issue_comments: 362902669
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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/1388#issuecomment-362902669 | https://api.github.com/repos/pydata/xarray/issues/1388 | 362902669 | MDEyOklzc3VlQ29tbWVudDM2MjkwMjY2OQ== | 6815844 | 2018-02-04T12:20:33Z | 2018-02-04T12:52:29Z | MEMBER | @gajomi Sorry for my late response and thank you for the proposal. But aside from my previous proposal, I was thinking whether such aggregation methods (including Such specific rules may be confusing and bring additional complexity. I think the rule we do not track coordinates after aggregations would be much simpler and easier to understand. If we adopt the above rule, I think the In [4]: da.argmin(dim='x') Out[4]: <xarray.DataArray (y: 3)> array([0, 1, 0]) Coordinates: * y (y) <U1 'a' 'b' 'c' In [3]: da.isel(x=da.argmin(dim='x')) Out[3]: <xarray.DataArray (y: 3)> array([0, 1, 2]) Coordinates: x (y) int64 1 2 1 * y (y) <U1 'a' 'b' 'c' ``` I think your logic would be useful even we do not track the coordinate. I would appreciate any feedback. |
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