R/compute_concentration.R

In PoliticaArgentina/electorAr: Toolbox for Argentina's Electoral Data

#' Calcula Concentración Elecotral
#'  (\emph{Computes Electoral Concentration})
#'
#' @description
#' Calcula el índice de concentración electoral de una elección en función del porecentaje acumulado de las dos listas más votadas
#'
#'  (\emph{Computes the electoral concentration index of an election based on the accumulated percentage of the two most voted lists})
#'
#' @param data la base de datos para hacer el cálculo obtenida con \code{\link{get_election_data}}
#'
#'  (\emph{tiblle downloaded with \code{\link{get_election_data}} needed to compute disproportion}).#'
#' @details \strong{REQUISITO:}
#'
#' @details El formato de \code{data} debe ser \code{long} para calcular \code{\link{compute_concentration}}.
#'  Si \code{data} es \emph{wide} se puede transformar con \code{\link{make_long}}
#'
#'  (\emph{\code{long} format of \code{data} is required for \code{\link{compute_concentration}}.
#'  If \code{data} is in \emph{wide} format you can transform it with \code{\link{make_long}}})
#'
#' @details \strong{NOTA:}
#'
#' @details el grado de concentración será sensible al nivel de agregación de los datos determinados por el parámetro \code{level} de
#' \code{\link{get_election_data}}
#'
#'  (\emph{the degree of concentration will be sensitive to the level of aggregation of the data determined by the parameter \code{level} of
#'   \code{\link{get_election_data}}}).
#'
#' @seealso  \code{\link{compute_competitiveness}, \link{compute_seats}, \link{compute_nep}, \link{compute_disproportion} }
#'
#' @return  Devuelve un tibble con \code{class "tbl_df","tbl", "data.frame"} con el cómputo de concentración. Puede tomar valores entre \code{0} y \code{1},
#' siendo \code{concentracion = 1} el de mayor grado (un solo partido obtiene todos los votos).
#'
#'  (\emph{Returns a tibble with \code{class "tbl_df", "tbl", "data.frame"} with concentration computation. It can take values between \code{0}, \code{1},
#'  with \code{concentration = 1} being the highest degree (a single party gets all the votes)}).
#'
#' @examples
#'
#' tucuman_dip_gral_2017
#'
#' tucuman_dip_gral_2017 %>%
#'   compute_concentration()
#'
#' @export

compute_concentration <- function(data){

  assertthat::assert_that(is.data.frame(data),
                          msg = glue::glue("data is not a valid object. You can download a valid data.frame with get_election_data()"))


  assertthat::assert_that("listas" %in% colnames(data),
                          msg = "data is not in a long format. Use 'make_long()' to transform it")


  # Temp function:  level selection

  levels <- function(level = ""){

    # Replace if_elses with case_when
    dplyr::case_when(
      level == "provincia" ~ c("codprov", "name_prov"),
      level == "departamento" ~ c("codprov, name_prov, depto, coddepto"),
      level == "circuito" ~ c("codprov, name_prov, depto, coddepto, circuito"),
      T ~c("codprov")
    )

  }


  level <- if("circuito" %in% names(data)) {

    "circuito"

  } else if("depto" %in% names(data) & length(data) < 11) {

    "departamento"

  } else {

    "provincia"
    }

  levels <- stringr::str_split(string = levels(level = level), pattern = "\\,")
  levels <- stringr::str_squish(levels[[1]])


  # Get election metadata
  year <- unique(data$year)
  category <- unique(data$category)
  round <- unique(data$round)
  codprov <- unique(data$codprov)


  data <- data %>%
    dplyr::mutate(pct = votos/sum(votos)) %>%
    dplyr::arrange(dplyr::desc(pct)) %>%
    dplyr::slice(1:2) %>%
    dplyr::group_by_at( levels) %>%
    dplyr::summarise(concentration = round(sum(pct),2)) %>%
    dplyr::mutate(year = year ,
                  category = category,
                  round = round,
                  codprov = codprov)

  return(data)

  }