From f84c520428a376dd8f93c0d88872733322057a6f Mon Sep 17 00:00:00 2001
From: Matthew Roeschke <emailformattr@gmail.com>
Date: Sun, 22 Aug 2021 20:31:44 -0700
Subject: [PATCH 1/3] BUG: rolling with Int64
---
doc/source/whatsnew/v1.4.0.rst | 2 +-
pandas/core/window/rolling.py | 6 +++++-
pandas/tests/window/test_dtypes.py | 9 +++++++++
3 files changed, 15 insertions(+), 2 deletions(-)
diff --git a/doc/source/whatsnew/v1.4.0.rst b/doc/source/whatsnew/v1.4.0.rst
index 205a49e7786a7..d7de6ab7a5c79 100644
--- a/doc/source/whatsnew/v1.4.0.rst
+++ b/doc/source/whatsnew/v1.4.0.rst
@@ -341,7 +341,7 @@ 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
^^^^^^^^^
diff --git a/pandas/core/window/rolling.py b/pandas/core/window/rolling.py
index 637b7c705d73c..844d29bc41827 100644
--- a/pandas/core/window/rolling.py
+++ b/pandas/core/window/rolling.py
@@ -318,7 +318,11 @@ 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 hasattr(values, "to_numpy"):
+ # GH 43016: ExtensionArray
+ values = values.to_numpy(dtype=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
diff --git a/pandas/tests/window/test_dtypes.py b/pandas/tests/window/test_dtypes.py
index 7cd2bf4f1ca19..12c653ca3bf98 100644
--- a/pandas/tests/window/test_dtypes.py
+++ b/pandas/tests/window/test_dtypes.py
@@ -2,6 +2,7 @@
import pytest
from pandas import (
+ NA,
DataFrame,
Series,
)
@@ -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])
+ tm.assert_series_equal(result, expected)
+
+
@pytest.mark.parametrize(
"method, expected_data, min_periods",
[
From 57b0ceb26b38ab0a9295bb853fa5f7a053fe141e Mon Sep 17 00:00:00 2001
From: Matthew Roeschke <emailformattr@gmail.com>
Date: Thu, 26 Aug 2021 15:55:34 -0700
Subject: [PATCH 2/3] Move logic into ensure_float64
---
pandas/_libs/algos_common_helper.pxi.in | 34 ++++++++++++++-----------
pandas/core/window/rolling.py | 6 +----
2 files changed, 20 insertions(+), 20 deletions(-)
diff --git a/pandas/_libs/algos_common_helper.pxi.in b/pandas/_libs/algos_common_helper.pxi.in
index 64e8bdea4672c..c677845b3a96f 100644
--- a/pandas/_libs/algos_common_helper.pxi.in
+++ b/pandas/_libs/algos_common_helper.pxi.in
@@ -37,27 +37,27 @@ def ensure_object(object arr):
{{py:
# name, c_type, dtype
-dtypes = [('float64', 'FLOAT64', 'float64'),
- ('float32', 'FLOAT32', 'float32'),
- ('int8', 'INT8', 'int8'),
- ('int16', 'INT16', 'int16'),
- ('int32', 'INT32', 'int32'),
- ('int64', 'INT64', 'int64'),
- ('uint8', 'UINT8', 'uint8'),
- ('uint16', 'UINT16', 'uint16'),
- ('uint32', 'UINT32', 'uint32'),
- ('uint64', 'UINT64', 'uint64'),
- # ('platform_int', 'INT', 'int_'),
- # ('object', 'OBJECT', 'object_'),
+dtypes = [('float64', 'FLOAT64', 'float64', 'nan'),
+ ('float32', 'FLOAT32', 'float32', 'nan'),
+ ('int8', 'INT8', 'int8', None),
+ ('int16', 'INT16', 'int16', None),
+ ('int32', 'INT32', 'int32', None),
+ ('int64', 'INT64', 'int64', None),
+ ('uint8', 'UINT8', 'uint8', None),
+ ('uint16', 'UINT16', 'uint16', None),
+ ('uint32', 'UINT32', 'uint32', None),
+ ('uint64', 'UINT64', 'uint64', None),
+ # ('platform_int', 'INT', 'int_', None),
+ # ('object', 'OBJECT', 'object_', None),
]
def get_dispatch(dtypes):
- for name, c_type, dtype in dtypes:
- yield name, c_type, dtype
+ for name, c_type, dtype, na_val in dtypes:
+ yield name, c_type, dtype, na_val
}}
-{{for name, c_type, dtype in get_dispatch(dtypes)}}
+{{for name, c_type, dtype, na_val in get_dispatch(dtypes)}}
def ensure_{{name}}(object arr, copy=True):
