A function using ggplot2 and dplyr to create stacked donut charts

split_donut.R

set.seed(133742)
library(ggplot2)
library(dplyr)

# split_donut function to create stacked donut/pie charts
split_donut <- function(data, group, subgroup, n) {
    nths <- function(x, i) {
        x[(1:length(x)%%i)==0]
    }
    group <- ensym(group)
    subgroup <- ensym(subgroup)
    n <- ensym(n)
    
    data |> 
        rename(
            cat_1 = !!group,
            cat_2 = !!subgroup,
            n = !!n
        ) |> 
        select(cat_1, cat_2, n) |> 
        mutate(across(1:2, as.factor)) |> 
        arrange(desc(cat_1)) |> 
        group_by(cat_1) |> 
        mutate(cat_1_n = sum(n)) |> 
        ungroup() |> 
        arrange(desc(cat_1)) |> 
        mutate(cat_1_y = (((nths((cat_1_n)/2, 2)))+lag(cumsum(nths(cat_1_n, 2)), default = 0)) |> rep(each = 2)) |> 
        mutate(cat_1_y = ifelse(as.numeric(cat_2) == 2, cat_1_y, NA)) |> 
        arrange(desc(cat_1)) |> 
        mutate(cat_2_y = (n/2)+lag(cumsum(n), default = 0)) |> 
        ggplot(aes(y = n, fill = cat_1)) +
        geom_col(
            aes(x = 1, color = cat_1), 
            position = "stack", 
            width = 1.05
        ) +
        geom_text(
            aes(label = sprintf("%s\n%1.0f%%", cat_1, (cat_1_n/sum(cat_1_n))*100), x = 1, y = cat_1_y)
        ) +
        geom_col(
            aes(x = 2, group = cat_1, alpha = cat_2), 
            color = "white", 
            linewidth = 1.5,
            position = "stack"
        ) +
        geom_text(
            aes(label = cat_2, x = 2, y = cat_2_y)
        ) +
        scale_y_continuous(labels = scales::percent) +
        scale_alpha_manual(values = c(1, .75)) +
        coord_polar(theta="y") +
        labs(fill = group, color = group, alpha = subgroup) +
        theme_void() +
        theme(plot.margin = unit(c(1,1,1,1), "lines"))
}


# Examples
p <- tibble(
    favorite_flavor = rep(c("chocolate", "vanilla", "strawberry"), 2),
    gender = rep(c("male", "female"), 3),
    n = sample(1:10, 6)
) |> 
    split_donut(favorite_flavor, gender, n)
p

p <- tibble(
    mode_of_transportation = rep(c("bus", "car", "bike", "walk"), 2),
    gender = rep(c("male", "female"), each = 4),
    count = sample(5:10, 8, replace = TRUE)
) |> 
    split_donut(mode_of_transportation, gender, count)
p