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REGR: astype introducing decimals when casting from int with na to string #57489

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Merged
merged 1 commit into from
Feb 20, 2024
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REGR: astype introducing decimals when casting from int with na to string #57489

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1 change: 1 addition & 0 deletions doc/source/whatsnew/v2.2.1.rst
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Expand Up @@ -37,6 +37,7 @@ Fixed regressions
- Fixed regression in :meth:`DataFrameGroupBy.idxmin`, :meth:`DataFrameGroupBy.idxmax`, :meth:`SeriesGroupBy.idxmin`, :meth:`SeriesGroupBy.idxmax` where values containing the minimum or maximum value for the dtype could produce incorrect results (:issue:`57040`)
- Fixed regression in :meth:`ExtensionArray.to_numpy` raising for non-numeric masked dtypes (:issue:`56991`)
- Fixed regression in :meth:`Index.join` raising ``TypeError`` when joining an empty index to a non-empty index containing mixed dtype values (:issue:`57048`)
- Fixed regression in :meth:`Series.astype` introducing decimals when converting from integer with missing values to string dtype (:issue:`57418`)
- Fixed regression in :meth:`Series.pct_change` raising a ``ValueError`` for an empty :class:`Series` (:issue:`57056`)
- Fixed regression in :meth:`Series.to_numpy` when dtype is given as float and the data contains NaNs (:issue:`57121`)

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2 changes: 1 addition & 1 deletion pandas/_libs/lib.pyx
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Expand Up @@ -759,7 +759,7 @@ cpdef ndarray[object] ensure_string_array(
out = arr.astype(str).astype(object)
out[arr.isna()] = na_value
return out
arr = arr.to_numpy()
arr = arr.to_numpy(dtype=object)
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Should this only be done for certain dtypes? (integer?)

(maybe run the string.py::Construction benchmarks to check impact, as those were added for this code path #37371)

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no changes reported

elif not util.is_array(arr):
arr = np.array(arr, dtype="object")

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8 changes: 8 additions & 0 deletions pandas/tests/series/methods/test_astype.py
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Expand Up @@ -667,3 +667,11 @@ def test_astype_timedelta64_with_np_nan(self):
result = Series([Timedelta(1), np.nan], dtype="timedelta64[ns]")
expected = Series([Timedelta(1), NaT], dtype="timedelta64[ns]")
tm.assert_series_equal(result, expected)

@td.skip_if_no("pyarrow")
def test_astype_int_na_string(self):
# GH#57418
ser = Series([12, NA], dtype="Int64[pyarrow]")
result = ser.astype("string[pyarrow]")
expected = Series(["12", NA], dtype="string[pyarrow]")
tm.assert_series_equal(result, expected)