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BUG: stack with empty level list #60826

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Merged
merged 4 commits into from
Feb 4, 2025
Merged

BUG: stack with empty level list #60826

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7fb30fc
return early if set_levels is empty
quangngd Feb 2, 2025
d94258d
add test
quangngd Feb 2, 2025
9a5832c
add whatsnew
quangngd Feb 4, 2025
a0df9c4
check empty before make set
quangngd Feb 4, 2025
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2 changes: 2 additions & 0 deletions pandas/core/reshape/reshape.py
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Original file line number Diff line number Diff line change
Expand Up @@ -930,6 +930,8 @@ def stack_v3(frame: DataFrame, level: list[int]) -> Series | DataFrame:
if frame.columns.nunique() != len(frame.columns):
raise ValueError("Columns with duplicate values are not supported in stack")
set_levels = set(level)
if not len(set_levels):
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@mroeschke mroeschke Feb 3, 2025

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Nit: Could you just check if not level: before the set call?

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@quangngd quangngd Feb 4, 2025

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updated

return frame
stack_cols = frame.columns._drop_level_numbers(
[k for k in range(frame.columns.nlevels - 1, -1, -1) if k not in set_levels]
)
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19 changes: 19 additions & 0 deletions pandas/tests/frame/test_stack_unstack.py
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Expand Up @@ -1452,6 +1452,25 @@ def test_stack_empty_frame(dropna, future_stack):
tm.assert_series_equal(result, expected)


@pytest.mark.filterwarnings("ignore:The previous implementation of stack is deprecated")
@pytest.mark.parametrize("dropna", [True, False, lib.no_default])
def test_stack_empty_level(dropna, future_stack, int_frame):
# GH 60740
if future_stack and dropna is not lib.no_default:
with pytest.raises(ValueError, match="dropna must be unspecified"):
DataFrame(dtype=np.int64).stack(dropna=dropna, future_stack=future_stack)
else:
expected = int_frame
result = int_frame.copy().stack(
level=[], dropna=dropna, future_stack=future_stack
)
tm.assert_frame_equal(result, expected)

expected = DataFrame()
result = DataFrame().stack(level=[], dropna=dropna, future_stack=future_stack)
tm.assert_frame_equal(result, expected)


@pytest.mark.filterwarnings("ignore:The previous implementation of stack is deprecated")
@pytest.mark.parametrize("dropna", [True, False, lib.no_default])
@pytest.mark.parametrize("fill_value", [None, 0])
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