MultiIndex can't be indexed with an np.array

[toobaz]

From #15425

Code Sample, a copy-pastable example if possible

In [3]: mi = pd.MultiIndex.from_product([[1, 2], ['a', 'b']])

In [4]: pd.Series(range(4)).loc[np.array([1, 2])]
Out[4]: 
1    1
2    2
dtype: int64

In [5]: pd.Series(range(4), index=mi).loc[np.array([1, 2])]
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
/home/pietro/nobackup/repo/pandas/pandas/core/indexing.py in _get_label(self, label, axis)
     99             try:
--> 100                 return self.obj._xs(label, axis=axis)
    101             except:

/home/pietro/nobackup/repo/pandas/pandas/core/generic.py in xs(self, key, axis, level, drop_level)
   1842             loc, new_index = self.index.get_loc_level(key,
-> 1843                                                       drop_level=drop_level)
   1844         else:

/home/pietro/nobackup/repo/pandas/pandas/indexes/multi.py in get_loc_level(self, key, level, drop_level)
   1932                 else:
-> 1933                     return partial_selection(key)
   1934             else:

/home/pietro/nobackup/repo/pandas/pandas/indexes/multi.py in partial_selection(key, indexer)
   1897                     if indexer is None:
-> 1898                         indexer = self.get_loc(key)
   1899                     ilevels = [i for i in range(len(key))

/home/pietro/nobackup/repo/pandas/pandas/indexes/multi.py in get_loc(self, key, method)
   1807         start, stop = (self.slice_locs(lead_key, lead_key)
-> 1808                        if lead_key else (0, len(self)))
   1809 

/home/pietro/nobackup/repo/pandas/pandas/indexes/multi.py in slice_locs(self, start, end, step, kind)
   1713         # happens in get_slice_bound method), but it adds meaningful doc.
-> 1714         return super(MultiIndex, self).slice_locs(start, end, step, kind=kind)
   1715 

/home/pietro/nobackup/repo/pandas/pandas/indexes/base.py in slice_locs(self, start, end, step, kind)
   3346         if start is not None:
-> 3347             start_slice = self.get_slice_bound(start, 'left', kind)
   3348         if start_slice is None:

/home/pietro/nobackup/repo/pandas/pandas/indexes/multi.py in get_slice_bound(self, label, side, kind)
   1684             label = label,
-> 1685         return self._partial_tup_index(label, side=side)
   1686 

/home/pietro/nobackup/repo/pandas/pandas/indexes/multi.py in _partial_tup_index(self, tup, side)
   1727 
-> 1728             if lab not in lev:
   1729                 if not lev.is_type_compatible(lib.infer_dtype([lab])):

/home/pietro/nobackup/repo/pandas/pandas/indexes/base.py in __contains__(self, key)
   1495     def __contains__(self, key):
-> 1496         hash(key)
   1497         # work around some kind of odd cython bug

TypeError: unhashable type: 'numpy.ndarray'

During handling of the above exception, another exception occurred:

TypeError                                 Traceback (most recent call last)
<ipython-input-5-bf8891f2016d> in <module>()
----> 1 pd.Series(range(4), index=mi).loc[np.array([1, 2])]

/home/pietro/nobackup/repo/pandas/pandas/core/indexing.py in __getitem__(self, key)
   1339         else:
   1340             key = com._apply_if_callable(key, self.obj)
-> 1341             return self._getitem_axis(key, axis=0)
   1342 
   1343     def _is_scalar_access(self, key):

/home/pietro/nobackup/repo/pandas/pandas/core/indexing.py in _getitem_axis(self, key, axis)
   1550         # fall thru to straight lookup
   1551         self._has_valid_type(key, axis)
-> 1552         return self._get_label(key, axis=axis)
   1553 
   1554 

/home/pietro/nobackup/repo/pandas/pandas/core/indexing.py in _get_label(self, label, axis)
    100                 return self.obj._xs(label, axis=axis)
    101             except:
--> 102                 return self.obj[label]
    103         elif isinstance(label, tuple) and isinstance(label[axis], slice):
    104             raise IndexingError('no slices here, handle elsewhere')

/home/pietro/nobackup/repo/pandas/pandas/core/series.py in __getitem__(self, key)
    645             key = check_bool_indexer(self.index, key)
    646 
--> 647         return self._get_with(key)
    648 
    649     def _get_with(self, key):

/home/pietro/nobackup/repo/pandas/pandas/core/series.py in _get_with(self, key)
    658             if isinstance(key, tuple):
    659                 try:
--> 660                     return self._get_values_tuple(key)
    661                 except:
    662                     if len(key) == 1:

