Comments (3)
Supporting cross-product indexing (without broadcasting error seen above) would also be consistent with dataframe loc/iloc indexing e.g. df.iloc[[0, 4, 10], [2, 3]]
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This now triggers an error... One might think about implementing this in the future...
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Implemented in #164
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Related Issues (20)
- Make example dataset for file format docs available somewhere
- Redo branch protections to allow creating new release branches HOT 4
- ad.concat type unification fails for object + categorical in AnnData >= 0.10 HOT 5
- Catch lots of subtle bugs by setting -Werror in tests
- Keep around a deprecated SparseDataset class for this release cycle HOT 4
- Release note and test for #1169
- General array-api support
- Newest Version of Anndata incompatible with scvi-tools HOT 1
- A subset of a view can get a different .obs than the view itself HOT 2
- AnnData can be created with pd.MultiIndex dimension labels without erroring with pandas<2 HOT 8
- Minimum dependencies test job HOT 4
- Centralize testing warning filters using a custom pytest CLI option
- DataFrameView in pandas 2.1.2 changed behavior, breaking AnnData in several ways HOT 17
- scipy.sparse.issparse check is always false in AnnData.__sizeof__() method + csr_matrix() realizes data HOT 3
- AttributeError: 'DataFrameView' object has no attribute '_view_args' with Pandas 2.1.2+ HOT 4
- Better indexing performance for backed sparse arrays via slices HOT 7
- AnnData 0.10.2/0.10.3 with Pandas 2.0.x tries to use `Categorical.map(na_action=...)` introduced in Pandas 2.1 HOT 1
- Support for Awkward Arrays in AnnData's X HOT 7
- Support for sparse matrices that do not default to 0 but NaN instead HOT 1
- Extend linter config
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