pandas-dev/pandas · error · ValueError

check_like must be False if check_index is False

Error message

check_like must be False if check_index is False

What it means

Raised by assert_series_equal (asserters.py:1115-1116) when the caller passes check_like=True together with check_index=False. check_like instructs the assertion to reindex/reorder before comparing (which requires reading the index), so disabling index checking makes check_like meaningless and contradictory — hence the explicit ValueError.

Source

Thrown at pandas/_testing/asserters.py:1116

        right_index_dtypes = (
            [right.index.dtype]
            if right.index.nlevels == 1
            else cast("MultiIndex", right.index).dtypes
        )
        check_exact_index = all(
            dtype.kind in "iu" for dtype in left_index_dtypes
        ) or all(dtype.kind in "iu" for dtype in right_index_dtypes)
    elif check_exact is lib.no_default:
        check_exact = False
        check_exact_index = False
    else:
        check_exact_index = check_exact

    rtol = rtol if rtol is not lib.no_default else 1.0e-5
    atol = atol if atol is not lib.no_default else 1.0e-8

    if not check_index and check_like:
        raise ValueError("check_like must be False if check_index is False")

    # instance validation
    _check_isinstance(left, right, Series)

    if check_series_type:
        assert_class_equal(left, right, obj=obj)

    # length comparison
    if len(left) != len(right):
        msg1 = f"{len(left)}, {left.index}"
        msg2 = f"{len(right)}, {right.index}"
        raise_assert_detail(obj, "Series length are different", msg1, msg2)

    if check_flags:
        assert left.flags == right.flags, f"{left.flags!r} != {right.flags!r}"

    if check_index:
        # GH #38183

View on GitHub (pinned to 71959b8cb9)

Solutions

1. If you want to compare values ignoring index order, keep check_index=True (default) and set check_like=True.
2. If you truly want to skip the index entirely, set check_like=False (or omit it).
3. Re-read the assert_series_equal docstring for the precise meaning of each flag combination.

Example fix

# before
assert_series_equal(s1, s2, check_index=False, check_like=True)

# after — compare values ignoring index order
assert_series_equal(s1, s2, check_like=True)
# or — skip index entirely
assert_series_equal(s1, s2, check_index=False, check_like=False)

check_index = True  # or False
check_like = True   # or False
if not check_index and check_like:
    raise ValueError('check_like=True requires check_index=True')
assert_series_equal(left, right, check_index=check_index, check_like=check_like)

When it happens

Trigger: Calling assert_series_equal(left, right, check_index=False, check_like=True). check_like=True normally means 'ignore index order by reindexing right onto left', which is nonsensical when the index is not being checked at all.

Common situations: Layering multiple check_* flags from different test helpers without reconciling them; copy-pasting an assert call and toggling check_index=False to silence an index mismatch, while check_like=True was already set.

Related errors

• {cls_name} Expected type {cls}, found {type(left)} instead
• {cls_name} Expected type {cls}, found {type(right)} instead
• [datetimelike_compat=True] {left._values} is not equal to {r
• {obj} are different {message}
• {left_base!r} is not {right_base!r}

AI-assisted analysis of pandas-dev/pandas@71959b8cb9 (2026-08-07). Data as JSON: /api/errors/3ca10c35cef7500f. Report an issue: GitHub.