/home/pietro/nobackup/repo/pandas/pandas/core/series.py in _get_values_tuple(self, key)
    706 
    707         # If key is contained, would have returned by now
--> 708         indexer, new_index = self.index.get_loc_level(key)
    709         return self._constructor(self._values[indexer],
    710                                  index=new_index).__finalize__(self)

/home/pietro/nobackup/repo/pandas/pandas/indexes/multi.py in get_loc_level(self, key, level, drop_level)
   1931                         return partial_selection(key)
   1932                 else:
-> 1933                     return partial_selection(key)
   1934             else:
   1935                 indexer = None

/home/pietro/nobackup/repo/pandas/pandas/indexes/multi.py in partial_selection(key, indexer)
   1896                 def partial_selection(key, indexer=None):
   1897                     if indexer is None:
-> 1898                         indexer = self.get_loc(key)
   1899                     ilevels = [i for i in range(len(key))
   1900                                if key[i] != slice(None, None)]

/home/pietro/nobackup/repo/pandas/pandas/indexes/multi.py in get_loc(self, key, method)
   1806         lead_key, follow_key = key[:i], key[i:]
   1807         start, stop = (self.slice_locs(lead_key, lead_key)
-> 1808                        if lead_key else (0, len(self)))
   1809 
   1810         if start == stop:

/home/pietro/nobackup/repo/pandas/pandas/indexes/multi.py in slice_locs(self, start, end, step, kind)
   1712         # This function adds nothing to its parent implementation (the magic
   1713         # happens in get_slice_bound method), but it adds meaningful doc.
-> 1714         return super(MultiIndex, self).slice_locs(start, end, step, kind=kind)
   1715 
   1716     def _partial_tup_index(self, tup, side='left'):

/home/pietro/nobackup/repo/pandas/pandas/indexes/base.py in slice_locs(self, start, end, step, kind)
   3345         start_slice = None
   3346         if start is not None:
-> 3347             start_slice = self.get_slice_bound(start, 'left', kind)
   3348         if start_slice is None:
   3349             start_slice = 0

/home/pietro/nobackup/repo/pandas/pandas/indexes/multi.py in get_slice_bound(self, label, side, kind)
   1683         if not isinstance(label, tuple):
   1684             label = label,
-> 1685         return self._partial_tup_index(label, side=side)
   1686 
   1687     def slice_locs(self, start=None, end=None, step=None, kind=None):

/home/pietro/nobackup/repo/pandas/pandas/indexes/multi.py in _partial_tup_index(self, tup, side)
   1726             section = labs[start:end]
   1727 
-> 1728             if lab not in lev:
   1729                 if not lev.is_type_compatible(lib.infer_dtype([lab])):
   1730                     raise TypeError('Level type mismatch: %s' % lab)

/home/pietro/nobackup/repo/pandas/pandas/indexes/base.py in __contains__(self, key)
   1494 
   1495     def __contains__(self, key):
-> 1496         hash(key)
   1497         # work around some kind of odd cython bug
   1498         try:

TypeError: unhashable type: 'numpy.ndarray'

Problem description

The array should be accepted as it is accepted for the (non-Multi)Index

Expected Output

In [6]: pd.Series(range(4), index=mi).loc[np.array([1, 2])]
Out[6]: 
1  a    0
   b    1
2  a    2
   b    3
dtype: int64

Output of pd.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 3.5.2.final.0 python-bits: 64 OS: Linux OS-release: 4.7.0-1-amd64 machine: x86_64 processor: byteorder: little LC_ALL: None LANG: it_IT.utf8 LOCALE: it_IT.UTF-8

pandas: 0.19.0+466.g5a8883b
pytest: 3.0.6
pip: 8.1.2
setuptools: 28.0.0
Cython: 0.23.4
numpy: 1.12.0
scipy: 0.18.1
xarray: None
IPython: 5.1.0.dev
sphinx: 1.4.8
patsy: 0.3.0-dev
dateutil: 2.5.3
pytz: 2015.7
blosc: None
bottleneck: 1.2.0
tables: 3.2.2
numexpr: 2.6.0
feather: None
matplotlib: 2.0.0rc2
openpyxl: 2.3.0
xlrd: 1.0.0
xlwt: 1.1.2
xlsxwriter: 0.9.3
lxml: 3.6.4
bs4: 4.5.1
html5lib: 0.999
httplib2: 0.9.1
apiclient: 1.5.2
sqlalchemy: 1.0.15
pymysql: None
psycopg2: None
jinja2: 2.8
s3fs: None
pandas_datareader: 0.2.1

[jreback]

why don't you add the fix for this in #15425 as well (as its quite similar). Be sure that the ndarray is 1d though (if its NOT 1d it should raise), and pls test this.