Remove rows where all variables are NA using dplyr

Question

I\'m having some issues with a seemingly simple task: to remove all rows where all variables are NA using dplyr. I know it can be done using base R (Re

Answer 1

Here's another solution that uses purrr::map_lgl() and tidyr::nest():

library(tidyverse)

dat <- tibble(a = c(1, 2, NA), b = c(1, NA, NA), c = c(2, NA, NA))

any_not_na <- function(x) {
  !all(map_lgl(x, is.na))
}


dat_cleaned <- dat %>%
  rownames_to_column("ID") %>%
  group_by(ID) %>%
  nest() %>%
  filter(map_lgl(data, any_not_na)) %>%
  unnest() %>%
  select(-ID)
## Warning: package 'bindrcpp' was built under R version 3.4.2

dat_cleaned
## # A tibble: 2 x 3
##       a     b     c
##     
## 1    1.    1.    2.
## 2    2.   NA    NA

I doubt this approach will be able to compete with the benchmarks in @hejseb's answer, but I think it does a pretty good job at showing how the nest %>% map %>% unnest pattern works and users can run through it line-by-line to figure out what's going on.