pandas-dev/pandas · error · TypeError

`other` must be Interval-like, got

Error message

`other` must be Interval-like, got {type(other).__name__}

What it means

Raised in IntervalArray.overlaps when 'other' is neither an IntervalArray/IntervalIndex (which separately raises NotImplementedError) nor a scalar pandas.Interval. Only a scalar Interval is supported as 'other' for vectorized overlap checks.

Solutions

1. Wrap as a scalar Interval: arr.overlaps(pd.Interval(1, 2, closed=arr.closed)).
2. Use arr.contains(point) if you want point-in-interval membership instead of overlap.
3. For interval-vs-interval overlap arrays, iterate or implement manually.

Example fix

// before
arr.overlaps(2)
// after
arr.overlaps(pd.Interval(1, 3, closed=arr.closed))

import pandas as pd

def as_interval_for_overlaps(v, closed):
    if isinstance(v, pd.Interval):
        return v
    raise TypeError('overlaps requires a scalar pandas.Interval')

import pandas as pd

def is_scalar_interval(v):
    return isinstance(v, pd.Interval)

When it happens

Trigger: arr.overlaps(5); arr.overlaps('x'); arr.overlaps([1, 2]); passing a scalar point or a plain tuple/list.

Common situations: Passing a point instead of an interval; confusing overlaps with contains; passing a tuple in place of an Interval.

Related errors

• can only insert Interval objects and NA into an…
• Cannot cast to dtype
• Cannot convert to ; subtypes are incompatible
• Cannot set float NaN to integer-backed IntervalArray
• (...) must be called with a collection of some kind, was…

AI-assisted analysis of pandas-dev/pandas@3b7651241d (2026-08-11). Data as JSON: /api/errors/6a05ad7f5c9a4442. Report an issue: GitHub.

Appendix: source

Thrown at pandas/core/arrays/interval.py:1397

        >>> intervals.overlaps(pd.Interval(0.5, 1.5))
        array([ True,  True, False])

        Intervals that share closed endpoints overlap:

        >>> intervals.overlaps(pd.Interval(1, 3, closed="left"))
        array([ True,  True, True])

        Intervals that only have an open endpoint in common do not overlap:

        >>> intervals.overlaps(pd.Interval(1, 2, closed="right"))
        array([False,  True, False])
        """
        if isinstance(other, (IntervalArray, ABCIntervalIndex)):
            raise NotImplementedError
        if not isinstance(other, Interval):
            msg = f"`other` must be Interval-like, got {type(other).__name__}"
            raise TypeError(msg)

        # equality is okay if both endpoints are closed (overlap at a point)
        op1 = le if (self.closed_left and other.closed_right) else lt
        op2 = le if (other.closed_left and self.closed_right) else lt

        # overlaps is equivalent negation of two interval being disjoint:
        # disjoint = (A.left > B.right) or (B.left > A.right)
        # (simplifying the negation allows this to be done in less operations)
        return op1(self.left, other.right) & op2(other.left, self.right)

    # ---------------------------------------------------------------------

    @property
    def closed(self) -> IntervalClosedType:
        """
        String describing the inclusive side the intervals.

        Either ``left``, ``right``, ``both`` or ``neither``.

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