R/read_capitals.R

In geobr: Download Official Spatial Data Sets of Brazil

#' Download data of state capitals
#'
#' @description
#' This function downloads either a spatial `sf` object with the location of the
#' municipal seats (sede dos municipios) of state capitals, or a `data.frame`
#' with the names and codes of state capitals. Data downloaded for the latest
#' available year.
#'
#' @template output
#' @template showProgress
#' @template cache
#' @template verbose
#'
#' @return An `"sf" "data.frame"` OR an `ArrowObject`
#'
#' @export
#'
#' @examplesIf identical(tolower(Sys.getenv("NOT_CRAN")), "true")
#' # Read spatial data with the  municipal seats of state capitals
#' capitals_sf <- read_capitals(output = "sf")
#'
read_capitals <- function(output = "sf",
                          showProgress = TRUE,
                          cache = TRUE,
                          verbose = TRUE){

  # check input
  checkmate::assert_logical(showProgress)

  # base data.frame of capitals
  df <- data.frame(name_muni = c("S\u00e3o Paulo", "Rio de Janeiro", "Belo Horizonte",
                           "Salvador", "Fortaleza", "Vit\u00f3ria", "Goi\u00e2nia", "Cuiab\u00e1",
                           "S\u00e3o Lu\u00eds",  "Teresina", "Recife", "Aracaju", "Jo\u00e3o Pessoa",
                           "Natal", "Macei\u00f3",  "Porto Alegre", "Curitiba", "Florian\u00f3polis",
                           "Bel\u00e9m",  "Manaus",  "Palmas", "Campo Grande", "Macap\u00e1",
                           "Rio Branco", "Boa Vista", "Bras\u00edlia", "Porto Velho"),
                   code_muni = c(3550308L, 3304557L, 3106200L, 2927408L, 2304400L,
                                 3205309L, 5208707L, 5103403L, 2111300L, 2211001L,
                                 2611606L, 2800308L, 2507507L, 2408102L, 2704302L,
                                 4314902L, 4106902L, 4205407L, 1501402L, 1302603L,
                                 1721000L, 5002704L, 1600303L, 1200401L, 1400100L,
                                 5300108L, 1100205L),
                   name_state = c("S\u00e3o Paulo", "Rio de Janeiro", "Minas Gerais",
                                  "Bahia", "Cear\u00e1", "Esp\u00edrito Santo", "Goi\u00e1s",
                                  "Mato Grosso", "Maranh\u00e3o",  "Piau\u00ed", "Pernambuco",
                                  "Sergipe", "Para\u00edba", "Rio Grande do Norte",
                                  "Alagoas", "Rio Grande do Sul", "Paran\u00e1",
                                  "Santa Catarina", "Par\u00e1", "Amazonas", "Tocantins",
                                  "Mato Grosso do Sul", "Amap\u00e1", "Acre", "Roraima",
                                  "Distrito Federal", "Rond\u00f4nia"),
                   code_state = c(35L, 33L, 31L, 29L, 23L, 32L, 52L, 51L, 21L, 22L,
                                  26L, 28L, 25L, 24L, 27L, 43L, 41L, 42L, 15L, 13L,
                                  17L, 50L, 16L, 12L, 14L, 53L, 11L)
                   )

  df <- df[order(df$code_muni, decreasing = FALSE), ]


  temp_output <- geobr::read_municipal_seat(
    code_muni = df$code_muni,
    year = 2010,
    showProgress = showProgress,
    output = output
    )

  return( temp_output )
}