ISSS608 2016-17 T1 Assign1 XU Qiuhui

Abstract

This report focuses on analysis of resale public housing market, 5 factors, flat type, flat size, flat age, flat location, resale price per sqm, are considered.

Problem and Motivation

Huge influence and fast changing make resale public housing market one of the most concerned market by Singapore residents. This report is aimed to provide visualized analysis to

• help buyers get good knowledge of resale public housing market price distribution break down by flat type, location, flat age, etc. to choose the most suitable house according to their particular conditions;
• let sellers acknowledged with resale public housing market trends of both supply and price, to sell their house in a good time and price;
• help investors find houses with highest investment potential

Data

Data Acquisition

Dataset Resale Transaction by Flat Type (based on registered cases) is downloaded in csv directly from data.gov.sg.

Dataset Variables

Dataset contain following variables:

Variables	Description
Month	It's the date of registration, in the format of 'yyyy-mm'.
Town	Shows the location of the flat by town.
Flat Type	Includes 7 type of HDB flat
Block	Shows the block number of the flat
Street Name	Shows the street name that the flat located
Story Range	Divide story into 25 ranges, in the format of 'xx To xx"
Floor Area sqm	Shows flat area in square meters.
Flat Model	Shows the model type of the flat, including 19 types of models.
Lease Commencement Date	It is the date that the flat first time push into market.
Resale Price	It is the total price of the flat.

Data Preparation

Convert Data Type:

1. Convert Month from String to Date format: Dateparse('yyyy-MM',[Month])
2. Convert Lease Commencement Date from Numeric to Date: The Lease Commencement Date was actually in YYYY format. A similar conversion was done using DATEADD('year',INT([Lease Commence Date])-1900,#1/1/1900#).

Calculations:

1. Calculating flat age: Given the of dates above, the age of flat is estimated by getting the difference between transaction date and lease commencement date. The formula used was ([Year-Month]-[Lease commencement year])/365. As this estimated age is likely to be overstated, given that lease commencement date was using default 1st Jan of the respective years, this calculated field is rounded down to a whole number using if [Age of flat]=int([Age of flat]) then [Age of flat] elseif [Age of flat]<0 then int([Age of flat]) else int([Age of flat]+1) end.
2. Calculating the price per square metre of resale prices: The prices in the resale transactions were expressed in absolute price of the units. For a more uniform comparison, the prices were converted to price per square meter (psm) using [Resale Price]/[Floor Area Sqm]

Approaches

Share of the resale public housing supply in 2015

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Distribution of the resale public housing prices in 2015

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Comparison of patterns of the first-half of 2016 with the patterns of 2015

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Tools Utilised

1. SAS JMP 12 – for initial data exploration and analysis
2. Tableau 10.0 – for charting
3. Microsoft Powerpoint – for Infographics layout