这可能会帮助您开始：

library(dplyr)
library(ggplot2)
prop <- data %>% 
    mutate(race = factor(race, levels = c(1, 2, 3), labels = c("White", "Black", "Others"))) %>% 
    group_by(race) %>% 
    mutate(race_n  = n()) %>% 
    group_by(race, score) %>% 
    summarise(percent = round(100*n()/race_n[1], 1))

prop %>% 
    ggplot(aes(x = percent, y = score, fill = race)) +
    geom_col(orientation = "y", width = .9) +
    geom_text(aes(label = percent), hjust = 1)+
    facet_grid(~race) +
    labs(title = "Demographic breakdown of 'Score'") +
    theme_bw()

编辑

将所有字符放在一起，可以得到一个更大的图形：

df <- data %>% mutate(
        gender = factor(2-gender), 
        race = factor(race), 
        education = factor(education)) %>%
    pivot_longer(!score, names_to = "character", values_to = "levels")

df %>% group_by(character, levels) %>% 
    mutate(group_n  = n()) %>% 
    group_by(character, levels, score) %>% 
    summarise(percent = round(100*n()/group_n[1], 1)) %>% 
    ggplot(aes(x = percent, y = score, fill = character)) +
    geom_col(orientation = "y", width = .9) +
    geom_text(aes(label = percent), hjust = 1)+
    facet_grid(character ~ levels) +
    labs(title = "Demographic breakdown of 'Score'") +
    theme_bw()

请注意：我已经改变了性别的代码。

从@王志强出色的第一关中得到灵感，我终于想出了一个解决办法。我仍然需要改变标签的顺序（把教育水平按顺序排列，把种族变量移到图的顶部），但这基本上是我所设想的。

d_test <- d %>% mutate(
        gender = factor(2-gender), 
        race = factor(race), 
        education = factor(education)) %>%
    pivot_longer(!score, names_to = "group", values_to = "levels")

d_test <- d_test %>% group_by(group, levels) %>% 
    mutate(group_n  = n()) %>% 
    group_by(group, levels, score) %>% 
    summarise(percent = round(100*n()/group_n[1], 1))

d_test <- d_test %>% 
  mutate(var = case_when(group == "gender" & levels == 1 ~ "female",
                         group == "gender" & levels == 2 ~ "male",
                         group == "race" & levels == 1 ~ "white",
                         group == "race" & levels == 2 ~ "black",
                         group == "race" & levels == 3 ~ "hispanic",
                         group == "education" & levels == 1 ~ "dropout HS",
                         group == "education" & levels == 2 ~ "grad HS",
                         group == "education" & levels == 3 ~ "some coll",
                         group == "education" & levels == 4 ~ "grad coll"))

ggplot(d_test, aes(x = percent, y = var, fill = group)) +
  geom_col(orientation = "y", width = .9) +
  facet_grid(group ~ score,
               scales = "free_y", space = "free_y") +
  labs(title = "Demographic breakdown of 'Score'",
         y = "",
         x = "Percent") +
  theme_minimal() +
  theme(legend.position = "none",
        strip.text.y = element_blank())