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PERF: fail-fast in object-dtype mean #62280

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Merged
merged 4 commits into from
Sep 15, 2025
Merged

PERF: fail-fast in object-dtype mean #62280

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PERF: fail-fast in object-dtype mean
jbrockmendel Sep 6, 2025
337469f
Merge branch 'main' into fail-fast
jbrockmendel Sep 9, 2025
cee423e
Merge branch 'main' into fail-fast
jbrockmendel Sep 10, 2025
4e388b8
5->1000
jbrockmendel Sep 10, 2025
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4 changes: 4 additions & 0 deletions pandas/core/nanops.py
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Original file line number Diff line number Diff line change
Expand Up @@ -693,6 +693,10 @@ def nanmean(
>>> nanops.nanmean(s.values)
np.float64(1.5)
"""
if values.dtype == object and len(values) > 1_000 and mask is None:
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Can we just not infer_dtype(values) for object dtype to raise early if the inferred type are strings?

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  1. infer_dtype is a pattern im trying to move us away from, 2) that would still require a full pass through the data, 3) that would for strings but not hypothetical other cases

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OK sure thing. Should the 5 below then match the 1000 above then for consistency?

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ok, will update

# GH#54754 if we are going to fail, try to fail-fast
nanmean(values[:1000], axis=axis, skipna=skipna)

dtype = values.dtype
values, mask = _get_values(values, skipna, fill_value=0, mask=mask)
dtype_sum = _get_dtype_max(dtype)
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