BUG: groupy().nth() throws error on multiple groups, empty result
#### Code Sample, a copy-pastable example if possible

```python
>>> import pandas as pd
>>> df = pd.DataFrame(index=[0], columns=['a', 'b', 'c'])
>>> df.groupby('a').nth(10)

Empty DataFrame
Columns: [b, c]
Index: []

>>> df.groupby(['a', 'b']).nth(10)

Traceback (most recent call last):
  File "<ipython-input-3-ae8299c3984e>", line 1, in <module>
    df.groupby(['a', 'b']).nth(10)
  File "~/anaconda3/lib/python3.5/site-packages/pandas/core/groupby.py", line 1390, in nth
    return out.sort_index() if self.sort else out
  File "~/anaconda3/lib/python3.5/site-packages/pandas/core/frame.py", line 3344, in sort_index
    indexer = lexsort_indexer(labels._get_labels_for_sorting(),
  File "~/anaconda3/lib/python3.5/site-packages/pandas/core/indexes/multi.py", line 1652, in _get_labels_for_sorting
    for label in self.labels]
  File "~/anaconda3/lib/python3.5/site-packages/pandas/core/indexes/multi.py", line 1652, in <listcomp>
    for label in self.labels]
  File "~/anaconda3/lib/python3.5/site-packages/numpy/core/_methods.py", line 26, in _amax
    return umr_maximum(a, axis, None, out, keepdims)
ValueError: zero-size array to reduction operation maximum which has no identity

```
#### Problem description

In the current Github version of Pandas, when calling `groupby().nth()` with multiple grouping columns, an error is raised if the result is empty. This is a regression from version 0.19.2.

#### Expected Output

```python

Empty DataFrame
Columns: [b, c]
Index: []

Empty DataFrame
Columns: [c]
Index: []

```

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.5.2.final.0
python-bits: 64
OS: Linux
OS-release: 4.9.8-100.fc24.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: C
LANG: C
LOCALE: None.None

pandas: 0.19.0+829.gb17e286
pytest: 3.0.5
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.11.3
scipy: 0.18.1
xarray: 0.9.1
IPython: 4.2.0
sphinx: 1.5.1
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2016.10
blosc: None
bottleneck: 1.2.0
tables: 3.3.0
numexpr: 2.6.2
feather: None
matplotlib: 2.0.0
openpyxl: 2.4.1
xlrd: 1.0.0
xlwt: 1.2.0
xlsxwriter: 0.9.6
lxml: 3.7.2
bs4: 4.5.3
html5lib: 0.999
sqlalchemy: 1.1.5
pymysql: None
psycopg2: None
jinja2: 2.9.4
s3fs: None
pandas_gbq: None
pandas_datareader: None
</details>
