ggplotでグループ毎の頻度ヒストグラムを隣り合わせて作成

group histogram by ggplot

タイトル通りにplotしようとしたら詰まったためメモ。

サンプルデータ。\(x1 \sim Binom(20, 0.2)\), \(x2 \sim Binom(20, 0.5)\)

library(tidyverse)
set.seed(123)
n1 <- 200
n2 <- n1 * 3
df <- tibble(type = c(rep("x1", n1), rep("x2", n2)), 
             value = c(abs(rbinom(n = n1, 20, 0.2)), abs(rbinom(n = n2, 20, 0.5))))

Githubにissueが上がっていたが、そのままだとgroup毎の頻度がずれていた。結論としては、geom_histogramにbinwidthではなくbreaksを渡さないといけなかった。

breaksなし

bw <- 2; min_val <- 0; max_val <- 20
ggplot(df, aes(x = value, y = stat(density*width), fill=type)) +
  geom_histogram(binwidth = bw, position=position_dodge()) +
  scale_x_continuous(breaks = seq(min_val, max_val, bw), limits = c(min_val, max_val), expand = c(0, 0))

breaksあり

ggplot(df, aes(x = value, y = stat(density*width), fill=type)) +
  geom_histogram(breaks = seq(min_val, max_val, bw), position=position_dodge()) +
  scale_x_continuous(breaks = seq(min_val, max_val, bw), limits = c(min_val, max_val), expand = c(0, 0))

頻度表

df %>% 
group_by(type, ints = cut_width(value, width = 2, boundary = 0)) %>% 
  summarise(n = n()) %>% 
  mutate(freq = n / sum(n)) %>% 
  select(-n) %>% 
  pivot_wider(names_from = type, values_from = freq, values_fill = 0)

# A tibble: 9 × 3
  ints       x1      x2
  <fct>   <dbl>   <dbl>
1 [0,2]   0.155 0      
2 (2,4]   0.485 0.005  
3 (4,6]   0.285 0.055  
4 (6,8]   0.07  0.195  
5 (8,10]  0.005 0.345  
6 (10,12] 0     0.275  
7 (12,14] 0     0.103  
8 (14,16] 0     0.02   
9 (16,18] 0     0.00167