Feature: Aggregate using one or more operations over the specified axis.
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- Dominant language
- Python
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- Avg merge
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- Merged PRs (30d)
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Description
Is your feature request related to a problem?
I'm always frustrated when I need to resample a ds and the resampling method is different for the variables present, i.e. for one variable I want the sum and for the other the mean.
Describe the solution you'd like
Ideally there would be some functionality similar to pandas .agg functionality.
Not sure if this is feasible.
ds = ds.resample(time="D").agg({"pr":"sum","tas":np.mean})
Describe alternatives you've considered
Current workaround which gets unwieldy for multiple variables.
ds_pr = ds.pr.resample(time="D").sum()
ds_tas = ds.tas.resample(time="D").mean()
ds = xr.merge([ds_pr, ds_tas])
Additional context
No response
Contributor guide
First steps
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Research direction
Start at the Dataset resample entry point and compare the requested API with pandas aggregation behavior. Define how mappings of variables to operations should work, including the shown sum and mean case, then add coverage for the new behavior. Done means one resampling call can apply different operations to the specified variables without the manual merge workaround.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- numpy, pandas, python
- Domain
- data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100