refugees is an R package designed to facilitate access
to the United Nations High Commissioner for Refugees (UNHCR) Refugee
Data Finder. It provides an easy-to-use interface to the database, which
covers forcibly displaced populations, including refugees,
asylum-seekers, internally displaced people, stateless people, and
others over a span of more than 70 years.
This package provides data from three major sources:
Data from UNHCR’s annual statistical activities dating back to 1951.
Data from the United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), specifically for registered Palestine refugees under UNRWA’s mandate.
Data from the Internal Displacement Monitoring Centre (IDMC) on people displaced within their country due to conflict or violence.
The refugees package includes eight datasets:
population: Data on forcibly displaced and stateless
persons by year, including refugees, asylum-seekers, returned refugees,
internally displaced persons (IDPs), and stateless persons.
idmc: Data from the Internal Displacement Monitoring
Centre on the total number of IDPs due to conflict and
violence.
asylum_applications: Data on asylum applications
including procedure type and application type.
asylum_decisions: Data on asylum decisions,
including recognised, rejected, and otherwise closed claims.
demographics: Demographic and sub-national data,
where available, including age and sex disaggregation.
solutions: Data on durable solutions for refugees
and IDPs.
unrwa: Data on registered Palestine refugees under
UNRWA’s mandate.
flows: Numbers of the people forced to flee during
each of the years since 1962.
Please check the individual dataset description for more details on the content of each dataset.
Install either from CRAN with:
install.packages("refugees")Or retrieve the development version from Github using the pak package:
pak::pkg_install("PopulationStatistics/refugees")Here are some examples of how you can use the
refugees`` package. Thepopulation` dataset can be used to
easily get data on forced displacement or statelessness.
library(refugees)
library(dplyr)
glimpse(refugees::population)
#> Rows: 126,402
#> Columns: 16
#> $ year <dbl> 1951, 1951, 1951, 1951, 1951, 1951, 1951, 1951, 1951…
#> $ coo_name <chr> "Unknown", "Unknown", "Unknown", "Unknown", "Unknown…
#> $ coo <chr> "UKN", "UKN", "UKN", "UKN", "UKN", "UKN", "UKN", "UK…
#> $ coo_iso <chr> "UNK", "UNK", "UNK", "UNK", "UNK", "UNK", "UNK", "UN…
#> $ coa_name <chr> "Australia", "Austria", "Belgium", "Canada", "Denmar…
#> $ coa <chr> "AUL", "AUS", "BEL", "CAN", "DEN", "FRA", "GBR", "GF…
#> $ coa_iso <chr> "AUS", "AUT", "BEL", "CAN", "DNK", "FRA", "GBR", "DE…
#> $ refugees <dbl> 180000, 282000, 55000, 168511, 2000, 290000, 208000,…
#> $ asylum_seekers <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ returned_refugees <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ idps <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ returned_idps <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ stateless <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ ooc <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ oip <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ hst <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…The population dataset can be used to get the 10
countries of origin with highest number of refugees, people in
refugee-like situations including people in need of international
protection in 2022.
ref_coo_10 <- refugees::population |>
filter(year == 2022) |>
summarise(refugees = sum(refugees, na.rm = TRUE) + sum(oip, na.rm = TRUE),
.by = coo_name) |>
slice_max(order_by = refugees, n = 10)
ref_coo_10
#> # A tibble: 10 × 2
#> coo_name refugees
#> <chr> <dbl>
#> 1 Syrian Arab Rep. 6559736
#> 2 Ukraine 5684177
#> 3 Afghanistan 5661717
#> 4 Venezuela (Bolivarian Republic of) 5447849
#> 5 South Sudan 2295082
#> 6 Myanmar 1251618
#> 7 Dem. Rep. of the Congo 932680
#> 8 Sudan 837188
#> 9 Somalia 786794
#> 10 Central African Rep. 748344We can use ggplot2 and the unhcrthemes
to visualize our data following the UNHCR data
visualization guidelines.
library(ggplot2)
library(unhcrthemes)
ref_coo_10 |>
ggplot(aes(refugees, reorder(coo_name, refugees))) +
geom_col(fill = unhcr_pal(n = 1, "pal_blue"),
width = 0.8) +
geom_text(aes(label = scales::label_comma()(refugees)),
hjust = -0.2) +
scale_x_continuous(expand = expansion(mult = c(0, 0.1))) +
labs(title = "Refugees, people in refugee-like situations and other people in need of international protection",
subtitle = "By country of origin | mid-2024",
caption = "Source: UNHCR Refugee Data Finder") +
theme_unhcr(font_size = 12,
grid = FALSE,
axis = FALSE,
axis_title = FALSE,
axis_text = "y")
For more examples, see How to use UNHCR’s refugees R package.
This package is released under the Creative Commons Attribution 4.0 International Public License.