core\common.py\mask_missing handles arr=[nan,...,nan] poorly
_Edit_ Looks like this is probably solved in 0.11; currently on 0.10, but upgrading. _Edit_

Apologies in advance if this is known, fixed, etc.--I am new to pandas/python/Git (trifecta...).

mask_missing appears to handle an all-NaN array (arr=[nan,...,nan]) poorly (discovered while trying to do a .replace()).

The problem point appears to be mask=arr==x.

If arr is all nan, then arr==x results in mask=False.

This promulgates downwards and causes mask_missing to return [False], which then causes higher-level functions (which expect mask_missing to return something the same size as arr) to error out.
