DataFrame.xs() throws value error with non-unique multi index if `level` kwarg is called.
DataFrame.xs() returns a value error if a non-unique multi-index is used and the `level` kwarg is called. However, if the `level` karg is not called, or a tuple is passed the function behaves normally. 

```
import sys

if sys.version[0] == '2':
    from StringIO import StringIO
if sys.version[0] == '3':
    from io import StringIO

import pandas as pd

sstring = """\
m,p,tstep,value,jday,normed_value,datetime
6,407,0,1,564.5,5.75,1964-07-18 12:00:00
6,407,0,1,564.5,5.75,1964-07-18 12:00:00
7,407,0,1,564.5,5.75,1964-07-18 12:00:00
8,408,0,1,564.5,6.75,1964-07-18 12:00:00
"""

subset = pd.read_csv(StringIO(sstring),
                     index_col=['m', 'p'],
                     parse_dates=['datetime'])
```
#### Example output of various use cases
##### Working example 1

```
subset.xs(6)

     tstep  value   jday  normed_value            datetime
p                                                         
407      0      1  564.5          5.75 1964-07-18 12:00:00
407      0      1  564.5          5.75 1964-07-18 12:00:00

```
##### Working example 2

```
subset.xs((6,), level=['m'])

     tstep  value   jday  normed_value            datetime
p                                                         
407      0      1  564.5          5.75 1964-07-18 12:00:00
407      0      1  564.5          5.75 1964-07-18 12:00:00

```
##### Working example 3

```
subset.xs((6, 407), level=['m', 'p'])

       tstep  value   jday  normed_value            datetime
m p                                                         
6 407      0      1  564.5          5.75 1964-07-18 12:00:00
  407      0      1  564.5          5.75 1964-07-18 12:00:00

```
##### Value error

I would expect this to return the same as example 1 or 2

```
subset.xs(6, level='m')
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-1-1d10441983d6> in <module>()
     20                      parse_dates=['datetime'])
     21 
---> 22 subset.xs(6, level='m')

C:\Anaconda3\lib\site-packages\pandas\core\generic.py in xs(self, key, axis, level, copy, drop_level)
   1734 
   1735             result = self.ix[indexer]
-> 1736             setattr(result, result._get_axis_name(axis), new_ax)
   1737             return result
   1738 

C:\Anaconda3\lib\site-packages\pandas\core\generic.py in __setattr__(self, name, value)
   2683         try:
   2684             object.__getattribute__(self, name)
-> 2685             return object.__setattr__(self, name, value)
   2686         except AttributeError:
   2687             pass

pandas\src\properties.pyx in pandas.lib.AxisProperty.__set__ (pandas\lib.c:44748)()

C:\Anaconda3\lib\site-packages\pandas\core\generic.py in _set_axis(self, axis, labels)
    426 
    427     def _set_axis(self, axis, labels):
--> 428         self._data.set_axis(axis, labels)
    429         self._clear_item_cache()
    430 

C:\Anaconda3\lib\site-packages\pandas\core\internals.py in set_axis(self, axis, new_labels)
   2633             raise ValueError('Length mismatch: Expected axis has %d elements, '
   2634                              'new values have %d elements' %
-> 2635                              (old_len, new_len))
   2636 
   2637         self.axes[axis] = new_labels

ValueError: Length mismatch: Expected axis has 4 elements, new values have 2 elements
```
#### output of `pd.show_versions()`

commit: None
python: 3.5.1.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 58 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None

pandas: 0.18.1
nose: 1.3.7
pip: 8.1.1
setuptools: 20.3
Cython: 0.23.4
numpy: 1.10.4
scipy: 0.17.0
statsmodels: 0.6.1
xarray: None
IPython: 4.1.2
sphinx: 1.3.1
patsy: 0.4.0
dateutil: 2.5.1
pytz: 2016.2
blosc: None
bottleneck: 1.0.0
tables: 3.2.2
numexpr: 2.5
matplotlib: 1.5.1
openpyxl: 2.3.2
xlrd: 0.9.4
xlwt: 1.0.0
xlsxwriter: 0.8.4
lxml: 3.6.0
bs4: 4.4.1
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.12
pymysql: None
psycopg2: None
jinja2: 2.8
boto: 2.39.0
pandas_datareader: None
