Study price distribution of past sales and lease transactions in a reactive map and a violin plot by selecting varaibles such as postal district, size, tenure etc
How the unit price varies across different property characteristics? Uses statistical tests to check if the effect of each attribute on price is statistically significant.
Explore how property market reacted to sigificant COVID-19 events through time series visualisations.
Pre-conceptions about property market demystified! Are older houses bigger? Are EC always far from MRT stations? Are first launch new condominiums cheaper?
Many Singaporeans liken owning a second property for passive rental income to owning a goose that lays golden eggs. Yet, research reported that buying a second property yielded the lowest investment growth over the past decade. The Singapore housing market is heavily regulated with frequent interventions to manage prices. The COVID-19 pandemic has also impacted both supply and demand in the housing market: 2 years into the pandemic, construction projects are still facing delays because of tight immigration controls and work-from-home arrangements also pushed more to turn to the rental market.
In the face of such volatile Property and Rental market, we developed a Shiny App to provide truthful visual insights on the sales and rental private housing market to help potential property investors make data-driven decisions when looking for their golden goose.
Using SGGoldenGoose App, informed choices about investing in private residential property in Singapore to earn passive rental income can be made.
Step-by-step guide on how to use the data visualisation functions of SGGoldenGoose App
Overview of our project which includes Problem Statement, Motivation, Techniques and approach used, Results and Future Work.
Three SMU Master of IT in Business (Analytics) students, excited in building visually driven web-enabled Shiny App for democratising data and analytics.
We hope to develop an app which is free, interactive, and easy-to-use to aid all landlord wannabes who have no technical training in data analysis to identify their their dream golden goose, based on their individual preferences such as location, property tenure, and floor area.
Master of IT in Business (Analytics) @ SMU. Fifteen years of experinece in tax audit, investigation and compliance in Singapore and HK. Enjoy gaining data insights using SQL, R, Tableau and Python.
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Master of IT in Business (Analytics) @ SMU. More than five years of experinece in in the land transport sector with good writing and quantitative analysis skills using Stata, QGIS and Excel.
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Master of IT in Business (Analytics) @ SMU. Keen in data engineering and developing analytic solutions using R and Python.
