na.omit inconsistent with is.na on list

Hi Toby,

This definitely appears intentional, the first  expression of
stats:::na.omit.default is

   if (!is.atomic(object))

        return(object)

Based on this code it does seem that the documentation could be clarified

So it is explicitly just returning the object in non-atomic cases, which
includes lists. I was not involved in this decision (obviously) but my
guess is that it is due to the fact that what constitutes an observation
"being complete" in unclear in the list case. What should

na.omit(list(5, NA, c(NA, 5)))

return? Just the first element, or the first and the last? It seems, at
least to me, unclear.

A small change to the documentation to to add "atomic (in the sense of
is.atomic returning \code{TRUE})" in front of "vectors"  or similar  where
what types of objects are supported seems justified, though, imho, as the
current documentation is either ambiguous or technically incorrect,
depending on what we take "vector" to mean.

Best,
~G

On Wed, Aug 11, 2021 at 10:16 PM Toby Hocking <tdhock5 at gmail.com> wrote:

Also, the na.omit method for data.frame with list column seems to be
inconsistent with is.na,

L <- list(NULL, NA, 0)
str(f <- data.frame(I(L)))

'data.frame': 3 obs. of  1 variable:
 $ L:List of 3
  ..$ : NULL
  ..$ : logi NA
  ..$ : num 0
  ..- attr(*, "class")= chr "AsIs"

is.na(f)

         L
[1,] FALSE
[2,]  TRUE
[3,] FALSE

na.omit(f)

   L
1
2 NA
3  0

On Wed, Aug 11, 2021 at 9:58 PM Toby Hocking <tdhock5 at gmail.com> wrote:

na.omit is documented as "na.omit returns the object with incomplete

cases

removed." and "At present these will handle vectors," so I expected that
when it is used on a list, it should return the same thing as if we

subset

via is.na; however I observed the following,

L <- list(NULL, NA, 0)
str(L[!is.na(L)])

List of 2
 $ : NULL
 $ : num 0

str(na.omit(L))

List of 3
 $ : NULL
 $ : logi NA
 $ : num 0

Should na.omit be fixed so that it returns a result that is consistent
with is.na? I assume that is.na is the canonical definition of what
should be considered a missing value in R.

        [[alternative HTML version deleted]]