Description
Code Sample, a copy-pastable example if possible
In [2]: s = pd.Series(range(9), index=pd.MultiIndex.from_product([['A', 'B', 'C'], ['foo', 'bar', 'baz']],names=['one', 'two']))
In [3]: s.loc._getitem_iterable(['A', 'E'], 0)
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
<ipython-input-3-62e87e14f902> in <module>()
----> 1 s.loc._getitem_iterable(['A', 'E'])
/home/pietro/nobackup/repo/pandas/pandas/core/indexing.py in _getitem_iterable(self, key, axis)
1095 # if it cannot handle; we only act on all found values
1096 indexer, keyarr = labels._convert_listlike_indexer(
-> 1097 key, kind=self.name)
1098 if indexer is not None and (indexer != -1).all():
1099 return self.obj.take(indexer, axis=axis)
/home/pietro/nobackup/repo/pandas/pandas/core/indexes/multi.py in _convert_listlike_indexer(self, keyarr, kind)
1760 mask = check == -1
1761 if mask.any():
-> 1762 raise KeyError('%s not in index' % keyarr[mask])
1763
1764 return indexer, keyarr
KeyError: "['E'] not in index"
Problem description
(Unless/until we change our general approach to this - related discussion is in #15747,) indexing with a list containing at least one valid key should not raise an error. Indeed, before 05d70f4 ,
In [2]: s = pd.Series(range(9), index=pd.MultiIndex.from_product([['A', 'B', 'C'], ['foo', 'bar', 'baz']],names=['one', 'two']))
In [3]: s.loc._getitem_iterable(['A', 'E'])
Out[3]:
one two
A foo 0
bar 1
baz 2
dtype: int64
Expected Output
See above. This had already been reported here, opening an independent issue for clarity, as suggested by @gfyoung .
Output of pd.show_versions()
pandas: 0.21.0.dev+231.g03cec7563
pytest: 3.0.6
pip: 9.0.1
setuptools: None
Cython: 0.25.2
numpy: 1.12.1
scipy: 0.19.0
xarray: None
IPython: 5.1.0.dev
sphinx: 1.5.6
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.3.0
numexpr: 2.6.1
feather: 0.3.1
matplotlib: 2.0.2
openpyxl: None
xlrd: 1.0.0
xlwt: 1.1.2
xlsxwriter: 0.9.6
lxml: None
bs4: 4.5.3
html5lib: 0.999999999
sqlalchemy: 1.0.15
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: 0.2.1