dask.dataframe.Series.memory_usage

dask.dataframe.Series.memory_usage

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

Return the memory usage of the Series.

This docstring was copied from pandas.core.series.Series.memory_usage.

Some inconsistencies with the Dask version may exist.

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

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