Geospatial Public Policy Analysis with GeoPandas
summary
Uses GeoPandas and pandas with geoplot, TIGER shapefiles, NCES IPEDS and ACS via the census-data-downloader to build reproducible JupyterLab/Binder notebooks. The workflow does spatial joins, CRS reprojecting and overlay/difference operations to create 10/25/50‑mile buffers around institutions, then clips counties to find gaps. Results: 3,714 institutions in the contiguous US, 294 counties are majority underrepresented and 659 institutions sit inside those counties. Outputs are saved as shapefiles and CSVs, and the notebooks and maps run successfully.
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chapters (28)
- 0:00Introduction
- 0:42Who am I
- 2:18What do I do
- 4:01What this tutorial covers
- 4:54Who is this tutorial for
- 6:29Tools
- 7:51Data Sources
- 8:47Research Questions
- 12:01Research Data
- 18:48Getting Started
- 25:46Data Preparation
- 38:01Transpose View
- 39:39Variables of Interest
- 43:41Copy DataFrame
- 44:22Sector Variable
- 45:03Strings
- 45:26String Access
- 46:18series
- 48:09return data frame
- 48:50save on itself
- 49:44markdown
- 50:24index
- 51:05last name
- 52:57API key
- 55:36Universe
- 56:14Check Data
- 56:55Recap
- 57:39Creating a Notebook
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