pandas-dev/pandas · error · TypeError

'{type(self).__name__}' with dtype {self.dtype} does not sup

Error message

'{type(self).__name__}' with dtype {self.dtype} does not support operation '{name}'

What it means

Raised in _reduce when `getattr(pyarrow.compute, name)` returns None — i.e. the installed pyarrow version does not expose the requested reduction function at all. This is a static capability miss, not a runtime kernel miss.

Source

Thrown at pandas/core/arrays/arrow/array.py:2574

                )[0]
                return pc.binary_join(data_list, "")
        elif name in ["argmin", "argmax"]:
            return super()._reduce(name, skipna=skipna, **kwargs)

        else:
            pyarrow_name = {
                "median": "quantile",
                "prod": "product",
                "std": "stddev",
                "var": "variance",
                "kurt": "kurtosis",
            }.get(name, name)
            # error: Incompatible types in assignment
            # (expression has type "Optional[Any]", variable has type
            # "Callable[[Any, Any, KwArg(Any)], Any]")
            pyarrow_meth = getattr(pc, pyarrow_name, None)  # type: ignore[assignment]
            if pyarrow_meth is None:
                raise TypeError(
                    f"'{type(self).__name__}' with dtype {self.dtype} "
                    f"does not support operation '{name}'"
                )

        # GH51624: pyarrow defaults to min_count=1, pandas behavior is min_count=0
        if name in ["any", "all", "sum", "prod"] and "min_count" not in kwargs:
            kwargs["min_count"] = 0
        elif name == "median":
            # GH 52679: Use quantile instead of approximate_median
            kwargs["q"] = 0.5
        elif name in ["std", "var", "sem"] and "ddof" not in kwargs:
            # pyarrow defaults to ddof=0, pandas behavior is ddof=1
            kwargs["ddof"] = 1
        elif name in ["skew", "kurt"] and "biased" not in kwargs:
            kwargs["biased"] = False

        try:
            result = pyarrow_meth(data_to_reduce, skip_nulls=skipna, **kwargs)

View on GitHub (pinned to 71959b8cb9)

Solutions

1. Upgrade pyarrow to a version that implements the function: `pip install -U pyarrow`.
2. Fall back to numpy-based reduction by converting: `s.to_numpy().kurt()`.
3. Pick a supported reduction for the current pyarrow version.

Example fix

// before
# pyarrow too old
pd.Series([1, 2, 3], dtype="int64[pyarrow]").kurt()

// after
pip install -U 'pyarrow>=14'
pd.Series([1, 2, 3], dtype="int64[pyarrow]").kurt()

import pyarrow as pa
import pyarrow.compute as pc

def supports_reduction(name) -> bool:
    return getattr(pc, {"median": "quantile", "prod": "product", "std": "stddev", "var": "variance", "kurt": "kurtosis"}.get(name, name), None) is not None

def pyarrow_has_reduction(name) -> bool:
    import pyarrow.compute as pc
    mapped = {"median": "quantile", "prod": "product", "std": "stddev", "var": "variance", "kurt": "kurtosis"}.get(name, name)
    return hasattr(pc, mapped)

try:
    s.kurt()
except TypeError as e:
    if "does not support operation" in str(e) and "pyarrow version" not in str(e):
        s.to_numpy().kurt()  # fall back to numpy
    else:
        raise

When it happens

Trigger: Calling a reduction (e.g. `Series.kurt`, `.skew`, `.sem`) on an ArrowExtensionArray where the running pyarrow version lacks that compute function entirely.

Common situations: Older pyarrow installs (e.g. pinned at <14) lacking newer compute functions like `kurtosis`, or a CI image with an outdated pyarrow.

Related errors

• '{type(self).__name__}' with dtype {self.dtype} does not sup
• Length of 'value' does not match. Got ({len(value)}) expect
• Invalid value '{value!s}' for dtype '{self.dtype}'
• {type(self)} does not support reshape as backed by a 1D pyar
• searchsorted requires array to be sorted, which is impossibl

AI-assisted analysis of pandas-dev/pandas@71959b8cb9 (2026-08-07). Data as JSON: /api/errors/3d0611b48356b510. Report an issue: GitHub.