Removing the borders in geom_boxplot in ggplot2 - r

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)
P.S. To my knowledge, the above code cannot be used for generating plotly graphs.