zipcodeR

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

# Load zipcodeR into R
library(zipcodeR)
#> Warning: package 'zipcodeR' was built under R version 4.3.2

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…
#> # ℹ 722 more rows
#> # ℹ 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>, …

Calculate the distance between two ZIP codes in miles

zip_distance('08901','08731')
#>   zipcode_a zipcode_b distance
#> 1     08901     08731     40.7

Calculate 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     8.06

Geocode a ZIP code to get its centroid

geocode_zip('08901')
#> # A tibble: 1 × 3
#>   zipcode   lat   lng
#>   <chr>   <dbl> <dbl>
#> 1 08901    40.5 -74.4

Get 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   
#> # ℹ 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…
#> # ℹ 22 more rows
#> # ℹ 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>, …

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…
#> # ℹ 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…
#> # ℹ 14,015 more rows
#> # ℹ 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>, …

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 34029733000

Documentation

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.