Skip to content

PERF: improve construct_1d_object_array_from_listlike #60461

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 2 commits into from
Dec 3, 2024
Merged

PERF: improve construct_1d_object_array_from_listlike #60461

Changes from 1 commit
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
bda2878
PERF: improve construct_1d_object_array_from_listlike
jorisvandenbossche Dec 1, 2024
86a4b5f
use np.fromiter and update annotation
jorisvandenbossche Dec 3, 2024
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
7 changes: 4 additions & 3 deletions pandas/core/dtypes/cast.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -87,8 +87,8 @@

if TYPE_CHECKING:
from collections.abc import (
Iterable,
Sequence,
Sized,
)

from pandas._typing import (
Expand Down Expand Up @@ -1581,7 +1581,7 @@ def _maybe_box_and_unbox_datetimelike(value: Scalar, dtype: DtypeObj):
return _maybe_unbox_datetimelike(value, dtype)


def construct_1d_object_array_from_listlike(values: Sized) -> np.ndarray:
def construct_1d_object_array_from_listlike(values: Iterable) -> np.ndarray:
"""
Transform any list-like object in a 1-dimensional numpy array of object
dtype.
Expand All @@ -1602,7 +1602,8 @@ def construct_1d_object_array_from_listlike(values: Sized) -> np.ndarray:
# numpy will try to interpret nested lists as further dimensions, hence
# making a 1D array that contains list-likes is a bit tricky:
result = np.empty(len(values), dtype="object")
result[:] = values
for i, obj in enumerate(values):
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Any advantage of using np.fromiter(values, dtype="object", count=len(values))?

Copy link
Member Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Ah, nice, wasn't aware of that. From a quick test that seems to be even a bit faster

result[i] = obj
return result


Expand Down
Loading