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

knitr::opts_chunk$set(
  collapse = TRUE,
  echo=TRUE,
  comment = "#>"
)

Load Packages

library(tidyverse)

Prepare Data

## Loading the stat tables
data <- dplyr::left_join( x= unhcrdatapackage::end_year_population_totals_long, 
                                                     y= unhcrdatapackage::reference, 
                                                     by = c("CountryAsylumCode" = "iso_3")) %>%
  filter(#Population.type  == "REF" &
           !(is.na(UNHCRBureau))) %>%
  group_by(Year, UNHCRBureau ) %>%
  summarise(Value2 = sum(Value) ) 

lastyear <- max(unhcrdatapackage::end_year_population_totals_long$Year)

generate plot

#Make plot
ggplot(data, aes(x = Year, y = Value2, 
                                              colour = UNHCRBureau)) + # Adding reference to color
  geom_line(size = 1) + # Here we mention that it will be a line chart
  geom_hline(yintercept = 0, size = 1, colour = "#333333") +
  scale_y_continuous( label = scales::label_number_si()) + ## Format axis number
  xlim(c(1960, lastyear + 8)) +

  #scale_colour_viridis_d() + ## Add color for each lines based on color-blind friendly palette
  #scale_fill_manual(name = 'UNHCRBureau', values = c("#b2df8a", "#fb9a99", "#1f78b4", "#33a02c", "#a6cee3")) +
  #   "WestAfrica" 
  scale_fill_manual(name = 'UNHCRBureau', values = c( "Americas" = "#a6cee3",
                                                      "Asia"  = "#1f78b4", 
                                                     "EastAfrica" = "#b2df8a",  
                                                     "Europe" = "#33a02c",
                                                      "MENA" = "#fb9a99", 
                                                      "SouthAfrica" = "#e31a1c", 
                                                     "WestAfrica"= "#fdbf6f")) +  
  geom_label(aes(x = lastyear + .5 , 
                 y = as.numeric(data[data$UNHCRBureau == "Americas" & data$Year == lastyear , c("Value2")]), 
                 label = "Americas"), 
                             hjust = 0, 
                             vjust = 0.5, 
                             colour = "#a6cee3",  
                             fill = "white", 
                             label.size = NA, 
                             family = "Lato", 
                             size = 6) +
   geom_label(aes(x = lastyear +.5, 
                  y = as.numeric(data[data$UNHCRBureau == "Asia" & data$Year == lastyear , c("Value2")]), 
                  label = "Asia"), 
                             hjust = 0, 
                             vjust = 0.5,
                             colour = "#1f78b4",   
                             fill = "white", 
                             label.size = NA, 
                             family = "Lato", 
                             size = 6) +
   geom_label(aes(x = lastyear + .5,  
                  y = as.numeric(data[data$UNHCRBureau == "EastAfrica" & data$Year == lastyear , c("Value2")]), 
                   label = "Eastern Africa"), 
                             hjust = 0, 
                             vjust = 0.5, 
                             colour = "#b2df8a",  
                             fill = "white", 
                             label.size = NA, 
                             family = "Lato", 
                             size = 6) +
    geom_label(aes(x = lastyear + .5,  
                  y = as.numeric(data[data$UNHCRBureau == "Europe" & data$Year == lastyear , c("Value2")]), 
                    label = "Europe"), 
                             hjust = 0, 
                             vjust = 0.5, 
                             colour = "#33a02c",  
                             fill = "white", 
                             label.size = NA, 
                             family = "Lato", 
                             size = 6) +
    geom_label(aes(x = lastyear + .5,  
                  y = as.numeric(data[data$UNHCRBureau == "MENA" & data$Year == lastyear , c("Value2")]), 
                    label = "Middle East / North Africa"), 
                             hjust = 0, 
                             vjust = 0.5,  
                             colour = "#fb9a99", 
                             fill = "white", 
                             label.size = NA, 
                             family = "Lato", 
                             size = 6) +
    geom_label(aes(x = lastyear + .5,  
                  y = as.numeric(data[data$UNHCRBureau == "SouthAfrica" & data$Year == lastyear , c("Value2")]), 
                    label = "Southern Africa"), 
                             hjust = 0, 
                             vjust = 0.5, 
                             colour = "#e31a1c",  
                             fill = "white", 
                             label.size = NA, 
                             family = "Lato", 
                             size = 6) +
    geom_label(aes(x = lastyear + .5,  
                  y = as.numeric(data[data$UNHCRBureau == "WestAfrica" & data$Year == lastyear , c("Value2")]), 
                    label = "Western Africa"), 
                             hjust = 0, 
                             vjust = 0.5, 
                             colour = "#fdbf6f",  
                             fill = "white", 
                             label.size = NA, 
                             family = "Lato", 
                             size = 6) +

  unhcRstyle::unhcr_theme() + ## Insert UNHCR Style
  ## and the chart labels
  labs(title = "Refugees Population are not equally spread",
       subtitle = "World wide refugee population 1951-2017",
       x = "",
       y = "",
       caption = "UNHCR https://www.unhcr.org/refugee-statistics/")

Edouard-Legoupil/unhcrdatapackage documentation built on Nov. 6, 2023, 6:10 p.m.