Skip to content

Backport PR #31529 on branch 1.0.x (BUG: Series multiplication with timedelta scalar numexpr path) #31543

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Feb 1, 2020
Merged

Backport PR #31529 on branch 1.0.x (BUG: Series multiplication with timedelta scalar numexpr path) #31543

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
1 change: 1 addition & 0 deletions doc/source/whatsnew/v1.0.1.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -44,6 +44,7 @@ Timezones
Numeric
^^^^^^^
- Bug in dtypes being lost in ``DataFrame.__invert__`` (``~`` operator) with mixed dtypes (:issue:`31183`)
- Bug in :class:`Series` multiplication when multiplying a numeric :class:`Series` with >10000 elements with a timedelta-like scalar (:issue:`31467`)
-

Conversion
Expand Down
5 changes: 3 additions & 2 deletions pandas/core/ops/array_ops.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@

import numpy as np

from pandas._libs import Timestamp, lib, ops as libops
from pandas._libs import Timedelta, Timestamp, lib, ops as libops

from pandas.core.dtypes.cast import (
construct_1d_object_array_from_listlike,
Expand Down Expand Up @@ -184,11 +184,12 @@ def arithmetic_op(
rvalues = maybe_upcast_for_op(rvalues, lvalues.shape)

if should_extension_dispatch(left, rvalues) or isinstance(
rvalues, (ABCTimedeltaArray, ABCDatetimeArray, Timestamp)
rvalues, (ABCTimedeltaArray, ABCDatetimeArray, Timestamp, Timedelta)
):
# TimedeltaArray, DatetimeArray, and Timestamp are included here
# because they have `freq` attribute which is handled correctly
# by dispatch_to_extension_op.
# Timedelta is included because numexpr will fail on it, see GH#31457
res_values = dispatch_to_extension_op(op, lvalues, rvalues)

else:
Expand Down
22 changes: 22 additions & 0 deletions pandas/tests/arithmetic/test_numeric.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -176,6 +176,28 @@ def test_numeric_arr_mul_tdscalar(self, scalar_td, numeric_idx, box):
commute = scalar_td * index
tm.assert_equal(commute, expected)

@pytest.mark.parametrize(
"scalar_td",
[
Timedelta(days=1),
Timedelta(days=1).to_timedelta64(),
Timedelta(days=1).to_pytimedelta(),
],
ids=lambda x: type(x).__name__,
)
def test_numeric_arr_mul_tdscalar_numexpr_path(self, scalar_td, box):
arr = np.arange(2 * 10 ** 4).astype(np.int64)
obj = tm.box_expected(arr, box, transpose=False)

expected = arr.view("timedelta64[D]").astype("timedelta64[ns]")
expected = tm.box_expected(expected, box, transpose=False)

result = obj * scalar_td
tm.assert_equal(result, expected)

result = scalar_td * obj
tm.assert_equal(result, expected)

def test_numeric_arr_rdiv_tdscalar(self, three_days, numeric_idx, box):
index = numeric_idx[1:3]

Expand Down