Groupby + sum by multiple columns on an empty DataFrame drops list of columns
#### Code Sample

```python
import pandas as pd

print pd.DataFrame(data=[[1,2,3]], columns=['A', 'B', 'C'])\
    .groupby(['A', 'B'])\
    .sum()\
    .reset_index()\
    .columns\
    .tolist()
# ['A', 'B', 'C']

print pd.DataFrame(data=[], columns=['A', 'B', 'C'])\
    .groupby(['A'])\
    .sum()\
    .reset_index()\
    .columns\
    .tolist()
# ['A', 'B', 'C']

print pd.DataFrame(data=[], columns=['A', 'B', 'C'])\
    .groupby(['A', 'B'])\
    .sum()\
    .reset_index()\
    .columns\
    .tolist()
# ['index']
```
#### Problem description

As the original list of columns is lost in the second case, I have to handle empty data frames differently, or add columns back by myself, both of which are inconvenient.

#### Expected Output

The list of columns is expected to be equal to the original one from data frame

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.12.final.0
python-bits: 64
OS: Linux
OS-release: 4.4.0-57-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: None.None

pandas: 0.19.1
nose: 1.3.7
pip: 9.0.1
setuptools: 28.8.0
Cython: None
numpy: 1.11.2
scipy: None
statsmodels: None
xarray: None
IPython: 5.1.0
sphinx: None
patsy: None
dateutil: 2.6.0
pytz: 2016.7
blosc: None
bottleneck: None
tables: None
numexpr: None
matplotlib: 1.5.3
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
httplib2: 0.9.2
apiclient: None
sqlalchemy: 1.1.4
pymysql: None
psycopg2: 2.6.2 (dt dec pq3 ext lo64)
jinja2: 2.8
boto: None
pandas_datareader: None
</details>
