DataFrameGroupBy.idxmin() returns DataFrame, documentation says Series
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
df = pd.DataFrame([[0, 0],
                  [3, 0],
                  [1, 1]], index=list('ABC'), columns=list('ab'))

gby = df.groupby(by='b')

print(type(gby))            # <class 'pandas.core.groupby.DataFrameGroupBy'>
print(type(gby.idxmin()))   # <class 'pandas.core.frame.DataFrame'>
```
#### Problem description
According to [the documentation](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.core.groupby.DataFrameGroupBy.idxmin.html), this is supposed to output a `pandas.core.Series`. To me, that seems to be what makes sense, but I'm not sure how or why this ended up returning a `DataFrame`. Is this just an issue with the documentation, or is it an issue with the code?

**Edit**: Ah, I understand why this returns a `DataFrame` now - if you have multiple columns the `idxmin()` might be different for each column. Seems that the documentation needs to be updated. I can make a PR if that's appropriate.

#### Output of ``pd.show_versions()``

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.0.final.0
python-bits: 64
OS: Linux
OS-release: 4.9.6-1-ARCH
machine: x86_64
processor: 
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.19.2
nose: None
pip: 9.0.1
setuptools: 34.0.3
Cython: 0.25.2
numpy: 1.12.0
scipy: None
statsmodels: None
xarray: None
IPython: 5.1.0
sphinx: None
patsy: None
dateutil: 2.6.0
pytz: 2016.10
blosc: None
bottleneck: None
tables: None
numexpr: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: None
boto: None
pandas_datareader: None
</details>
