Evolution over time of the different Population of Concern

Load Packages

library(tidyverse)
library(circlize)

Prepare Data

thisbureau <- "Americas"
lastyear <- max(unhcrdatapackage::end_year_population_totals_long$Year) 

#Prepare data
end_year_population_totals_long.asy <- dplyr::left_join( x= unhcrdatapackage::end_year_population_totals_long, 
                                                     y= unhcrdatapackage::reference, 
                                                     by = c("CountryAsylumCode" = "iso_3"))

multiple_line_df <- end_year_population_totals_long.asy %>%
  filter(UNHCRBureau  == thisbureau &
           !(is.na(UNHCRBureau))) %>%
  group_by(Year, Population.type, Population.type.label ) %>%
  summarise(Value2 = sum(Value) ) 
#> `summarise()` has grouped output by 'Year', 'Population.type'. You can override using the `.groups` argument.

Generate Plot

#Make plot
evol_america <- ggplot(multiple_line_df, aes(x = Year, y = Value2, 
                                              colour = Population.type)) + # Adding reference to color
  geom_line(size = 1) + # Here we mention that it will be a line chart
    # stat_smooth(size=1.5, 
    #           method = "loess", 
    #           level = 0.95, 
    #           fullrange = TRUE, 
    #           se = FALSE) + 
  
  geom_hline(yintercept = 0, size = 1.1, colour = "#333333") +
  scale_y_continuous( label = scales::label_number_si()) + ## Format axis number
  xlim(c(2000, lastyear + 7)) +
  
  #scale_colour_viridis_d() + ## Add color for each lines based on color-blind friendly palette
  scale_colour_manual( values = c("IDP" = "#00B398",
                                     "VDA"="#EF4A60",
                                     "ASY" = "#18375F",
                                     "REF" = "#0072BC",
                                     "OOC" ="#8395b9",
                                     "STA"="#E1CC0D")) +
  geom_label(aes(x = lastyear + .5 ,
                 y = as.numeric(multiple_line_df[multiple_line_df$Population.type == "REF" & multiple_line_df$Year == lastyear , c("Value2")]),
                 label = "Refugees"),
                             hjust = 0,
                             vjust = 0.5,
                             colour = "#0072BC",
                             fill = "white",
                             label.size = NA,
                             family = "Lato",
                             size = 4) +
   geom_label(aes(x = lastyear +.5,
                  y = as.numeric(multiple_line_df[multiple_line_df$Population.type == "ASY" & multiple_line_df$Year == lastyear , c("Value2")]),
                  label = "Asylum Seekers"),
                             hjust = 0,
                             vjust = 0.5,
                             colour = "#18375F",
                             fill = "white",
                             label.size = NA,
                             family = "Lato",
                             size = 4) +
   geom_label(aes(x = lastyear + .5,
                  y = as.numeric(multiple_line_df[multiple_line_df$Population.type == "IDP" & multiple_line_df$Year == lastyear , c("Value2")]),
                   label = "Internally Displaced \n Persons"),
                             hjust = 0,
                             vjust = 0.5,
                             colour = "#00B398",
                             fill = "white",
                             label.size = NA,
                             family = "Lato",
                             size = 4) +
    geom_label(aes(x = lastyear + .5,
                  y = as.numeric(multiple_line_df[multiple_line_df$Population.type == "STA" & multiple_line_df$Year == lastyear , c("Value2")]),
                    label = "Statelessness"),
                             hjust = 0,
                             vjust = 0.5,
                             colour = "#E1CC0D",
                             fill = "white",
                             label.size = NA,
                             family = "Lato",
                             size = 4) +
    geom_label(aes(x = lastyear + .5,
                  y = as.numeric(multiple_line_df[multiple_line_df$Population.type == "OOC" & multiple_line_df$Year == lastyear , c("Value2")]),
                    label = "Other of Concern"),
                             hjust = 0,
                             vjust = 0.5,
                             colour = "#8395b9",
                             fill = "white",
                             label.size = NA,
                             family = "Lato",
                             size = 4) +
    geom_label(aes(x = lastyear + .5,
                  y = as.numeric(multiple_line_df[multiple_line_df$Population.type == "VDA" & multiple_line_df$Year == lastyear , c("Value2")]),
                    label = "Venezuelan Displaced \n Abroad"),
                             hjust = 0,
                             vjust = 0.5,
                             colour = "#EF4A60",
                             fill = "white",
                             label.size = NA,
                             family = "Lato",
                             size = 4) +
  
  unhcRstyle::unhcr_theme(base_size = 8)  + ## Insert UNHCR Style
  theme(legend.position = "none",
        panel.grid.major.y  = element_line(color = "#cbcbcb"), 
        panel.grid.major.x  = element_blank(), 
        panel.grid.minor = element_blank()) + ### changing grid line that should appear
  ## and the chart labels
  labs(title = "Forcible Displacement in the Americas ",
       subtitle = "Evolution in the past 20 years",
       x = " ",
       y = " ",
       caption = "Source: UNHCR.org/refugee-statistics ")

evol_america