ibgeR is a work in progress. The idea is to download and make available (in a tidy format) the data from the IBGE Cidades project.
As this is A WIP, contributions are welcome. GET requests for this are quite straightforward.
Proof of concept:
library(dplyr) # pipe
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
x <- httr::GET("https://servicodados.ibge.gov.br/api/v1/biblioteca?aspas=3&codmun=280030") %>%
xml2::read_html() %>%
rvest::html_text() %>%
jsonlite::fromJSON()
library(purrr)
df <- tibble(
municipio = map_chr(x, "MUNICIPIO", .null = NA_character_),
estado = map_chr(x, "ESTADO", .null = NA_character_),
history = map_chr(x, "HISTORICO", .null = NA_character_),
source_history = map_chr(x, "HISTORICO_FONTE", .null = NA_character_),
administrative_history = map_chr(x, "FORMACAO_ADMINISTRATIVA", .null = NA_character_),
locals = map_chr(x, "GENTILICO", .null = NA_character_)
) %>%
tidyr::separate(estado, into = c("state", "uf"), sep = " - ")
df
#> # A tibble: 1 x 7
#> municipio state uf history source_history administrative_h… locals
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 Aracaju Sergi… SE "Logo a… Aracaju (SE). … "Distrito criado… araca…There is a dataset of municipio codes, names and UFs included.
data("ibge_codes")
head(ibge_codes)
#> # A tibble: 6 x 4
#> codes municipio uf municipio_ascii
#> <int> <chr> <chr> <chr>
#> 1 1100015 Alta Floresta DOeste RO Alta Floresta DOeste
#> 2 1100023 Ariquemes RO Ariquemes
#> 3 1100031 Cabixi RO Cabixi
#> 4 1100049 Cacoal RO Cacoal
#> 5 1100056 Cerejeiras RO Cerejeiras
#> 6 1100064 Colorado do Oeste RO Colorado do Oeste