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BUG: DTI-datetime_scalar preserve freq #48818

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Merged
merged 3 commits into from
Sep 28, 2022
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BUG: DTI-datetime_scalar preserve freq #48818

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d93dd6d
BUG: DTI-datetime_scalar preserve freq
jbrockmendel Sep 27, 2022
f4d5328
GH ref
jbrockmendel Sep 27, 2022
4339bd5
add xfail test across DST boundary
jbrockmendel Sep 28, 2022
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v1.6.0.rst
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Expand Up @@ -165,6 +165,7 @@ Datetimelike
^^^^^^^^^^^^
- Bug in :func:`pandas.infer_freq`, raising ``TypeError`` when inferred on :class:`RangeIndex` (:issue:`47084`)
- Bug in :class:`DatetimeIndex` constructor failing to raise when ``tz=None`` is explicitly specified in conjunction with timezone-aware ``dtype`` or data (:issue:`48659`)
- Bug in subtracting a ``datetime`` scalar from :class:`DatetimeIndex` failing to retain the original ``freq`` attribute (:issue:`48818`)

Timedelta
^^^^^^^^^
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11 changes: 10 additions & 1 deletion pandas/core/arrays/datetimelike.py
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Expand Up @@ -1186,7 +1186,16 @@ def _sub_datetimelike_scalar(self, other: datetime | np.datetime64):

i8 = self.asi8
result = checked_add_with_arr(i8, -other.value, arr_mask=self._isnan)
return result.view("timedelta64[ns]")
res_m8 = result.view(f"timedelta64[{self._unit}]")

new_freq = None
if isinstance(self.freq, Tick):
# adding a scalar preserves freq
new_freq = self.freq

from pandas.core.arrays import TimedeltaArray

return TimedeltaArray._simple_new(res_m8, dtype=res_m8.dtype, freq=new_freq)

@final
def _sub_datetime_arraylike(self, other):
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9 changes: 9 additions & 0 deletions pandas/tests/indexes/datetimes/test_datetime.py
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Expand Up @@ -17,6 +17,15 @@


class TestDatetimeIndex:
def test_sub_datetime_preserves_reso(self, tz_naive_fixture):
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Could you add a test where this goes over a DST transition?

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good catch. when we cross a DST transition, dti.freq is actually wrong bc of the (deprecated) kludge in generate_range. As a result, inheriting the freq is incorrect in this case. But it will return to being correct once the deprecation is enforced.

i think the thing to do is add the test and xfail it

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test added (and xfailed) + green

# GH#48818
dti = date_range("2016-01-01", periods=12, tz=tz_naive_fixture)

res = dti - dti[0]
expected = pd.timedelta_range("0 Days", "11 Days")
tm.assert_index_equal(res, expected)
assert res.freq == expected.freq

def test_time_overflow_for_32bit_machines(self):
# GH8943. On some machines NumPy defaults to np.int32 (for example,
# 32-bit Linux machines). In the function _generate_regular_range
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