groupby on index and columns mixed: strange behaviour
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
df1 = pd.DataFrame([[1, 2, 3]], columns=['a', 'b', 'c']).set_index('a')
df2 = pd.DataFrame([[1, 2, 3], [4, 5, 6]], columns=['a', 'b', 'c']).set_index('a')
df3 = pd.DataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 9]], columns=['a', 'b', 'c']).set_index('a')

print(df1.groupby(['a', 'c']).sum())
print('==============')
print(df2.groupby(['a', 'c']).sum())
print('==============')
print(df3.groupby(['a', 'c']).sum())
# output:
#    b
# a c   
# 1 3  2
# ==============
#    b  c
# a  2  3
# c  5  6
# ==============
#      b
# a c   
# 1 3  2
# 4 6  5
# 7 9  8
```
#### Problem description

This is a problem because the output structure depends on the number of rows in a dataframe. I figured out that this issue can be solved by calling reset_index() on the dataframe before the groupby, but this issue has caused unexpected troubles for our production framework. 
Here the only **exception** is when the input dataframe has **2 rows**.

#### Expected Output

```
     b
a c   
1 3  2
==============
     b
a c   
1 3  2
4 6  5
==============
     b
a c   
1 3  2
4 6  5
7 9  8
```

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

<details>

[paste the output of ``pd.show_versions()`` here below this line]
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.1.final.0
python-bits: 64
OS: Darwin
OS-release: 16.7.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: en_US.UTF-8
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.20.3
pytest: 3.1.3
pip: 9.0.1
setuptools: 33.1.1.post20170320
Cython: 0.26
numpy: 1.13.1
scipy: 0.19.1
xarray: None
IPython: 6.1.0
sphinx: None
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.0.2
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 0.9999999
sqlalchemy: 1.1.13
pymysql: 0.7.9.None
psycopg2: 2.7.3 (dt dec pq3 ext lo64)
jinja2: 2.9.5
s3fs: None
pandas_gbq: None
pandas_datareader: None

</details>
