Implement pd.NA checking function
- [ ] tests added / passed
- [ ] passes `black pandas`
- [ ] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry

This may already exist in some form, but if not I think it could be useful to have a fast function for checking specifically for the presence of pd.NA (e.g. if we're looking at an arbitrary array and don't know if we'll have access to a _mask attribute, or if we're handling some other data type that uses pd.NA for missing values but doesn't have this attribute).
> isna already does this

What I was thinking here was a way to get a mask for _only_ pd.NA (so not including np.NaN, None or other missing value indicators like isna does).  The main motivation was trying to think of a way to fix https://github.com/pandas-dev/pandas/issues/31990 without writing the equivalent of a Python for loop to do this check related helper function ive wanted is `is_matching_na` > What I was thinking here was a way to get a mask for _only_ pd.NA (so not including np.NaN, None or other missing value indicators like isna does). The main motivation was trying to think of a way to fix #31990 without writing the equivalent of a Python for loop to do this check

Can't you use the mask that the StringDtype has to check this?  Closing since it looks like others aren't in favor of the idea. I do think some kind of "dtype agnostic" way of checking for NA could be helpful later