BUG/TST: verify that groupby apply with a column aggregation does not return the column
related https://github.com/pydata/pandas/pull/7000

```
In [1]:  df = DataFrame({'foo1' : ['one', 'two', 'two', 'three', 'one', 'two'],
                                      'foo2' : np.random.randn(6)})

In [2]: df
Out[2]: 
    foo1      foo2
0    one  1.006666
1    two  0.002063
2    two  1.507785
3  three  1.865921
4    one  0.141202
5    two -1.079792

[6 rows x 2 columns]
```

```
In [3]: df.groupby('foo1').mean()
Out[3]: 
           foo2
foo1           
one    0.573934
three  1.865921
two    0.143352

[3 rows x 1 columns]

In [4]: df.groupby('foo1').apply(lambda x: x.mean())
Out[4]: 
           foo2
foo1           
one    0.573934
three  1.865921
two    0.143352

[3 rows x 1 columns]
```

This should return the foo1 column as well

```
[6]: df.groupby('foo1',as_index=False).apply(lambda x: x.mean())
Out[6]: 
       foo2
0  0.573934
1  1.865921
2  0.143352

[3 rows x 1 columns]

In [7]: df.groupby('foo1',as_index=False).mean()
Out[7]: 
    foo1      foo2
0    one  0.573934
1  three  1.865921
2    two  0.143352

[3 rows x 2 columns]

```
