Can you facet on a indicator variable in ggplot2?

Question

types = c("A", "B", "C")
df = data.frame(n = rnorm(100), type=sample(types, 100, replace = TRUE))
ggplot(data=df, aes(n)) + geom_histogram() + facet_grid(~type)

Above is how I normally used facetting. But can I use it when instead of a categorical variable I have a set of columns that are indicator variables such as:

df = data.frame(n = rnorm(100), A=rbinom(100, 1, .5), B=rbinom(100, 1, .5), C=rbinom(100, 1, .5))

Now the "Type" variable from my previous example isn't mutually exclusive. An observation can be "A and B" or "A and B and C" for example. However, I'd still like an individual histogram for any observation that has the presence of A, B, or C?

Answer 1

I would reshape the data with tidyr so that data in more that one category are duplicated. filter to remove unwanted cases.

df <- data.frame(
  n = rnorm(100),
  A = rbinom(100, 1, .5),
  B = rbinom(100, 1, .5),
  C = rbinom(100, 1, .5)
)

library("tidyr")
library("dplyr")
library("ggplot2")

df %>% gather(key = "type", value = "value", -n) %>%
  filter(value == 1) %>%
  ggplot(aes(x = n)) +
    geom_histogram() +
    facet_wrap(~type)

Answer 2

I've always despised gather, so I'll add another method and one for the data.table fans.

library(data.table)
DT <- melt(setDT(df), id= "n", variable = "type")[value > 0]
ggplot(DT,aes(n)) + geom_histogram() + facet_grid(~type)

#tidyland
library(reshape2)
library(dplyr)
library(ggplot2)
df %>% 
  melt(id = "n", variable = "type") %>% 
  filter(value > 0) %>% 
  ggplot(aes(n)) + geom_histogram() + facet_grid(~type)