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Showing content from https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.memory_usage.html below:

pandas.Series.memory_usage — pandas 2.3.1 documentation

Series.memory_usage(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:

indexbool, default True

Specifies whether to include the memory usage of the Series index.

deepbool, 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.

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)
244

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