2023w34_European_refugees.R

library(tidyverse)
library(ggsankey)
library(ggh4x)
library(camcorder)

gg_record(dir = "tidytuesday-temp", device = "png", width = 12, height = 8, units = "in", dpi = 320)

population <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2023/2023-08-22/population.csv')

# European countries
eu <- rnaturalearthdata::countries110 %>% 
  as_tibble() %>% 
  filter(continent == "Europe")

# Refugees by year to Europe
ref_eu_year <- population %>%
  mutate(
    coo_name = case_when(
      str_detect(coo_name, "Syria") ~ "Syria",
      str_detect(coo_name, "Serbia") ~ "Serbia and Kosovo",
      TRUE ~ coo_name
    )
  ) %>% 
  filter(coa_iso %in% eu$sov_a3) %>% 
  group_by(year, coo_name) %>% 
  summarise(
    total = sum(refugees)
    ) %>% 
  ungroup() %>% 
  group_by(year) %>% 
  mutate(top_year = total == max(total)) %>% 
  ungroup()

# Regions with > 100 000 refugees
ref_top <- ref_eu_year %>% 
  group_by(coo_name) %>% 
  summarise(total = sum(total)) %>% 
  ungroup() %>% 
  arrange(-total) %>% 
  filter(total >= 1e5) 

# Annotations for highlighted regions
annot <- tribble(
  ~country, ~x, ~y, ~yr1, ~yr2,
  "Serbia and Kosovo", 2011, 1.5e6, 2010, 2012,
  "Iraq", 2013, 1.3e6, 2013, 2013,
  "Ukraine", 2014.5, 1.8e6, 2014, 2015,
  "Syria", 2018, 2.6e6, 2016, 2021,
  "Ukraine", 2020.7, 5e6, 2022, 2022
  ) %>% 
  rowwise() %>% 
  mutate(
    tot = sum(subset(ref_eu_year, coo_name == country & between(year, yr1, yr2))[, "total"]),
    label = paste0("**", country, "**", if_else(yr1 != yr2, paste0("<br>", yr1, "-", yr2), paste0("<br>", yr2)), "<br>", "**", scales::number(tot, accuracy = 0.1, scale_cut = scales::cut_short_scale()), "**")
    ) %>% 
  ungroup()

f1 <- "Outfit"
f2 <- "Newsreader Display"

ref_eu_year %>% 
  # Keep only top countries
  filter(coo_name %in% ref_top$coo_name) %>%
  ggplot() +
  # Alluvial, highlight some top countries
  geom_sankey_bump(aes(x = year, node = coo_name, fill = if_else(coo_name %in% annot$country, coo_name, NA), value = total, color = after_scale(colorspace::lighten(fill, 0.4))), linewidth = 0.3, type = "alluvial", space = 1e4, alpha = 0.9) +
  # Labels for top countries by year(s)
  ggtext::geom_richtext(data = annot, aes(x = x, y = y, label = label, color = country, size = tot), vjust = 0, family = f1, fill = NA, label.color = NA) +
  # Sums of the top 5 countries for 2010-2022
  annotate("text", x = 2022.2, y = 7.3e6, label = "Totals for\n2010-2022\n↓", family = f1, hjust = 0, vjust = 1, color = "grey30") +
  geom_text(data = ref_top %>% filter(row_number() <= 5), aes(x = 2022.2, y = c(5e6, 1.9e6, 1.25e6, 1e6, 0.8e6), label = scales::number(total, accuracy = 0.1, scale_cut = scales::cut_short_scale())), family = f1, hjust = 0, color = c("#0057B7", "#CE1126", "grey10", "#017b3d", "grey10")) +
  # Labels for two countries
  annotate("text", x = c(2020, 2020.5), y = c(1.28e6, 0.85e6), label = c("Afghanistan", "Eritrea"), color = "grey99", family = f1, size = c(4, 3.2)) +
  # Title and subtitle
  annotate("text", x = 2010, y = 7.2e6, label = "Where do the 22 million refugees in Europe come from?", size = 8, family = f2, fontface = "bold", hjust = 0, color = "#181716") +
  annotate("text", x = 2010, y = 6.8e6, label = str_wrap("The chart displays rankings and the number of refugees from each region from 2010 to 2022. Top-ranked regions during different periods are highlighted. Only regions with a total of at least 100 000 refugees for the period 2010-2022 are included.", 78), size = 5.5, family = f1, hjust = 0, vjust = 1, color = "#393433") +
  # Scales, coord, theme
  scale_x_continuous(breaks = seq(2010, 2022, 2), guide = "axis_minor") +
  scale_fill_manual(values = c("#017b3d", "#0C4077", "#CE1126", "#0057B7"), na.value = "grey60") +
  scale_color_manual(values = c("#017b3d", "#0C4077", "#CE1126", "#0057B7"), na.value = "grey60") +
  scale_size_continuous(range = c(4, 6)) +
  coord_cartesian(clip = "off", expand = FALSE) +
  labs(
    caption = "Souce: UNHCR Refugee Population Statistics Database · Graphics: Georgios Karamanis"
  ) +
  theme_minimal(base_family = f1) +
  theme(
    legend.position = "none",
    plot.background = element_rect(fill = "#FFFFFE", color = NA),
    axis.title = element_blank(),
    axis.text.y = element_blank(),
    axis.text.x = element_text(size = 12, margin = margin(5, 0, 0, 0), family = f1, color = "#393433"),
    panel.grid = element_blank(),
    axis.ticks.x = element_line(color = "grey70"),
    ggh4x.axis.ticks.length.minor = rel(1),
    plot.margin = margin(20, 75, 10, 35),
    plot.caption = element_text(margin = margin(20, 0, 0, 0))
  )