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GIS Project With Python and GeoPandas
A GIS project implemented entirely with Python
Preamble
Some background info…I recently signed up to volunteer for Statistics Without Borders, which provide pro bono services in statistics and Data Science.
As a Data Analyst/Scientist with a penchant for environmental responsibility social equity, and sustainability, I felt it would make sense to use my skills for social good. This project was for Chicago400, who campaign on behalf of Chicagoans with past convictions. The goal was to create both static and web maps, outlining banishment zones for Chicagoans with past convictions. I decided to challenge myself and use Python entirely for this project, this way it could be deployed on Github and code shared with others that wanted to do the same.
Additionally, I was hard-pressed to find any Python GIS tutorials that went over all the aspects needed for a complete GIS map. I wanted to provide that for folks that were hoping to break away from being bound to desktop GIS systems.
Now that the formalities are done…let’s get to some code!
Get the Data
The first thing I needed to do was get the data. Chicago has an Open Data Portal (ODP) with tons of freely available information. The banishment zones fell into two distinct categories: one for Housing Banishment (where folks cannot reside), and another for Public Banishment (where folks cannot be present).
I will stick to the Housing Banishment code here, the project code in its entirety can be viewed in my GitHub repo. Housing Banishment geographies needed, including Schools, Parks, and Daycare centers.
Once the data was obtained from the ODP, it was time to import them into Python with GeoPandas as GeoDataFrames (GDF) and get them all in the same Coordinate Reference System (CRS).
For this project I chose to project them all in EPSG: 32616 WGS 84 / UTM zone 16N. See the code below for basic import and CRS transformation:
