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BUG: Weighted rolling aggregations min_periods=0 #51611

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Merged
merged 3 commits into from
Mar 4, 2023
Merged

BUG: Weighted rolling aggregations min_periods=0 #51611

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88335ae
BUG: Weighted rolling aggregations min_periods=0
tomas-pavlik-SF Feb 24, 2023
e1b53a6
added whatsnew
tomas-pavlik-SF Feb 26, 2023
2f59795
Merge branch 'main' into 51449-weighted-roll-aggs-min-periods
tomas-pavlik-SF Feb 27, 2023
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6 changes: 5 additions & 1 deletion pandas/core/window/rolling.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1204,7 +1204,11 @@ def homogeneous_func(values: np.ndarray):
def calc(x):
additional_nans = np.array([np.nan] * offset)
x = np.concatenate((x, additional_nans))
return func(x, window, self.min_periods or len(window))
return func(
x,
window,
self.min_periods if self.min_periods is not None else len(window),
)

with np.errstate(all="ignore"):
# Our weighted aggregations return memoryviews
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8 changes: 4 additions & 4 deletions pandas/tests/window/test_win_type.py
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Original file line number Diff line number Diff line change
Expand Up @@ -321,16 +321,16 @@ def test_cmov_window_frame(f, xp, step):
tm.assert_frame_equal(xp, rs)


@pytest.mark.parametrize("min_periods", [0, 1, 2, 3, 4, 5])
@td.skip_if_no_scipy
def test_cmov_window_na_min_periods(step):
# min_periods
def test_cmov_window_na_min_periods(step, min_periods):
vals = Series(np.random.randn(10))
vals[4] = np.nan
vals[8] = np.nan

xp = vals.rolling(5, min_periods=4, center=True, step=step).mean()
xp = vals.rolling(5, min_periods=min_periods, center=True, step=step).mean()
rs = vals.rolling(
5, win_type="boxcar", min_periods=4, center=True, step=step
5, win_type="boxcar", min_periods=min_periods, center=True, step=step
).mean()
tm.assert_series_equal(xp, rs)

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