pandas.Series.memory_usage#
- 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.
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) 244