BUG: groupby sub-selection ignored with some methods
related #6512, #6524, #6346

_Update from @hayd I think these should reference `_selected_obj` rather than `obj`._

Looking through some others, looks these also ignore the selection
- [x] count #6570
- [x] corr #6570
- [x] cummax #6570
- [x] cummin #6570 
- [x] cumsum #6570 
- [x] cumprod  #6570 
- [x] describe #6570
- [x] fillna #6570
- [x] quantile #6570
- [x] head #6533
- [x] hist? the output is ok but the plots have all
- [ ] ohlc? possibly fixed with #6570 (resample with ohlc is tested), should this method exist? see #6594
- [x] plot
- [x] rank #6570
- [x] tail #6533 
- [x] filter, #6570 (tested in #6593)
- [x] resample, #6570
- [x] nth #6569
- [x] diff/shift, #6570
- [x] all/any #6570
- [x] ffill, #6570
- [x] pct_change  #6570
- [x] idxmin/idxmax, #6570
- [x] dtypes #6570 
- [ ] apply  #6570 (could be tested more / different paths?)

Aggregation functions like (they already _kind_ of do, but they allow bad selections ie column names not in columns, may be sep issue?):
- [x] sum/max/min/median/mean/var/std/.. (not tested)
- [x] agg (not tested)
  (these "work" with the described bug)

Atm selecting a column not in df doesn't raise:
- [ ]  it should raise a Key Error, #6578

what about `iloc/loc/ix` (current all disabled)?
- [x] iloc (very similar to head/tail)
- [ ] loc/ix (maybe push off for now, this is pretty tricky)
- [x] iterate over all (whitelisted) functions to check they adhere to this

The column selection on a groupby object is being ignored when `.quantile()` is called. So it computes the quantile on all the (numeric) columns and returns the full DataFrame.

``` python
In [92]: t = pd.DataFrame(np.random.randn(10, 4)); t[0] = np.hstack([np.ones(5), np.zeros(5)])

In [95]: t.groupby(0)[[1, 2]].quantile()  # shows other cols
Out[95]: 
   0         1         2         3
0                                 
0  0  0.127152  0.108908  0.369601
1  1 -0.321279  0.265550 -0.382398

In [96]: t[[1, 2]].groupby(t[0]).quantile()  # Should be equivalent to:
Out[96]: 
          1         2
0                    
0  0.127152  0.108908
1 -0.321279  0.265550
```

Seeing all these, I'm wondering if this is a bug or just how some of the methods are implementer. The [docs](http://pandas.pydata.org/pandas-docs/dev/groupby.html#dataframe-column-selection-in-groupby) don't mention anything about only supporting some methods though.

version: '0.12.0-883-g988d4be'
