td>\n",
       "      <td>148.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>2019</td>\n",
       "      <td>2019-Q2</td>\n",
       "      <td>Residential Properties</td>\n",
       "      <td>150.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>2019</td>\n",
       "      <td>2019-Q3</td>\n",
       "      <td>Residential Properties</td>\n",
       "      <td>152.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>2019</td>\n",
       "      <td>2019-Q4</td>\n",
       "      <td>Residential Properties</td>\n",
       "      <td>153.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>2020</td>\n",
       "      <td>2020-Q1</td>\n",
       "      <td>Residential Properties</td>\n",
       "      <td>152.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>181 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     year  quarter                 level_1  value\n",
       "0    1975  1975-Q1  Residential Properties    8.9\n",
       "1    1975  1975-Q2  Residential Properties    9.1\n",
       "2    1975  1975-Q3  Residential Properties    9.1\n",
       "3    1975  1975-Q4  Residential Properties    9.1\n",
       "4    1976  1976-Q1  Residential Properties    9.5\n",
       "..    ...      ...                     ...    ...\n",
       "176  2019  2019-Q1  Residential Properties  148.6\n",
       "177  2019  2019-Q2  Residential Properties  150.8\n",
       "178  2019  2019-Q3  Residential Properties  152.8\n",
       "179  2019  2019-Q4  Residential Properties  153.6\n",
       "180  2020  2020-Q1  Residential Properties  152.1\n",
       "\n",
       "[181 rows x 4 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# re-ordering column names\n",
    "\n",
    "private2020[['year','quarter','level_1','value']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# compute average price by year\n",
    "\n",
    "private_avg_price = private2020.groupby('year')['value'].agg(np.mean).to_frame()\n",
    "private_avg_price.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "# format year to integter\n",
    "\n",
    "private_avg_price['year']=[int(j) for j in private_avg_price['year']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "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>year</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1990</td>\n",
       "      <td>41.250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1991</td>\n",
       "      <td>45.525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1992</td>\n",
       "      <td>52.700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1993</td>\n",
       "      <td>67.350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1994</td>\n",
       "      <td>96.775</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    year   value\n",
       "15  1990  41.250\n",
       "16  1991  45.525\n",
       "17  1992  52.700\n",
       "18  1993  67.350\n",
       "19  1994  96.775"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create dataframe for transactions after 1989\n",
    "\n",
    "private_avg_price = private_avg_price[private_avg_price['year']>1989]\n",
    "\n",
    "private_avg_price.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# standardize the chart\n",
    "\n",
    "scaler = StandardScaler()\n",
    "x=private_avg_price.value.values.reshape(-1,1)\n",
    "private_avg_price['value1']=scaler.fit_transform(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "# remove year 2021 from dataframe\n",
    "\n",
    "avg_price_before_2021=avg_price[avg_price['year']<2021]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "x5=np.array(avg_price_before_2021['year'])\n",
    "y5=np.array(avg_price_before_2021['price_per_sqm_sc'])\n",
    "\n",
    "slope, intercept, r, p, stderr = stats.linregress(x5,y5)\n",
    "func = lambda x: slope*x + intercept\n",
    "\n",
    "x6=np.array([1990,2020])\n",
    "y6=np.array([func(1990), func(2020)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "x7=np.array(private_avg_price['year'])\n",
    "y7=np.array(private_avg_price['value1'])\n",
    "\n",
    "slope1, intercept1, r, p, stderr = stats.linregress(x7,y7)\n",
    "func1 = lambda x: slope1*x + intercept1\n",
    "\n",
    "x8=np.array([1990,2020])\n",
    "y8=np.array([func1(1990), func1(2020)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x792 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create dataframe for HDB for year before 2021 to align with private property price index\n",
    "\n",
    "fig=plt.gcf()\n",
    "fig.set_size_inches(15,11)\n",
    "\n",
    "plt.plot(avg_price_before_2021['year'],avg_price_before_2021['price_per_sqm_sc'],c = 'g', linestyle='--',linewidth=4);\n",
    "plt.plot(x6,y6,linestyle ='--',linewidth=4 );\n",
    "plt.plot(private_avg_price['year'],private_avg_price['value1']);\n",
    "plt.plot(x8,y8,);\n",
    "\n",
    "plt.xlabel('Year',fontsize=15);\n",
    "plt.ylabel('Price',fontsize=15);\n",
    "plt.title('HDB VS Private Property By Year',fontsize=15);\n",
    "plt.legend(['HDB','Prediction HDB','Private Property','Prediction Private Property'], fontsize=15);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Thank You!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}