An exploratory data analysis project to uncover patterns and trends in Singapore's HDB Resale Market
I did this project for 2 main reasons:
- Build my skills in working with data, as well as becoming more comfortable with programming.
- To see if I could uncover any useful insights about the HDB resale market in Singapore, and how it has transformed over time.
It was a tiring process, doing this as a side project while working and pursuing all my other hobbies. But it was a great learning experience.
I got to dabble in:
- Using pandas to do basic data manipulation, processing, and analysis.
- Using Seaborn to come up with visualisations to better understand patterns.
- Using BeautifulSoup to do some webpage scraping (specifically, to retrieve coordinates of every MRT station in Singapore, so that I could add this to my data set and see how distance to the MRT station affects the resale price of a flat)
- Using the Google Maps API to retrieve coordinates of every HDB block in the data set (for the same reason as listed above)
Most importantly, I learnt how to tackle new problems creatively and efficiently, and got my hands dirty.