Makes dealing with U.S. ZIP codes painless.
zipcodeR is an R package that makes working with ZIP codes in R easier. It provides data on all U.S. ZIP codes using multiple open data sources, making it easier for social science researchers and data scientists to work with ZIP code-level data in data science projects using R.
The latest update to zipcodeR includes new functions for searching ZIP codes at various geographic levels & geocoding.
Installation
You can install the released version of zipcodeR from CRAN with:
install.packages("zipcodeR")And the development version from GitHub with:
# install.packages("devtools")
devtools::install_github("gavinrozzi/zipcodeR")Citing {zipcodeR} in Publications
If you use zipcodeR in a publication, please cite the following journal article.
A BibTeX entry for LaTeX users is:
@article{ROZZI2021100099,
title = {zipcodeR: Advancing the analysis of spatial data at the ZIP code level in R},
journal = {Software Impacts},
volume = {9},
pages = {100099},
year = {2021},
issn = {2665-9638},
doi = {https://doi.org/10.1016/j.simpa.2021.100099},
url = {https://www.sciencedirect.com/science/article/pii/S2665963821000373},
author = {Gavin C. Rozzi},
keywords = {ZIP code, R, ZCTA, ZIP code tabulation area, zipcodeR},
abstract = {The United States Postal Service (USPS) assigns unique identifiers for postal service areas known as ZIP codes which are commonly used to identify cities and regions throughout the United States in datasets. Despite the widespread use of ZIP codes, there are challenges in using them for geospatial analysis in the social sciences. This paper presents zipcodeR, an R package that facilitates analysis of ZIP code-level data by providing an offline database of ZIP codes and functions for geocoding, normalizing and retrieving data about ZIP codes and relating them to other geographies in R without depending on any external services.}
}Examples
Find all ZIP codes for a state
search_state('NJ')
#> # A tibble: 732 × 24
#> zipcode zipcode_type major_city post_office_city common_city_list county
#> <chr> <chr> <chr> <chr> <blob> <chr>
#> 1 07001 Standard Avenel Avenel, NJ <raw 18 B> Middl…
#> 2 07002 Standard Bayonne Bayonne, NJ <raw 19 B> Hudso…
#> 3 07003 Standard Bloomfield Bloomfield, NJ <raw 22 B> Essex…
#> 4 07004 Standard Fairfield Fairfield, NJ <raw 21 B> Essex…
#> 5 07005 Standard Boonton Boonton, NJ <raw 36 B> Morri…
#> 6 07006 Standard Caldwell Caldwell, NJ <raw 39 B> Essex…
#> 7 07007 PO Box Caldwell <NA> <raw 30 B> Essex…
#> 8 07008 Standard Carteret Carteret, NJ <raw 20 B> Middl…
#> 9 07009 Standard Cedar Grove Cedar Grove, NJ <raw 23 B> Essex…
#> 10 07010 Standard Cliffside Park Cliffside Park, … <raw 32 B> Berge…
#> # … with 722 more rows, and 18 more variables: state <chr>, lat <dbl>,
#> # lng <dbl>, timezone <chr>, radius_in_miles <dbl>, area_code_list <blob>,
#> # population <int>, population_density <dbl>, land_area_in_sqmi <dbl>,
#> # water_area_in_sqmi <dbl>, housing_units <int>,
#> # occupied_housing_units <int>, median_home_value <int>,
#> # median_household_income <int>, bounds_west <dbl>, bounds_east <dbl>,
#> # bounds_north <dbl>, bounds_south <dbl>Calculate the distance between two ZIP codes in miles
zip_distance('08901','08731')
#> zipcode_a zipcode_b distance
#> 1 08901 08731 40.7Calculate the distance between vectors of ZIP codes
zip_codes <- tribble(~zip_a, ~zip_b,
"08731", "08901",
"08734", "08005")
zip_distance(zip_codes$zip_a,zip_codes$zip_b)
#> zipcode_a zipcode_b distance
#> 1 08731 08901 40.70
#> 2 08734 08005 8.06Geocode a ZIP code to get its centroid
geocode_zip('08901')
#> # A tibble: 1 × 3
#> zipcode lat lng
#> <chr> <dbl> <dbl>
#> 1 08901 40.5 -74.4Get data about a ZIP code
reverse_zipcode('08901')
#> # A tibble: 1 × 24
#> zipcode zipcode_type major_city post_office_city common_city_list county state
#> <chr> <chr> <chr> <chr> <blob> <chr> <chr>
#> 1 08901 Standard New Bruns… New Brunswick, … <raw 25 B> Middl… NJ
#> # … with 17 more variables: lat <dbl>, lng <dbl>, timezone <chr>,
#> # radius_in_miles <dbl>, area_code_list <blob>, population <int>,
#> # population_density <dbl>, land_area_in_sqmi <dbl>,
#> # water_area_in_sqmi <dbl>, housing_units <int>,
#> # occupied_housing_units <int>, median_home_value <int>,
#> # median_household_income <int>, bounds_west <dbl>, bounds_east <dbl>,
#> # bounds_north <dbl>, bounds_south <dbl>Find all ZIP codes for a county
search_county('Ocean','NJ')
#> # A tibble: 32 × 24
#> zipcode zipcode_type major_city post_office_city common_city_list county
#> <chr> <chr> <chr> <chr> <blob> <chr>
