Accessing US Census data and CDC health data via API to support demographic data summaries in SNAP's Northern Climate Reports.

This repo includes functions and lookup tables to support the EPA-Justice-HIA project which pulls demographic data from the US Census and CDC datasets. The functions here will take Alaska community IDs (from this collection) as their input, cross-reference these communities to their respective geographies using the most recent NCRPlaces_Census_{MMDDYYYY}.csv table, and compute data items relevant to the EPA-Justice-HIA project. These functions and/or the resulting tables will be incorporated into Northern Climate Reports.

Some places have a one-to-many relationship with census geographies. In these cases, when results are available for every geographic unit, value are aggregated according to the guidance here. If results are unavailable for any geographic unit, values are not aggregated and and instead replaced with NA.

This repo accesses US Census datasets via their survey-specific API endpoints (ACS 5-year and DHC), the CDC PLACES datasets via their geography-specific API endpoints (for county, place, tract, and zip code), and the CDC SDOH datasets via their geography-specific API endpoints (for county, place, tract, and zip code). Note that zip code geographies are not currently used in this project, but the codebase here supports using zip codes if desired.

• Activate a conda environment that includes pandas (>2.0) and numpy.
• Use the fetch_data_and_export.ipynb notebook to run the processing pipeline. (This notebook also contains some tests of individual functions used for review during development.)
• View the data_to_export.csv results.

This repo also contains additional processing tools that were used for adding new places to the GVV repo that were required for this specific project (update_NCR_points.ipynb, add_to_NCR.csv, alaska_point_locations.csv, and add_point_location.py). These shouldn't need to be run again, but are saved here for now in case the project scope changes and more places need to be added.

The data variables below are pulled for each geography. The short name column is the abbreviated name used in the exported data_to_export.csv. All other column names should be self explanatory.