Duplicated annotation in ggplot2

March 21, 2024

I’m trying to plot two different results from tests in the boxplot below. The problem is that it is duplicating my annotation.

Plot:

The data:

These are the results of two tests (E, P) that were taken by two groups (I and II) and each group’s score.
I want to plot the difference between scores in the plot, but I can’t get it right.

> head(df)
  ID GROUP TEST SCORE
1  1     I    E     0
2  2     I    P     3
3  3     I    E     3
4  4     I    P    11
5  5     I    P     8
6  6     I    E     0


#code:

ggplot(df, aes(x =GROUP, y = SCORE, fill = TEST)) +
  stat_boxplot(geom = "errorbar",
               width = 0.15) +
  geom_boxplot(aes(fill = TEST), outlier.colour = "black", outlier.shape = 19,
               outlier.size= 2, notch = T) +
  stat_summary(fun = mean, geom = "point", shape = 20, size= 3, 
               color= "black", show.legend = FALSE) +
  facet_wrap(~ TEST) +
  labs(x = "Group",
       y = "Score") +
  
 annotate("text",
            x = 1.2,
            y = max(df$SCORE), 
            label = expression(paste(italic("t"), "(", 97, ") = ", 9.45, ", ", italic("p"), " < .001")), 
            parse = TRUE, hjust = 0, vjust = 1, size = 4, color = "black")

Supposing that I wanted to annotate "t (97) = 9.45, p < .0001" on the right and "W = 5253.50, p < .001" on the left (being it the p italicized). How can I do it?

** Note: I saw it here that annotate() duplicates it, but I couldn’t get the italics without it…

dataset:

