BUG: Categorical.map() sort categories for unordered categoricals (#58153)

[tinezivic]

• closes BUG: sort_values() with key not working on categorical column #58153
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Bug

DataFrame.sort_values(key=...) on a Categorical column where the key maps values to a custom order ignored the key, sorting alphabetically instead of by the mapped values.

Minimal reproduction:

import pandas as pd

df = pd.DataFrame(
    [[1, 2, "March"], [5, 6, "Dec"], [3, 4, "April"]],
    columns=["a", "b", "month"],
)
df.month = df.month.astype("category")
custom_dict = {"March": 0, "April": 1, "Dec": 3}
print(df.sort_values(by=["month"], key=lambda x: x.map(custom_dict)))
# Before fix: sorted alphabetically (April, Dec, March) — key ignored
# After fix:  sorted by custom_dict order (March, April, Dec)

Root Cause

Categorical.map() preserved the positional category order from the original categories. For unordered categoricals the mapped values inherited an arbitrary ordering, so sort_values sorted by old category position instead of the mapped values.

Fix: In Categorical.map(), when the categorical is unordered, sort the mapped categories and remap codes accordingly. For ordered categoricals the existing category order is preserved. Mixed-type categories that cannot be compared (e.g. str and float) fall back to original order via TypeError catch.

AI Disclosure

This fix was developed with the assistance of GitHub Copilot (Claude Sonnet 4.6). The AI assisted with code generation and diff review. The contributor verified the fix locally and confirmed all 49 tests pass.