pandas-dev/pandas · error · TypeError

Not supported to convert IntervalArray to type with differen

Error message

Not supported to convert IntervalArray to type with different 'subtype' ({self.dtype.subtype} vs {type.subtype}) and 'closed' ({self.closed} vs {type.closed}) attributes

What it means

Raised by IntervalArray.__arrow_array__ when the caller passes an explicit target pyarrow type that is an ArrowIntervalType but does not equal the array's natural interval_type — i.e. its subtype or closed differs from the source. The library refuses to silently reinterpret closure or precision during conversion.

Source

Thrown at pandas/core/arrays/interval.py:1625

        )
        mask = self.isna()
        if mask.any():
            # if there are missing values, set validity bitmap also on the array level
            null_bitmap = pyarrow.array(~mask).buffers()[1]
            storage_array = pyarrow.StructArray.from_buffers(
                storage_array.type,
                len(storage_array),
                [null_bitmap],
                children=[storage_array.field(0), storage_array.field(1)],
            )

        if type is not None:
            if type.equals(interval_type.storage_type):
                return storage_array
            elif isinstance(type, ArrowIntervalType):
                # ensure we have the same subtype and closed attributes
                if not type.equals(interval_type):
                    raise TypeError(
                        "Not supported to convert IntervalArray to type with "
                        f"different 'subtype' ({self.dtype.subtype} vs {type.subtype}) "
                        f"and 'closed' ({self.closed} vs {type.closed}) attributes"
                    )
            else:
                raise TypeError(
                    f"Not supported to convert IntervalArray to '{type}' type"
                )

        return pyarrow.ExtensionArray.from_storage(interval_type, storage_array)

    def to_tuples(self, na_tuple: bool = True) -> np.ndarray:
        """
        Return an ndarray (if self is IntervalArray) or Index \
        (if self is IntervalIndex) of tuples of the form (left, right).

        This method extracts the bounds of each interval as a tuple,
        useful for iteration or conversion to other data structures.

View on GitHub (pinned to 71959b8cb9)

Solutions

1. Align the target ArrowIntervalType's subtype and closed with the source: pa.array(arr, type=ArrowIntervalType(pa.from_numpy_dtype(arr.dtype.subtype), arr.closed)).
2. Drop the explicit type argument and let pandas infer it.
3. Re-cast arr (arr.astype / arr.set_closed) so it matches the target schema before conversion.

Example fix

# before
from pandas.core.arrays.arrow.extension_types import ArrowIntervalType
target = ArrowIntervalType(pa.int32(), 'left')
pa.array(arr, type=target)  # arr is interval[int64, right]

# after
target = ArrowIntervalType(pa.int64(), 'right')
pa.array(arr, type=target)

import pyarrow as pa
from pandas.core.arrays.arrow.extension_types import ArrowIntervalType

def matching_arrow_type(arr):
    subtype = pa.from_numpy_dtype(arr.dtype.subtype)
    return ArrowIntervalType(subtype, arr.closed)

def arrow_type_matches(arr, target) -> bool:
    import pyarrow as pa
    from pandas.core.arrays.arrow.extension_types import ArrowIntervalType
    if not isinstance(target, ArrowIntervalType):
        return False
    return (target.subtype == pa.from_numpy_dtype(arr.dtype.subtype)
            and target.closed == arr.closed)

When it happens

Trigger: Calling pa.array(arr, type=ArrowIntervalType(pa.int32(), 'left')) on an array whose subtype is int64 and closed='right', or any mismatched (subtype, closed) pair.

Common situations: Schema-driven ETL pipelines that pass a fixed ArrowIntervalType without aligning it to the source, or migrations that change closure conventions.

Related errors

• Conversion to arrow with subtype '{self.dtype.subtype}' is n
• Not supported to convert IntervalArray to '{type}' type
• Invalid side: {side}. Side must be one of 'left', 'right', '
• invalid normalization form
• replace is not supported with a re.Pattern, callable repl, c

AI-assisted analysis of pandas-dev/pandas@71959b8cb9 (2026-08-07). Data as JSON: /api/errors/000b116235278e0d. Report an issue: GitHub.