pandas-dev/pandas · error · ValueError

invalid validation method '{method}'

Error message

invalid validation method '{method}'

What it means

Raised by `CompatValidator.validate` in pandas.compat.numpy.function when the `method` argument is not one of the supported values: `'args'`, `'kwargs'`, or `'both'`. These validators mirror numpy's argument signature validation for methods pandas delegates to numpy (argmin, argmax, etc.). An unknown method indicates a programming error in registering or invoking a validator.

Source

Thrown at pandas/compat/numpy/function.py:93

        fname = self.fname if fname is None else fname
        max_fname_arg_count = (
            self.max_fname_arg_count
            if max_fname_arg_count is None
            else max_fname_arg_count
        )
        method = self.method if method is None else method

        if method == "args":
            validate_args(fname, args, cast("int", max_fname_arg_count), self.defaults)
        elif method == "kwargs":
            validate_kwargs(fname, kwargs, self.defaults)
        elif method == "both":
            validate_args_and_kwargs(
                fname, args, kwargs, cast("int", max_fname_arg_count), self.defaults
            )
        else:
            raise ValueError(f"invalid validation method '{method}'")


ARGMINMAX_DEFAULTS = {"out": None}
validate_argmin = CompatValidator(
    ARGMINMAX_DEFAULTS, fname="argmin", method="both", max_fname_arg_count=1
)
validate_argmax = CompatValidator(
    ARGMINMAX_DEFAULTS, fname="argmax", method="both", max_fname_arg_count=1
)


def process_skipna(
    skipna: bool | ndarray | None, args: tuple[Any, ...]
) -> tuple[bool, tuple[Any, ...]]:
    if isinstance(skipna, ndarray) or skipna is None:
        args = (skipna, *args)
        skipna = True

View on GitHub (pinned to 3b7651241d)

Solutions

1. Use one of the three documented methods: 'args', 'kwargs', or 'both'.
2. If you wrote a custom validator, audit the method value passed to `.validate()`.
3. Search the codebase for `CompatValidator(` to find the offending registration.

Example fix

// before
v = CompatValidator(defaults, fname='op', method='arguments')

// after
v = CompatValidator(defaults, fname='op', method='args')

assert method in {'args', 'kwargs', 'both'}, f'invalid method {method}'

from typing import Literal
ValidMethod = Literal['args', 'kwargs', 'both']

When it happens

Trigger: Constructing a `CompatValidator(..., method='something')` with an invalid method string; calling `validator.validate(..., method='nope')`. This is essentially only reachable from internal pandas code or plugins extending the numpy-compat layer.

Common situations: Typos in validator registration; downstream libraries subclassing the CompatValidator; pandas internal refactor introducing a new method without updating the dispatch.

Related errors

• numpy operations are not valid with groupby. Use .groupby(..
• `axis` must be fewer than the number of dimensions ({ndim})
• by_row={by_row} not allowed
• No accumulation for {func} implemented on BaseMaskedArray
• No masked accumulation defined for dtype {values.dtype.type}

AI-assisted analysis of pandas-dev/pandas@3b7651241d (2026-08-11). Data as JSON: /api/errors/afc2f80189f61eb4. Report an issue: GitHub.