[英]How to use a function to place text in geom_boxplot
I'm working on some boxplots.我正在研究一些箱线图。 Here is a working example:这是一个工作示例:
data(mtcars)
# Compute means for each group
mpgmn <- aggregate(mpg ~ cyl, mtcars, mean)
mpgmn$mpg <- round(mpgmn$mpg, 2)
# Same thing for 50th and 75th %tiles
mpglims <- mtcars %>% group_by(cyl) %>%
summarize(q50 = quantile(mpg, probs = 0.50),
q75 = quantile(mpg, probs = 0.75))
# Plot
library(ggplot2)
g <- ggplot(mtcars, aes(x = as.factor(cyl), y = mpg,
fill = as.factor(cyl)))
g <- g + geom_boxplot()
g <- g + stat_summary(fun = mean, color = "white", geom = "point",
shape = 18, size = 3, show.legend = FALSE)
g <- g + geom_text(data = mpgmn,
aes(label = paste("mean = ", mpg),
y = mpg + 0.5), color = "white")
g
All of this works.所有这些都有效。 However, I would like to use the mpglims
that I computed (that look correct to me) to place the white text inside each of the boxplots (ie, instead of the current vertical position argument: y = mpg + 0.05
).但是,我想使用我计算的mpglims
(对我来说看起来正确)将白色文本放置在每个箱线图中(即,而不是当前的垂直 position 参数: y = mpg + 0.05
)。 Is there a way to tell R to pick the halfway point between the two values that I computed for each group for the vertical position?有没有办法告诉 R 选择我为垂直 position 为每个组计算的两个值之间的中间点?
The easiest way might be to add one more variable to the creation of mpglims
:最简单的方法可能是在创建mpglims
时再添加一个变量:
mpglims <- mtcars %>% group_by(cyl) %>%
summarize(q50 = quantile(mpg, probs = 0.50),
q75 = quantile(mpg, probs = 0.75),
mid = (q50 + q75)/ 2)
Use mid
in y = mid
in the geom_text()
call.在geom_text()
调用中使用mid
in y = mid
。
If you want to use what you calculated in the first data frame mpgmn
, make it a bit easier on yourself and add that to mpglims
, as well:如果您想使用您在第一个数据帧mpgmn
中计算的内容,请让自己更轻松一些并将其添加到mpglims
中,以及:
mpglims <- mtcars %>% group_by(cyl) %>%
summarize(q50 = quantile(mpg, probs = 0.50),
q75 = quantile(mpg, probs = 0.75),
mid = (q50 + q75)/ 2,
mmpg = mean(mpg) %>% round(., digits = 2))
It creates the same thing as your aggregate()
call.它创建与您的aggregate()
调用相同的东西。 Check it out:一探究竟:
mpglims[, 5] %>% unlist()
# mmpg1 mmpg2 mmpg3
# 26.66 19.74 15.10
Putting all informations already provided by Kat (this answer should be the accepted one) and the OP, here is one possibly tidyverse
way:将 Kat 已经提供的所有信息(这个答案应该是公认的)和 OP 提供,这是一种可能tidyverse
方式:
library(tidyverse)
mtcars %>%
select(cyl, mpg) %>%
group_by(cyl = as.factor(cyl)) %>%
mutate(mpg_mean = round(mean(mpg, na.rm = TRUE),2)) %>%
mutate(q50 = quantile(mpg, probs = 0.50),
q75 = quantile(mpg, probs = 0.75)) %>%
mutate(mid = (q50 + q75)/ 2) %>%
ggplot(aes(x = cyl, y = mpg, fill = cyl)) +
geom_boxplot() +
stat_summary(fun = mean, color = "white", geom = "point",
shape = 18, size = 3, show.legend = FALSE) +
geom_text(aes(label = paste("mean = ", mpg_mean),
y = mid), color = "white")
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