The purpose of this project was to conduct a series of advanced geospatial analyses in ArcGIS. The project was completed for the class CP 6581, Programming for GIS. Naturally, all map building and analysis had to be done in a programming language.

I built this map using open source data from the city of Chicago, and geopandas. My main research question was whether different zoning classifications held more affordable housing units than others. Additionally, I was interested in the physical accessibility of affordable using to public transit infrastructure. The map below displays zoning classes in Chicago, the number of affordable units per building, as well as “L” heavy rail transit stops. I also conducted a number of analyses in pandas to determine which stations had the most affordable units near them, as well as which affordable units had a station within a 0.25mi radius.