Get Brazilian municipalities geographic coordinates

brazil_municipality_coords() returns a tibble with the latitude and longitude coordinates of Brazilian municipalities.

Note: This function requires an internet connection to work and the geobr or geocodebr package to be installed, depending on the chosen method for retrieving coordinates.

Usage

brazil_municipality_coords(
  municipality_code = NULL,
  year = as.numeric(substr(Sys.Date(), 1, 4)),
  coords_method = "geobr",
  force = FALSE
)

Arguments

municipality_code

(optional) An integerish vector with the IBGE codes of Brazilian municipalities. Use brazil_municipality_code() to obtain codes from municipality names and states. If NULL the function returns all municipalities (default: NULL).

year

(optional) An integerish number indicating the year of the data regarding the municipalities (default: Sys.Date() |> substr(1, 4) |> as.numeric()).

coords_method

(optional) A string indicating the method to retrieve the latitude and longitude coordinates of the municipalities (default: "geobr"). Options are:

• "geobr": Uses read_municipal_seat() from the geobr package to retrieve the coordinates.

• "geocodebr": Uses the geocode() from the geocodebr package to retrieve the coordinates.

force

(optional) A logical flag indicating whether to force the download of the data again (default: FALSE).

Value

A tibble with the following columns:

• municipality_code: The municipality code.

• latitude: The municipality latitude.

• longitude: The municipality longitude.

Details

The data from this function is based on data from the Brazilian Institute of Geography and Statistics (IBGE) via the geobr and geocodebr R packages.

Both packages are produced by Brazil's Institute for Applied Economic Research (IPEA) and access the Brazilian Institute of Geography and Statistics (IBGE) data.

See also

Other Brazil functions: brazil_fu(), brazil_municipality(), brazil_municipality_code(), brazil_municipality_latitude(), brazil_municipality_longitude(), brazil_region(), brazil_region_code(), brazil_render_address(), brazil_state(), brazil_state_by_utc(), brazil_state_capital(), brazil_state_code(), brazil_state_latitude(), brazil_state_longitude()

Examples

library(curl)

# \dontrun{
  if (has_internet()) {
    brazil_municipality_coords()
  }
#> ! The closest map year to 2025 is 2010. Using year 2010 instead.
#> Using year/date 2010
#> # A tibble: 5,565 × 3
#>   municipality_code latitude longitude
#>               <dbl>    <dbl>     <dbl>
#> 1           1100015   -11.9      -62.0
#> 2           1100023    -9.91     -63.0
#> 3           1100031   -13.5      -60.5
#> 4           1100049   -11.4      -61.4
#> 5           1100056   -13.2      -60.8
#> 6           1100064   -13.1      -60.6
#> # ℹ 5,559 more rows
# }

# \dontrun{
  if (has_internet()) {
    brazil_municipality_coords(municipality_code = 3550308)
  }
#> ! The closest map year to 2025 is 2010. Using year 2010 instead.
#> Using year/date 2010
#> # A tibble: 1 × 3
#>   municipality_code latitude longitude
#>               <dbl>    <dbl>     <dbl>
#> 1           3550308    -23.6     -46.6
# }

# \dontrun{
  if (has_internet()) {
    brazil_municipality_coords(municipality_code = 3550)
  }
#> ! The closest map year to 2025 is 2010. Using year 2010 instead.
#> Using year/date 2010
#> # A tibble: 10 × 3
#>   municipality_code latitude longitude
#>               <dbl>    <dbl>     <dbl>
#> 1           3550001    -23.2     -45.3
#> 2           3550100    -22.7     -48.6
#> 3           3550209    -23.9     -48.0
#> 4           3550308    -23.6     -46.6
#> 5           3550407    -22.5     -47.9
#> 6           3550506    -22.8     -49.7
#> # ℹ 4 more rows
# }

# \dontrun{
  if (has_internet()) {
    brazil_municipality_coords(municipality_code = c(3550308, 3304557))
  }
#> ! The closest map year to 2025 is 2010. Using year 2010 instead.
#> Using year/date 2010
#> # A tibble: 2 × 3
#>   municipality_code latitude longitude
#>               <dbl>    <dbl>     <dbl>
#> 1           3304557    -22.9     -43.2
#> 2           3550308    -23.6     -46.6
# }