pull_requests: 238972759
This data as json
| id | node_id | number | state | locked | title | user | body | created_at | updated_at | closed_at | merged_at | merge_commit_sha | assignee | milestone | draft | head | base | author_association | auto_merge | repo | url | merged_by |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 238972759 | MDExOlB1bGxSZXF1ZXN0MjM4OTcyNzU5 | 2612 | closed | 0 | Added Coarsen | 6815844 | - [x] Closes #2525 - [x] Tests added - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API Started to implement `corsen`. The API is currently something like ```python actual = ds.coarsen(time=2, x=3, side='right', coordinate_func={'time': np.max}).max() ``` Currently, it is not working for a datetime coordinate, since `mean` does not work for this dtype. e.g. ```python da = xr.DataArray(np.linspace(0, 365, num=365), dims='time', coords={'time': pd.date_range('15/12/1999', periods=365)}) da['time'].mean() # -> TypeError: ufunc add cannot use operands with types dtype('<M8[ns]') and dtype('<M8[ns]') ``` I am not familiar with datetime things. Any advice will be appreciated. | 2018-12-16T15:28:31Z | 2019-01-06T09:13:56Z | 2019-01-06T09:13:46Z | 2019-01-06T09:13:46Z | ede3e0101bae2f45c3f4634a1e1ecb8e2ccd0258 | 0 | 1523292b876ec5578b806c9c2cc43ce80d73a061 | dba299befbdf19b02612573b218bcc1e97d4e010 | MEMBER | 13221727 | https://github.com/pydata/xarray/pull/2612 |
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