How to sort NA first in dplyr?

Question

Consider the following example:

require(tibble) require(dplyr) set.seed(42) tbl <- data_frame(id = letters[1:10], val = c(runif(5), NA, runif(4))) tbl 

 # A tibble: 10 × 2 id val <chr> <dbl> 1 a 0.9148060435 2 b 0.9370754133 3 c 0.2861395348 4 d 0.8304476261 5 e 0.6417455189 6 f NA 7 g 0.5190959491 8 h 0.7365883146 9 i 0.1346665972 10 j 0.6569922904 

I want to sort the tibble by val , putting NA first:

 tbl %>% arrange(val) 

 # A tibble: 10 × 2 id val <chr> <dbl> 1 i 0.1346665972 2 c 0.2861395348 3 g 0.5190959491 4 e 0.6417455189 5 j 0.6569922904 6 h 0.7365883146 7 d 0.8304476261 8 a 0.9148060435 9 b 0.9370754133 10 f NA 

Unfortunately, arrange are put last on arrange .

The best hack I've found so far is combining slice with the good old order :

 tbl %>% slice(order(.$val, na.last = FALSE)) 

 # A tibble: 10 × 2 id val <chr> <dbl> 1 f NA 2 i 0.1346665972 3 c 0.2861395348 4 g 0.5190959491 5 e 0.6417455189 6 j 0.6569922904 7 h 0.7365883146 8 d 0.8304476261 9 a 0.9148060435 10 b 0.9370754133 

What is the way dplyr get the above result?

Answer 1

We can arrange on the logical vector first before placing the 'val' column

 tbl %>% arrange(!is.na(val), val) # A tibble: 10 × 2 # id val # <chr> <dbl> #1 f NA #2 i 0.1346666 #3 c 0.2861395 #4 g 0.5190959 #5 e 0.6417455 #6 j 0.6569923 #7 h 0.7365883 #8 d 0.8304476 #9 a 0.9148060 #10 b 0.9370754