get_brazil_municipality()
returns a tibble
with data
about Brazilian municipalities.
Arguments
- municipality
(optional) A
character
vector with the name of the municipalities. IfNULL
the function returns all municipalities (default:NULL
).- state
(optional) A
character
vector with the name of the states (default:NULL
).- year
(optional) An
integerish
number indicating the year of the data regarding the municipalities (default:2017
).- force
(optional) A
logical
flag indicating whether to force the download of the data again (default:FALSE
).
Value
A tibble
with the following columns:
region_code
: The region code.region
: The region name.state_code
: The state code.state
: The state name.federal_unit
: The state abbreviation.municipality_code
: The municipality code.municipality
: The municipality name.
Details
The data from this function is based on data from the Brazilian Institute
of Geography and Statistics (IBGE) via the
geobr
R package.
The geobr
package is produced by Brazil's Institute for
Applied Economic Research (IPEA) and access the
Brazilian Institute of Geography and Statistics (IBGE) data. You can see a
list of all geobr
datasets by running
geobr::list_geobr()
.
See also
Other Brazil functions:
get_brazil_fu()
,
get_brazil_municipality_code()
,
get_brazil_region()
,
get_brazil_region_code()
,
get_brazil_state()
,
get_brazil_state_by_utc()
,
get_brazil_state_capital()
,
get_brazil_state_code()
,
get_brazil_state_latitude()
,
get_brazil_state_longitude()
,
render_brazil_address()
Examples
get_brazil_municipality() |> dplyr::glimpse()
#> Rows: 5,570
#> Columns: 7
#> $ region_code <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1…
#> $ region <chr> "North", "North", "North", "North", "North", "North"…
#> $ state_code <int> 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, …
#> $ state <chr> "Rondônia", "Rondônia", "Rondônia", "Rondônia", "Ron…
#> $ federal_unit <chr> "RO", "RO", "RO", "RO", "RO", "RO", "RO", "RO", "RO"…
#> $ municipality_code <int> 1100015, 1100023, 1100031, 1100049, 1100056, 1100064…
#> $ municipality <chr> "Alta Floresta D'Oeste", "Ariquemes", "Cabixi", "Cac…
get_brazil_municipality(municipality = "Belém")
#> # A tibble: 3 × 7
#> region_code region state_code state federal_unit municipality_code
#> <int> <chr> <int> <chr> <chr> <int>
#> 1 1 North 15 Pará PA 1501402
#> 2 2 Northeast 25 Paraíba PB 2501906
#> 3 2 Northeast 27 Alagoas AL 2700805
#> # ℹ 1 more variable: municipality <chr>
get_brazil_municipality(municipality = "Belém", state = "Pará")
#> # A tibble: 1 × 7
#> region_code region state_code state federal_unit municipality_code
#> <int> <chr> <int> <chr> <chr> <int>
#> 1 1 North 15 Pará PA 1501402
#> # ℹ 1 more variable: municipality <chr>
get_brazil_municipality(municipality = c("Belém", "São Paulo"))
#> # A tibble: 4 × 7
#> region_code region state_code state federal_unit municipality_code
#> <int> <chr> <int> <chr> <chr> <int>
#> 1 1 North 15 Pará PA 1501402
#> 2 2 Northeast 25 Paraíba PB 2501906
#> 3 2 Northeast 27 Alagoas AL 2700805
#> 4 3 Southeast 35 São Paulo SP 3550308
#> # ℹ 1 more variable: municipality <chr>