issue_comments: 1364696481
This data as json
| 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/7401#issuecomment-1364696481 | https://api.github.com/repos/pydata/xarray/issues/7401 | 1364696481 | IC_kwDOAMm_X85RV52h | 15239248 | 2022-12-25T15:12:15Z | 2022-12-25T15:12:15Z | NONE | thanks for the reply. Somehow i don't find an elegant way that does not involve many loops and hoops. Lets consider the following short example:
I want to produce a figure that takes the xr.tutorial.open_dataset("air_temperature") and produces a mean grouped by season and hour in the same figure:
da = xr.tutorial.open_dataset("air_temperature")['air'] ( da.groupby(da['time'].dt.season) .mean() .plot(col='season') ) (
da.groupby(da['time'].dt.hour)
.mean()
.plot(col='hour')
)
```
but combining both seems quite complicated to me. I wish I could pass a subfigure to the plot function in the following way ```python fig:plt.Figure = plt.figure() (fig_top,fig_bot) = fig.subfigures(2,1) ( da.groupby(da['time'].dt.season) .mean() .plot(col='season',fig=fig_top) ) (
da.groupby(da['time'].dt.hour)
.mean()
.plot(col='hour', fig=fig_bot)
)
```
maybe I am missing a smart way of doing this? cheers |
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1510151748 |
Creating the top and bottom rows independently is super efficient with xarray:
```python
import xarray as xr
import matplotlib.pyplot as plt
