R ggpubr Boxplot向动态Y轴添加摘要统计信息标签

Question

我想在动态y轴最大值处的箱形图上添加摘要统计信息。

在实际数据中，y轴是动态下拉列表，一个值在0-6之间；另一个在0-100之间。在下面的示例中，我已经硬编码了我希望标签位于的位置，但是我无法在真实数据中硬编码它们。

是否有办法：

是否在y轴上方的图形外部设置标签？这样即使轴发生变化，标签也不会移动？

或者是否有办法将其设置为Y + n的最大值？

示例：

# library
library(ggplot2)
library(ggpubr)

# create a data frame
variety=rep(LETTERS[1:7], each=40)
treatment=rep(c("high","low"),each=20)
note=seq(1:280)+sample(1:150, 280, replace=T)
data=data.frame(variety, treatment ,  note)

# grouped boxplot
ggplot(data, aes(x = variety, y = note, fill = treatment)) +
  geom_boxplot() +
  scale_fill_manual(values = c("#79AAB9", "#467786")) +
  stat_compare_means(aes(group = treatment), label = "p.format") +
  stat_summary(
    fun.data = function(x)
      data.frame(y = 460, label = paste(round(median(
        x
      ), 1))),
    geom = "text",
    aes(group = treatment),
    hjust = 0.5,
    position = position_dodge(0.9)
  ) +
  stat_summary(
    fun.data = function(x)
      data.frame(y = 445, label = paste("n", length(x))),
    geom = "text",
    aes(group = treatment),
    hjust = 0.5,
    position = position_dodge(0.9)
  ) +
  expand_limits(y = 100)

非常感谢您提前提供的帮助。

Answer 1

设法通过@MarkNeal获得以下建议的工作

# library
library(ggplot2)
library(ggpubr)

# create a data frame
variety=rep(LETTERS[1:7], each=40)
treatment=rep(c("high","low"),each=20)
note=seq(1:280)+sample(1:150, 280, replace=T)
data=data.frame(variety, treatment ,  note)

# grouped boxplot
ggplot(data, aes(x = variety, y = note, fill = treatment)) +
  geom_boxplot() +
  scale_fill_manual(values = c("#79AAB9", "#467786")) +
  stat_compare_means(aes(group = treatment), label = "p.format", vjust = 3) +
  stat_summary(
    fun.data = function(x)
      data.frame(y= Inf, label = paste(round(median(
        x
      ), 1))),
    geom = "text",
    aes(group = treatment),
    hjust = 0.5, vjust = 1,
    position = position_dodge(0.9)
  ) +
  stat_summary(
    fun.data = function(x)
      data.frame(y = Inf, label = paste("n", length(x))),
    geom = "text",
    aes(group = treatment),
    hjust = 0.5, vjust = 2,
    position = position_dodge(0.9)
  )