gghighlight in clustered (grouped) bar chart in R

I need to use gghighlight in a clustered bar chart in R in order to highlight only one single bar. My code and sample data looks like this:

library(tidyr)
library(ggplot2)
dat <- data.frame(country=c('USA','Brazil','Ghana','England','Australia'), Stabbing=c(15,10,9,6,7), Accidents=c(20,25,21,28,15), Suicide=c(3,10,7,8,6))
dat.m <- melt(dat, id.vars='country')
dat.g <- gather(dat, type, value, -country)
ggplot(dat.g, aes(type, value)) + 
  geom_bar(aes(fill = country), stat = "identity", position = "dodge") +
  gghighlight(type == "Accidents" & country == "Brazil")

But this gives me this awkward

How can I get gghighlight to highlight only one single bar of one group (so combining two conditions for two discrete variables)?

I think gghighlight is not built for this kind of plot - not yet! You could file a feature request ? It is a bit unclear though if this visualisation is very helpful. Gghighlight always draws everything - this makes the "weird" shadows when dodging.

If you want to keep using gghightlight, maybe try faceting, which they suggest in their vignette

A suggestion - Use facets:

(using mtcars as example)

library(tidyverse)
library(gghighlight)

mtcars2 <- mtcars %>% mutate(cyl = as.character(cyl), gear = as.character(gear))
ggplot(mtcars2, aes(cyl, disp, fill = gear))  +
  geom_col() + #no dodge
  gghighlight(cyl == "4") + #only one variable
  facet_grid(~ gear) #the other variable is here
#> Warning: Tried to calculate with group_by(), but the calculation failed.
#> Falling back to ungrouped filter operation...

^{Created on 2020-03-09 by the reprex package (v0.3.0)}

Or, here without gghighlight, in a more traditional subsetting approach. You need to make a subset of data which contains rows for each group you want to dodge by, in this case "cyl" and "gear". I replace the irrelevant data with "NA", you could also use "0".

library(tidyverse)

mtcars2 <- mtcars %>% 
  mutate(cyl = as.character(cyl), gear = as.character(gear)) %>% 
  group_by(cyl, gear) %>% 
  summarise(disp = mean(disp))

subset_mt <- mtcars2 %>% mutate(highlight = if_else(cyl == '4' & gear == '3', disp, NA_real_))

ggplot()  +
  geom_col(data = mtcars2, aes(cyl, disp, group = gear), fill = 'grey', alpha = 0.6, position = 'dodge') +
  geom_col(data = subset_mt, aes(cyl, highlight, fill = gear), position = 'dodge') 
#> Warning: Removed 7 rows containing missing values (geom_col).

^{Created on 2020-03-10 by the reprex package (v0.3.0)}