issue_comments: 521411228
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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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| https://github.com/pydata/xarray/issues/3218#issuecomment-521411228 | https://api.github.com/repos/pydata/xarray/issues/3218 | 521411228 | MDEyOklzc3VlQ29tbWVudDUyMTQxMTIyOA== | 5635139 | 2019-08-14T20:43:57Z | 2019-08-14T20:43:57Z | MEMBER |
Yes this is right! Mea culpa. We can already use the pandas reindexing for the 1D case (which should cover your case @fjanoos ?) @fjanoos can you confirm this is what you're looking for? ```python In [4]: da=xr.DataArray(list('abcdefghil'), dims=['x'],coords=dict(x=range(10))) In [8]: da.reindex(x=[0,2.5,2.6,2.7,5,6.2], method='nearest') Out[8]: <xarray.DataArray (x: 6)> array(['a', 'd', 'd', 'd', 'f', 'g'], dtype='<U1') Coordinates: * x (x) float64 0.0 2.5 2.6 2.7 5.0 6.2 ``` |
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