Takes a dataframe containing addresses as an input and returns
the results from a specified geocoding service in a dataframe format using the
geo function. See example usage in vignette("tidygeocoder")
.
This function passes all additional parameters (...
) to the
geo function, so you can refer to its documentation for more details
on possible arguments.
Note that the arguments used for specifying address columns (address
,
street
, city
, county
, state
, postalcode
, and country
) accept either
quoted or unquoted column names (ie. "address_col"
and address_col
are
both acceptable).
geocode( .tbl, address = NULL, street = NULL, city = NULL, county = NULL, state = NULL, postalcode = NULL, country = NULL, lat = "lat", long = "long", return_input = TRUE, limit = 1, return_addresses = NULL, unique_only = FALSE, ... )
.tbl | dataframe containing addresses |
---|---|
address | single line street address column name. Do not combine with
address component arguments ( |
street | street address column name |
city | city column name |
county | county column name |
state | state column name |
postalcode | postalcode column name (zip code if in the United States) |
country | country column name |
lat | latitude column name. Can be quoted or unquoted (ie. lat or 'lat'). |
long | longitude column name. Can be quoted or unquoted (ie. long or 'long'). |
return_input | if TRUE then the input dataset will be combined with the geocoder query results and returned. If FALSE only the geocoder results will be returned. |
limit | maximum number of results to return per input address. For many geocoding services
the maximum value of the limit parameter is 100. Pass |
return_addresses | if TRUE return input addresses. Defaults to TRUE if |
unique_only | if TRUE then only unique results will be returned and return_input will be set to FALSE. |
... | arguments passed to the geo function |
tibble (dataframe)
# \donttest{ library(dplyr, warn.conflicts = FALSE) sample_addresses %>% slice(1:2) %>% geocode(addr, method = 'arcgis')#>#>#> # A tibble: 2 × 4 #> name addr lat long #> <chr> <chr> <dbl> <dbl> #> 1 White House 1600 Pennsylvania Ave NW Washington, DC 38.9 -77.0 #> 2 Transamerica Pyramid 600 Montgomery St, San Francisco, CA 94111 37.8 -122.louisville %>% head(2) %>% geocode(street = street, city = city, state = state, postalcode = zip, method = 'census', full_results = TRUE)#>#>#> # A tibble: 2 × 15 #> street city state zip latitude longitude lat long id input_address #> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <int> <chr> #> 1 2722 ELLIOTT AVE Loui… Kent… 40211 38.3 -85.8 38.3 -85.8 1 2722 ELLIOTT… #> 2 850 WASHBURN AVE Loui… Kent… 40222 38.3 -85.6 38.3 -85.6 2 850 WASHBURN… #> # … with 5 more variables: match_indicator <chr>, match_type <chr>, #> # matched_address <chr>, tiger_line_id <int>, tiger_side <chr>sample_addresses %>% slice(8:9) %>% geocode(addr, method = 'osm', limit = 2, return_input = FALSE, full_results = TRUE)#>#>#> # A tibble: 4 × 13 #> address lat long place_id licence osm_type osm_id boundingbox display_name #> <chr> <dbl> <dbl> <int> <chr> <chr> <dbl> <list> <chr> #> 1 Istanbu… 41.0 29.0 1.70e7 Data ©… node 1.88e9 <chr [4]> İstanbul, F… #> 2 Istanbu… 41.1 29.1 2.82e8 Data ©… relation 2.23e5 <chr [4]> İstanbul, M… #> 3 Tokyo, … 35.7 140. 2.83e8 Data ©… relation 1.54e6 <chr [4]> 東京都, 日本 #> 4 Tokyo, … 35.7 140. 6.99e7 Data ©… node 6.40e9 <chr [4]> 東京, 丸の… #> # … with 4 more variables: class <chr>, type <chr>, importance <dbl>, #> # icon <chr>sample_addresses %>% slice(4:5) %>% geocode(addr, method = 'arcgis', lat = latitude, long = longitude, full_results = TRUE)#>#>#> # A tibble: 2 × 12 #> name addr latitude longitude arcgis_address score location.x location.y #> <chr> <chr> <dbl> <dbl> <chr> <int> <dbl> <dbl> #> 1 Willi… 233 S W… 41.9 -87.6 233 S Wacker D… 100 -87.6 41.9 #> 2 Chate… 1 Rue d… 46.8 -71.2 1 Rue des Carr… 100 -71.2 46.8 #> # … with 4 more variables: extent.xmin <dbl>, extent.ymin <dbl>, #> # extent.xmax <dbl>, extent.ymax <dbl># }