Tidygeocoder makes getting data from geocoder services easy. A unified high-level interface is provided for the supported geocoder services and results are returned in tibble (dataframe) format. For details see the usage example below, the Getting Started Vignette, and blog posts on tidygeocoder.

Features:

• Both forward geocoding (addresses ⮕ coordinates) and reverse geocoding (coordinates ⮕ addresses) are supported.
• Batch geocoding (geocoding multiple addresses or coordinates in a single query) is used by default if supported by the geocoder service when multiple inputs (addresses or coordinates) are provided (with some noted exceptions for services with slower batch geocoding).
• Duplicate, NA, and blank input data is handled elegantly; only unique inputs are submitted in queries, but the rows in the original data are preserved by default.
• The rate of querying is automatically slowed in order to comply with API usage policies.

To install the stable version from CRAN (the official R package servers):

install.packages('tidygeocoder')

Alternatively, you can install the latest development version from GitHub:

devtools::install_github("jessecambon/tidygeocoder")

In this example we will geocode a few addresses using the geocode() function and plot them on a map with ggplot.

library(dplyr)
library(tibble)
library(tidygeocoder)

# create a dataframe with addresses
some_addresses <- tribble(
~name,                  ~addr,
"White House",          "1600 Pennsylvania Ave NW, Washington, DC",
"Transamerica Pyramid", "600 Montgomery St, San Francisco, CA 94111",     
"Willis Tower",         "233 S Wacker Dr, Chicago, IL 60606"                                  
)

# geocode the addresses
lat_longs <- some_addresses %>%
  geocode(addr, method = 'osm', lat = latitude , long = longitude)

The geocode() function attaches latitude and longitude columns to our input dataset of addresses. The Nominatim (“osm”) geocoder is used here, but other services can be specified with the method argument. See the geo() function documentation for details.

Now that we have the longitude and latitude coordinates, we can use ggplot to plot our addresses on a map.

library(ggplot2)
library(maps)
library(ggrepel)

ggplot(lat_longs, aes(longitude, latitude), color = "grey99") +
  borders("state") + geom_point() + 
  geom_label_repel(aes(label = name)) + 
  theme_void()

To return the full results from a geocoder service (not just latitude and longitude) you can use full_results = TRUE. Additionally, for the Census geocoder you can use return_type = 'geographies' to return geography columns (state, county, Census tract, and Census block).

full <- some_addresses %>%
  geocode(addr, method = 'census', full_results = TRUE, 
          return_type = 'geographies')

To perform reverse geocoding (obtaining addresses from latitude and longitude coordinates), we can use the reverse_geocode() function. The arguments are similar to the geocode() function, but we now are specifying the latitude and longitude columns in our dataset with the lat and long arguments. The single line address is returned in a column named by the address argument. See the reverse_geo() function documentation for more details on reverse geocoding.

rev1 <- lat_longs %>%
  reverse_geocode(lat = latitude, long = longitude, method = 'osm',
                  address = address_found, full_results = TRUE)

For further documentation, refer to the Getting Started Vignette and the function documentation.

A few articles that use tidygeocoder in their code:

• Exercises: Spatial Data Wrangling with sf
• Mapping a network of women in demography
• Road Routing in R
• Mapping Texas Ports With R

Contributions to the tidygeocoder package are welcome. File an issue for bug fixes or suggested features. If you would like to add support for a new geocoder service, reference the developer notes for instructions.

citation('tidygeocoder')

To cite tidygeocoder in publications use:

  Jesse Cambon, Christopher Belanger (2021). tidygeocoder: Geocoding
  Made Easy (version 1.0.2). DOI: 10.5281/zenodo.4448251. URL:
  https://CRAN.R-project.org/package=tidygeocoder

A BibTeX entry for LaTeX users is

  @Misc{,
    title = {tidygeocoder: Geocoding Made Easy},
    author = {Jesse Cambon and Christopher Belanger},
    year = {2021},
    publisher = {Zenodo},
    note = {R package version 1.0.2},
    url = {https://CRAN.R-project.org/package=tidygeocoder},
    doi = {10.5281/zenodo.4448251},
  }

Or refer to the citation page.