(
        arr: ndarray, out: Optional[ndarray] = None, where: Optional[ndarray] = True,
        dtype=None, **kwargs
)
return _parse_float(arr, out, where=where, **kwargs)
Convert elements of the input array using builtin `float`, fill elements
    where conversion failed with NaN.
Convert elements of the input array using builtin `float`, fill elements
    where conversion failed with NaN.
Convert elements of the input array using builtin float fill elements where conversion failed with NaN .
def as_float_or_nan(
        arr: ndarray, out: Optional[ndarray] = None, where: Optional[ndarray] = True,
        dtype=None, **kwargs
) -> ndarray:
    """
    Convert elements of the input array using builtin `float`, fill elements
    where conversion failed with NaN.
    """
    if out is None:
        out = np.full(arr.shape, np.nan, float if dtype is None else dtype)
    if np.issubdtype(arr.dtype, np.inexact) or \
            np.issubdtype(arr.dtype, np.integer):
        np.copyto(out, arr, casting="unsafe", where=where)
        return out
    return _parse_float(arr, out, where=where, **kwargs)
def as_float_or_nan ( arr : ndarray , out : Optional [ ndarray ] = None , where : Optional [ ndarray ] = True , dtype = None , * * kwargs ) -> ndarray : if out is None : out = np . full ( arr . shape , np . nan , float if dtype is None else dtype ) if np . issubdtype ( arr . dtype , np . inexact ) or np . issubdtype ( arr . dtype , np . integer ) : np . copyto ( out , arr , casting = "unsafe" , where = where ) return out return _parse_float ( arr , out , where = where , * * kwargs )