How should xarray use/support sparse arrays?
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topic-arrays
- Dominant language
- Python
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Description
I'm looking forward to being easily able to create sparse xarray objects from pandas: https://github.com/pydata/xarray/issues/3206
Are there other xarray APIs that could make good use of sparse arrays, or could make sparse arrays easier to use?
Some ideas:
to_sparse()/to_dense()methods for converting to/from sparse without requiring using.datato_dataframe()/to_series()could grow options for skipping the fill-value in sparse arrays, so they can round-trip MultiIndex data back to pandas- Serialization to/from netCDF files, using some custom convention (see https://github.com/pydata/xarray/issues/1375#issuecomment-402699810)
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reviewing the linked xarray issue #3206 and the referenced netCDF discussion. Compare the proposed to_sparse/to_dense methods, dataframe and series fill-value handling, and netCDF serialization options with the current APIs. Done would require a decided scope and concrete acceptance criteria for sparse-array support.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- pandas, python
- Domain
- data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100