Joining means on a boxplot with a line (ggplot2)

I have a boxplot showing multiple boxes. I want to connect the mean for each box together with a line. The boxplot does not display the mean by default, instead the middle line only indicates the median. I tried

ggplot(data, aes(x=xData, y=yData, group=g)) 
    + geom_boxplot() 
    + stat_summary(fun.y=mean, geom="line")

This does not work.

Interestingly enough, doing

stat_summary(fun.y=mean, geom="point") 

draws the median point in each box. Why would "line" not work?

Something li开发者_如何学编程ke this but using ggplot2, http://www.aliquote.org/articles/tech/RMB/c4_sols/plot45.png

Is that what you are looking for?

library(ggplot2)

x <- factor(rep(1:10, 100))
y <- rnorm(1000)
df <- data.frame(x=x, y=y)

ggplot(df, aes(x=x, y=y)) + 
geom_boxplot() + 
stat_summary(fun=mean, geom="line", aes(group=1))  + 
stat_summary(fun=mean, geom="point")

Update:

Some clarification about setting group=1: I think that I found an explanation in Hadley Wickham's book "ggplot2: Elegant Graphics for Data Analysis. On page 51 he writes:

Different groups on different layers.

Sometimes we want to plot summaries based on different levels of aggregation. Different layers might have different group aesthetics, so that some display individual level data while others display summaries of larger groups.

Building on the previous example, suppose we want to add a single smooth line to the plot just created, based on the ages and heights of all the boys. If we use the same grouping for the smooth that we used for the line, we get the first plot in Figure 4.4.

p + geom_smooth(aes(group = Subject), method="lm", se = F)

This is not what we wanted; we have inadvertently added a smoothed line for each boy. This new layer needs a different group aesthetic, group = 1, so that the new line will be based on all the data, as shown in the second plot in the figure. The modified layer looks like this:

p + geom_smooth(aes(group = 1), method="lm", size = 2, se = F)

[...] Using aes(group = 1) in the smooth layer fits a single line of best fit across all boys."

Another longer approach (in case if the data is in two different dataframes) is:

library(dplyr); library(ggplot2)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union

x <- factor(rep(1:10, 100)); y <- rnorm(1000);
df <- data.frame(x=x, y=y);
df_for_line <- df %>% group_by(x) %>% summarise(mean_y = mean(y));
ggplot(df, aes(x = x, y = y)) + geom_boxplot() + 
    geom_path(data = df_for_line, aes(x = x, y = mean_y, group = 1))

^{Created on 2021-04-15 by the reprex package (v1.0.0)}

Again, `group = 1` is the key.