Undocumented API changes in groupby.apply
At some time [last year](https://github.com/pydata/pandas/issues/4646#issue-18447522), 

```
pd.DataFrame([[1, 2], [2, 3], [1, 4], [1, 5], [2, 6]]).groupby(0).apply(lambda x: pd.Series(np.arange(len(x)), x.index))
```

would return

```
0    0
1    0
2    1
3    2
4    1
dtype: int64
```

In 0.14, it returns 

```
0
1    0    0
2    1
3    2
dtype: int64
2           1    0
4    1
dtype: int64
dtype: object
```

while in current git snapshot, it returns

```
1  0    0
   2    1
   3    2
2  1    0
   4    1
dtype: int64
```

No nostalgia... but would it make sense to refer to the different behavior in different versions in the documentation of GroupBy.apply()?
Moreover: the (last version of the) docs say "case 2: group DataFrame apply transform function ((f(chunk) -> DataFrame with same indexes) yield DataFrame with resulting chunks glued together", and I think this is the case which applies. However the docs omit to mention "with group axis having group labels", as they do instead for case 1 (f(chunk) -> Series).

I will/would gladly submit a PR to enhance the docs... once I myself understand how things are supposed to work.
