Inconsistent NA handling for BinGrouper and Grouper
BinGrouper and Grouper handle NA values differently when looking at the codes.

```python
In [79]: df = pd.DataFrame({"A": [1, 2, 3]}, index=pd.PeriodIndex([pd.NaT, pd.NaT, pd.NaT], freq="D"))

In [80]: a = df.groupby(df.index).grouper

In [81]: b = df.resample("1D")._get_binner()[1]

In [82]: a.codes
Out[82]: [array([-1, -1, -1])]

In [83]: b.codes
Out[83]: [array([], dtype=int64)]
```

With https://github.com/pandas-dev/pandas/pull/34998, this can cause a false positive on the apply `group_index` warning if you have an all NA group.

Ideally they have the same representation (I think all `-1` is correct).

xref https://github.com/pandas-dev/pandas/pull/34998#issuecomment-652497050.