structure(list(ID = 1:525, GROUP = structure(c(1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), levels = c("I", "II"), class = "factor"), 
    TEST = structure(c(2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 
    2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 
    1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 
    1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 
    1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 
    1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 
    2L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 
    2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 
    1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 
    1L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 
    1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 
    2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 
    1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 
    1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 
    2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 
    1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 
    1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 
    2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 
    1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 
    1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 
    2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 
    2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 
    1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 
    2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 
    1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 
    1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 
    1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 
    1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 
    1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 
    2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 
    2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 
    2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 
    2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 
    1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 
    1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 
    2L, 1L, 2L, 2L, 1L), levels = c("P", "E"), class = "factor"), 
    SCORE = c(0L, 3L, 3L, 11L, 8L, 0L, 8L, 0L, 1L, 7L, 0L, 6L, 
    2L, 6L, 4L, 9L, 7L, 4L, 15L, 4L, 9L, 1L, 7L, 1L, 0L, 4L, 
    1L, 3L, 2L, 9L, 2L, 4L, 0L, 7L, 1L, 10L, 12L, 1L, 9L, 0L, 
    6L, 2L, 8L, 4L, 9L, 0L, 10L, 0L, 6L, 10L, 2L, 7L, 0L, 5L, 
    5L, 10L, 1L, 10L, 1L, 4L, 2L, 10L, 0L, 6L, 9L, 1L, 11L, 1L, 
    7L, 7L, 12L, 0L, 4L, 11L, 3L, 7L, 12L, 12L, 0L, 8L, 1L, 12L, 
    11L, 1L, 10L, 2L, 13L, 3L, 9L, 7L, 9L, 3L, 12L, 4L, 10L, 
    8L, 2L, 5L, 5L, 12L, 7L, 11L, 0L, 6L, 1L, 7L, 0L, 10L, 1L, 
    6L, 0L, 5L, 10L, 0L, 2L, 8L, 1L, 10L, 7L, 1L, 10L, 0L, 0L, 
    5L, 1L, 11L, 4L, 1L, 5L, 1L, 10L, 8L, 0L, 0L, 6L, 0L, 10L, 
    0L, 7L, 1L, 0L, 0L, 1L, 0L, 1L, 11L, 0L, 7L, 0L, 8L, 2L, 
    7L, 3L, 10L, 3L, 12L, 2L, 9L, 0L, 3L, 5L, 12L, 6L, 14L, 1L, 
    9L, 1L, 10L, 1L, 8L, 1L, 11L, 0L, 4L, 2L, 11L, 0L, 9L, 1L, 
    9L, 7L, 1L, 8L, 1L, 8L, 0L, 11L, 3L, 11L, 9L, 11L, 2L, 9L, 
    1L, 8L, 2L, 9L, 0L, 6L, 3L, 7L, 1L, 7L, 4L, 11L, 2L, 7L, 
    3L, 9L, 0L, 5L, 0L, 5L, 5L, 11L, 4L, 14L, 2L, 6L, 3L, 6L, 
    2L, 6L, 5L, 11L, 9L, 3L, 11L, 0L, 9L, 0L, 0L, 0L, 0L, 4L, 
    13L, 0L, 6L, 2L, 6L, 1L, 7L, 0L, 7L, 0L, 5L, 2L, 4L, 9L, 
    12L, 2L, 11L, 3L, 9L, 5L, 9L, 0L, 6L, 9L, 4L, 13L, 12L, 6L, 
    15L, 5L, 12L, 2L, 12L, 12L, 1L, 5L, 4L, 8L, 3L, 9L, 7L, 13L, 
    4L, 10L, 6L, 12L, 1L, 11L, 7L, 12L, 10L, 13L, 4L, 14L, 6L, 
    11L, 2L, 14L, 1L, 9L, 4L, 9L, 1L, 11L, 1L, 8L, 11L, 3L, 12L, 
    3L, 11L, 4L, 7L, 1L, 5L, 1L, 11L, 8L, 12L, 0L, 8L, 2L, 10L, 
    6L, 12L, 0L, 4L, 2L, 10L, 7L, 13L, 7L, 13L, 11L, 14L, 2L, 
    10L, 7L, 13L, 3L, 11L, 6L, 10L, 1L, 10L, 3L, 12L, 7L, 14L, 
    5L, 9L, 1L, 9L, 4L, 12L, 10L, 4L, 8L, 12L, 4L, 8L, 7L, 15L, 
    6L, 11L, 13L, 10L, 14L, 2L, 11L, 2L, 10L, 4L, 11L, 4L, 14L, 
    2L, 9L, 2L, 12L, 1L, 9L, 9L, 1L, 9L, 5L, 11L, 1L, 9L, 1L, 
    11L, 6L, 14L, 4L, 13L, 10L, 4L, 11L, 15L, 12L, 2L, 13L, 1L, 
    11L, 0L, 8L, 1L, 9L, 2L, 0L, 11L, 6L, 15L, 5L, 9L, 10L, 14L, 
    7L, 15L, 5L, 13L, 6L, 13L, 1L, 5L, 1L, 11L, 8L, 12L, 1L, 
    7L, 6L, 13L, 3L, 12L, 4L, 12L, 6L, 15L, 1L, 10L, 4L, 12L, 
    3L, 10L, 3L, 11L, 13L, 1L, 9L, 1L, 11L, 8L, 13L, 7L, 2L, 
    8L, 2L, 10L, 2L, 9L, 3L, 11L, 5L, 11L, 3L, 11L, 2L, 7L, 3L, 
    9L, 12L, 2L, 13L, 1L, 12L, 0L, 9L, 1L, 11L, 11L, 11L, 4L, 
    11L, 5L, 12L, 12L, 10L, 6L, 11L, 6L, 11L, 12L, 14L, 5L, 14L, 
    10L, 14L, 7L, 11L, 2L, 9L, 4L, 12L, 5L, 11L, 2L, 10L, 2L, 
    2L, 7L, 1L, 10L, 0L, 14L, 6L, 14L, 10L, 11L, 11L, 8L, 15L, 
    1L, 9L, 12L, 7L, 12L, 4L, 3L, 10L)), class = "data.frame", row.names = c(NA, 
-525L))

>Solution :

You could create a little dummy data frame which includes the TEST variable, then draw the annotation using geom_richtext from ggtext:

library(ggtext)

ggplot(df, aes(x = GROUP, y = SCORE, fill = TEST)) +
  stat_boxplot(geom = "errorbar",
               width = 0.15) +
  geom_boxplot(aes(fill = TEST), outlier.colour = "black", outlier.shape = 19,
               outlier.size= 2, notch = T) +
  stat_summary(fun = mean, geom = "point", shape = 20, size= 3, 
               color= "black", show.legend = FALSE) +
  facet_wrap(~ TEST) +
  labs(x = "Group",
       y = "Score") +
  geom_richtext(data = data.frame(x = 1.5, SCORE = 16, 
                                  TEST = factor(c('E', 'P'), c('P', 'E')),
                                  label = c('t(97) = 9.45, <i>p</i> < 0.001',
                                            'W = 5253.50, <i>p</i> < 0.001')),
                aes(x = x, label = label), fill = NA, label.colour = NA)