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BUG: rolling with Int64 #43174

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Merged
merged 5 commits into from
Aug 31, 2021
Merged

BUG: rolling with Int64 #43174

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f84c520
BUG: rolling with Int64
mroeschke Aug 23, 2021
bc4a45e
Merge remote-tracking branch 'upstream/master' into bug/series_null_i…
mroeschke Aug 26, 2021
57b0ceb
Move logic into ensure_float64
mroeschke Aug 26, 2021
77416cc
Use isinstance check instead
mroeschke Aug 31, 2021
3594d79
Merge remote-tracking branch 'upstream/master' into bug/series_null_i…
mroeschke Aug 31, 2021
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2 changes: 1 addition & 1 deletion doc/source/whatsnew/v1.4.0.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -356,7 +356,7 @@ Groupby/resample/rolling
- Bug in :meth:`pandas.DataFrame.ewm`, where non-float64 dtypes were silently failing (:issue:`42452`)
- Bug in :meth:`pandas.DataFrame.rolling` operation along rows (``axis=1``) incorrectly omits columns containing ``float16`` and ``float32`` (:issue:`41779`)
- Bug in :meth:`Resampler.aggregate` did not allow the use of Named Aggregation (:issue:`32803`)
-
- Bug in :meth:`Series.rolling` when the :class:`Series` ``dtype`` was ``Int64`` (:issue:`43016`)

Reshaping
^^^^^^^^^
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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 @@ -50,6 +50,7 @@

from pandas.core.algorithms import factorize
from pandas.core.apply import ResamplerWindowApply
from pandas.core.arrays import ExtensionArray
from pandas.core.base import (
DataError,
SelectionMixin,
Expand Down Expand Up @@ -317,7 +318,10 @@ def _prep_values(self, values: ArrayLike) -> np.ndarray:
# GH #12373 : rolling functions error on float32 data
# make sure the data is coerced to float64
try:
values = ensure_float64(values)
if isinstance(values, ExtensionArray):
values = values.to_numpy(np.float64, na_value=np.nan)
else:
values = ensure_float64(values)
except (ValueError, TypeError) as err:
raise TypeError(f"cannot handle this type -> {values.dtype}") from err

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9 changes: 9 additions & 0 deletions pandas/tests/window/test_dtypes.py
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Expand Up @@ -2,6 +2,7 @@
import pytest

from pandas import (
NA,
DataFrame,
Series,
)
Expand Down Expand Up @@ -76,6 +77,14 @@ def test_series_dtypes(method, data, expected_data, coerce_int, dtypes, min_peri
tm.assert_almost_equal(result, expected)


def test_series_nullable_int(any_signed_int_ea_dtype):
# GH 43016
s = Series([0, 1, NA], dtype=any_signed_int_ea_dtype)
result = s.rolling(2).mean()
expected = Series([np.nan, 0.5, np.nan])
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shouldn't we actually replace and use pd.NA as the output? or is this too big of a change?

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Ideally, but currently all rolling/expanding/ewm results always return np.float64 (which is documented as well). So that would be a big change to return the same dtype as the caller.

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ok, do we have an issue about this? we should make this change in 1.4

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#11446

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hmm no was speaking about supporting pd.NA specifically (i think rolling_apply is totally fine) if you can add one

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I modified that issue to generally support same input/output dtypes (which include ExtensionDtypes that support pd.NA)

tm.assert_series_equal(result, expected)


@pytest.mark.parametrize(
"method, expected_data, min_periods",
[
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