def _memory_usage(self, deep: bool=False) -> int:
    '\n        Memory usage of the values.\n\n        Parameters\n        ----------\n        deep : bool, default False\n            Introspect the data deeply, interrogate\n            `object` dtypes for system-level memory consumption.\n\n        Returns\n        -------\n        bytes used\n\n        See Also\n        --------\n        numpy.ndarray.nbytes : Total bytes consumed by the elements of the\n            array.\n\n        Notes\n        -----\n        Memory usage does not include memory consumed by elements that\n        are not components of the array if deep=False or if used on PyPy\n        '
    if hasattr(self.array, 'memory_usage'):
        return self.array.memory_usage(deep=deep)
    v = self.array.nbytes
    if (deep and is_object_dtype(self) and (not PYPY)):
        values = cast(np.ndarray, self._values)
        v += lib.memory_usage_of_objects(values)
    return v
Memory usage of the values.

Parameters
----------
deep : bool, default False
    Introspect the data deeply, interrogate
    `object` dtypes for system-level memory consumption.

Returns
-------
bytes used

See Also
--------
numpy.ndarray.nbytes : Total bytes consumed by the elements of the
    array.

Notes
-----
Memory usage does not include memory consumed by elements that
are not components of the array if deep=False or if used on PyPy
def _memory_usage(self, deep: bool=False) -> int:
    '\n        Memory usage of the values.\n\n        Parameters\n        ----------\n        deep : bool, default False\n            Introspect the data deeply, interrogate\n            `object` dtypes for system-level memory consumption.\n\n        Returns\n        -------\n        bytes used\n\n        See Also\n        --------\n        numpy.ndarray.nbytes : Total bytes consumed by the elements of the\n            array.\n\n        Notes\n        -----\n        Memory usage does not include memory consumed by elements that\n        are not components of the array if deep=False or if used on PyPy\n        '
    if hasattr(self.array, 'memory_usage'):
        return self.array.memory_usage(deep=deep)
    v = self.array.nbytes
    if (deep and is_object_dtype(self) and (not PYPY)):
        values = cast(np.ndarray, self._values)
        v += lib.memory_usage_of_objects(values)
    return v