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id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
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448817147 | https://github.com/pydata/xarray/pull/2621#issuecomment-448817147 | https://api.github.com/repos/pydata/xarray/issues/2621 | MDEyOklzc3VlQ29tbWVudDQ0ODgxNzE0Nw== | shoyer 1217238 | 2018-12-20T01:07:27Z | 2018-12-20T01:07:27Z | MEMBER |
Can you explain why matters for My inclination was just to copy what pandas does (which is only removing unused levels in |
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Fix multiindex selection 392535505 | |
448677802 | https://github.com/pydata/xarray/pull/2621#issuecomment-448677802 | https://api.github.com/repos/pydata/xarray/issues/2621 | MDEyOklzc3VlQ29tbWVudDQ0ODY3NzgwMg== | shoyer 1217238 | 2018-12-19T17:26:36Z | 2018-12-19T17:26:36Z | MEMBER | Should we update levels after indexing or when stacking? Pandas does the later: ``` In [31]: import pandas as pd In [32]: mindex = pd.MultiIndex.from_product([[1, 2, 3], ['a', 'b']]) In [33]: s = pd.Series(range(6), mindex) In [34]: s.loc[:1].index Out[34]: MultiIndex(levels=[[1, 2, 3], ['a', 'b']], labels=[[0, 0], [0, 1]]) In [35]: s.loc[:1].unstack() Out[35]: a b 1 0 1 ``` The advantage of waiting until unstacking is that removing unused levels could be expensive compared to indexing: it runs in time O(L+N), where L is the size of the original level and N is the length of the new multi-index. |
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Fix multiindex selection 392535505 |
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