Filter for NAs only if group has more than 1 observation in dplyr

Question

I would like to be able to keep NAs for only groups that have more than two entries and just want to leave alone any groups that have 1 entry (regardless if they have NAs or not). That is, if the group has two elements, keep only the NA. If it has one then just take whatever is there. Here is a reprex of the type of data I have:

library(dplyr)

data <- data.frame(
  x = c(1, NA_real_, 3, NA_real_),
  y = c("grp1", "grp2", "grp2", "grp3")
)
data
#>    x    y
#> 1  1 grp1
#> 2 NA grp2
#> 3  3 grp2
#> 4 NA grp3

Then here is the fairly ugly way I have achieved what I want:

raw <- data %>%
  group_by(y) %>%
  mutate(n = n())

results <- bind_rows(
  raw %>%
    filter(n == 2) %>%
    filter(is.na(x)),
  raw %>%
    filter(n == 1)
) %>%
  ungroup() %>%
  select(-n)

results
#> # A tibble: 3 × 2
#>       x y    
#>   <dbl> <chr>
#> 1    NA grp2 
#> 2     1 grp1 
#> 3    NA grp3

Answer 1

Update after clarification: We have only to add ! and change == to >:

library(dplyr)
data %>% 
  group_by(y) %>% 
  filter(!(!is.na(x) & n() > 1))

      x y    
  <dbl> <chr>
1     1 grp1 
2    NA grp2 
3    NA grp3 

We could define filter with the max(row_number(): update: instead of max(row_number() we could use n() (many thanks to @Juan C)

library(dplyr)
data %>% 
  group_by(y) %>% 
   filter(!(is.na(x) & n() == 1))
 # filter(!(is.na(x) & max(row_number()) == 1))

     x y    
  <dbl> <chr>
1     1 grp1 
2    NA grp2 
3     3 grp2 

Answer 2

Here's another approach that works

data %>% 
  group_by(y) %>%  
  filter(!(!is.na(x) & n() > 1))

# A tibble: 3 × 2
# Groups:   y [3]
      x y    
  <dbl> <chr>
1     1 grp1 
2    NA grp2 
3    NA grp3