pandas.Series.memory_usage

Series.memory_usage(self, index=True, deep=False) [source]

Return the memory usage of the Series.

The memory usage can optionally include the contribution of the index and of elements of object dtype.

Parameters:	index : bool, default True Specifies whether to include the memory usage of the Series index. deep : bool, default False If True, introspect the data deeply by interrogating object dtypes for system-level memory consumption, and include it in the returned value.
Returns:	int Bytes of memory consumed.

See also

numpy.ndarray.nbytes

Total bytes consumed by the elements of the array.

DataFrame.memory_usage

Bytes consumed by a DataFrame.

Examples

>>> s = pd.Series(range(3))
>>> s.memory_usage()
152

Not including the index gives the size of the rest of the data, which is necessarily smaller:

>>> s.memory_usage(index=False)
24

The memory footprint of object values is ignored by default:

>>> s = pd.Series(["a", "b"])
>>> s.values
array(['a', 'b'], dtype=object)
>>> s.memory_usage()
144
>>> s.memory_usage(deep=True)
260