Abstract

Still in Progress

Motivation

Tableau was mainly used to run the data.

Data preparations: The data set is not ready for use immediately. Slight calculations were required in the following:

Conversion of Date field: The Date field of the data set was in the format YYYY-QQ, as in “2012-03” for 2012Q3 and was treated as string character field by Tableau. To convert to a date format, the following formula was used on the Month field: DATEADD('month',INT(RIGHT([Month],2))-1,DATEADD('year',INT(LEFT([Month],4))-1900,#1/1/1900#)).
Standardisation of Lease Commencement 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#).
Calculating a proxy for flat age: Given the standardisation 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.
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]

During analysis:

Preparation of infographics:

General observations