pandas-dev/pandas · error · TypeError

pd.api.extensions.take requires a numpy.ndarray, ExtensionAr

Error message

pd.api.extensions.take requires a numpy.ndarray, ExtensionArray, Index, Series, or NumpyExtensionArray got {type(arr).__name__}.

What it means

Raised by pd.api.extensions.take when the source array is not one of the supported types (numpy.ndarray, ExtensionArray, Index, Series, NumpyExtensionArray). The take routine needs array-like indexing semantics; a plain Python list, dict, or scalar cannot be safely indexed.

Source

Thrown at pandas/core/algorithms.py:1374

    >>> pd.api.extensions.take(np.array([10, 20, 30]), [0, 0, -1])
    array([10, 10, 30])

    Setting ``allow_fill=True`` will place `fill_value` in those positions.

    >>> pd.api.extensions.take(np.array([10, 20, 30]), [0, 0, -1], allow_fill=True)
    array([10., 10., nan])

    >>> pd.api.extensions.take(
    ...     np.array([10, 20, 30]), [0, 0, -1], allow_fill=True, fill_value=-10
    ... )
    array([ 10,  10, -10])
    """
    if not isinstance(
        arr,
        (np.ndarray, ABCExtensionArray, ABCIndex, ABCSeries, ABCNumpyExtensionArray),
    ):
        # GH#52981
        raise TypeError(
            "pd.api.extensions.take requires a numpy.ndarray, ExtensionArray, "
            f"Index, Series, or NumpyExtensionArray got {type(arr).__name__}."
        )

    indices = ensure_platform_int(indices)

    if allow_fill:
        # Pandas style, -1 means NA
        validate_indices(indices, arr.shape[axis])
        # error: Argument 1 to "take_nd" has incompatible type
        # "ndarray[Any, Any] | ExtensionArray | Index | Series"; expected
        # "ndarray[Any, Any]"
        result = take_nd(
            arr,  # type: ignore[arg-type]
            indices,
            axis=axis,
            allow_fill=True,
            fill_value=fill_value,

View on GitHub (pinned to 71959b8cb9)

Solutions

Convert the input to np.ndarray or a pandas Series/Index first.
Use np.take for plain lists, or pd.api.extensions.take(np.asarray(lst), idx).
Validate the type before calling take.

Example fix

# before
pd.api.extensions.take([10, 20, 30], [0, 2])
# after
pd.api.extensions.take(np.array([10, 20, 30]), [0, 2])

Defensive patterns

Strategy: type-guard

Validate before calling

import numpy as np, pandas as pd

def safe_take(arr, indices, **kw):
    if not isinstance(arr, (np.ndarray, pd.Index, pd.Series, pd.api.extensions.ExtensionArray)):
        arr = np.asarray(arr)
    return pd.api.extensions.take(arr, indices, **kw)

Type guard

import numpy as np, pandas as pd

def is_takeable(arr) -> bool:
    return isinstance(arr, (np.ndarray, pd.Index, pd.Series, pd.api.extensions.ExtensionArray))

Prevention

Convert lists to np.ndarray before pd.api.extensions.take.
Use np.take for plain lists when code remapping isn't needed.
Validate the source type at the boundary.

When it happens

Trigger: pd.api.extensions.take([10, 20, 30], [0, 1]) with a Python list; passing a set or tuple; passing a scalar value where an array is required.

Common situations: Using pd.api.extensions.take as a generic indexing helper with native lists; refactors that drop the np.asarray conversion before calling take.

Related errors

AI-assisted analysis of pandas-dev/pandas@71959b8cb9 (2026-08-07). Data as JSON: /api/errors/ec18464f3e38a607. Report an issue: GitHub.