R/plot_results.R

In PoliticaArgentina/polArViz: Vizualization Functions for the polAr Universe

#' Grafica resultados (\emph{Plot results})
#'
#' @description
#' Función para graficar resultados de la elección
#'  (\emph{Function to plot election results})
#'
#' @param data un tibble guardado como objeto en el Enviroment luego de consultar \code{\link[electorAr]{get_election_data}} con parámetro
#'  \code{level} en \code{provincia}
#'  (\emph{tibble saved as an object in the Enviroment after querying \code{\link[electorAr]{get_election_data}} with \code{provincia} as
#'  \code{level} parameter}).
#'
#' @param national un boleano opcional para graficar elecciones presidenciales sin desagregar
#'  (\emph{an optional boolean to plot presidential elections without disaggregating}).
#'
#' @details \strong{REQUISITOS:}
#'
#' @details \strong{1}. El formato de \code{data} debe ser \code{long} para poder graficar. Si \code{data} es \emph{wide} se puede
#'  transformar con \code{\link[electorAr]{make_long}}
#'  (\emph{\code{long} format of \code{data} is required for plotting results. If \code{data} is in \emph{wide} format you can transform
#'  it with \code{\link[electorAr]{make_long}}})
#'
#' @details \strong{2.} \code{data} tiene que haber incorporando los nombres de las listas. Agreguelos con \code{\link[electorAr]{get_names}}
#'  (\emph{\code{data} must have party names. Add them with \code{\link[electorAr]{get_names}}})
#'
#' @details \strong{3.} \code{data} tiene que haber sido descargada con parametro \code{level = provincia} con la funcion \code{\link[electorAr]{get_election_data}}
#'  (\emph{\code{data} must have \code{level = provincia} wen downloading it with \code{\link[electorAr]{get_election_data}}})
#'
#' @return Devuelve un objeto de \code{class"gg" "ggplot"} que grafica el resultado de una eleccion condicional al nivel de agregacion de data
#'  (\emph{Returns an object of \code{class "gg" "ggplot"} that plots the election results conditional on the level of \code{data} aggregation.}).
#'
#' @examples
#'
#'  (data <- electorAr::tucuman_dip_gral_2017)
#'
#'
#'  data %>%
#'        electorAr::get_names() %>%
#'        plot_results()
#'
#' @seealso
#' \code{\link{tabulate_results}}
#'
#' @export

plot_results <- function(data,
                         national = FALSE){

  ## Check for internet coection
  attempt::stop_if_not(.x = curl::has_internet(),
                       msg = "Internet access was not detected. Please check your connection //
No se detecto acceso a internet. Por favor chequear la conexion.")



  level <- if(dim(data)[2] == 11) {

    c("departamento")

  } else if  (dim(data)[1]> 40){ #arbitrary number but large enough to think its provincial level for president election

    c("departamento")

  } else {
    c("provincia")
  }

  # Check parameters and data format

  assertthat::assert_that(level %in% c("provincia", "departamento"),
                          msg = glue::glue({level}," is not a valid level. Options are 'provincia' & 'departamento'"))

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



  if(level == "departamento"){
    assertthat::assert_that("coddepto" %in% colnames(data) | unique(data$category == "presi"),
                            msg = "data input is not at the correct level. Download it again with parameters:
  get_election_data(..., level = 'parameter')")

  }

  if(national == TRUE){
    assertthat::assert_that(unique(data$category == "presi"),
                            msg = "The bolean 'national = TRUE' is only for presidential elections.")
  }

  # ADD NAMES

  data <- if("nombre_lista" %in% names(data)){

    data

  }else{

    data <- data %>%  electorAr::get_names()

  }



  assertthat::assert_that("nombre_lista" %in% colnames(data),
                          msg = "you have to add party labes to 'data' using 'get_names()'")




  # FIX CORRUPT INPUT DATA
  data <- data %>%
    dplyr::mutate(votos = ifelse(is.na(votos), 0, votos)) # code 0 for NA votes (not reported!)

