issue_comments: 191826844
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| html_url | issue_url | id | node_id | user | created_at | updated_at | author_association | body | reactions | performed_via_github_app | issue |
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| https://github.com/pydata/xarray/issues/767#issuecomment-191826844 | https://api.github.com/repos/pydata/xarray/issues/767 | 191826844 | MDEyOklzc3VlQ29tbWVudDE5MTgyNjg0NA== | 1217238 | 2016-03-03T16:00:50Z | 2016-03-03T16:00:50Z | MEMBER | If you try that doing that indexing with a pandas.Series, you actually get an error message: ``` In [71]: s.loc['bar', slice(4000, 4100.3)] .../Users/shoyer/conda/envs/xarray-dev/lib/python3.5/site-packages/pandas/core/indexing.py in _getitem_axis(self, key, axis) 1363 # nested tuple slicing 1364 if is_nested_tuple(key, labels): -> 1365 locs = labels.get_locs(key) 1366 indexer = [ slice(None) ] * self.ndim 1367 indexer[axis] = locs /Users/shoyer/conda/envs/xarray-dev/lib/python3.5/site-packages/pandas/core/index.py in get_locs(self, tup) 5692 if not self.is_lexsorted_for_tuple(tup): 5693 raise KeyError('MultiIndex Slicing requires the index to be fully lexsorted' -> 5694 ' tuple len ({0}), lexsort depth ({1})'.format(len(tup), self.lexsort_depth)) 5695 5696 # indexer KeyError: 'MultiIndex Slicing requires the index to be fully lexsorted tuple len (2), lexsort depth (0,) ``` I guess it's also worth investigating |
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