pandas-dev/pandas · error · ValueError

Unable to avoid copy while creating an array as requested.

Error message

Unable to avoid copy while creating an array as requested.

What it means

Raised by PeriodArray.__array__ when the caller requests copy=False (numpy's no-copy contract) but the target dtype is not 'i8' (int64 ordinals). PeriodArray's natural in-memory form is int64 ordinals; any other dtype (object, bool, etc.) requires materializing a new array, so a no-copy guarantee cannot be honoured. With numpy's __array__(copy=...) protocol, copy=False means 'never copy'.

Solutions

1. Allow a copy: np.asarray(period_arr, dtype=object) without copy=False, or pass copy=True.
2. Request the cheap int64 view when you only need ordinals: np.asarray(period_arr, dtype='i8').
3. Update callers that hard-code copy=False to pass copy=None (copy-if-needed) instead.

Example fix

# before
np.asarray(period_arr, dtype=object).copy  # numpy 2 may pass copy=False internally

# after
np.array(period_arr, dtype=object, copy=True)

import numpy as np

def to_numpy_period(period_arr, dtype=None, *, allow_copy=True):
    if not allow_copy and dtype not in (None, 'i8', np.int64):
        raise ValueError('cannot avoid copy for non-int64 dtype')
    return np.array(period_arr, dtype=dtype, copy=True if dtype not in (None, 'i8') else None)

def is_no_copy_safe_dtype(dtype) -> bool:
    import numpy as np
    return dtype in (None, 'i8', np.int64)

try:
    np.asarray(period_arr, dtype=target_dtype)  # may pass copy=False internally on np2
except ValueError as e:
    if 'avoid copy' in str(e):
        np.array(period_arr, dtype=target_dtype, copy=True)
    else:
        raise

When it happens

Trigger: np.asarray(period_arr, dtype=object) when numpy passes copy=False. Internal ops that request a no-copy object/bool view. np.array(period_arr, copy=False, dtype=object) on Python 3.12+ / numpy 2.x where the copy protocol is enforced.

Common situations: numpy 2.x stricter copy semantics; downstream libraries (pyarrow, numba) that pass copy=False; explicit user request for a no-copy conversion to object dtype.

Related errors

• Unable to avoid copy while creating an array as requested.
• Cannot add or subtract timedelta64[ns] dtype from
• Cannot add/subtract timedelta-like from PeriodArray that is…
• cannot convert float NaN to integer
• Cannot return a copy of the target

AI-assisted analysis of pandas-dev/pandas@3b7651241d (2026-08-11). Data as JSON: /api/errors/8ce9e4350845bfbd. Report an issue: GitHub.

Appendix: source

Thrown at pandas/core/arrays/period.py:462

            return None  # type: ignore[return-value]

    def __array__(
        self, dtype: NpDtype | None = None, copy: bool | None = None
    ) -> np.ndarray:
        if dtype == "i8":
            # For NumPy 1.x compatibility we cannot use copy=None.  And
            # `copy=False` has the meaning of `copy=None` here:
            if not copy:
                result = np.asarray(self.asi8, dtype=dtype)
                if self._readonly:
                    result = result.view()
                    result.flags.writeable = False
                return result
            else:
                return np.array(self.asi8, dtype=dtype)

        if copy is False:
            raise ValueError(
                "Unable to avoid copy while creating an array as requested."
            )

        if dtype == bool:
            return ~self._isnan

        # This will raise TypeError for non-object dtypes
        return np.array(list(self), dtype=object)

    def __arrow_array__(self, type=None):
        """
        Convert myself into a pyarrow Array.
        """
        import pyarrow

        from pandas.core.arrays.arrow.extension_types import ArrowPeriodType

        if type is not None:

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