What's new in zipcodeR v0.2?

I first released my open-source R package for processing U.S. ZIP codes, zipcodeR, in September. From then until December, when I am writing this, the package has received more than 3000 downloads and a lot of interest from the community.

I’m grateful for all of the interest in the package - I created this to simplify my own personal data science workflow, and the adoption of zipcodeR by the wider R community shows that there was a clear need for such a package.

I’ve heard from several users & community members that have had suggestions and requests for features. One of our users, Andre Mikulec, also recently contributed code to allow the search_county() function to perfom an approximate match for county names.

After incorporating some community feedback along with a few of my own new ideas, I am very happy to share that the next release of zipcodeR, version 0.2 is now available on CRAN, and can be installed from the R console by running install.packages('zipcodeR')

New & updated features in v0.2

Here are some of the major changes in this update:

• search_county() function now allows for approximate matching of county names using agrep (Andre Mikulec)
• search_state() is now vectorized and will accept a vector of state abbreviations
• search_tz() is now vectorized and will accept a vector of timezones
• zip_code_db has been updated to use latest upstream data
• Added reverse_zipcode() function for obtaining metadata about a given ZIP code.
• Added search_cd() function for searching ZIP codes contained within a given congressional district.
• Added is_zcta() function for testing whether a given ZIP code is a ZIP code tabulation area (ZCTA).
• Added search_fips() function for searching ZIP codes by state and county FIPS codes.
• Added get_cd() and search_cd() functions for relating ZIP codes to congressional districts
• Added the first vignette, “Introduction to zipcodeR”

As always, review the documentation for a full reference on each of the package’s functions.

Looking ahead

This update aims to improve upon the initial features of zipcodeR, but there is still more work to be done. In the next release I aim to implement some much-requested GIS related features for geocoding ZIP codes performing geographic lookups.

It has also been really cool to see how folks have been using zipcodeR in their work. So far I’ve seen two very interesting project done by graudate students in data science and urban informatics that implemented the package. I’m always interested in hearing about interesting use cases of the package, so feel free to reach out if you’re working on anything particularly interesting.