BUG: filter with a multi-grouping including a datetimelike fails
this was changed in #9921 (worked prior to 0.16.0)
cc @evanpw

so using a multiple grouper where one item is a datetimelike fails as the `name in self.indices` fails. Instead `.get_group()` can be used to fix

```
In [1]: df = DataFrame({'A' : np.arange(5), 'B' : ['foo','bar','foo','bar','bar'], 'C' : Timestamp('20130101') })

In [2]: df
Out[2]: 
   A    B          C
0  0  foo 2013-01-01
1  1  bar 2013-01-01
2  2  foo 2013-01-01
3  3  bar 2013-01-01
4  4  bar 2013-01-01

In [3]: df.groupby(['B','C']).filter(lambda x: True)
Out[3]: 
Empty DataFrame
Columns: [A, B, C]
Index: []

In [4]: df.groupby(['B']).filter(lambda x: True)
Out[4]: 
   A    B          C
0  0  foo 2013-01-01
1  1  bar 2013-01-01
2  2  foo 2013-01-01
3  3  bar 2013-01-01
4  4  bar 2013-01-01

In [5]: df.groupby(['C']).filter(lambda x: True)
Out[5]: 
   A    B          C
0  0  foo 2013-01-01
1  1  bar 2013-01-01
2  2  foo 2013-01-01
3  3  bar 2013-01-01
4  4  bar 2013-01-01
```