  ### summarize for presidential election

  data <-  if(national == TRUE & unique(data$category == "presi")){


    data %>%
      dplyr::group_by(category, round, year, listas , nombre_lista) %>%
      dplyr::summarise_at(.vars = "votos", .funs = sum) %>%
      dplyr::mutate(codprov = "00",
                    name_prov = "Argentina") %>%
      dplyr::ungroup()

  }else{

    data %>%
      dplyr::select(-electores) # Add here  for fixing bug with presidential elections.
    # Previous version drop variable afterwards

  }


  # DATA INPUT

  election_district <- if(unique(data$category == "presi")){
    "ARGENTINA"
  } else {
    unique(data$name_prov)
  }

  election_date <- unique(data$year)

  election_category <- data %>%
    dplyr::ungroup() %>%
    dplyr::select(category) %>%
    dplyr::distinct() %>%
    dplyr::mutate(value = dplyr::case_when(
      category == "dip" ~ "Diputado Nacional",
      category == "sen" ~ "Senador Nacional",
      category == "presi" ~ "Presidente de la Naci\u00F3n"
    )) %>%
    dplyr::pull()

  election_round <- data %>%
    dplyr::ungroup() %>%
    dplyr::select(round) %>%
    dplyr::distinct() %>%
    dplyr::mutate(value = dplyr::case_when(
      round == "gral" ~ "General",
      round == "paso" ~ "PASO",
      round == "balota" ~ "Balotaje"
    )) %>%
    dplyr::pull()



  ### Plots conditional to level selections

  if(level == "provincia" | national == TRUE){

    datos_prov<- data %>%
      dplyr::mutate(pct = votos/sum(votos)) %>%
      dplyr::ungroup()  %>%
      dplyr::mutate(listas_fct = as.factor(nombre_lista),
                    listas_fct = forcats::fct_reorder(listas_fct, pct))


    # hack for fill brewer palete

    colourCount = length(unique(datos_prov$listas_fct))
    getPalette = grDevices::colorRampPalette(RColorBrewer::brewer.pal(9, "Set1"))



    # plot
    ggplot2::ggplot(data = datos_prov ,
                    ggplot2::aes(x = listas_fct, y = pct,
                                 label = listas_fct)) +
      ggplot2::geom_col(show.legend = F, fill = getPalette(colourCount))  +
      ggplot2::geom_text(hjust = "inward") +
      ggplot2::coord_flip() +
      ggplot2::scale_y_continuous(labels = scales::percent) +
      ggplot2::labs(fill = "Listas",
                    y = "%",
                    title = glue::glue("{election_district} - {election_date}"),
                    subtitle = glue::glue("Elecci\u00F3n {election_round} - {election_category}"),
                    caption = "Fuente: polAr - Pol\u00EDtica Argentina usando R - https://electorarg.github.io/polAr") +
      ggthemes::theme_fivethirtyeight() +
      ggplot2::theme(axis.text.y =  ggplot2::element_blank(),
                     axis.title.y = ggplot2::element_blank(),
                     panel.spacing.x =ggplot2::unit(0, "cm"),
                     panel.spacing.y =ggplot2::unit(0, "cm"))



  }else{


    ##### DEPARTAMENTO

    # Load geo-grids for 'departamento'

    facet_select <-  grillas_geofacet %>%
      purrr::pluck(paste0(election_district))

    datos_depto <-  if(election_district == "BUENOS AIRES"){


      facet_select <-  grillas_geofacet %>%
        purrr::pluck(paste0("PBA"))


      data %>%
        dplyr::left_join(secciones_pba, by = "coddepto") %>%
        dplyr::ungroup() %>%
        dplyr::mutate(nombre_lista = forcats::fct_lump(f =nombre_lista,  n = 3,
                                                       w = votos,
                                                       other_level = "Otros")) %>%
        dplyr::group_by(seccion, codprov, nombre_lista) %>%
        dplyr::summarise_if(is.numeric, sum)  %>%
        dplyr::group_by(codprov, seccion) %>%
        dplyr::mutate(pct = votos/sum(votos)) %>%
        dplyr::ungroup()  %>%
        dplyr::mutate(listas_fct = as.factor(nombre_lista),
                      listas_fct = forcats::fct_reorder(listas_fct, dplyr::desc(pct)))



