Fix add_peak_annotation crash on empty distance values#182
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LiudengZhang wants to merge 2 commits intoscverse:mainfrom
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Fix add_peak_annotation crash on empty distance values#182LiudengZhang wants to merge 2 commits intoscverse:mainfrom
LiudengZhang wants to merge 2 commits intoscverse:mainfrom
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When the distance column in peak annotation TSV contains empty values (intergenic peaks), pandas may infer a numeric dtype. This caused LossySetitemError when trying to assign "" into the numeric column. Fix by converting distance to string via object dtype early, and using pd.to_numeric with errors="coerce" for the final int conversion, which gracefully handles empty/NaN values as 0. Add regression tests for empty distance values and semicolon-separated multi-gene annotations. Closes scverse#181
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Thank you for the fix! I've pushed a slight update to your branch: Given how long ago Pandas 1.0 was released, we can assume that people using a somewhat up to date muon have it, and get rid of all this string casting nonsense and just use |
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Thanks for the cleanup — the |
Author
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Thanks for the cleanup! Feel free to merge. |
Pandas 1.0 has been released sufficiently long ago that we can assume muon users have it.
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Description
Fix
add_peak_annotationcrashing when the peak annotation TSV contains empty distance values (intergenic peaks).Root cause: When the distance column contains a mix of numeric values and empty strings,
pd.read_csvinfers it asfloat64. The existing code then tries to assign""into a numeric column, triggeringLossySetitemError. On newer pandas withStringDtype, a similar issue occurs withpd.NAvalues.Fix:
astype(object).fillna("").astype(str)to safely handle both numeric and nullable string dtypes""→0→float→intconversion withpd.to_numeric(errors="coerce").fillna(0).astype(int), which handles all edge cases in one expressionHow has this been tested?
pytest tests/— 13 passed)Closes
Closes #181