Download past and current versions of the UN DESA World Population Prospects data into R. See the pkgdown site for full details.
Install the developmental version with:
library(devtools)
install_github("guyabel/tidywpp", ref = "main")Data downloaded using tidywpp is in tidy form, and hence does not require any major manipulations for use in popular modelling and visualisation functions in R.
library(tidywpp)
#> Suggested citation for WPP2022 data: United Nations, Department of Economic and Social Affairs, Population Division (2022). World Population Prospects 2022, Online Edition. Rev. 1
d <- get_wpp(indicator = "pop", pop_age = "single", pop_sex = "both", tidy_pop_sex = TRUE, drop_id_cols = TRUE)
d
#> # A tibble: 8,693,070 × 6
#> Location Variant Time AgeGrp Sex Pop
#> <chr> <chr> <dbl> <fct> <chr> <dbl>
#> 1 World Medium 1950 0 Male 41782.
#> 2 World Medium 1950 0 Female 39929.
#> 3 World Medium 1950 1 Male 37134.
#> 4 World Medium 1950 1 Female 35539.
#> 5 World Medium 1950 2 Male 34054.
#> 6 World Medium 1950 2 Female 32655.
#> 7 World Medium 1950 3 Male 31959.
#> 8 World Medium 1950 3 Female 30610.
#> 9 World Medium 1950 4 Male 29718.
#> 10 World Medium 1950 4 Female 28497.
#> # … with 8,693,060 more rowslibrary(tidyverse)
library(ggpol)
library(gganimate)
g <- d %>%
filter(Location == "World") %>%
mutate(pop = ifelse(Sex == "Male", -Pop/1e3, Pop/1e3),
sex = fct_rev(Sex),
age = as.numeric(AgeGrp) - 1) %>%
ggplot(mapping = aes(x = pop, y = age))+
geom_col(orientation = "y") +
facet_share(facets = "sex", scales = "free_x") +
scale_x_continuous(labels = abs) +
theme_bw() +
transition_time(time = Time) +
labs(x = "Population (millions)", y = "",
title = 'WPP2022 World Population Medium Variant {round(frame_time)}')
animate(g, width = 15, height = 15, units = "cm", res = 200,
renderer = gifski_renderer(), nframes = n_distinct(d$Time))
anim_save(filename = "wpp2022_med.gif")
This package is in no way officially related to, or endorsed by, UN DESA.