pandas-dev/pandas · error · ValueError

cannot pass mask for BooleanArray input

Error message

cannot pass mask for BooleanArray input

What it means

Raised by coerce_to_array when values is already a BooleanArray and a separate mask argument is also passed. A BooleanArray already carries its own mask, so supplying another is ambiguous; pandas refuses to silently merge them.

Solutions

1. Drop the mask argument when passing a BooleanArray; rely on its built-in mask.
2. If you need a different mask, extract the underlying data first: boolean_array._data, then pass mask explicitly.
3. Combine masks yourself: combined = boolean_array._mask | your_mask, then build BooleanArray(boolean_array._data, combined).

Example fix

// before
pd.array(existing_bool_array, mask=my_mask, dtype='boolean')
// after
pd.array(existing_bool_array, dtype='boolean')
// or
BooleanArray(existing_bool_array._data, existing_bool_array._mask | my_mask)

if isinstance(values, BooleanArray) and mask is not None:
    raise ValueError('BooleanArray already has a mask; drop the mask argument')

def is_boolean_array(v) -> bool:
    from pandas.core.arrays.boolean import BooleanArray
    return isinstance(v, BooleanArray)

try:
    coerce_to_array(values, mask=mask)
except ValueError as e:
    if 'cannot pass mask' in str(e):
        values, mask = values._data, values._mask
        ...

When it happens

Trigger: Calling pd.array(boolean_array, mask=..., dtype='boolean'), or BooleanArray(values=existing_boolean_array, mask=...). Also reachable via internal coerce_to_array calls when a BooleanArray is forwarded together with a user-supplied mask.

Common situations: Wrapping an existing nullable BooleanArray with an externally computed mask; pipeline code that always passes a mask regardless of input type; refactor that passes BooleanArray where previously an ndarray was used.

Related errors

• values.shape and mask.shape must match
• Need to pass bool-like values
• values should be boolean numpy array. Use the 'pd.array'…
• Cannot cast NaN value to Integer dtype.
• cannot convert float NaN to bool

AI-assisted analysis of pandas-dev/pandas@3b7651241d (2026-08-11). Data as JSON: /api/errors/d4c27a2a2202b24a. Report an issue: GitHub.

Appendix: source

Thrown at pandas/core/arrays/boolean.py:201

    values, mask=None, copy: bool = False
) -> tuple[np.ndarray, np.ndarray]:
    """
    Coerce the input values array to numpy arrays with a mask.

    Parameters
    ----------
    values : 1D list-like
    mask : bool 1D array, optional
    copy : bool, default False
        if True, copy the input

    Returns
    -------
    tuple of (values, mask)
    """
    if isinstance(values, BooleanArray):
        if mask is not None:
            raise ValueError("cannot pass mask for BooleanArray input")
        values, mask = values._data, values._mask
        if copy:
            values = values.copy()
            mask = mask.copy()
        return values, mask

    mask_values = None
    if isinstance(values, np.ndarray) and values.dtype == np.bool_:
        if copy:
            values = values.copy()
    elif isinstance(values, np.ndarray) and values.dtype.kind in "iufcb":
        mask_values = isna(values)

        values_bool = np.zeros(len(values), dtype=bool)
        values_bool[~mask_values] = values[~mask_values].astype(bool)

        if not np.all(
            values_bool[~mask_values].astype(values.dtype) == values[~mask_values]

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