R/uflist.R

In owdbr: Open Welfare Data Brazil

#' All the State's UF Codes.
#'
#' Returns a tibble which contains the IBGE identification code of each one of all 23 UFs (Units of the Federation) in Brazil.
#'
#' @param region filter the UFs (Units of the Federation or States) by geographical region. If NA, all state are shown. According to the Brazilian Institute of Geography and Statistics, the country is divided in 5 regions: "Norte", "Nordeste", "Centro-Oeste", "Sul" and "Sudeste".
#'
#' @return a tibble with 3 columns.
#' \describe{
#'    \item{State}{The full name of the state.}
#'    \item{UF}{The abbreviation of the state's name.}
#'    \item{num}{The identification number of the state.}
#'    \item{region}{Region of the country in which the State is located.}
#' }
#'
#' @examples
#' \dontrun{
#' uflist(reg = NA) # show all states of the country.
#' uflist(region = "Sul") # only exhibit States in the 'Sul' region of the country.
#' }
#' @author Joao Pedro Oliveira dos Santos, International Relations Institute, Pontifical Catholic University of Rio de Janeiro
#'
#' @export
#'
#' @references Source: \href{https://cidades.ibge.gov.br}{IBGE (Brazilian Institute of Geography and Statistics)}

uflist <- function(region = NA) {
  State <-
    c(
      "Acre",
      "Alagoas",
      "Amapa",
      "Amazonas",
      "Bahia",
      "Ceara",
      "Espirito Santo",
      "Goias",
      "Maranhao",
      "Mato Grosso",
      "Mato Grosso do Sul",
      "Minas Gerais",
      "Para",
      "Paraiba",
      "Parana",
      "Pernambuco",
      "Piaui",
      "Rio de Janeiro",
      "Rio Grande do Norte",
      "Rio Grande do Sul",
      "Rondonia",
      "Roraima",
      "Santa Catarina",
      "Sao Paulo",
      "Sergipe",
      "Tocantins",
      "Distrito Federal"
    )
  UF <-
    c(
      "AC",
      "AL",
      "AP",
      "AM",
      "BA",
      "CE",
      "ES",
      "GO",
      "MA",
      "MT",
      "MS",
      "MG",
      "PA",
      "PB",
      "PR",
      "PE",
      "PI",
      "RJ",
      "RN",
      "RS",
      "RO",
      "RR",
      "SC",
      "SP",
      "SE",
      "TO",
      "DF"
    )
  num <- c(
    12,
    27,
    16,
    13,
    29,
    23,
    32,
    52,
    21,
    51,
    50,
    31,
    15,
    25,
    41,
    26,
    22,
    33,
    24,
    43,
    11,
    14,
    42,
    35,
    28,
    17,
    53
  )
  regiao <- c(
    "Norte",
    "Nordeste",
    "Norte",
    "Norte",
    "Nordeste",
    "Nordeste",
    "Sudeste",
    "Centro-Oeste",
    "Nordeste",
    "Centro-Oeste",
    "Centro-Oeste",
    "Sudeste",
    "Norte",
    "Nordeste",
    "Sul",
    "Nordeste",
    "Nordeste",
    "Sudeste",
    "Nordeste",
    "Sul",
    "Norte",
    "Norte",
    "Sul",
    "Sudeste",
    "Nordeste",
    "Norte",
    "Centro-Oeste"
  )

  regf <- region
  df <- tibble::as_tibble(data.frame(State, UF, num, regiao))

  if (is.na(region) != TRUE) {
    dplyr::filter(df, df$regiao == regf) -> df
  }
  return(df)
}