Skip to content

BUG: min/max on empty categorical fails #30227

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 16 commits into from
Dec 17, 2019
Merged

BUG: min/max on empty categorical fails #30227

Changes from 1 commit
Commits
Show all changes
16 commits
Select commit Hold shift + click to select a range
5db7e01
TST: Add failing test for min/max on empty categorical.
Dec 12, 2019
9c36841
BUG: min/max on empty categorical crashed
Dec 12, 2019
4d5df3a
DOC: Added whatsnew.
Dec 12, 2019
d788332
CLN: Black test_reductions.
Dec 12, 2019
3ec816c
Added .. versionchanged and correct NA value for dtype.
Dec 12, 2019
51f21d5
DOC: Add issue number to whatsnew.
Dec 12, 2019
8dee71e
CLN: Cleaner empty checks.
Dec 12, 2019
c3f0d77
CLN: Move and clean up test_min_max_empty.
Dec 12, 2019
f0efeeb
DOC: Add issue number comment to test.
Dec 12, 2019
1888238
TST: Parametrize test case on different categorical dtypes.
Dec 12, 2019
c74b8d0
TST: Split and rename tests.
Dec 12, 2019
34ad68d
TST; Fix test on datetime categorical.
Dec 16, 2019
d8346ee
CLN: Fixed unused import.
Dec 16, 2019
4dca2d9
CLN: Parametrize tests over min,max
Dec 16, 2019
38bab51
CLN: Remove unused import.
Dec 16, 2019
890b278
TST: xfail datetime categorical tests.
Dec 17, 2019
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
14 changes: 11 additions & 3 deletions pandas/core/arrays/categorical.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -39,7 +39,7 @@
from pandas.core.dtypes.dtypes import CategoricalDtype
from pandas.core.dtypes.generic import ABCIndexClass, ABCSeries
from pandas.core.dtypes.inference import is_hashable
from pandas.core.dtypes.missing import isna, notna
from pandas.core.dtypes.missing import isna, na_value_for_dtype, notna

from pandas._typing import ArrayLike, Dtype, Ordered
from pandas.core import ops
Expand Down Expand Up @@ -2116,6 +2116,10 @@ def min(self, skipna=True):

Only ordered `Categoricals` have a minimum!

.. versionchanged:: 1.0.0

Returns an NA value on empty arrays

Raises
------
TypeError
Expand All @@ -2128,7 +2132,7 @@ def min(self, skipna=True):
self.check_for_ordered("min")

if len(self._codes) == 0:
return np.nan
return na_value_for_dtype(self.dtype)

good = self._codes != -1
if not good.all():
Expand All @@ -2147,6 +2151,10 @@ def max(self, skipna=True):

Only ordered `Categoricals` have a maximum!

.. versionchanged:: 1.0.0

Returns an NA value on empty arrays

Raises
------
TypeError
Expand All @@ -2159,7 +2167,7 @@ def max(self, skipna=True):
self.check_for_ordered("max")

if len(self._codes) == 0:
return np.nan
return na_value_for_dtype(self.dtype)

good = self._codes != -1
if not good.all():
Expand Down