10000 BUG: Offset-based rolling window, with only one raw in dataframe and closed='left', max and min functions make python crash by jh-wu · Pull Request #24811 · pandas-dev/pandas · GitHub
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BUG: Offset-based rolling window, with only one raw in dataframe and closed='left', max and min functions make python crash #24811

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Merged
jreback merged 3 commits into from
Jan 18, 2019
Merged

BUG: Offset-based rolling window, with only one raw in dataframe and closed='left', max and min functions make python crash #24811

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417ca64
BUG: GH24718 fixed
jwu-pb Jan 17, 2019
e394748
BUG: closes GH24718
jwu-pb Jan 17, 2019
2e513db
BUG:GH24718 remove the unnecessary parens in pytest.mark.parametrize
jwu-pb Jan 17, 2019
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BUG: GH24718 fixed
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@jwu-pb
jwu-pb committed Jan 17, 2019
commit 417ca64cce66dc50bb952f3940c732ce44a39b44
5 changes: 4 additions & 1 deletion pandas/_libs/window.pyx
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Original file line number Diff line number Diff line change
Expand Up @@ -1339,7 +1339,10 @@ cdef _roll_min_max_variable(ndarray[numeric] values,
Q.push_back(i)
W.push_back(i)

output[N-1] = calc_mm(minp, nobs, values[Q.front()])
if not Q.empty():
output[N-1] = calc_mm(minp, nobs, values[Q.front()])
else:
output[N-1] = NaN

return output

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20 changes: 20 additions & 0 deletions pandas/tests/test_window.py
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Expand Up @@ -520,6 +520,26 @@ def test_closed(self):
with pytest.raises(ValueError):
df.rolling(window=3, closed='neither')

@pytest.mark.parametrize("func", [('min'), ('max')])
def test_closed_one_entry(self, func):
# GH24718
ser = pd.Series(data=[2], index=pd.date_range('2000', periods=1))
result = getattr(ser.rolling('10D', closed='left'), func)()
tm.assert_series_equal(result, pd.Series([np.nan], index=ser.index))

@pytest.mark.parametrize("func", [('min'), ('max')])
def test_closed_one_entry_groupby(self, func):
# GH24718
ser = pd.DataFrame(data={'A': [1, 1, 2], 'B': [3, 2, 1]},
index=pd.date_range('2000', periods=3))
result = getattr(
ser.groupby('A', sort=False)['B'].rolling('10D', closed='left'),
func)()
exp_idx = pd.MultiIndex.from_arrays(arrays=[[1, 1, 2], ser.index],
names=('A', None))
expected = pd.Series(data=[np.nan, 3, np.nan], index=exp_idx, name='B')
tm.assert_series_equal(result, expected)

@pytest.mark.parametrize("input_dtype", ['int', 'float'])
@pytest.mark.parametrize("func,closed,expected", [
('min', 'right', [0.0, 0, 0, 1, 2, 3, 4, 5, 6, 7]),
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0