Groupby on a column with tuples creates a multiindex, yielding unexpected behaviour.
#### Code Sample, a copy-pastable example if possible

```python
import numpy as np
import pandas as pd

df = pd.DataFrame(np.random.randint(0, 11, (10, 3)), columns=['num1', 'num2', 'num3'])
df['category_tuple'] = [(0, 1), (0, 1), (0, 1), (2, 3), (2, 3), (2, 3), (2, 3), (0, 4), (5,), (6,)]
df['category_string'] = list('aaabbbbcde')
df = df[['category_tuple', 'category_string', 'num1', 'num2', 'num3']]

# df.groupby('category_string').apply(lambda x: x.sort_values(by='num1'))
df.groupby('category_tuple').apply(lambda x: x.sort_values(by='num1'))
```
#### Problem description

I get this error: `ValueError: Names should be list-like for a MultiIndex`

This behaviour changed somewhere between 0.19.0 and 0.19.1. This can be sidestepped by casting the tuples to a string before doing the groupby, but the behaviour is definitely unexpected.

`category_string` works, but `category_tuple` does not. Other operations also break in the same way (e.g., `describe()`). I'd expect them both to work in the same way, and not create a multiindex unless I request it.

#### Expected Output
```
                  category_tuple category_string  num1  num2  num3
category_tuple                                                   
(0, 1)          0         (0, 1)               a     0     0    10
                2         (0, 1)               a     0     7     1
                1         (0, 1)               a     6     7     2
(2, 3)          4         (2, 3)               b     1     3     0
                6         (2, 3)               b     3     6     8
                3         (2, 3)               b     6    10     3
                5         (2, 3)               b     6     0     1
(0, 4)          7         (0, 4)               c     7     7     5
(5,)            8           (5,)               d     4     5     7
(6,)            9           (6,)               e     9     1     5
```

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

<details>

INSTALLED VERSIONS
------------------
commit: None

pandas: 0.22.0
pytest: None
pip: 10.0.0
setuptools: 28.8.0
Cython: None
numpy: 1.14.2
scipy: 1.0.1
pyarrow: None
xarray: None
IPython: 6.3.1
sphinx: None
patsy: 0.5.0
dateutil: 2.6.1
pytz: 2018.4
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.2.2
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 1.0.1
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>
