pull_requests: 355258632
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| 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 |
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| 355258632 | MDExOlB1bGxSZXF1ZXN0MzU1MjU4NjMy | 3646 | open | 0 | [WIP] GroupBy plotting | 2448579 | <!-- Feel free to remove check-list items aren't relevant to your change --> - [x] Tests added - [x] Passes `black . && mypy . && flake8` - [ ] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API This adds plotting methods to GroupBy objects so that it's easy to plot each group as a facet. I'm finding this super helpful in my current research project. It's pretty self-contained, mostly just adding `map_groupby*` methods to `FacetGrid`. But that's because I make `GroupBy` mimic the underlying `DataArray` by adding `coords`, `attrs` and `__getitem__`. This still needs more tests but I would like feedback on the feature and the implementation. ## Example ``` python import numpy as np import xarray as xr time = np.arange(80) da = xr.DataArray(5 * np.sin(2*np.pi*time/10), coords={"time": time}, dims="time") da["period"] = da.time.where((time % 10) == 0).ffill("time")/10 da.plot() ```  ``` python da.groupby("period").plot(col="period", col_wrap=4) ```  ``` python da = da.expand_dims(y=10) da.groupby("period").plot(col="period", col_wrap=4, sharex=False, sharey=True, robust=True) ```  | 2019-12-19T17:26:39Z | 2022-06-09T14:50:17Z | c4a14cdad43c7522ed7a0f65f9dc3da8edcfd8dc | 1 | 8f4ea871bad8d42b5c9edf7d620655163b060c31 | d1e4164f3961d7bbb3eb79037e96cae14f7182f8 | MEMBER | 13221727 | https://github.com/pydata/xarray/pull/3646 |
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