Streamline datasets for documenation
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docs 📜
- Dominant language
- Python
- Stars
- 394
- Forks
- 95
- Avg merge
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- Merged PRs (30d)
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Description
We should make the usage of datasets more heterogenous across the notebooks in the docs.
Practically:
- select 1, max 3, small datasets (<1 GB each, ideally ~100 MB), use these datasets in all the notebooks across the repos:
-
spatialdata -
spatialdata-plot -
napari-spatialdata
-
- in particular, remove the non-bio datasets from the docs (e.g. remove the raccoon dataset from the transformation notebook, and the blobs dataset from the aggregation and rasterize notebooks)
- implement a dataset class, like in
squidpy, to automatically download the datasets
CC @timtreis @melonora
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
Review the notebooks in spatialdata, spatialdata-plot, and napari-spatialdata, especially the transformation, aggregation, and rasterize notebooks, and compare squidpy's dataset class. Define the small shared bio-dataset set and automatic-download behavior; done means non-bio examples are removed and the listed notebooks use the shared datasets.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook, python
- Domain
- data, documentation
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 32/100