R/plot_ctr_process.R

In Edouard-Legoupil/unhcrdatapackage: UNHCR Population Statistics Database with Chart Library and Factsheet Template

# WARNING - Generated by {fusen} from /dev/dev_plot_Country.Rmd: do not edit by hand

#' Asylum Processing
#' 
#' Displaying Asylum processing 
#' 
#' @param year Numeric value of the year (for instance 2020)
#' @param country_asylum_iso3c Character value with the ISO-3 character code of the Country of Asylum
#' @param otherprop value set by default to .02 - used to merge origin as "Other"
#' 
#' 
#' @importFrom ggplot2  ggplot  aes  coord_flip   element_blank element_line
#'             element_text expansion geom_bar geom_col geom_hline unit stat_summary
#'             geom_label geom_text labs  position_stack  scale_color_manual scale_colour_manual 
#'             geom_text guide_axis facet_wrap vars theme_void
#'             scale_fill_manual scale_x_continuous scale_x_discrete  scale_y_continuous   sym theme  
#' @importFrom utils  head
#' @importFrom tidyselect where
#' @importFrom stringr  str_replace str_wrap
#' @importFrom scales cut_short_scale label_percent label_number breaks_pretty
#' @importFrom stats  reorder aggregate 
#' @importFrom dplyr  desc select  case_when lag mutate group_by filter summarise ungroup
#'               pull distinct n arrange across slice left_join rename count
#' @importFrom tidyr pivot_longer
#' @importFrom forcats fct_relevel
#' @importFrom  ggforce geom_parallel_sets geom_parallel_sets_axes  
#'                  geom_parallel_sets_labels gather_set_data
#' @importFrom unhcrthemes theme_unhcr
#' 
#' @return a ggplot2 object
#' 
#' @export 
#' @examples
#' plot_ctr_process(year = 2022,   country_asylum_iso3c = "BOL")
#' 
#' plot_ctr_process(year = 2022,   country_asylum_iso3c = "CHL")
#' 
#' 
#' plot_ctr_process(year = 2022,   country_asylum_iso3c = "USA",
#'                               otherprop = .02)
#' 
#' plot_ctr_process(year = 2022,   country_asylum_iso3c = "USA",
#'                               otherprop = .04)
#' 
#' 
plot_ctr_process <- function(year = 2022,
                             country_asylum_iso3c,
                             otherprop = .02){
  

  #table(as.factor(ForcedDisplacementStat::asylum_decisions_long$CountryAsylumCode))
  
  links <- ForcedDisplacementStat::asylum_decisions_long |>
    filter(Year == year   & CountryAsylumCode  == country_asylum_iso3c ) |> 
    dplyr::mutate(CountryOriginName = forcats::fct_lump_prop(CountryOriginName,
                                                             prop = otherprop, 
                                                             w = Value)) |>
    ## Group small records under other
    ## Calculate grouped value for Origin to procedure..
    group_by(CountryOriginName, ProcedureName, DecisionTypeName,Decision.output ) |>
    summarise(n = sum(Value, na.rm = TRUE) )  
  # levels(links$Decision.output)
  
  ## Case no record outut a ggplot2 object with anotation
  if( nrow(links) == 0) {
    info <-  paste0("There\'s no recorded Asylum Decisions \n in ", ForcedDisplacementStat::reference |>
             dplyr::filter( iso_3 == country_asylum_iso3c) |>
             dplyr::pull(ctryname) , " for ", year)
    p <- ggplot() +  annotate(stringr::str_wrap("text", 80), 
                              x = 1, y = 1, size = 11,  
                              label = info ) +  theme_void() 
    
  } else {

  ## summarize data
 flow_table <- links  |>
  ggforce::gather_set_data(x = c("CountryOriginName","ProcedureName","DecisionTypeName","Decision.output") ) 


  flow_table$Decision.output <- factor(flow_table$Decision.output,
                                  levels = c("Rejected",
                                             "ComplementaryProtection",
                                             "Recognized",    
                                             "OtherwiseClosed"))
## plot your dataset 
  ## on the x axis is the start and end causes
  ## gather_set_data generates an ID for each possible combination
  ## splitting by y gives the possible start/end combos
  ## value as n gives it as counts (could also be changed to proportion)
p <- ggplot(flow_table, 
       aes(x, 
          id = id, 
          split = y, 
          value = n)) +
  ## colour lines by sex 
  ggforce::geom_parallel_sets( aes(fill = Decision.output),
                     alpha = 0.5,
                     axis.width = 0.2) +
  ## fill in the label boxes grey
  ggforce::geom_parallel_sets_axes(axis.width = 0.15,
                          fill = "grey80", 
                          color = "grey80") +
  ## change text colour and angle (needs to be adjusted)
  ggforce::geom_parallel_sets_labels(color = "black",
                            angle = 0,
                            size = 5) +
  ## adjusted y and x axes (probably needs more vertical space)
  scale_x_discrete(name = NULL, 
                   expand = c(0, 0.2)) + 
   theme_unhcr(font_size = 14, 
               grid = FALSE ) +
  ## remove axis labels
  theme(  axis.line = element_blank(),
          axis.ticks = element_blank(),
         axis.text.y = element_blank(),
        panel.background = element_blank(),
        legend.position = "none",                    # move legend to bottom
      legend.title = element_blank(),                # remove title
  ) +
  labs(title = "Refugee Status Determination Decisions",
       subtitle = glue::glue("{ForcedDisplacementStat::reference |>
             dplyr::filter( iso_3 == country_asylum_iso3c) |>
             dplyr::pull(ctryname) }, {format(sum(links$n),  big.mark=\",\")} decisions recorded in {year}"),
       x = NULL,
       y = NULL,
       caption = "Source: UNHCR.org/refugee-statistics")
}
  return(p)
  
}