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BUG: min/max on empty categorical fails #30227

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Merged
merged 16 commits into from
Dec 17, 2019
Merged

BUG: min/max on empty categorical fails #30227

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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
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16 changes: 12 additions & 4 deletions pandas/tests/arrays/categorical/test_analytics.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,7 @@

from pandas.compat import PYPY

from pandas import Categorical, Index, Series
from pandas import Categorical, Index, Series, date_range, NaT
from pandas.api.types import is_scalar
import pandas.util.testing as tm

Expand Down Expand Up @@ -35,15 +35,23 @@ def test_min_max(self):
assert _min == "d"
assert _max == "a"

def test_min_max_empty(self):
@pytest.mark.parametrize(
"categories,expected",
[
(list("ABC"), np.NaN),
([1, 2, 3], np.NaN),
(Series(date_range("2020-01-01", periods=3), dtype="category"), NaT),
],
)
def test_min_max_empty(self, categories, expected):
# GH 30227
cat = Categorical([], categories=list("ABC"), ordered=True)

result = cat.min()
assert isinstance(result, float) and np.isnan(result)
assert result is expected

result = cat.max()
assert isinstance(result, float) and np.isnan(result)
assert result is expected

@pytest.mark.parametrize("skipna", [True, False])
def test_min_max_with_nan(self, skipna):
Expand Down