pandas-dev/pandas · error · ValueError

Operation does not support axis=1

Error message

Operation {func} does not support axis=1

What it means

Raised in `apply_str` (the string-dispatch path) when the user passes `axis=1` to a method that either has no `axis` parameter on its signature or is explicitly excluded (`corrwith`, `skew`). Pandas inspects the method's fullargspec; if `axis` is not accepted (or the method is on the exclusion list) it cannot honor `axis=1` and raises immediately rather than silently running along the wrong axis.

Solutions

  1. Drop the `axis=1` argument for methods that only operate column-wise (corrwith, skew without axis support).
  2. For row-wise skew, call `df.skew(axis=1)` directly on the DataFrame instead of through apply.
  3. If you need a row-wise custom op, pass a callable (not a string) to `df.apply(..., axis=1)`.

Example fix

// before
df.apply('skew', axis=1)
// after
df.skew(axis=1)
Defensive patterns

Strategy: validation

Validate before calling

AXIS1_BLOCKED = {'corrwith', 'skew'}
def apply_str_axis1_safe(df, func, axis=0):
    import inspect
    if axis == 1 and isinstance(func, str):
        method = getattr(df, func, None)
        if method is None:
            raise ValueError(f'{func} not found on DataFrame')
        sig = inspect.getfullargspec(method)
        arg_names = (*sig.args, *sig.kwonlyargs)
        if 'axis' not in arg_names or func in AXIS1_BLOCKED:
            raise ValueError(f'{func} does not support axis=1; call directly or drop axis')
    return df.apply(func, axis=axis)

Type guard

def str_method_supports_axis1(df, func) -> bool:
    import inspect
    if func in ('corrwith', 'skew'):
        return False
    m = getattr(df, func, None)
    if not callable(m):
        return False
    spec = inspect.getfullargspec(m)
    return 'axis' in (*spec.args, *spec.kwonlyargs)

Try / catch

try:
    out = df.apply(func, axis=1)
except ValueError as e:
    if 'does not support axis=1' in str(e):
        out = getattr(df, func)()  # fall back to default axis
    else:
        raise

Prevention

When it happens

Trigger: Calls like `df.apply('corrwith', axis=1)`, `df.apply('skew', axis=1)`, or `df.apply('<method_without_axis_param>', axis=1)`. Common with frame.transform('method', axis=1) routing through the same path.

Common situations: Passing axis=1 globally to a pipeline that calls apply with method-name strings; misremembering which stats methods support row-wise operation; migrating code from axis=0 default to row-wise and assuming all methods comply.

Related errors

AI-assisted analysis of pandas-dev/pandas@3b7651241d (2026-08-11). Data as JSON: /api/errors/1adcd6b541890744. Report an issue: GitHub.

Appendix: source

Thrown at pandas/core/apply.py:737

        obj = self.obj

        from pandas.core.groupby.generic import (
            DataFrameGroupBy,
            SeriesGroupBy,
        )

        # Support for `frame.transform('method')`
        # Some methods (shift, etc.) require the axis argument, others
        # don't, so inspect and insert if necessary.
        method = getattr(obj, func, None)
        if callable(method):
            sig = inspect.getfullargspec(method)
            arg_names = (*sig.args, *sig.kwonlyargs)
            if self.axis != 0 and (
                "axis" not in arg_names or func in ("corrwith", "skew")
            ):
                raise ValueError(f"Operation {func} does not support axis=1")
            if "axis" in arg_names and not isinstance(
                obj, (SeriesGroupBy, DataFrameGroupBy)
            ):
                self.kwargs["axis"] = self.axis
        return self._apply_str(obj, func, *self.args, **self.kwargs)

    def apply_list_or_dict_like(self) -> DataFrame | Series:
        """
        Compute apply in case of a list-like or dict-like.

        Returns
        -------
        result: Series, DataFrame, or None
            Result when self.func is a list-like or dict-like, None otherwise.
        """

        if self.engine == "numba":
            raise NotImplementedError(

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