pandas-dev/pandas · error · ValueError

Lengths must match to compare

Error message

Lengths must match to compare

What it means

Raised in `_cmp_method` when `other` is list-like (after the deprecation warning for non-castable types) but `len(self) != len(other)`. Comparison broadcasts require equal lengths; pandas refuses to broadcast list-likes of different length against the IntervalArray.

Solutions

1. For scalar comparison, pass a single Interval (not a list): `arr == pd.Interval(0,1)`.
2. Align lengths: filter the comparison operand with the same mask as the array.
3. Broadcast explicitly via a Series reindex if you want position-aligned comparison.

Example fix

# before (len mismatch)
arr == [pd.Interval(0,1)]  # arr has length 3

# after
arr == pd.Interval(0,1)  # scalar broadcast

import pandas as pd
from pandas.api.types import is_list_like

def compare_interval_array(arr, other):
    if is_list_like(other) and len(other) != len(arr):
        if len(other) == 1:
            other = other[0]  # treat as scalar
        else:
            raise ValueError('length mismatch in comparison')
    return arr == other

from pandas.api.types import is_list_like

def length_matches_or_scalar(arr, other) -> bool:
    if not is_list_like(other):
        return True
    return len(other) == len(arr)

try:
    res = arr == other
except ValueError as e:
    if 'Lengths must match to compare' in str(e) and hasattr(other, '__len__') and len(other) == 1:
        res = arr == other[0]
    else:
        raise

When it happens

Trigger: `arr == [pd.Interval(0,1)]` where arr has length 3; comparing against a list/Series shorter or longer than the array.

Common situations: Comparing against a single-element list expecting scalar broadcast (use a bare Interval instead); mismatched filter results; passing a column of a differently-shaped DataFrame.

Related errors

• left and right must have the same length
• Cannot modify read-only array
• closed keyword does not match dtype.closed
• invalid dtype
• left and right must have the same time zone, got

AI-assisted analysis of pandas-dev/pandas@3b7651241d (2026-08-11). Data as JSON: /api/errors/cfd027343b65ede8. Report an issue: GitHub.

Appendix: source

Thrown at pandas/core/arrays/interval.py:719

        self._left[key] = value_left
        self._right[key] = value_right

    def _cmp_method(self, other, op):
        # ensure pandas array for list-like and eliminate non-interval scalars
        if is_list_like(other):
            if not isinstance(
                other, (list, np.ndarray, ExtensionArray)
            ) and not ops.has_castable_attr(other):
                warnings.warn(
                    f"Operation with {type(other).__name__} is deprecated. "
                    "In a future version these will be treated as scalar-like. "
                    "To retain the old behavior, explicitly wrap in a Series "
                    "instead.",
                    Pandas4Warning,
                    stacklevel=find_stack_level(),
                )
            if len(self) != len(other):
                raise ValueError("Lengths must match to compare")
            other = pd_array(other)
        elif not isinstance(other, Interval):
            # non-interval scalar -> no matches
            if other is NA:
                # GH#31882
                from pandas.core.arrays import BooleanArray

                arr = np.empty(self.shape, dtype=bool)
                mask = np.ones(self.shape, dtype=bool)
                return BooleanArray(arr, mask)
            return invalid_comparison(self, other, op)

        # determine the dtype of the elements we want to compare
        if isinstance(other, Interval):
            other_dtype = pandas_dtype("interval")
        elif not isinstance(other.dtype, CategoricalDtype):
            other_dtype = other.dtype
        else:

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