Pandas Practice Set-1: Calculate the memory usage for each Series of diamonds DataFrame

Last update on May 03 2025 13:02:34 (UTC/GMT +8 hours)

61. Calculate Memory Usage for Each Series in Diamonds DataFrame

Write a Pandas program to calculate the memory usage for each Series (in bytes) of diamonds DataFrame.

Sample Solution:

Python Code:

import pandas as pd
diamonds = pd.read_csv('https://raw.githubusercontent.com/mwaskom/seaborn-data/master/diamonds.csv')
print("Original Dataframe:")
print(diamonds.head())
print("\nMemory usage for each Series (in bytes) of diamonds DataFrame:")
print(diamonds.memory_usage(deep=True))

Sample Output:

Original Dataframe:
   carat      cut color clarity  depth  table  price     x     y     z
0   0.23    Ideal     E     SI2   61.5   55.0    326  3.95  3.98  2.43
1   0.21  Premium     E     SI1   59.8   61.0    326  3.89  3.84  2.31
2   0.23     Good     E     VS1   56.9   65.0    327  4.05  4.07  2.31
3   0.29  Premium     I     VS2   62.4   58.0    334  4.20  4.23  2.63
4   0.31     Good     J     SI2   63.3   58.0    335  4.34  4.35  2.75

Memory usage for each Series (in bytes) of diamonds DataFrame:
Index           80
carat       431520
cut        3413674
color      3344280
clarity    3242590
depth       431520
table       431520
price       431520
x           431520
y           431520
z           431520
dtype: int64

For more Practice: Solve these Related Problems:

Write a Pandas program to iterate through each column in the diamonds DataFrame and print its memory usage in bytes.
Write a Pandas program to compute and display the memory usage of every series in the diamonds DataFrame using a loop.
Write a Pandas program to calculate the memory usage for each column and then create a summary DataFrame of the results.
Write a Pandas program to list each column with its corresponding memory usage and sort the list by memory consumption.

Go to:

Previous: Write a Pandas program to get the true memory usage by diamonds DataFrame.
Next: Write a Pandas program to get randomly sample rows from diamonds DataFrame.

Python Code Editor:

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