Feature Request: groupby retaining indexes
The feature I'd like to suggest/request is pretty simple, it has workarounds but it seems very odd to me that this is not a native behavior. Specially because the workarounds seem so slow.

I imagine it as a simple parameter for the `groupby` function.

The feature is: the ability to group a level (of a MultiIndex dataframe) but still retain that level's labels. I think it will be clear with the example below.

Note that this came from a question I asked in [stack overflow](http://stackoverflow.com/questions/37845306/pandas-multiindex-groupby-retaining-index-levels/37845567?noredirect=1#37845567)
#### Code Sample

```
df = pd.DataFrame([['A', 1, 3],
                   ['A', 2, 4],
                   ['A', 3, 6],
                   ['B', 1, 9],
                   ['B', 2, 10],
                   ['B', 4, 6]],
                  columns=pd.Index(['Name', 'Date', 'Value'], name='ColumnName')
                 ).set_index(['Name', 'Date'])

df.groupby(level=('Name')).last()
```
#### Intended Output

```
ColumnName         Value
Name    Date
A        3           6
B        4           6
```
#### output of `pandas 0.18.0`

```
ColumnName         Value
Name    
A                    6
B                    6
```
