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2 rows where issue = 811321550 and user = 2448579 sorted by updated_at descending
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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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791011542 | https://github.com/pydata/xarray/issues/4922#issuecomment-791011542 | https://api.github.com/repos/pydata/xarray/issues/4922 | MDEyOklzc3VlQ29tbWVudDc5MTAxMTU0Mg== | dcherian 2448579 | 2021-03-04T23:02:48Z | 2021-03-04T23:02:48Z | MEMBER | ``` Just apply rolling to the base array.ds.rolling(time=6, center=False, min_periods=1).mean() ``` I feel like this should not work i.e. rolling window length (6) < size along axis (3). So the bottleneck error seems right. The chunk size error in the last example should go away with #4977 |
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Bottleneck and dask objects ignore `min_periods` on `rolling` 811321550 | |
781571084 | https://github.com/pydata/xarray/issues/4922#issuecomment-781571084 | https://api.github.com/repos/pydata/xarray/issues/4922 | MDEyOklzc3VlQ29tbWVudDc4MTU3MTA4NA== | dcherian 2448579 | 2021-02-18T19:08:44Z | 2021-02-18T19:08:44Z | MEMBER | Maybe the padding is breaking down for length-1 arrays? I would look at |
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Bottleneck and dask objects ignore `min_periods` on `rolling` 811321550 |
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