Spatial data science -- Map your way into analytics
In a world awash with data and intellectual forums abuzz with predictive analytics, machine learning, and AI, somehow the focus is not on spatial data science. This is rather strange. Why? Because most of the economic, demographic or climate data is geo-referenced and hence can be analyzed, summarized and visualized as maps. Need convincing. Let me illustrate spatial analytics with two simple maps that demonstrate the east-centre-west divide in the American housing markets.
I sourced housing data from https://www.realtor.com/research/data/. The variables of interest are the median list price and the year-over-year percentage change in listings across the states in September 2022. I downloaded the data as an Excel file and imported it in a Geographic Information Sytems (GIS) software Maptitude. I spatially linked the tabular data to a GIS file depicting the States. The process takes a couple of minutes. Using the thematic mapping feature in Maptitude, I plotted a choropleth map of the median list price. What did I find? Nothing special. Just that the median list price is higher on the eastern and western coasts and lower in the centre.
I also found that the listing activity was slightly higher in September from the same time last year in the western states, and slightly lower in the eastern states. So, what did I conclude: I see western states are faring the housing market downtown better than the eastern states.
The strength of spatial data science lies in its inherent ability to expose spatial trends that one may not readily observe in tabular summaries. Predictive analytics and AI are all the rage, but do not ignore learning from data by plotting and visualizing it. For more on spatial analytics, visit this URL.
Construction Coordinator (Central District) - Dufferin Construction (A CRH Canada Company) | Project management & Sustainability professional | *Opinions expressed here are my own*
2 年Ashir Shah
Strategy | Senior Analyst | Economy | Risk management
2 年Thanks Murtaza Haider! You have clearly and interestingly described everything. You have cettainly given me a lot to think about. I well remember one of your lectures in cursero on Data Science - where you talked about how you determined why there are a lot of complaints about the transport company on certain days (reason: people wet their feet when getting off the bus - bad weather)
Civil Engineering, Analysis and design of structure, Reliability, Structural Health Monitoring, Damage Detection, Remaining Useful Life, Data Analysis, Bayesian Approach, Data Science, Databases.
2 年Well written and motivating. Thanks
Data Strategy Advisor | 20+ years in Data & AI | Fortune 500 Global Energy Company's Data Architect
2 年Thanks for adding me to the newsletter. You are a great mentor, I glad to tell you, and thanks for be part of this wonderful journey that I been made it into the Data Science and Statistics Word
BRI Researcher | Post Doc Economics @SDU | China | Belt and Road
2 年It was very insightful and thrilling at the same time. It is thrilling because it is kind of magical for a nave learner like me. Thank you, Professor Murtaza Haider, for adding me here.