ZIP-Code Converters

Python functions for using USA ZIP Codes in geospatial processes.

By J. A. Cooper -- https://github.com/cooperjaXC

Overview

Crosswalks for easy python conversions of USA ZIP Codes.

1. ZIP Codes → ZCTAs

• Input
  • USA ZIP Codes (string)
• Outputs:
  • 5 digit US Census Zip Code Tabulation Areas (ZCTAs) (string)
  • ZCTA's latitude & longitude centroid coordinates (list)

2. ZIP Codes → ZCTAs

• Input
  • ZCTAs (string)
• Outputs:
  • Each corresponding 5 digit postal Zip Codes (list)

Operates with both individual ZIP Codes and pandas dataframes. Compatible with both US Census year 2010 and 2020 (default) ZCTAs.

Key Functions

• zip_code_crosswalk - Takes a (1) postal ZIP Code and transforms it into a Zip Code Tract Area (ZCTAs), the US Census-defined polygonal region for a ZIP Code. Compatible with both 2010 and 2020 ZCTAs.
• df_zip_crosswalk - Takes a Pandas Dataframe with a ZIP-Code field and returns a ZCTA field using the crosswalk function.
• reverse_zcta_crosswalk - Takes a (1) Zip Code Tract Area (ZCTAs) and returns all its associated postal ZIP Codes. Compatible with both 2010 and 2020 ZCTAs.
• df_reverse_zcta_crosswalk - Takes a Pandas Dataframe with a ZCTA field and returns a field with a list of associated ZIP-Codes. Uses the reverse crosswalk function.
• lat_lon_centroid - Takes a (1) postal ZIP Code and returns its ZCTA's spatial coordinates in a [latitude, longitude] format based on US Census TIGER shapefiles. Compatible with both 2010 and 2020 ZCTAs.
• df_latlon_centroids - Takes a Pandas Dataframe with a ZIP-Code field and returns fields with the ZCTA's central latitude and longitude coordinates using the centroid function.