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BUG: dataframe.rolling along rows drops float16 #42884

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Merged
merged 2 commits into from
Aug 5, 2021
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BUG: dataframe.rolling along rows drops float16 #42884

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cfeae3b
BUG: dataframe.rolling along rows drops float16
debnathshoham Aug 4, 2021
d980589
added whatsnew; uint tests
debnathshoham Aug 5, 2021
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v1.4.0.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -271,6 +271,7 @@ Groupby/resample/rolling
- Bug in :meth:`DataFrame.groupby.rolling.var` would calculate the rolling variance only on the first group (:issue:`42442`)
- Bug in :meth:`GroupBy.shift` that would return the grouping columns if ``fill_value`` was not None (:issue:`41556`)
- 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`)

Reshaping
^^^^^^^^^
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2 changes: 1 addition & 1 deletion pandas/core/window/rolling.py
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Expand Up @@ -226,7 +226,7 @@ def _create_data(self, obj: FrameOrSeries) -> FrameOrSeries:
# GH: 20649 in case of mixed dtype and axis=1 we have to convert everything
# to float to calculate the complete row at once. We exclude all non-numeric
# dtypes.
obj = obj.select_dtypes(include=["integer", "float"], exclude=["timedelta"])
obj = obj.select_dtypes(include=["number"], exclude=["timedelta"])
obj = obj.astype("float64", copy=False)
obj._mgr = obj._mgr.consolidate()
return obj
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35 changes: 35 additions & 0 deletions pandas/tests/window/test_rolling.py
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Expand Up @@ -1432,3 +1432,38 @@ def test_rolling_float_dtype(float_dtype):
expected = DataFrame({"A": [np.nan] * 5, "B": range(10, 20, 2)}, dtype=float_dtype)
result = df.rolling(2, axis=1).sum()
tm.assert_frame_equal(result, expected, check_dtype=False)


def test_rolling_numeric_dtypes():
# GH#41779
df = DataFrame(np.arange(40).reshape(4, 10), columns=list("abcdefghij")).astype(
{
"a": "float16",
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can you add the uint dtypes as well

"b": "float32",
"c": "float64",
"d": "int8",
"e": "int16",
"f": "int32",
"g": "uint8",
"h": "uint16",
"i": "uint32",
"j": "uint64",
}
)
result = df.rolling(window=2, min_periods=1, axis=1).min()
expected = DataFrame(
{
"a": range(0, 40, 10),
"b": range(0, 40, 10),
"c": range(1, 40, 10),
"d": range(2, 40, 10),
"e": range(3, 40, 10),
"f": range(4, 40, 10),
"g": range(5, 40, 10),
"h": range(6, 40, 10),
"i": range(7, 40, 10),
"j": range(8, 40, 10),
},
dtype="float64",
)
tm.assert_frame_equal(result, expected)