Ok since the Tableau embed code won't work, click here to see the visualisation.

Context

After completing the Tableau Essential Training course on Lynda, I wanted to build a portfolio of work on Tableau. Since many friends were looking to buy property, why not see if I could help them narrow down:

  1. Where to buy
  2. How much to offer

Also, to give them the flexibility of filtering the size, age and location of the houses.

Artificially-imposed data restrictions

1. 4-room flats only

As most friends are young couples, the assumption is that a large resale 4-room flat would suffice for their needs (and budget) for now. I also wanted to seperate 4 and 5-room flats for now to reduce visual clutter.

2. Data from 2010 onwards

Though data is available as far back as 1990, I assumed that looking 8 years back of data is more than sufficient.

3. 6-floor units and above

The assumption is that the friends would prefer units on higher floors.

4. Geylang only

Being as "Eastie", I am more familiar with houses in this area. Hence, I chose to look at this area first to get a functional visualisation up, before later expanding to other areas.

Analysis

Honestly, this is still a work in progress. I still want to move some data around before seeing if any trends emerge. That being said, a surprising discovery was made on another batch of property data, which will not be revealed for now :). This post is to make me accountable for a proper analysis soon.