pandas-dev/pandas · error · TypeError

Conversion to arrow with subtype

Error message

Conversion to arrow with subtype '{self.dtype.subtype}' is not supported

What it means

Raised in IntervalArray.__arrow_array__ when pyarrow.from_numpy_dtype(self.dtype.subtype) raises TypeError - the interval subtype has no Arrow equivalent (e.g., object subtype, or an unsupported/unusual dtype). The conversion cannot proceed without a mappable Arrow storage type.

Solutions

Cast the IntervalArray to a supported numeric/datetime subtype before arrow conversion: arr.astype('interval[int64]').
Inspect arr.dtype.subtype and convert endpoints to a pyarrow-friendly numpy type first.
Avoid object-backed intervals; build intervals from typed endpoint arrays.

Example fix

// before
pyarrow.array(obj_arr)
// after
arr = obj_arr.astype('interval[int64]')
pyarrow.array(arr)

Defensive patterns

Strategy: validation

Validate before calling

import pyarrow

def arrow_subtype_supported(arr):
    try:
        pyarrow.from_numpy_dtype(arr.dtype.subtype)
        return True
    except TypeError:
        return False

def to_arrow_safe(arr):
    if not arrow_subtype_supported(arr):
        arr = arr.astype('interval[int64]')
    return pyarrow.array(arr)

Try / catch

try:
    pa_arr = pyarrow.array(arr)
except TypeError as e:
    if 'subtype' in str(e) and 'not supported' in str(e):
        arr = arr.astype('interval[int64]')
        pa_arr = pyarrow.array(arr)
    else:
        raise

Prevention

Ensure interval endpoints are numeric or datetime before arrow conversion.
Avoid object-backed intervals; construct from typed endpoint arrays.
Inspect arr.dtype.subtype before pyarrow.array/ to_parquet.

When it happens

Trigger: pyarrow.array(interval_arr) where the subtype is object or unsupported; arr.__arrow_array__() on intervals whose endpoints inferred object dtype.

Common situations: Mixed-type endpoint data inferring object dtype; custom or unusual subtypes; passing intervals through pyarrow conversion (e.g., to_parquet).

Related errors

AI-assisted analysis of pandas-dev/pandas@3b7651241d (2026-08-11). Data as JSON: /api/errors/ee20dc3ce1d2e40b. Report an issue: GitHub.

Appendix: source

Thrown at pandas/core/arrays/interval.py:1596

        for i, left_value in enumerate(left):
            if mask[i]:
                result[i] = np.nan
            else:
                result[i] = Interval(left_value, right[i], closed)
        return result

    def __arrow_array__(self, type=None):
        """
        Convert myself into a pyarrow Array.
        """
        import pyarrow

        from pandas.core.arrays.arrow.extension_types import ArrowIntervalType

        try:
            subtype = pyarrow.from_numpy_dtype(self.dtype.subtype)
        except TypeError as err:
            raise TypeError(
                f"Conversion to arrow with subtype '{self.dtype.subtype}' "
                "is not supported"
            ) from err
        interval_type = ArrowIntervalType(subtype, self.closed)
        storage_array = pyarrow.StructArray.from_arrays(
            [
                pyarrow.array(self._left, type=subtype, from_pandas=True),
                pyarrow.array(self._right, type=subtype, from_pandas=True),
            ],
            names=["left", "right"],
        )
        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),

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