    }else if(unique(data$category) == "presi"){

      data %>%
        dplyr::ungroup() %>%
        dplyr::mutate(nombre_lista = forcats::fct_lump(f =nombre_lista,  n = 3,
                                                       w = votos,
                                                       other_level = "Otros")) %>%
        dplyr::group_by(codprov, nombre_lista) %>%
        dplyr::summarise(votos = sum(votos)) %>%
        dplyr::mutate(pct = votos/sum(votos)) %>%
        dplyr::ungroup()  %>%
        dplyr::mutate(listas_fct = as.factor(nombre_lista),
                      listas_fct = forcats::fct_reorder(listas_fct, dplyr::desc(pct)))

    } else{


      data %>%
        dplyr::ungroup() %>%
        dplyr::mutate(nombre_lista = forcats::fct_lump(f =nombre_lista,  n = 3,
                                                       w = votos,
                                                       other_level = "Otros")) %>%
        dplyr::group_by(codprov, coddepto, nombre_lista) %>%
        dplyr::summarise(votos = sum(votos)) %>%
        dplyr::mutate(pct = votos/sum(votos)) %>%
        dplyr::ungroup()  %>%
        dplyr::mutate(listas_fct = as.factor(nombre_lista),
                      listas_fct = forcats::fct_reorder(listas_fct, dplyr::desc(pct)))




    }
    # hack for fill brewer palete
    colourCount = length(unique(datos_depto$listas_fct))
    getPalette = grDevices::colorRampPalette(RColorBrewer::brewer.pal(9, "Set1"))


    # plot


    base_plot_depto <- ggplot2::ggplot(data = datos_depto ,
                                       ggplot2::aes("", y = pct, fill = listas_fct)) +
      ggplot2::geom_col(show.legend = T, alpha = 0.85, width = 1) +
      ggplot2::scale_y_continuous(expand = c(0,0), labels = scales::percent,
                                  breaks =  c(.5, 1)) +
      ggplot2::scale_fill_manual(values = getPalette(colourCount)) +
      ggplot2::labs(fill = "",
                    y = "% votos",
                    title = glue::glue("{election_district} - {election_date}"),
                    subtitle = glue::glue("Elecci\u00F3n {election_round} - {election_category}"),
                    caption = "Fuente: polAr - Pol\u00EDtica Argentina usando R - https://electorarg.github.io/polAr") +
      ggplot2::theme_minimal() +
      ggplot2::theme(axis.text.x = ggplot2::element_blank(),
                     axis.title.x = ggplot2::element_blank(),
                     axis.ticks.x = ggplot2::element_blank(),
                     legend.position = "bottom",
                     aspect.ratio = .8,
                     legend.key.size = ggplot2::unit(0.2, "cm"),
                     legend.key.width = ggplot2::unit(0.2,"cm"),
                     panel.spacing.x =ggplot2::unit(0, "cm"),
                     panel.spacing.y =ggplot2::unit(0, "cm"),
                     strip.text = ggplot2::element_text(size = 7)) +
      ggplot2::guides(fill = ggplot2::guide_legend(nrow = 5))


    if("coddepto" %in% colnames(datos_depto)){

      suppressMessages(base_plot_depto + geofacet::facet_geo(~ coddepto, grid = facet_select, label = "name"))

    }else if("seccion" %in% colnames(datos_depto)){

      suppressMessages(base_plot_depto + geofacet::facet_geo(~ seccion, grid = facet_select, label = "name"))

    } else {

      suppressMessages(base_plot_depto + geofacet::facet_geo(~ codprov, grid = facet_select, label = "name"))

    }  # Close departament geofacet
  } # close conditional ploting
} #close function