pandas-dev/pandas · error · TypeError

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

Error message

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

What it means

Raised by IntervalArray.overlaps when 'other' is neither a pd.Interval, IntervalArray, nor IntervalIndex. The method only supports a single Interval argument; passing an IntervalArray/Index raises NotImplementedError, and any other type raises this TypeError with the offending type name.

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``.

View on GitHub (pinned to 71959b8cb9)

Solutions

1. Wrap the argument in a single pd.Interval(left, right, closed=...) before calling .overlaps.
2. For element-wise overlap against another array of intervals, currently unsupported — convert to a loop or use IntervalIndex.overlaps if available.
3. For point-in-interval checks use arr.contains(point) instead of overlaps.

Example fix

# before
arr = pd.arrays.IntervalArray.from_tuples([(0, 2), (3, 5)])
arr.overlaps(1)

# after
arr.overlaps(pd.Interval(1, 4, closed='right'))

def overlaps_arg(value, closed):
    if isinstance(value, pd.Interval):
        return value
    if isinstance(value, (tuple, list)) and len(value) == 2:
        return pd.Interval(value[0], value[1], closed=closed)
    raise TypeError('overlaps expects an Interval or a (left, right) pair')

def is_single_interval(value) -> bool:
    return isinstance(value, pd.Interval)

When it happens

Trigger: Calling arr.overlaps(0.5), arr.overlaps([0,1]), or arr.overlaps('a') where arr is an IntervalArray.

Common situations: Assuming overlaps accepts a scalar point (it does not — use .contains for that), passing a list of intervals instead of a single Interval, or forgetting to wrap endpoints.

Related errors

• 'value' should be an interval type, got {type(value)} instea
• can only insert Interval objects and NA into an IntervalArra
• Not supported to convert IntervalArray to '{type}' type
• {func_name} requires a Series, Index, ExtensionArray, np.nda
• func is expected but received {} in **kwargs.

AI-assisted analysis of pandas-dev/pandas@71959b8cb9 (2026-08-07). Data as JSON: /api/errors/6a05ad7f5c9a4442. Report an issue: GitHub.