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PERF: remove categories #51344

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Merged
merged 2 commits into from
Feb 13, 2023
Merged

PERF: remove categories #51344

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0270e4d
PERF: remove categories
lukemanley Feb 12, 2023
c643afc
swap unique/dropna order
lukemanley Feb 12, 2023
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6 changes: 4 additions & 2 deletions pandas/core/arrays/categorical.py
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Original file line number Diff line number Diff line change
Expand Up @@ -73,7 +73,6 @@
from pandas.core.dtypes.missing import (
is_valid_na_for_dtype,
isna,
notna,
)

from pandas.core import (
Expand Down Expand Up @@ -1135,14 +1134,17 @@ def remove_categories(self, removals):
[NaN, 'c', 'b', 'c', NaN]
Categories (2, object): ['b', 'c']
"""
from pandas import Index

if not is_list_like(removals):
removals = [removals]

removals = {x for x in set(removals) if notna(x)}
removals = Index(removals).dropna().unique()
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Wouldn't the other way round be faster? e.g. unique().dropna()?

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Good point. Its not measurable with that benchmark, but I swapped it anyway.

new_categories = self.dtype.categories.difference(removals)
not_included = removals.difference(self.dtype.categories)

if len(not_included) != 0:
not_included = set(not_included)
raise ValueError(f"removals must all be in old categories: {not_included}")

return self.set_categories(new_categories, ordered=self.ordered, rename=False)
Expand Down