    >>> df_copy = df.copy()
        >>> df_copy.iloc[0, 0] = pd.NA
        >>> df_copy.map(lambda x: len(str(x)), na_action='ignore')
             0  1
        0  NaN  4
        1  5.0  5

        Note that a vectorized version of `func` often exists, which will
        be much faster. You could square each number elementwise.

        >>> df.map(lambda x: x**2)
                   0          1
        0   1.000000   4.494400
        1  11.262736  20.857489

        But it's better to avoid map in that case.

        >>> df ** 2
                   0          1
        0   1.000000   4.494400
        1  11.262736  20.857489
        >