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BUG: Fix bug in to_datetime that occasionally throws FloatingPointErr… #61022

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Merged
merged 2 commits into from
Mar 2, 2025
Merged

BUG: Fix bug in to_datetime that occasionally throws FloatingPointErr… #61022

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767cc43
BUG: Fix bug in to_datetime that occasionally throws FloatingPointErr…
snitish Mar 1, 2025
d2dc204
Address review comment
snitish Mar 1, 2025
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v3.0.0.rst
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Expand Up @@ -649,6 +649,7 @@ Datetimelike
- Bug in :meth:`DatetimeIndex.union` and :meth:`DatetimeIndex.intersection` when ``unit`` was non-nanosecond (:issue:`59036`)
- Bug in :meth:`Series.dt.microsecond` producing incorrect results for pyarrow backed :class:`Series`. (:issue:`59154`)
- Bug in :meth:`to_datetime` not respecting dayfirst if an uncommon date string was passed. (:issue:`58859`)
- Bug in :meth:`to_datetime` on float array with missing values throwing ``FloatingPointError`` (:issue:`58419`)
- Bug in :meth:`to_datetime` on float32 df with year, month, day etc. columns leads to precision issues and incorrect result. (:issue:`60506`)
- Bug in :meth:`to_datetime` reports incorrect index in case of any failure scenario. (:issue:`58298`)
- Bug in :meth:`to_datetime` wrongly converts when ``arg`` is a ``np.datetime64`` object with unit of ``ps``. (:issue:`60341`)
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1 change: 1 addition & 0 deletions pandas/_libs/tslibs/conversion.pyx
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Expand Up @@ -142,6 +142,7 @@ def cast_from_unit_vectorized(
for i in range(len(values)):
if is_nan(values[i]):
base[i] = NPY_NAT
frac[i] = 0
else:
base[i] = <int64_t>values[i]
frac[i] = values[i] - base[i]
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9 changes: 9 additions & 0 deletions pandas/tests/tools/test_to_datetime.py
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Expand Up @@ -2520,6 +2520,15 @@ def test_to_datetime_overflow(self):
with pytest.raises(OutOfBoundsTimedelta, match=msg):
date_range(start="1/1/1700", freq="B", periods=100000)

def test_to_datetime_float_with_nans_floating_point_error(self):
# GH#58419
ser = Series([np.nan] * 1000 + [1712219033.0], dtype=np.float64)
result = to_datetime(ser, unit="s", errors="coerce")
expected = Series(
[NaT] * 1000 + [Timestamp("2024-04-04 08:23:53")], dtype="datetime64[ns]"
)
tm.assert_series_equal(result, expected)

def test_string_invalid_operation(self, cache):
invalid = np.array(["87156549591102612381000001219H5"], dtype=object)
# GH #51084
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