Weird behaviour of groupby with quantile
Hi

```
import pandas as pd
X = pd.DataFrame(dict(g=['a','a','b','b','b'],a=range(5)))
```

For some reason this loses the grouping variable 'g':

```
X.groupby(['g'],as_index=False).quantile(0.5)

     a
0  0.5
1  3.0
```

I was expecting this output:

```
X.groupby(['g']).quantile(0.5).reset_index()

   g    a
0  a  0.5
1  b  3.0
```

Maybe related to the above this throws an error (this is useful if I have tons of columns but need result only for one).

```
X.groupby(['g'],as_index=False)['a'].quantile(0.5)

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<string>", line 40, in quantile
  File "C:\Anaconda\lib\site-packages\pandas\core\groupby.py", line 579, in wrapper
    return self._aggregate_item_by_item(name, *args, **kwargs)
  File "C:\Anaconda\lib\site-packages\pandas\core\groupby.py", line 2789, in _aggregate_item_by_item
    raise errors
TypeError: quantile() got an unexpected keyword argument 'numeric_only'
```

If I replace `.quantile()` with other aggregate like mean or sum it works just fine.

---

```
>>> pd.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.10.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 58 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: FI

pandas: 0.16.2
nose: 1.3.7
Cython: 0.22.1
numpy: 1.9.2
scipy: 0.15.1
statsmodels: 0.6.1
IPython: 3.2.0
sphinx: 1.3.1
patsy: 0.3.0
dateutil: 2.4.2
pytz: 2015.4
bottleneck: 1.0.0
tables: 3.2.0
numexpr: 2.4.3
matplotlib: 1.4.3
openpyxl: 1.8.5
xlrd: 0.9.3
xlwt: 1.0.0
xlsxwriter: 0.7.3
lxml: 3.4.4
bs4: 4.3.2
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.6
pymysql: None
psycopg2: None
```
