Difficulties in combining two boxplots per x-value in ggplot2 / R - r

Question

Please find My Data below.
I wish to produce a combined boxplot as this one:
I have four different patient categories in w$WHO==1,2,3,4 each corresponding to WHO-I, WHO-II, WHO-III and Unknown tumors.
I wish to produce two boxplots per w$WHO
The first boxplot should show time to death as in w$Follow.up.death[w$Death==1]. I would like to color/outline + fill to be blue but the fill should have an alpha=0.2.
The second boxplot should show time to progression as in w$resp.time[w$response==1]. I would like to color/outline + fill to be red but the fill should have an alpha=0.2.
w$Death and w$response does not have the same length.
The corresponding legend should read "Overall survival" and "Progression-free survival".
I tried several manuals but I can't figure how to do this specifically - I have only managed to produce single plots.
Any ideas how to solve this??
A sample of My data
w <- structure(list(WHO = c(1L, 3L, 2L, 2L, 2L, 3L, 2L, 3L, 1L, 2L,
3L, 3L, 3L, 1L, 2L, 1L, 2L, 3L, 3L, 1L, 2L, 1L, 3L, 1L, 1L, 1L,
1L, 1L, 1L, 2L, 4L, 4L, 1L, 4L, 1L, 2L, 1L, 4L, 1L, 4L, 4L, 4L,
4L, 3L, 3L, 4L, 4L, 4L, 4L, 1L, 4L, 4L, 2L, 1L, 2L, 2L, 4L, 4L,
4L, 2L, 4L, 1L, 4L, 4L, 2L, 4L, 4L, 3L, 4L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 3L, 2L, 2L, 3L, 3L, 3L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L
), Death = c(0L, 1L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 1L,
0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 1L,
0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L,
1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
1L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 1L, 1L, 1L, 0L, 0L, 1L, 0L, 1L,
0L, 0L, 1L, 0L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 0L, 1L, 1L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L), Follow.up.death = c(18,
2, 14, 17, 31, 4, 20, 15, 12, 19, 10, 17, 27, 22, 3, 43, 24,
14, 13, 5, 12, 137, 22, 87, 48, 24, 72, 32, 14, 83, 68, 56, 57,
18, 16, 70, 1.9, 69.2, 126.3, 41.6, 17.9, 1.3, 87.4, 4.4, 137.4,
17.5, 95.8, 65.2, 14.8, 98.5, 16.6, 74.9, 10.3, 43.4, 32.5, 4.8,
7.3, 107.8, 6.8, 18.3, 33, 25.2, 49.2, 15.9, 1.2, 42.7, 1, 9,
1.8, 15.6, 8.9, 15, 16.4, 7.7, 75.5, 12.2, 54.8, 22.2, 9.7, 14.3,
5.2, 64.5, 21.8, 0.2, 7.3, 18.7, 5.1, 17.3, 27.4, 16, 24.2, 9.7,
8.2, 5.7, 41.8, 10.6, 22.8, 4.8, 6, 4, 50, 21, 30, 5, 11, 12),
response = c(0L, 1L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L,
1L, 1L, 0L, 1L, 0L, 1L, 1L, 1L, 0L, 1L, 0L, 1L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0L, 0L,
0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 1L, 1L, 0L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 0L,
0L, 0L, 0L, 0L, 0L), resp.time = c(18, 2, 13, 17, 22, 2,
6, 5, 12, 8, 3, 2, 1, 21, 2, 43, 4, 2, 4, 5, 0.1, 137, 4,
87, 17, 24, 72, 19, 14, 83, 68, 56, 57, 18, 14, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, 15.6, 8.9, 15, 16.4, 7.7, 75.5, 3, 54.8, 22.2, 12, 14.3,
6, 12, 21.8, 6, 3, 12, 3, 6, 3, 3, 12, 9.7, 3, 3, 12, 3,
6, 3, 6, 4, 50, 21, 30, 5, 11, 12)), .Names = c("WHO", "Death",
"Follow.up.death", "response", "resp.time"), class = "data.frame", row.names = c(NA,
-106L))

Answer 1

Does this come close?
# Wrangling data into a digestable format
v <- w[w$Death == 1,]
vv <- w[w$response == 1,]
df <- data.frame(x = as.factor(c(v$WHO, vv$WHO)),
y = c(v$Follow.up.death, vv$resp.time),
f = rep(c("Death", "Response"), c(nrow(v), nrow(vv))))
df <- df[!is.na(df$x),]
And then making the plot:
ggplot(df) +
geom_boxplot(aes(x, y, fill = f, colour = f)) +
scale_x_discrete(name = "WHO") +
scale_y_continuous(name = "Time") +
# Alpha encoded as hex values as to force to apply on fill only
# Not sure if alpha = 0.2 corresponds to '33'
scale_fill_manual(values = c("#FF000033", "#0000FF33"), name = "Survival",
labels = c("Overall", "Progression-free")) +
scale_colour_manual(values = c("red", "blue"), name = "Survival",
labels = c("Overall", "Progression-free"))

Answer 2

Similar to #tuenbrand's approach, but using dplyr/tidyr to wrangle the data:
library(tidyverse)
df <- w %>%
rename(Overall = "Follow.up.death", `Progression-free` = "resp.time") %>%
gather(key = Survival, value = Time, Overall, `Progression-free`) %>%
filter((Death == 1 & Survival == "Overall") |
(response == 1 & Survival == "Progression-free")) %>%
mutate(WHO = paste("WHO:", WHO))
And then facet on WHO to space the boxplots:
ggplot(df, aes(x = Survival, y = Time, fill = Survival)) +
geom_boxplot() + facet_wrap(~WHO, nrow = 1) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
axis.title.x = element_blank(),
legend.position = "bottom")