In R, how do I drop a column whose values are all FALSE?

Question

I have a dataframe, df. Some of its columns include logicals. I would like to drop the ones that are all FALSE.

library(tibble)
df <- tibble(A = rep(TRUE, 5),
             B = rep(FALSE, 5),
             C = c(TRUE, FALSE, TRUE, TRUE, FALSE))

df

# A tibble: 5 x 3
  A     B     C    
  <lgl> <lgl> <lgl>
1 TRUE  FALSE TRUE 
2 TRUE  FALSE FALSE
3 TRUE  FALSE TRUE 
4 TRUE  FALSE TRUE 
5 TRUE  FALSE FALSE

The desired output is:

  A     C    
  <lgl> <lgl>
1 TRUE  TRUE 
2 TRUE  FALSE
3 TRUE  TRUE 
4 TRUE  TRUE 
5 TRUE  FALSE

I have tried selecting constant columns using the janitor package, but that will remove columns that are all TRUE also.

How may I do this? (I prefer a tidyverse solution, but barring that base R or some other available package is acceptable.)

Edit: My minimal working example above was too minimal. I should have mentioned that there are non-logical columns I want to keep too. The solution for me, provided by akrun in chat, was:

library(dplyr)
library(purrr)
df %>% select(where(~ is.logical(.) && any(.)), where(negate(is.logical)))

Answer 1

Using base R with Filter and any

Filter(any, df)

---

Or in dplyr

library(dplyr)
df %>%
    select(where(any))

-output

# A tibble: 5 x 2
#  A     C    
#  <lgl> <lgl>
#1 TRUE  TRUE 
#2 TRUE  FALSE
#3 TRUE  TRUE 
#4 TRUE  TRUE 
#5 TRUE  FALSE

---

Based on the OP's comments, wanted to keep columns that are not logical in type along with columns with logical type and any TRUE

library(purrr)
df %>% 
  select(where(~ is.logical(.) && any(.)), where(negate(is.logical)))

Answer 2

That's cleanest solution:

select_if(.tbl = df, .predicate = any)

Explanation:

• .predicate - applied to columns, will leave columns for which returned values are all TRUE
• any - will return TRUE for any TRUE values present. Will also work for combinations any(0,-1). There is one edge case where any(0, 0) would return FALSE.
  • If you may have a column that may contain only 0s you may want implement additional check. Again that would be equivalent to any(NULL, NULL)

---

Let's say that you want to avoid those edge cases, better option:

select_if(.tbl = df, .predicate = ~ all(isFALSE(.x)))