Mapping the Housing Crisis in Washington D.C.,using Python, Pandas and Carto Mapping Software

Affordable Housing Locations in Washington D.C.

Planned Unit Developments in Washington D.C.

Course: Computer Programming for GIS
Date: November 2020
Author: Rachel Corcoran-Adams

Background: Exacerbated by the current pandemic, the United States is currently facing a housing crisis. Due to the cost of housing skyrocketing and wages plummeting, housing instability threatens millions of American people. The Eviction Lab is a good resource that is currently studying this phenomenon. One of the small aspects of this crisis is evictions which have a devastating effect on families during the current pandemic. Not only does this crisis disproportionately affect the marginalized, it also aids in gentrification. 

Data and Methods: Using Planned Unit Developments data offered by the city, this code examines the ways the city attempts to broadly redistribute the benefits of urban redevelopment by offering amenities such as affordable housing, improved public transportation in exchange for zoning exemptions.

Outcomes: The DC_Zoning.py code studies how eviction can be studies by examining the ways in the city of Washington D.C., handles zoning. By using Python to gather open data on zoning from the city's portal, a map was created of zoning exemptions. This code specifically looks at the ways in which we can categorize and visualize buildings that received a zoning exemption in Washington, D.C.

Citation: This tutorial was originally created by Nicole Janeway Bills, who provides a nice video walkthrough on YouTube here. I've changed some of the code slightly to deal with different inputs (Open Data D.C.'s file formatting has changed since the original tutorial); added more background context on the scenario, and added the use of Carto for a final output.
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You can access the code on GitHub: Here.