#> 1 08005 Standard Barnegat Barnegat, NJ <raw 20 B> Ocean…
#> 2 08006 PO Box Barnegat Light Barnegat Light, … <raw 33 B> Ocean…
#> 3 08008 Standard Beach Haven Beach Haven, NJ <raw 61 B> Ocean…
#> 4 08050 Standard Manahawkin Manahawkin, NJ <raw 47 B> Ocean…
#> 5 08087 Standard Tuckerton Tuckerton, NJ <raw 51 B> Ocean…
#> 6 08092 Standard West Creek West Creek, NJ <raw 22 B> Ocean…
#> 7 08527 Standard Jackson Jackson, NJ <raw 19 B> Ocean…
#> 8 08533 Standard New Egypt New Egypt, NJ <raw 21 B> Ocean…
#> 9 08701 Standard Lakewood Lakewood, NJ <raw 20 B> Ocean…
#> 10 08721 Standard Bayville Bayville, NJ <raw 20 B> Ocean…
#> # … with 22 more rows, and 18 more variables: state <chr>, lat <dbl>,
#> # lng <dbl>, timezone <chr>, radius_in_miles <dbl>, area_code_list <blob>,
#> # population <int>, population_density <dbl>, land_area_in_sqmi <dbl>,
#> # water_area_in_sqmi <dbl>, housing_units <int>,
#> # occupied_housing_units <int>, median_home_value <int>,
#> # median_household_income <int>, bounds_west <dbl>, bounds_east <dbl>,
#> # bounds_north <dbl>, bounds_south <dbl>Find all ZIP codes for a city
search_city('Jersey City','NJ')
#> # A tibble: 13 × 24
#> zipcode zipcode_type major_city post_office_city common_city_list county
#> <chr> <chr> <chr> <chr> <blob> <chr>
#> 1 07097 Unique Jersey City <NA> <raw 23 B> Hudson Co…
#> 2 07302 Standard Jersey City Jersey City, NJ <raw 23 B> Hudson Co…
#> 3 07303 PO Box Jersey City <NA> <raw 23 B> Hudson Co…
#> 4 07304 Standard Jersey City Jersey City, NJ <raw 23 B> Hudson Co…
#> 5 07305 Standard Jersey City Jersey City, NJ <raw 23 B> Hudson Co…
#> 6 07306 Standard Jersey City Jersey City, NJ <raw 23 B> Hudson Co…
#> 7 07307 Standard Jersey City Jersey City, NJ <raw 23 B> Hudson Co…
#> 8 07308 PO Box Jersey City <NA> <raw 23 B> Hudson Co…
#> 9 07309 Standard Jersey City <NA> <raw 23 B> Hudson Co…
#> 10 07310 Standard Jersey City Jersey City, NJ <raw 23 B> Hudson Co…
#> 11 07311 Standard Jersey City Jersey City, NJ <raw 23 B> Hudson Co…
#> 12 07395 Unique Jersey City <NA> <raw 23 B> Hudson Co…
#> 13 07399 Unique Jersey City <NA> <raw 23 B> Hudson Co…
#> # … with 18 more variables: state <chr>, lat <dbl>, lng <dbl>, timezone <chr>,
#> # radius_in_miles <dbl>, area_code_list <blob>, population <int>,
#> # population_density <dbl>, land_area_in_sqmi <dbl>,
#> # water_area_in_sqmi <dbl>, housing_units <int>,
#> # occupied_housing_units <int>, median_home_value <int>,
#> # median_household_income <int>, bounds_west <dbl>, bounds_east <dbl>,
#> # bounds_north <dbl>, bounds_south <dbl>Find all ZIP codes for a timezone
search_tz('Eastern')
#> # A tibble: 14,025 × 24
#> zipcode zipcode_type major_city post_office_city common_city_list county
#> <chr> <chr> <chr> <chr> <blob> <chr>
#> 1 06001 Standard Avon Avon, CT <raw 16 B> Hartfo…
#> 2 06002 Standard Bloomfield Bloomfield, CT <raw 22 B> Hartfo…
#> 3 06010 Standard Bristol Bristol, CT <raw 19 B> Hartfo…
#> 4 06013 Standard Burlington Burlington, CT <raw 36 B> Hartfo…
#> 5 06016 Standard Broad Brook Broad Brook, CT <raw 46 B> Hartfo…
#> 6 06018 Standard Canaan Canaan, CT <raw 18 B> Litchf…
#> 7 06019 Standard Canton Canton, CT <raw 34 B> Hartfo…
#> 8 06020 Standard Canton Center Canton Center, CT <raw 25 B> Hartfo…
#> 9 06021 Standard Colebrook Colebrook, CT <raw 21 B> Litchf…
#> 10 06022 Standard Collinsville Collinsville, CT <raw 24 B> Hartfo…
#> # … with 14,015 more rows, and 18 more variables: state <chr>, lat <dbl>,
#> # lng <dbl>, timezone <chr>, radius_in_miles <dbl>, area_code_list <blob>,
#> # population <int>, population_density <dbl>, land_area_in_sqmi <dbl>,
#> # water_area_in_sqmi <dbl>, housing_units <int>,
#> # occupied_housing_units <int>, median_home_value <int>,
#> # median_household_income <int>, bounds_west <dbl>, bounds_east <dbl>,
#> # bounds_north <dbl>, bounds_south <dbl>Get all Census tracts for a given ZIP code
get_tracts('08731')
#> # A tibble: 6 × 3
#> ZCTA5 TRACT GEOID
#> <chr> <chr> <dbl>
#> 1 08731 732001 34029732001
#> 2 08731 732002 34029732002
#> 3 08731 732101 34029732101
#> 4 08731 732103 34029732103
#> 5 08731 732104 34029732104
#> 6 08731 733000 34029733000Documentation
Documentation for the current release is available here. See the reference section for full details on how to use each of the functions provided by zipcodeR.
Data Sources
This project was inspired by the excellent uszipcode library for Python and utilizes the same backend database released by its author under the MIT license. This project also incorporates open data from the U.S. Census Bureau and Department of Housing & Urban Development.
