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
 


    
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