The U.S. Department of Transportation partners with address programs from state, local, and tribal governments to compile their authoritative data into a database. Find more information here: https://www.transportation.gov/gis/national-address-database
nad_read() reads data from the NAD geodatabase by county,
using source data already downloaded with nad_download() or downloading
it when refresh_source = "yes", and readies it for R.
Counties can be identified either by county name plus state, or by a
5-digit county FIPS identifier. County names and state abbreviations are
resolved internally and still determine the cache path and source query.
The NAD geodatabase has a very large size on disk (~10 GB).
Data binaries are the cached outputs of nad_read() for each
County/State and are created on first run with nad().
Download data binaries to the tools::R_user_dir() data directory, or
point R to these files on disk, to read NAD tables without downloading the
nationwide NAD geodatabase.
(Files are organized by major package version,
NAD version, state, and named by county; e.g., see
list.files(tools::R_user_dir("addr", "data"), recursive = TRUE))
Arguments
- county
character, length one; county name or 5-digit county FIPS identifier
- state
character, length one; name or abbreviation of state. Required when
countyis a county name; ignored whencountyis a 5-digit county FIPS identifier- version
integer, length one; NAD revision to use. Defaults to
22L, revision 22 of the National Address Database.- refresh_binary
character, length one; choose how to refresh NAD data binaries cached on disk if not already present; "yes" will create data binary if not already present, "no" will error if data binary is not already present, "force" will create the data binary and overwrite any existing data binary
- refresh_source
character, length one; choose how to refresh NAD source geodatabase on disk if not already present; "yes" will download the geodatabase if not already present, "no" will error if the file does not already exist, "force" will download and overwrite any existing geodatabase
Details
NAD source geodatabases are downloaded from the transportation.gov data
portal:
https://data.transportation.gov/d/yw36-suxr
Downloads use the R curl package and resume from any interrupted
partial download left in the addr user data directory.
If the download cannot complete, nad_download() will also work with a
NAD ZIP file that was downloaded another way and placed where
tools::R_user_dir("addr", "data") can find it.
For the original schema, see
https://www.transportation.gov/sites/dot.gov/files/2023-07/NAD_Schema_202304.pdf
Before downloading, please read the disclaimer here:
https://www.transportation.gov/mission/open/gis/national-address-database/national-address-database-nad-disclaimer
Investigate individual address points in the online viewer: https://usdot.maps.arcgis.com/apps/instant/portfolio/index.html?appid=59f7e4fb71994d13b61f424e21a6cffe
The NAD does not distinguish between empty and missing address components.
When reading into R, all missing address components are replaced with an
empty string ("") except for address number (digits), street name,
and ZIP code.
Addresses with malformed ZIP codes are removed.
Examples
# explicitly download source data, then cache county output on first read
if (FALSE) { # \dontrun{
nad_download(version = 22L)
nad("Butler", "OH")
nad("39017")
} # }
# example data preloaded for Hamilton County, OH
# works without downloading NAD gdb first
Sys.setenv(R_USER_DATA_DIR = tempfile())
nad("Hamilton", "OH", refresh_source = "no", refresh_binary = "no")
#> # A tibble: 349,407 × 7
#> nad_addr subaddress uuid date_update s2 address_type parcel_id
#> <addr> <chr> <chr> <date> <s2c> <chr> <chr>
#> 1 7610 THOMPSON Rd C… NA {68A… 2025-03-30 8840… Unknown NA
#> 2 9483 ZOLA Ct HARRI… NA {CBF… 2025-03-30 8840… Unknown NA
#> 3 208 MOHAWK St CINC… NA {B18… 2025-03-30 8841… Unknown NA
#> 4 11800 READING Rd C… NA {393… 2025-03-30 8840… Unknown NA
#> 5 12050 PRINCETON Pi… NA {478… 2025-03-30 8840… Unknown NA
#> 6 6610 PFEIFFER Rd C… NA {947… 2025-03-30 8840… Unknown NA
#> 7 6501 PFEIFFER Rd C… NA {998… 2025-03-30 8840… Unknown NA
#> 8 4244 ROUND BOTTOM … NA {5F5… 2025-03-30 8841… Unknown NA
#> 9 8210 MARKET PLACE … NA {C01… 2025-03-30 8840… Unknown NA
#> 10 8212 MARKET PLACE … NA {2A8… 2025-03-30 8840… Unknown NA
#> # ℹ 349,397 more rows
nad("39061", refresh_source = "no", refresh_binary = "no")
#> # A tibble: 349,407 × 7
#> nad_addr subaddress uuid date_update s2 address_type parcel_id
#> <addr> <chr> <chr> <date> <s2c> <chr> <chr>
#> 1 7610 THOMPSON Rd C… NA {68A… 2025-03-30 8840… Unknown NA
#> 2 9483 ZOLA Ct HARRI… NA {CBF… 2025-03-30 8840… Unknown NA
#> 3 208 MOHAWK St CINC… NA {B18… 2025-03-30 8841… Unknown NA
#> 4 11800 READING Rd C… NA {393… 2025-03-30 8840… Unknown NA
#> 5 12050 PRINCETON Pi… NA {478… 2025-03-30 8840… Unknown NA
#> 6 6610 PFEIFFER Rd C… NA {947… 2025-03-30 8840… Unknown NA
#> 7 6501 PFEIFFER Rd C… NA {998… 2025-03-30 8840… Unknown NA
#> 8 4244 ROUND BOTTOM … NA {5F5… 2025-03-30 8841… Unknown NA
#> 9 8210 MARKET PLACE … NA {C01… 2025-03-30 8840… Unknown NA
#> 10 8212 MARKET PLACE … NA {2A8… 2025-03-30 8840… Unknown NA
#> # ℹ 349,397 more rows