@@ -66,6 +66,10 @@ def ensure_{{name}}(object arr, copy=True):
return arr
else:
return arr.astype(np.{{dtype}}, copy=copy)
+{{if na_val == "nan"}}
+ elif hasattr(arr, "to_numpy"):
+ return arr.to_numpy(np.{{dtype}}, copy=copy, na_value=np.{{na_val}})
+{{endif}}
else:
return np.array(arr, dtype=np.{{dtype}})
diff --git a/pandas/core/window/rolling.py b/pandas/core/window/rolling.py
index 238aa7f962c67..ab23b84a3b8c6 100644
--- a/pandas/core/window/rolling.py
+++ b/pandas/core/window/rolling.py
@@ -317,11 +317,7 @@ 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:
- if hasattr(values, "to_numpy"):
- # GH 43016: ExtensionArray
- values = values.to_numpy(dtype=np.float64, na_value=np.nan)
- else:
- values = ensure_float64(values)
+ values = ensure_float64(values)
except (ValueError, TypeError) as err:
raise TypeError(f"cannot handle this type -> {values.dtype}") from err
From 77416cc76dbb64a5f2114fc06bf688d92b4e2245 Mon Sep 17 00:00:00 2001
From: Matthew Roeschke <emailformattr@gmail.com>
Date: Mon, 30 Aug 2021 22:52:53 -0700
Subject: [PATCH 3/3] Use isinstance check instead
---
pandas/_libs/algos_common_helper.pxi.in | 34 +++++++++++--------------
pandas/core/window/rolling.py | 6 ++++-
2 files changed, 20 insertions(+), 20 deletions(-)
diff --git a/pandas/_libs/algos_common_helper.pxi.in b/pandas/_libs/algos_common_helper.pxi.in
index c677845b3a96f..64e8bdea4672c 100644
--- a/pandas/_libs/algos_common_helper.pxi.in
+++ b/pandas/_libs/algos_common_helper.pxi.in
@@ -37,27 +37,27 @@ def ensure_object(object arr):
{{py:
# name, c_type, dtype
-dtypes = [('float64', 'FLOAT64', 'float64', 'nan'),
- ('float32', 'FLOAT32', 'float32', 'nan'),
- ('int8', 'INT8', 'int8', None),
- ('int16', 'INT16', 'int16', None),
- ('int32', 'INT32', 'int32', None),
- ('int64', 'INT64', 'int64', None),
- ('uint8', 'UINT8', 'uint8', None),
- ('uint16', 'UINT16', 'uint16', None),
- ('uint32', 'UINT32', 'uint32', None),
- ('uint64', 'UINT64', 'uint64', None),
- # ('platform_int', 'INT', 'int_', None),
- # ('object', 'OBJECT', 'object_', None),
+dtypes = [('float64', 'FLOAT64', 'float64'),
+ ('float32', 'FLOAT32', 'float32'),
+ ('int8', 'INT8', 'int8'),
+ ('int16', 'INT16', 'int16'),
+ ('int32', 'INT32', 'int32'),
+ ('int64', 'INT64', 'int64'),
+ ('uint8', 'UINT8', 'uint8'),
+ ('uint16', 'UINT16', 'uint16'),
+ ('uint32', 'UINT32', 'uint32'),
+ ('uint64', 'UINT64', 'uint64'),
+ # ('platform_int', 'INT', 'int_'),
+ # ('object', 'OBJECT', 'object_'),
]
def get_dispatch(dtypes):
- for name, c_type, dtype, na_val in dtypes:
- yield name, c_type, dtype, na_val
+ for name, c_type, dtype in dtypes:
+ yield name, c_type, dtype
}}
-{{for name, c_type, dtype, na_val in get_dispatch(dtypes)}}
+{{for name, c_type, dtype in get_dispatch(dtypes)}}
def ensure_{{name}}(object arr, copy=True):
@@ -66,10 +66,6 @@ def ensure_{{name}}(object arr, copy=True):
return arr
else:
return arr.astype(np.{{dtype}}, copy=copy)
-{{if na_val == "nan"}}
- elif hasattr(arr, "to_numpy"):
- return arr.to_numpy(np.{{dtype}}, copy=copy, na_value=np.{{na_val}})
-{{endif}}
else:
return np.array(arr, dtype=np.{{dtype}})
diff --git a/pandas/core/window/rolling.py b/pandas/core/window/rolling.py
index ab23b84a3b8c6..66ffc2600e88e 100644
--- a/pandas/core/window/rolling.py
+++ b/pandas/core/window/rolling.py
@@ -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,
@@ -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