FLATearthers proposal
As Singapore government ramps up efforts to collect and share data sets to the public, various kinds of information are readily available. There are however, no readily available tools that could allow analysts who are well-versed in real estate, but do not have the coding know-how to perform analysis. Thus, our group hopes to bridge the gap and provide these analysts with a friendly user interface and experience.
Our project aims to find out how external and internal factors may affect resale housing prices, specifically for HDB resale flats. External factors are, though not limited to, shopping malls, hawker centers, MRTs and LRTs, supermarkets, primary schools, pre-schools and eldercare services. Internal factors are, though not limited to, remaining lease, floor area, storey, flat type and model.
We will be using 2 different models:
- Multiple linear regression
- Geographically weighted regression
to compare and explain how the factors stated above may, affect resale housing prices.
| Data Set | Source | Data Type/Method |
|---|---|---|
| 2014 Master Plan Planning Subzone | data.gov.sg | SHP |
| Resale flat prices | data.gov.sg | CSV |
| Singapore Shopping malls | Wikipedia | Text to SHP |
| Singapore Hawker Centers | Hawker Centres Others |
KML |
| MRT / LRT Stations | LTA Datamall | SHP |
| Supermarkets | Wikipedia | Text to SHP |
| Primary Schools | Primary Schools | CSV |
| Premium Primary Schools | ||
| Premium Pre-schools |
| Key Challenges | Mitigation |
|---|---|
| Unfamiliarity with R and packages required for project |
|
| Unfamiliarity with proper approach to use for project |
|
| Limitations of OneMap API to handle large amount of data |
|
