Piping the removal of empty columns using dplyr

We can use a version of select_if

library(dplyr)
df %>%
   select_if(function(x) !(all(is.na(x)) | all(x=="")))

#  id Q2 Q3 Q4
#1  1  1 NA   
#2  2     2   
#3  3  4  3  2
#4  4  5  4  2

Or without using an anonymous function call

df %>% select_if(~!(all(is.na(.)) | all(. == "")))

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You can also modify your apply statement as

df[!apply(df, 2, function(x) all(is.na(x)) | all(x==""))]

Or using colSums

df[colSums(is.na(df) | df == "") != nrow(df)]

and inverse

df[colSums(!(is.na(df) | df == "")) > 0]

With dplyr version 1.0, you can use the helper function where() inside select instead of needing to use select_if.

library(tidyverse)
df <- data.frame(id = c(1, 2, 3, 4),
                 Q1 = c(1, "", 4, 5), 
                 Q2 = c(NA, NA, NA, NA),
                 Q3 = c(NA, 2, 3, 4), 
                 Q4 = c("", "", 2, 2), 
                 Q5 = c("", "", "", ""))

df %>% select(where(~ !(all(is.na(.)) | all(. == ""))))
#>   id Q1 Q3 Q4
#> 1  1  1 NA   
#> 2  2     2   
#> 3  3  4  3  2
#> 4  4  5  4  2