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DOC: definition of a scalar in rich comparison methods #62191

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f60bf95
doc: definition of a scalar
cmp0xff Aug 25, 2025
288f06e
fix(comment): https://github.com/pandas-dev/pandas/pull/62191#discuss…
cmp0xff Aug 26, 2025
414ffe5
Merge branch 'main' into hotfix/cmp0xff/62063-def-of-scalar
cmp0xff Aug 26, 2025
470d093
fix(comment): https://github.com/pandas-dev/pandas/issues/62063#issue…
cmp0xff Aug 27, 2025
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Merge branch 'main' into hotfix/cmp0xff/62063-def-of-scalar
cmp0xff Aug 27, 2025
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fix: ruff
cmp0xff Aug 27, 2025
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Merge branch 'main' into hotfix/cmp0xff/62063-def-of-scalar
cmp0xff Aug 27, 2025
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Merge branch 'main' into hotfix/cmp0xff/62063-def-of-scalar
cmp0xff Sep 7, 2025
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fix: comments
cmp0xff Sep 7, 2025
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Merge branch 'main' into hotfix/cmp0xff/62063-def-of-scalar
cmp0xff Sep 24, 2025
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6 changes: 4 additions & 2 deletions pandas/core/ops/docstrings.py
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Original file line number Diff line number Diff line change
Expand Up @@ -435,8 +435,10 @@ def make_flex_doc(op_name: str, typ: str) -> str:

Parameters
----------
other : Series or scalar value
The second operand in this operation.
other : object
When a Series is provided, will align on indexes. For all other types,
will behave the same as ``==`` but with possibly different results due
to the other arguments.
level : int or name
Broadcast across a level, matching Index values on the
passed MultiIndex level.
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18 changes: 12 additions & 6 deletions pandas/core/series.py
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Expand Up @@ -6072,8 +6072,10 @@ def eq(

Parameters
----------
other : Series or scalar value
The second operand in this operation.
other : object
When a Series is provided, will align on indexes. For all other types,
will behave the same as ``==`` but with possibly different results due
to the other arguments.
level : int or name
Broadcast across a level, matching Index values on the
passed MultiIndex level.
Expand Down Expand Up @@ -6141,8 +6143,10 @@ def le(self, other, level=None, fill_value=None, axis: Axis = 0) -> Series:

Parameters
----------
other : Series or scalar value
The second operand in this operation.
other : object
When a Series is provided, will align on indexes. For all other types,
will behave the same as ``==`` but with possibly different results due
to the other arguments.
level : int or name
Broadcast across a level, matching Index values on the
passed MultiIndex level.
Expand Down Expand Up @@ -6213,8 +6217,10 @@ def ge(self, other, level=None, fill_value=None, axis: Axis = 0) -> Series:

Parameters
----------
other : Series or scalar value
The second operand in this operation.
other : object
When a Series is provided, will align on indexes. For all other types,
will behave the same as ``==`` but with possibly different results due
to the other arguments.
level : int or name
Broadcast across a level, matching Index values on the
passed MultiIndex level.
Expand Down
49 changes: 49 additions & 0 deletions pandas/tests/series/methods/test_compare.py
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@@ -1,3 +1,8 @@
from enum import (
Enum,
auto,
)

import numpy as np
import pytest

Expand Down Expand Up @@ -138,3 +143,47 @@ def test_compare_datetime64_and_string():
tm.assert_series_equal(result_eq1, expected_eq)
tm.assert_series_equal(result_eq2, expected_eq)
tm.assert_series_equal(result_neq, expected_neq)


def test_eq_objects():
"""Test eq with Enum and List elements"""
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Can you make this a comment; our tests (mostly) do not utilize docstrings.

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Also add a reference to the PR as a comment here:

# GH#62191

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36bfdef


class Thing(Enum):
FIRST = auto()
SECOND = auto()

left = pd.Series([Thing.FIRST, Thing.SECOND])
tm.assert_series_equal(left.eq(Thing.FIRST), left == Thing.FIRST)
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Can you setup the asserts in the following pattern:

expected = ...
result = ...
tm.assert_series_equal(result, expected)

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36bfdef


py_l = [Thing.FIRST, Thing.SECOND]
tm.assert_series_equal(left.eq(py_l), left == py_l)

np_a = np.asarray(py_l)
tm.assert_series_equal(left.eq(np_a), left == np_a)

pd_s = pd.Series(py_l)
tm.assert_series_equal(left.eq(pd_s), left == pd_s)

left_non_scalar = pd.Series([[1, 2], [3, 4]])
with pytest.raises(AssertionError):
tm.assert_series_equal(left_non_scalar.eq([1, 2]), pd.Series([True, False]))
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What is the purpose of checking that the result does not equal?

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It was discussed that eq does not work properly when the elements of a Series is a list or other array-like objects. I wanted to verify this point, and show that the result is not as one would expected.

If this is not necessary, I can remove it.

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I'm okay with leaving something akin to this operation, but you should assert the result that pandas gives back. It's better to check two things are equal than not equal (as it's a stronger test).



def test_eq_with_index():
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Same requests with this test.

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You mean removing the whole test test_eq_with_index?

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No, the requests in the test above also to be done in this test as well.

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Hi @rhshadrach , from the context I am not too sure which lines to be remove. Could you be more specific and quote the line numbers? Thanks.

I have checked

    left_non_scalar = pd.Series([[1, 2], [3, 4]])
    result_non_scalar = left_non_scalar.eq([1, 2])
    expected_would_be = pd.Series([True, False])
    with pytest.raises(AssertionError):
        tm.assert_series_equal(result_non_scalar, expected_would_be)

which seems to have analogy with the lines I removed earlier. That seems to be a new test to me.

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The request that was made above which hasn't been applied here is to make all lines tm.assert_series_equal(result, expected) (#62191 (comment))

"""Test eq with non-trivial indices"""
left = pd.Series([1, 2], index=[1, 0])

py_l = [1, 2]
tm.assert_series_equal(left.eq(py_l), left == py_l)

np_a = np.asarray(py_l)
tm.assert_series_equal(left.eq(np_a), left == np_a)

pd_s = pd.Series(py_l)
tm.assert_series_equal(left.eq(pd_s), pd.Series([False, False]))

match = r"Can only compare identically-labeled Series objects"
with pytest.raises(ValueError, match=match):
_ = left == pd_s
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This test does not belong here and is already tested for elsewhere; can you remove.

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36bfdef


tm.assert_series_equal(left.eq(pd.Series([2, 1])), pd.Series([True, True]))
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