Real Estate Investment and Development: Data Visualization as a tool

Python and Geospatial tools create powerful and compelling data visualizations that supports Real Estate Analysis

Photo by Franki Chamaki on Unsplash

Point- And Aggregate- Level Visualizations

Fig 1. Barchart on 10 most and least expensive private residential projects in Singapore. Image by author.
Fig 2. Scatterplot on transacted prices for 3 chosen projects in Singapore. Image by author.
  1. The projects are aged with a wide time frame — Melville Park saw transactions starting pre-2000, while South Beach Residences was constructed in the mid-2010s.
  2. There is a general increase in project prices across time — Costa Del Sol and Melville Park saw a lift in their price lower bound.
  3. The price deviations vary significantly across different projects — South Beach Residences had a wider range of transacted price compared to the other two projects, despite its shorter transaction period.
Fig 3. Radar chart for project attribute comparison. Image by author.

Geospatial Visualization

Fig 4. Buffer arcs to segment Singapore’s different Central Region zones (silhouette). Image by author.
Fig 5. Buffer arcs to segment Singapore’s different Central Region zones (map). Image by author.
Fig 6. Residential property capital appreciation across OCR, RCR, CCR between 2012 to 2019, SIngapore. Image by author.
Fig 7. Residential property capital appreciation across districts between 2009 to 2014, SIngapore. Image by author.
Fig 8. Distance of buildings from CCR, Singapore. Image by author.

Time Series Visualizations

Fig 9. Residential Property Price Index for selected districts, Singapore, 2008–2019. Image by author.

Beyond That, What Else?

Fig 10. Gif of an interactive chart using Plotly, on house prices in Berlin. Image from Elizabeth Ter.
Fig 11. Interactive chart on 2014 US population, by city. Image from Plotly.
Fig 12. Bubble Chart on real estate investment flow and GDP. Image from JLL

Great! Where can I start learning these?

  1. How to create a plotly visualization and embed it on websites, TowardsDataScience: https://towardsdatascience.com/how-to-create-a-plotly-visualization-and-embed-it-on-websites-517c1a78568b
  2. Bubble Maps in Python, United States Bubble Map, Plotly: https://plotly.com/python/bubble-maps/
  3. Economic and Real Estate market performance for 300 cities globally, JLL: https://www.us.jll.com/en/trends-and-insights/research/global/crc/city-clustering-tool

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Keith is a Data Scientist at PropertyQuants, building time-series based machine- and deep- learning models for real estate valuation. He loves handling data.

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Keith Tan

Keith is a Data Scientist at PropertyQuants, building time-series based machine- and deep- learning models for real estate valuation. He loves handling data.