Skip to content
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

BUG: Fix return type of loc/iloc #61054

Open
wants to merge 8 commits into
base: main
Choose a base branch
from
Open

BUG: Fix return type of loc/iloc #61054

Show file tree
Hide file tree
Changes from 4 commits
Commits
Show all changes
8 commits
Select commit Hold shift + click to select a range
5003eaa
Fix loc dtype
sanggon6107 Mar 4, 2025
d4a031b
Modify test_loc_setitem_frame_mixed_labels accordingly
sanggon6107 Mar 4, 2025
2536652
Add test for the linked issue
sanggon6107 Mar 4, 2025
c5a5de1
Fix test_loc_dtype
sanggon6107 Mar 4, 2025
1f529ce
Fix dtype inference
sanggon6107 Mar 6, 2025
ec9fd4f
Merge branch 'main' of https://github.com/sanggon6107/pandas into fix…
sanggon6107 Mar 13, 2025
d2e29c0
Reverse tuple to avoid unintended dtype inference
sanggon6107 Mar 13, 2025
74eb356
Reverse axis order
sanggon6107 Mar 17, 2025
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
11 changes: 10 additions & 1 deletion pandas/core/indexing.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1094,7 +1094,16 @@ def _getitem_lowerdim(self, tup: tuple):
if com.is_null_slice(new_key):
return section
# This is an elided recursive call to iloc/loc
return getattr(section, self.name)[new_key]
out = getattr(section, self.name)[new_key]
# Re-interpret dtype of out.values for loc/iloc[int, list/slice].
# GH60600
if (
i == 0
and isinstance(key, int)
and isinstance(new_key, (list, slice))
):
out = out.infer_objects()
Copy link
Member

Choose a reason for hiding this comment

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

This will infer non-object dtype even on data that is object-dtype, no? I do not think this is the right change.

Copy link
Author

Choose a reason for hiding this comment

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

Thanks @rhshadrach !
I've also confirmed what you've mentioned.

>>>import pandas as pd
>>> df = pd.DataFrame({1: [11, 22], 2: [33, 44], "a": [55, 66]}, dtype=object)

>>>df.loc[0, [1, 2]]
1	11
2	33
Name: 0, dtype: int64

>>>df[[1, 2]].loc[0]
1	11
2	33
Name: 0, dtype: object

I'll do some further investigation to fix this.

return out

raise IndexingError("not applicable")

Expand Down
10 changes: 9 additions & 1 deletion pandas/tests/indexing/test_loc.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -60,6 +60,14 @@ def test_not_change_nan_loc(series, new_series, expected_ser):
tm.assert_frame_equal(df.notna(), ~expected)


def test_loc_dtype():
# GH 60600
df = DataFrame([["a", 1.0, 2.0], ["b", 3.0, 4.0]])
result = df.loc[0, [1, 2]]
expected = df[[1, 2]].loc[0]
tm.assert_series_equal(result, expected)


class TestLoc:
def test_none_values_on_string_columns(self, using_infer_string):
# Issue #32218
Expand Down Expand Up @@ -807,7 +815,7 @@ def test_loc_setitem_frame_mixed_labels(self):

result = df.loc[0, [1, 2]]
expected = Series(
[1, 3], index=Index([1, 2], dtype=object), dtype=object, name=0
[1, 3], index=Index([1, 2], dtype=object), dtype="int64", name=0
)
tm.assert_series_equal(result, expected)

Expand Down
Loading