Pandas series is a One-dimensional ndarray with axis labels. The labels need not be unique but must be a hashable type. The object supports both integer- and label-based indexing and provides a host of methods for performing operations involving the index.
Pandas Series.memory_usage() function return the memory usage of the Series. The memory usage can optionally include the contribution of the index and of elements of object dtype.
Syntax: Series.memory_usage(index=True, deep=False)
Parameter :
index : Specifies whether to include the memory usage of the Series index.
deep : If True, introspect the data deeply by interrogating object dtypes for system-level memory consumption, and include it in the returned value.Returns : Bytes of memory consumed.
Example #1: Use Series.memory_usage() function to find the memory usage of the given series object.
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series([10, 25, 3, 25, 24, 6]) # Create the Index index_ = ['Coca Cola', 'Sprite', 'Coke', 'Fanta', 'Dew', 'ThumbsUp'] # set the index sr.index = index_ # Print the series print(sr) |
Output :
Now we will use Series.memory_usage() function to find the memory usage of the given series object.
# return the memory usage result = sr.memory_usage() # Print the result print(result) |
Output :
As we can see in the output, the Series.memory_usage() function has successfully returned the memory usage of the given series object.
Example #2: Use Series.memory_usage() function to find the memory usage of the given series object.
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series([19.5, 16.8, None, 22.78, 16.8, 20.124, None, 18.1002, 19.5]) # Print the series print(sr) |
Output :
Now we will use Series.memory_usage() function to find the memory usage of the given series object.
# return the memory usage result = sr.memory_usage() # Print the result print(result) |
Output :
As we can see in the output, the Series.memory_usage() function has successfully returned the memory usage of the given series object.
