ggplot prioritize line overlap - r

Question

library(tidyverse)
mtcars %>%
mutate(ID = row_number()) %>%
select(ID, vs, am, gear, carb) %>%
gather(key, value, 2:5) %>%
mutate(violation = c(rep(FALSE, 96), rep(TRUE, 32))) %>%
ggplot(aes(ID, value, group = key, color = violation)) +
scale_color_manual(values = c("grey", "red")) +
geom_line() +
theme_classic()
In the image below the red 'violation' line is broken up into segments. I assume this is because ggplot is plotting lines sequentially, and one of the grey lines, is plotted after the red line, with the same coordinates. How do I stop the grey lines from overlapping the red?
As referenced in other stackoverflow questions, I would add a seperate line like this:
geom_line(df %>% filter(violation == TRUE), aes(color = "red")) +
but this causes problems when there are no violations in my data frames. I do monthly analyses and some months contain violations, some months do not. If I add this single line above I get an error "must be length greater than 0" for the months absent violations, so this one-liner approach probably won't work.

Answer 1

You might use the following code (with only 2 minor changes as compared to your code)
library(tidyverse)
mtcars %>%
mutate(ID = row_number()) %>%
select(ID, vs, am, gear, carb) %>%
gather(key, value, 2:5) %>%
mutate(violation = c(rep(FALSE, 96), rep(TRUE, 32))) %>%
ggplot(aes(ID, value, group = key, color = violation)) +
scale_color_manual(values = c("grey", "red")) +
geom_line(alpha = .5, size= 1.2) + ### changes in transparancy and thickness ###
theme_classic()
Yielding this plot:
"H 1"'s suggestion is an alternative approach which changes the sequence of line drawings:
mtcars %>%
mutate(ID = row_number()) %>%
select(ID, vs, am, gear, carb) %>%
gather(key, value, 2:5) %>%
mutate(violation = c(rep(FALSE, 96), rep(TRUE, 32))) %>%
ggplot(aes(ID, value, group = key, color = violation)) +
scale_color_manual(values = c("grey", "red")) +
geom_line(aes(group = rev(key))) + ### changes sequence of plotting of the lines ###
theme_classic()
This produces the following plot: