Skip to content

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

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.

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 3 commits into from
Jan 18, 2019
Merged
Show file tree
Hide file tree
Changes from 1 commit
Commits
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
5 changes: 4 additions & 1 deletion pandas/_libs/window.pyx
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

Expand Down
20 changes: 20 additions & 0 deletions pandas/tests/test_window.py
Original file line number Diff line number Diff line change
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]),
Expand Down