Comparing condominium transaction prices near MRT stations, grouped by station, line, and tenure.
In brief: Linked condominium transactions to MRT stations for comparisons of prices, PSF, and tenure mix.
How do condominium transaction prices differ near MRT stations, across lines and tenure types?
I used SQL geography functions to link condominium transactions to stations within a 1,000-metre radius. Transactions were grouped by station and tenure so freehold and leasehold properties could be compared separately.
Python prepared the results for presentation. GeoJSON layers for MRT lines made the comparisons easier to read on a map.
The workflow calculated average transaction prices and average price per square foot around each station. It supported comparisons between stations, lines, and tenure groups.
These are descriptive comparisons of nearby transactions. The surrounding neighbourhood and the mix of properties remain part of the interpretation.
The comparisons do not isolate a causal price premium from MRT access.
The cover above illustrates the method. This screenshot preserves an output from the original project.
