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Python | Pandas Series.memory_usage()

Last Updated : 11 Feb, 2019
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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. Python3
# 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. Python3
# 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. Python3
# 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. Python3
# 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.

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