R ggplot：更改Grouped Boxplot Median行

Question

I have plotted grouped boxplots and now I would like to replace the standard black median line with a white line while keeping the borders in an other color. I'm following the instructions on the site Minimalist Boxplots because I really like their style.

They use the command stat_summary(geom = "crossbar", width=0.65, fatten=0, color="white", fun.data = function(x){ return(c(y=median(x), ymin=median(x), ymax=median(x))) }) . That command worked well with simple boxplots:

But now that I'm trying to use it on my grouped boxplots its not working anymore (white median line is missing):

Here is my the code for reproducing my data:

Data <- data.frame(
  W = sample(1:100),
  M = sample(1:100),
  A = sample(1:100),
  O = sample(1:100),
  Type = sample(c("1", "2", "3", "4", "5")))

And my script:

Data_Boxplot <- melt(Data,id.vars='Type', measure.vars=c('W','M','A', 'O'))
Boxplots <- ggplot(Data_Boxplot, aes(Type, value, group=variable)) +
  geom_boxplot(outlier.colour = NULL, aes(color=variable, fill=variable)) + 
  stat_summary(geom = "crossbar", width=0.65, fatten=0, color="white", 
               fun.data = function(x){c(y=median(x), ymin=median(x), ymax=median(x))})
Boxplots

What do I have to change? Thank you very much for your help.

Answer 1

You only mapped x and y for the geom_boxplot . Variables that are shared among geoms should be mapped for all. In this case, you also need to group by variable .

ggplot(Data.m, aes(Type, value, group=variable) +
  geom_boxplot(outlier.colour = NULL, aes(color=variable, fill=variable)) + 
  stat_summary(geom = "crossbar", width=0.65, fatten=0, color="white", 
               fun.data = function(x){c(y=median(x), ymin=median(x), ymax=median(x))})

I did not test, as you did not provide data.

Edit:

Ok, now that we have a good example with data we can see what's going on.

There is actually a two issues I had missed. Both are because geom_boxplot will automatically solve some problems for you because of the fill , that stat_summary doesn't. So we'll have to do them manually.

Firstly, we want to be grouping on both variable as well as Type , we can do this by using the interaction function.

Secondly, the boxplots are automatically dodged (ie moved apart within groups), while the horizontal lines aren't. We'll define our positioning using position_dodge , and apply it to both geoms. Applying it to both is the easiest way to make them exactly line up. We end up with:

p <- position_dodge(0.8)
ggplot(Data_Boxplot, aes(Type, value, group = interaction(variable, Type))) +
  geom_boxplot(aes(color = variable, fill = variable), outlier.colour = NULL, position = p) + 
  stat_summary(geom = "crossbar", width = 0.6, fatten=0, color="white", position = p,
               fun.data = function(x){c(y=median(x), ymin=median(x), ymax=median(x))}) +
  theme_minimal()