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: 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() 104
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() 96 >>> s.memory_usage(deep=True) 212