groupby and aggregate passing different types to aggregating function
it seems that when no column is selected, groupby and aggregate pass different types to the aggregating function. I am not sure if this is not a bug:

```
>>> pd.__version__
'0.13.0rc1-118-gb0c2aa4'

>>> df
  tag       val
0   A -0.621620
1   A  0.386178
2   B  0.449459
3   B  0.421856
4   B -0.083518

[5 rows x 2 columns]

>>> _ = df.groupby( 'tag' ).aggregate( print )
  tag       val
0   A -0.621620
1   A  0.386178

[2 rows x 2 columns]
[-0.6216203   0.38617806]
[ 0.44945865  0.42185594 -0.0835182 ]

>>> _ = df.groupby( 'tag' ).aggregate( lambda x: print ( type( x ) ) )
<class 'pandas.core.frame.DataFrame'>
<class 'pandas.core.array.SNDArray'>
<class 'pandas.core.array.SNDArray'>
```
