Solution 1 :

The most succinct way I can think of is to use stat_summary. I've also mapped the labels to a color aesthetic, but you can, of course, set the labels to a single color if you wish:

ggplot(mtcars, aes(x=factor(cyl), y=mpg, fill=factor(cyl))) + 
  geom_boxplot(width=0.6) +
  stat_summary(geom="text", fun.y=quantile,
               aes(label=sprintf("%1.1f", ..y..), color=factor(cyl)),
               position=position_nudge(x=0.33), size=3.5) +
  theme_bw()

In the code above we use quantile as the summary function to get the label values. ..y.. refers back to the output of the quantile function (in general, ..*.. is a ggplot construction for using values calculated within ggplot).

enter image description here

Solution 2 :

One way is to simply make the data.frame you need, and pass it to geom_text or geom_label:

library(dplyr)

cyl_fivenum <- mtcars %>% 
    group_by(cyl) %>% 
    summarise(five = list(fivenum(mpg))) %>% 
    tidyr::unnest()

ggplot(mtcars, aes(x=factor(cyl), y=mpg)) + 
    geom_boxplot(aes(fill=factor(cyl))) + 
    geom_text(data = cyl_fivenum, 
              aes(x = factor(cyl), y = five, label = five), 
              nudge_x = .5)

boxplot with labels

Solution 3 :

In case anyone is dealing with large ranges and has to log10 transform their y-axis, I found some code that works great. Just add 10^..y.. and scale_y_log10(). If you don't add 10^ before ..y.. the actual quantile values will be log transformed and displayed as such.

Does not work

ggplot(mtcars, aes(x=factor(cyl), y=mpg, fill=factor(cyl))) + 
  geom_boxplot(width=0.6) +
  stat_summary(geom="text", fun.y=quantile,
           aes(label=sprintf("%1.1f", ..y..), color=factor(cyl)),
           position=position_nudge(x=0.45), size=3.5) +
  scale_y_log10()+
  theme_bw()

enter image description here

Works great

ggplot(mtcars, aes(x=factor(cyl), y=mpg, fill=factor(cyl))) + 
  geom_boxplot(width=0.6) +
  stat_summary(geom="text", fun.y=quantile,
           aes(label=sprintf("%1.1f", 10^..y..), color=factor(cyl)),
           position=position_nudge(x=0.45), size=3.5) +
  scale_y_log10()+
  theme_bw()

enter image description here

cc