如何在R中重命名我个人箱线图的标签

问题是，xlim是设置限制的简写，使用xlim(labels= c("A", "B"))可以将x刻度的限制设置为等于c("A", "B")，即，只有x值为"A"或"B"的观测值才会包含在曲线图中.所有其他观察结果都被丢弃了，这就是警告所要传达的.

要指定标签，请改用scale_x_discrete的labels参数.

使用一些虚假的随机示例数据:

library(tidyverse)

set.seed(123)

data3 <- data.frame(
  Treatment_A = runif(100, 0, 30),
  Treatment_B = runif(100, 0, 30)
)

p <- data3 %>%
  select(Treatment_A, Treatment_B) %>%
  pivot_longer(cols = everything(), names_to = "Variable", values_to = "Value") %>%
  ggplot(aes(x = Variable, y = Value, fill = Variable)) +
  stat_boxplot(geom = "errorbar", width = 0.5) +
  geom_boxplot(fill = c("skyblue2", "gold2")) +
  labs(x = "Treatment", y = "Frequency (total)", title = "Treatment comparison") +
  theme_minimal() +
  theme(axis.title.x = element_text(size = 10)) +
  theme(axis.title.y = element_text(size = 10)) +
  theme(plot.title = element_text(size = 16)) +
  theme(plot.title = element_text(hjust = 0.5)) +
  stat_summary(
    fun = mean, geom = "errorbar", aes(ymax = ..y.., ymin = ..y..),
    width = .75, lwd = 0.7, linetype = "dashed", col = "red"
  ) +
  ylim(0, 30)

首先，通过添加xlim(labels = c("A", "B"))来重现您的问题:

p +
  xlim(labels = c("A", "B"))
#> Warning: The dot-dot notation (`..y..`) was deprecated in ggplot2 3.4.0.
#> ℹ Please use `after_stat(y)` instead.
#> This warning is displayed once every 8 hours.
#> Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
#> generated.
#> Warning: Removed 200 rows containing missing values (`stat_boxplot()`).
#> Warning in min(x): no non-missing arguments to min; returning Inf
#> Warning in max(x): no non-missing arguments to max; returning -Inf
#> Warning in min(diff(sort(x))): no non-missing arguments to min; returning Inf
#> Warning: Removed 200 rows containing missing values (`stat_boxplot()`).
#> Warning: Removed 200 rows containing non-finite values (`stat_summary()`).
#> Warning in max(f): no non-missing arguments to max; returning -Inf
#> Warning: Computation failed in `stat_summary()`
#> Caused by error in `seq_len()`:
#> ! argument must be coercible to non-negative integer

改为使用scale_x_discrete可以得到所需的结果:

p +
  scale_x_discrete(labels = c("A", "B"))