1 Load packages
library(tidyverse) # data wrangling2 Data
data("mariokart", package = "openintro")3 Unadjusted labels
mario_quantile <-
mariokart %>%
filter(total_pr < 100) %>%
summarise(q25 = quantile(total_pr, .25),
q50 = quantile(total_pr, .50),
q75 = quantile(total_pr, .75))
mario_quantile <-
mariokart %>%
filter(total_pr < 100) %>%
reframe(qs = quantile(total_pr, c(.25, .5, .75)))
mariokart %>%
filter(total_pr < 100) %>%
ggplot(aes(x = total_pr)) +
geom_histogram() +
geom_vline(xintercept = mario_quantile$qs) +
annotate("label", x = mario_quantile$qs, y = 0, label = mario_quantile$qs) +
annotate("label", x = mario_quantile$qs, y = Inf, label = c("Q1", "Median", "Q3")) 
4 Adjusted labels manually
vjust = 2 does the trick:
mario_quantile <-
mariokart %>%
filter(total_pr < 100) %>%
summarise(q25 = quantile(total_pr, .25),
q50 = quantile(total_pr, .50),
q75 = quantile(total_pr, .75))
mario_quantile <-
mariokart %>%
filter(total_pr < 100) %>%
reframe(qs = quantile(total_pr, c(.25, .5, .75)))
mariokart %>%
filter(total_pr < 100) %>%
ggplot(aes(x = total_pr)) +
geom_histogram() +
geom_vline(xintercept = mario_quantile$qs) +
annotate("label", x = mario_quantile$qs, y = 0, label = mario_quantile$qs) +
annotate("label", x = mario_quantile$qs, y = Inf, label = c("Q1", "Median", "Q3"), vjust = 2) 
5 Adjust labels automatically
Using vjust = "top" (or “bottom”) does the trick in an automatic, comfortable way.
mariokart %>%
filter(total_pr < 100) %>%
ggplot(aes(x = total_pr)) +
geom_histogram() +
geom_vline(xintercept = mario_quantile$qs) +
annotate("label", x = mario_quantile$qs, y = 0, label = mario_quantile$qs, vjust = "bottom") +
annotate("label", x = mario_quantile$qs, y = Inf, label = c("Q1", "Median", "Q3"), vjust = "top") 
Similarly, one case use hjust = "left" for horizontal alignment.
6 Reproducibility
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