Removing the borders in geom_boxplot in ggplot2

Question

This should seem relatively straightforward but I can't find an argument which would allow me to do this and I've searched Google and Stack for an answer.

Sample code:

library(ggplot2)
library(plotly)

dat <- data.frame(cond = factor(rep(c("A","B"), each=200)), rating = c(rnorm(200),rnorm(200, mean=.8)))

p <- ggplot(dat, aes(x=cond, y=rating, fill=cond)) + geom_boxplot()

p <- ggplotly(p)

This outputs the first graph, I would want something like the second.

I tried including colour=cond but that gets rid of the median.

Answer 1

Two possible hacks for consideration, using the same dataset as Marco Sandri's answer.

Hack 1 . If you don't really need it to work in plotly, just static ggplot image:

ggplot(dat, aes(x=cond, y=rating, fill=cond)) + 
  geom_boxplot() +
  geom_boxplot(aes(color = cond),
               fatten = NULL, fill = NA, coef = 0, outlier.alpha = 0,
               show.legend = F)

This overlays the original boxplot with a version that's essentially an outline of the outer box, hiding the median ( fatten = NULL ), fill colour ( fill = NA ), whiskers ( coef = 0 ) & outliers ( outlier.alpha = 0 ).

However, it doesn't appear to work well with plotly. I've tested it with the dev version of ggplot2 (as recommended by plotly) to no avail. See output below:

Hack 2 . If you need it to work in plotly:

ggplot(dat %>%
         group_by(cond) %>%
         mutate(rating.IQR = case_when(rating <= quantile(rating, 0.3) ~ quantile(rating, 0.25),
                                       TRUE ~ quantile(rating, 0.75))), 
       aes(x=cond, y=rating, fill=cond)) + 
  geom_boxplot() +
  geom_boxplot(aes(color = cond, y = rating.IQR),
               fatten = NULL, fill = NA)

(ggplot output is same as above)

plotly doesn't seem to understand the coef = 0 & output.alpha = 0 commands, so this hack creates a modified version of the y variable, such that everything below P30 is set to P25, and everything above is set to P75. This creates a boxplot with no outliers, no whiskers, and the median sits together with the upper box limit at P75.

It's more cumbersome, but it works in plotly:

Answer 2

Here is an inelegant solution based on grobs:

set.seed(1)
dat <- data.frame(cond = factor(rep(c("A","B"), each=200)), 
                  rating = c(rnorm(200),rnorm(200, mean=.8)))

library(ggplot2)
library(plotly)
p <- ggplot(dat, aes(x=cond, y=rating, fill=cond)) + geom_boxplot() 

# Generate a ggplot2 plot grob
g <- ggplotGrob(p)

# The first box-and-whiskers grob
box_whisk1 <- g$grobs[[6]]$children[[3]]$children[[1]]
pos.box1 <- which(grepl("geom_crossbar",names(box_whisk1$children)))
g$grobs[[6]]$children[[3]]$children[[1]]$children[[pos.box1]]$children[[1]]$gp$col <-
  g$grobs[[6]]$children[[3]]$children[[1]]$children[[pos.box1]]$children[[1]]$gp$fill

# The second box-and-whiskers grob    
box_whisk2 <- g$grobs[[6]]$children[[3]]$children[[2]]
pos.box2 <- which(grepl("geom_crossbar",names(box_whisk2$children)))
g$grobs[[6]]$children[[3]]$children[[2]]$children[[pos.box2]]$children[[1]]$gp$col <-
  g$grobs[[6]]$children[[3]]$children[[2]]$children[[pos.box2]]$children[[1]]$gp$fill

library(grid)
grid.draw(g)

PS To my knowledge, the above code cannot be used for generating plotly graphs.