BUG: Categorical.remove_categories(np.nan) fails when underlying dtype is float
Fixes GH #10156. This also makes different null values indistinguishable inside of remove_categories, but they're already indistinguishable in most other contexts:

``` .python
>>> pd.Categorical([], categories=[np.nan, None])
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "pandas/core/categorical.py", line 289, in __init__
    categories = self._validate_categories(categories)
  File "pandas/core/categorical.py", line 447, in _validate_categories
    raise ValueError('Categorical categories must be unique')
ValueError: Categorical categories must be unique
```

can you update
 I think these tests are what you were asking for. Let me know if otherwise.
 yep, ping when green.
 It turns out that this already works for datetimelike categoricals. I added some tests and squashed.
 awesome @evanpw ! keep em coming
 Thanks very much for fixing this. I am not sure if I got this right but would not it make sense to reorder the code slightly to avoid trying removing categories twice when `nan` is present? So use this code:

```
    # GH 10156
    if any(isnull(removals)):
        not_included = [x for x in not_included if notnull(x)]
        new_categories = [x for x in new_categories if notnull(x)]
    else:
        removal_set = set(list(removals))
        not_included = removal_set - set(self._categories)
        new_categories = [ c for c in self._categories if c not in removal_set ]
```

Instead of this:

```
    removal_set = set(list(removals))
    not_included = removal_set - set(self._categories)
    new_categories = [ c for c in self._categories if c not in removal_set ]

    # GH 10156
    if any(isnull(removals)):
        not_included = [x for x in not_included if notnull(x)]
        new_categories = [x for x in new_categories if notnull(x)]
```
 In your if branch, what's the original definition of not_included and new_categories? It looks like they're defined in terms of themselves.
 Fair point ;)
Thanks again for the fix.
