有没有办法更改 R 中数据重要的箱线图颜色

Question

My data are as follows:

 df1<-read.table(text = "time type 12 B88 19 B44 18 B44 13 B88 17 B44",header=TRUE)

I can use the following codes to get my plot:

 ggplot(df1,aes(type,time)) + geom_boxplot(fill="green")+ stat_compare_means(method = "t.test")

I want to get a different colour, let's say blue, for the box which has a high medium when the P-value is less than 0.05%. Can we do it? NOTE: I am not interested in running ttest

Answer 1

ggplot(df1,aes(type,time)) + geom_boxplot(fill="green") +
stat_compare_means(method = "t.test") -> p #save your plot as p
build <- ggplot_build(p) # build plot
build$data[[1]][,"fill"] <- ifelse(build$data[[2]][1,"p.format"] < 0.05, list(c("blue","green")),list(rep("green",2))) # changes fill to blue if p value is < 0.05
plot(ggplot_gtable(build)) # plot new formatted graph

Answer 2

Probably not the most elegant way of doing it but you can calculate the p value outside ggplot2 and using an ifelse statement, attribute a color pattern you can call using scale_fill_identity .

Here an example using a dummy example:

df <- data.frame(Xval = rep(c("A","B"),each = 50),
                 Yval = c(sample(1:50,50), sample(50:100,50)))

I used dplyr pipe sequence here but you cna do that pretty easily in base r :

library(dplyr)
library(ggplot2)

df %>% mutate(pval = t.test(Yval~Xval)$p.value) %>%
  group_by(Xval) %>% mutate(Mean = mean(Yval)) %>% 
  ungroup() %>% 
  mutate(Color = ifelse(pval < 0.05 & Mean == max(Mean), "blue","green")) %>%
  ggplot(aes(x = Xval, y = Yval, fill = Color))+
  geom_boxplot()+
  stat_compare_means(method = "t.test")+
  scale_fill_identity()

---

Using your example:

df1 %>% mutate(pval = t.test(time~type)$p.value) %>%
  group_by(type) %>% mutate(Mean = mean(time)) %>% 
  ungroup() %>% 
  mutate(Color = ifelse(pval < 0.05 & Mean == max(Mean), "blue","green")) %>%
  ggplot(aes(x = type, y = time, fill = Color))+
  geom_boxplot()+
  stat_compare_means(method = "t.test")+
  scale_fill_identity()