Open
Description
Code Sample, a copy-pastable example if possible
In [2]: df = pd.DataFrame(-1, index=pd.MultiIndex.from_product([[1,2], ['a', 'b'], ['i', 'ii']]), columns=['A', 'B'])
In [3]: df.loc[[1]] # works
Out[3]:
A B
1 a i -1 -1
ii -1 -1
b i -1 -1
ii -1 -1
In [4]: df.loc[[(1, 'a')]] # misbehaves (acts as if labels were missing)
Out[4]:
A B
1 a NaN NaN
In [5]: df.loc[[(1,)]] # raises
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
/home/pietro/nobackup/repo/pandas/pandas/core/indexing.py in _getitem_iterable(self, key, axis)
1100 try:
-> 1101 return self.obj.reindex_axis(keyarr, axis=axis)
1102 except AttributeError:
/home/pietro/nobackup/repo/pandas/pandas/core/frame.py in reindex_axis(self, labels, axis, method, level, copy, limit, fill_value)
2836 method=method, level=level, copy=copy,
-> 2837 limit=limit, fill_value=fill_value)
2838
/home/pietro/nobackup/repo/pandas/pandas/core/generic.py in reindex_axis(self, labels, axis, method, level, copy, limit, fill_value)
2509 new_index, indexer = axis_values.reindex(labels, method, level,
-> 2510 limit=limit)
2511 return self._reindex_with_indexers({axis: [new_index, indexer]},
/home/pietro/nobackup/repo/pandas/pandas/core/indexes/multi.py in reindex(self, target, method, level, limit, tolerance)
1845 limit=limit,
-> 1846 tolerance=tolerance)
1847 else:
/home/pietro/nobackup/repo/pandas/pandas/core/indexes/multi.py in get_indexer(self, target, method, limit, tolerance)
1791 # don't have the same dtypes
-> 1792 if self._inferred_type_levels != target._inferred_type_levels:
1793 return Index(self.values).get_indexer(target.values)
AttributeError: 'Int64Index' object has no attribute '_inferred_type_levels'
During handling of the above exception, another exception occurred:
AttributeError Traceback (most recent call last)
<ipython-input-5-e5c902934a28> in <module>()
----> 1 df.loc[[(1,)]]
/home/pietro/nobackup/repo/pandas/pandas/core/indexing.py in __getitem__(self, key)
1326 else:
1327 key = com._apply_if_callable(key, self.obj)
-> 1328 return self._getitem_axis(key, axis=0)
1329
1330 def _is_scalar_access(self, key):
/home/pietro/nobackup/repo/pandas/pandas/core/indexing.py in _getitem_axis(self, key, axis)
1539 raise ValueError('Cannot index with multidimensional key')
1540
-> 1541 return self._getitem_iterable(key, axis=axis)
1542
1543 # nested tuple slicing
/home/pietro/nobackup/repo/pandas/pandas/core/indexing.py in _getitem_iterable(self, key, axis)
1105 if axis != 0:
1106 raise AssertionError('axis must be 0')
-> 1107 return self.obj.reindex(keyarr)
1108
1109 # existing labels are non-unique
/home/pietro/nobackup/repo/pandas/pandas/core/frame.py in reindex(self, index, columns, **kwargs)
2827 def reindex(self, index=None, columns=None, **kwargs):
2828 return super(DataFrame, self).reindex(index=index, columns=columns,
-> 2829 **kwargs)
2830
2831 @Appender(_shared_docs['reindex_axis'] % _shared_doc_kwargs)
/home/pietro/nobackup/repo/pandas/pandas/core/generic.py in reindex(self, *args, **kwargs)
2421 # perform the reindex on the axes
2422 return self._reindex_axes(axes, level, limit, tolerance, method,
-> 2423 fill_value, copy).__finalize__(self)
2424
2425 def _reindex_axes(self, axes, level, limit, tolerance, method, fill_value,
/home/pietro/nobackup/repo/pandas/pandas/core/frame.py in _reindex_axes(self, axes, level, limit, tolerance, method, fill_value, copy)
2773 if index is not None:
2774 frame = frame._reindex_index(index, method, copy, level,
-> 2775 fill_value, limit, tolerance)
2776
2777 return frame
/home/pietro/nobackup/repo/pandas/pandas/core/frame.py in _reindex_index(self, new_index, method, copy, level, fill_value, limit, tolerance)
2781 new_index, indexer = self.index.reindex(new_index, method=method,
2782 level=level, limit=limit,
-> 2783 tolerance=tolerance)
2784 return self._reindex_with_indexers({0: [new_index, indexer]},
2785 copy=copy, fill_value=fill_value,
/home/pietro/nobackup/repo/pandas/pandas/core/indexes/multi.py in reindex(self, target, method, level, limit, tolerance)
1844 indexer = self.get_indexer(target, method=method,
1845 limit=limit,
-> 1846 tolerance=tolerance)
1847 else:
1848 raise Exception("cannot handle a non-unique multi-index!")
/home/pietro/nobackup/repo/pandas/pandas/core/indexes/multi.py in get_indexer(self, target, method, limit, tolerance)
1790 # we may not compare equally because of hashing if we
1791 # don't have the same dtypes
-> 1792 if self._inferred_type_levels != target._inferred_type_levels:
1793 return Index(self.values).get_indexer(target.values)
1794
AttributeError: 'Int64Index' object has no attribute '_inferred_type_levels'
Problem description
This was already discussed here and here, opening a separate issue for clarity.
Expected Output
df.loc[[(1, 'a',)]] should return the same as df.loc[1, 'a', :] (or more explicitly, df.loc[(1, 'a', slice(None)), :]), while df.loc[[(1,)]] should return the same as df.loc[[1]].
Output of pd.show_versions()
INSTALLED VERSIONS
commit: None
python: 3.5.3.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+834.g8c7b9731f
pytest: 3.0.6
pip: 9.0.1
setuptools: 33.1.1
Cython: 0.25.2
numpy: 1.12.0
scipy: 0.18.1
xarray: 0.9.1
IPython: 5.1.0.dev
sphinx: 1.4.9
patsy: 0.3.0-dev
dateutil: 2.5.3
pytz: 2016.7
blosc: None
bottleneck: 1.2.0
tables: 3.3.0
numexpr: 2.6.1
feather: 0.3.1
matplotlib: 2.0.0
openpyxl: 2.3.0
xlrd: 1.0.0
xlwt: 1.1.2
xlsxwriter: 0.9.6
lxml: 3.7.1
bs4: 4.5.3
html5lib: 0.999999999
sqlalchemy: 1.0.15
pymysql: None
psycopg2: None
jinja2: 2.8
s3fs: None
pandas_gbq: None
pandas_datareader: 0.2.1