BUG: handle NaNs in FloatingArray.equals
- [x] closes #44382
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [x] whatsnew entry

do we have reference docs for these anywhere? (i don't remember), if so can you add otherwise lgtm actually would be great to tests Series equals with FloatDtype (does it dispatch to this?) > do we have reference docs for these anywhere? (i don't remember), if so can you add otherwise lgtm

Yes. The relevant one for users is https://pandas.pydata.org/docs/dev/reference/api/pandas.Series.equals.html#, and the ExtensionArray version is also listed: https://pandas.pydata.org/docs/dev/reference/api/pandas.api.extensions.ExtensionArray.equals.html

> actually would be great to tests Series equals with FloatDtype (does it dispatch to this?)

Yes, it does dispatch, and that's already tested. where is the series test explicitly added here?  It is not added here because we already have a general extension test (`test_equals`) that ensures both DataFrame and Series dispatch to the EA method. sure but do we have an example that was failing with Float dtypes that check nans - we couldn't have as it would have failed -  so need this case We have a lot of specific tests in the `/tests/arrays` that are not all repeated each time for Series or DataFrame. And I think that is fine. i think this wasnt ready, had failures on older numpys It seems the `equal_nan` keyword is new in numpy 1.19 (https://numpy.org/doc/stable/reference/generated/numpy.array_equal.html) shimmed a fix for this into #44428 Can you quickly put it in its own PR? That seems easier to merge it quickly, while the other PR still needs to be reviewed?