Closed
Description
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: int64Output 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