W3cubDocs

/pandas 0.25

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

© 2008–2012, AQR Capital Management, LLC, Lambda Foundry, Inc. and PyData Development Team
Licensed under the 3-clause BSD License.
https://pandas.pydata.org/pandas-docs/version/0.25.0/reference/api/pandas.Series.memory_usage.html