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REGR: to_datetime with non-ISO format, float, and nan fails on main #50238

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Merged
merged 1 commit into from
Dec 15, 2022
Merged

REGR: to_datetime with non-ISO format, float, and nan fails on main #50238

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1 change: 1 addition & 0 deletions doc/source/whatsnew/v1.5.3.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,7 @@ Fixed regressions
- Enforced reversion of ``color`` as an alias for ``c`` and ``size`` as an alias for ``s`` in function :meth:`DataFrame.plot.scatter` (:issue:`49732`)
- Fixed regression in :meth:`SeriesGroupBy.apply` setting a ``name`` attribute on the result if the result was a :class:`DataFrame` (:issue:`49907`)
- Fixed performance regression in setting with the :meth:`~DataFrame.at` indexer (:issue:`49771`)
- Fixed regression in :func:`to_datetime` raising ``ValueError`` when parsing array of ``float`` containing ``np.nan`` (:issue:`50237`)
-

.. ---------------------------------------------------------------------------
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12 changes: 11 additions & 1 deletion pandas/_libs/tslibs/strptime.pyx
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Expand Up @@ -42,7 +42,11 @@ from pandas._libs.tslibs.np_datetime cimport (
pydatetime_to_dt64,
)
from pandas._libs.tslibs.timestamps cimport _Timestamp
from pandas._libs.util cimport is_datetime64_object
from pandas._libs.util cimport (
is_datetime64_object,
is_float_object,
is_integer_object,
)

cnp.import_array()

Expand Down Expand Up @@ -185,6 +189,12 @@ def array_strptime(
elif is_datetime64_object(val):
iresult[i] = get_datetime64_nanos(val, NPY_FR_ns)
continue
elif (
(is_integer_object(val) or is_float_object(val))
and (val != val or val == NPY_NAT)
):
iresult[i] = NPY_NAT
Comment on lines +192 to +196
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matches

pandas/pandas/_libs/tslib.pyx

Lines 343 to 346 in 6598797

elif is_integer_object(val) or is_float_object(val):
if val != val or val == NPY_NAT:
iresult[i] = NPY_NAT

continue
else:
val = str(val)

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11 changes: 11 additions & 0 deletions pandas/tests/tools/test_to_datetime.py
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Expand Up @@ -135,6 +135,17 @@ def test_to_datetime_format_YYYYMMDD_with_nat(self, cache):
result = to_datetime(ser2, format="%Y%m%d", cache=cache)
tm.assert_series_equal(result, expected)

def test_to_datetime_format_YYYYMM_with_nat(self, cache):
# https://github.com/pandas-dev/pandas/issues/50237
ser = Series([198012, 198012] + [198101] * 5)
expected = Series(
[Timestamp("19801201"), Timestamp("19801201")] + [Timestamp("19810101")] * 5
)
expected[2] = np.nan
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If np.nan was pd.datetime64('NaT') would this hit the elif block added in this PR (and if so could you add a test for it)?

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hey - no, that would hit this branch:

pandas/pandas/_libs/tslibs/strptime.pyx

Lines 163 to 165 in e8e77c7

elif checknull_with_nat_and_na(val):
iresult[i] = NPY_NAT
continue

, which is covered by a bunch of tests, e.g.

pandas/pandas/tests/tools/test_to_datetime.py

Lines 168 to 189 in e8e77c7

@pytest.mark.parametrize(
"input_s",
[
# Null values with Strings
["19801222", "20010112", None],
["19801222", "20010112", np.nan],
["19801222", "20010112", NaT],
["19801222", "20010112", "NaT"],
# Null values with Integers
[19801222, 20010112, None],
[19801222, 20010112, np.nan],
[19801222, 20010112, NaT],
[19801222, 20010112, "NaT"],
],
)
def test_to_datetime_format_YYYYMMDD_with_none(self, input_s):
# GH 30011
# format='%Y%m%d'
# with None
expected = Series([Timestamp("19801222"), Timestamp("20010112"), NaT])
result = Series(to_datetime(input_s, format="%Y%m%d"))
tm.assert_series_equal(result, expected)

ser[2] = np.nan
result = to_datetime(ser, format="%Y%m", cache=cache)
tm.assert_series_equal(result, expected)

def test_to_datetime_format_YYYYMMDD_ignore(self, cache):
# coercion
# GH 7930
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