Concatenation of list columns fails when grouping on multiple columns
Assume we have a simple DF like this

```
x = pd.DataFrame({'a':[1,1,2,2],'b':['a','a','a','b'],'c':[[1,2],[3,4],[5,6],[7,8]]})

   a  b       c
0  1  a  [1, 2]
1  1  a  [3, 4]
2  2  a  [5, 6]
3  2  b  [7, 8]
```

and we want to do a groupby operation that concatenates the lists in column `c` together.  This works fine when grouping on one column:

```
x.groupby('b')['c'].sum()

b
a    [1, 2, 3, 4, 5, 6]
b                [7, 8]
dtype: object

x.groupby('a')['c'].sum()

a
1    [1, 2, 3, 4]
2    [5, 6, 7, 8]
dtype: object
```

But fails when grouping on multiple columns (i.e. `x.groupby(['a','b'])['c'].sum()`) with `ValueError: Function does not reduce`.

This is based on this SO question: https://stackoverflow.com/questions/40224793/pandas-concatenate-list-columns-with-groupby-when-grouping-on-multiple-columns/40226389#40226389
#### Output of `pd.show_versions()`
## INSTALLED VERSIONS

commit: None
python: 2.7.12.final.0
python-bits: 64
OS: Darwin
OS-release: 15.6.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.18.1
nose: 1.3.7
pip: 8.1.2
setuptools: 17.1.1
Cython: 0.22.1
numpy: 1.11.2
scipy: 0.18.1
statsmodels: 0.6.1
xarray: 0.8.2
IPython: 5.1.0
sphinx: 1.3.1
patsy: 0.3.0
dateutil: 2.5.3
pytz: 2015.4
blosc: None
bottleneck: 1.0.0
tables: 3.2.0
numexpr: 2.6.1
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: 4.4.1
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.5
pymysql: None
psycopg2: None
jinja2: 2.7.3
boto: 2.33.0
pandas_datareader: None
