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2 rows where issue = 182667672 and user = 2443309 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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254347566 | https://github.com/pydata/xarray/issues/1046#issuecomment-254347566 | https://api.github.com/repos/pydata/xarray/issues/1046 | MDEyOklzc3VlQ29tbWVudDI1NDM0NzU2Ng== | jhamman 2443309 | 2016-10-17T22:00:32Z | 2016-10-17T22:00:32Z | MEMBER | I'm fine with this approach for now. It would be great if we could convince bottleneck to help us out with a keyword argument of some kind. |
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center=True for xarray.DataArray.rolling() 182667672 | |
253408063 | https://github.com/pydata/xarray/issues/1046#issuecomment-253408063 | https://api.github.com/repos/pydata/xarray/issues/1046 | MDEyOklzc3VlQ29tbWVudDI1MzQwODA2Mw== | jhamman 2443309 | 2016-10-13T03:58:32Z | 2016-10-13T03:58:32Z | MEMBER | We do try to stay consistent with pandas except for the last position. Here's the unit test where we verify that behavior. Using ``` Python In [1]: import pandas as pd s In [2]: data = pd.Series([0, 3, 6]) In [3]: data.rolling(3, center=True, min_periods=1).mean() Out[3]: 0 1.5 1 3.0 2 4.5 ``` If I remember correctly, and my brain is a bit like mush right now so I could be wrong,
So, as you can see, bottleneck does something totally different that wouldn't otherwise work with |
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center=True for xarray.DataArray.rolling() 182667672 |
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