geom_boxplot 作为直方图中的插图

Posted 2023-02-16

【中文标题】geom_boxplot 作为直方图中的插图

【英文标题】：geom_boxplot as inset in histogram

【发布时间】：2022-01-17 17:04:25

【问题描述】：

我想知道是否可以将分组箱线图作为 插图 绘制成带有密度线的（更大的）直方图：

玩具数据：

df <- structure(list(role = c("Recipient", "Speaker", "Recipient", 
                           "Recipient", "Recipient", "Speaker", "Recipient", "Recipient", 
                           "Speaker", "Speaker", "Recipient", "Speaker", "Recipient", "Recipient", 
                           "Recipient", "Speaker", "Recipient", "Speaker", "Recipient", 
                           "Speaker", "Recipient", "Recipient", "Speaker", "Recipient", 
                           "Recipient", "Speaker", "Speaker", "Speaker", "Recipient", "Speaker", 
                           "Speaker", "Recipient", "Speaker", "Recipient", "Recipient", 
                           "Speaker", "Recipient", "Recipient", "Recipient", "Speaker", 
                           "Speaker", "Recipient", "Speaker", "Recipient", "Speaker", "Recipient", 
                           "Speaker", "Speaker", "Recipient", "Recipient", "Speaker", "Recipient", 
                           "Recipient", "Speaker", "Recipient", "Recipient", "Recipient", 
                           "Speaker", "Recipient", "Speaker", "Recipient", "Speaker", "Recipient", 
                           "Recipient", "Speaker", "Recipient", "Recipient", "Speaker", 
                           "Recipient", "Recipient", "Recipient", "Speaker", "Recipient", 
                           "Speaker", "Recipient", "Speaker", "Recipient", "Recipient", 
                           "Recipient", "Recipient", "Speaker", "Recipient", "Recipient", 
                           "Recipient", "Speaker", "Recipient", "Speaker", "Recipient", 
                           "Recipient", "Speaker", "Recipient", "Recipient", "Speaker", 
                           "Recipient", "Recipient", "Recipient", "Speaker", "Recipient", 
                           "Speaker", "Recipient"), increase_max = c(0.008, 0.118, NA, NA, 
                                                                     NA, 0.209, NA, 0.001, 0.111, NA, NA, NA, NA, NA, 0.007, 0.002, 
                                                                     0.006, 0.255, 0.009, NA, 0.004, 0.232, NA, 0.007, 0.004, 0.095, 
                                                                     0.09, NA, 0.002, NA, 0.05, NA, 0.02, 0.045, 0.002, NA, NA, 0.005, 
                                                                     0.012, NA, 0.037, NA, 0.066, NA, 0.019, 0.002, 0.136, NA, 0.003, 
                                                                     NA, 0.128, 0.004, 0.003, NA, NA, NA, 0.03, 0.042, NA, 0.138, 
                                                                     0.139, 0.126, 0.002, NA, 0.005, NA, 0.002, 0.01, 0.001, NA, 0.005, 
                                                                     0.003, NA, NA, 0.002, NA, 0.005, NA, NA, 0.015, 0.007, 0.021, 
                                                                     NA, NA, NA, NA, NA, 0.171, 0.02, 0.036, 0.026, 0.001, 0.033, 
                                                                     0.127, 0.339, 0.075, 0.037, 0.083, NA, 0.041)), class = c("tbl_df", 
                                                                                                                               "tbl", "data.frame"), row.names = c(NA, -100L))

我可以像这样单独绘制两个图形（注意：直方图的数据是根据多个参数过滤的，箱线图的数据是未过滤的）：

带密度线的直方图：

df %>% 
  filter(
    !is.na(increase_max) & 
      increase_max >= 0.05 & 
      increase_max <= 0.5) %>%
  ggplot(aes(x = increase_max)) +
  geom_histogram(aes(y = after_stat(density), fill = role), binwidth = 0.05, position = "identity", alpha = 0.35) +
  geom_density(aes(colour = role)) +
  scale_colour_manual(aesthetics = c("fill", "colour"), values = c("blue", "red")
  )

箱线图：

df %>%
  ggplot(aes(y = increase_max, x = role)) +
  geom_boxplot()

我正在寻找的输出将与此类似：

【参考方案1】：

您可以使用cowplot 轻松叠加和插入图。使用hp 作为直方图，bp 作为箱线图：

library(cowplot)

ggdraw() +
  draw_plot(hp) +
  draw_plot(bp, x = .5, y = .65, width = .35, height = .35)

【讨论】：

非常酷。谢谢！