Pandas Practice Set-1: Get the true memory usage by diamonds DataFrame
60. Get True Memory Usage of Diamonds DataFrame
Write a Pandas program to get the true memory usage by 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("\nTrue memory usage by diamonds DataFrame:")
print(diamonds.info(memory_usage='deep'))
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 True memory usage by diamonds DataFrame: <class 'pandas.core.frame.DataFrame'> RangeIndex: 53940 entries, 0 to 53939 Data columns (total 10 columns): carat 53940 non-null float64 cut 53940 non-null object color 53940 non-null object clarity 53940 non-null object depth 53940 non-null float64 table 53940 non-null float64 price 53940 non-null int64 x 53940 non-null float64 y 53940 non-null float64 z 53940 non-null float64 dtypes: float64(6), int64(1), object(3) memory usage: 12.4 MB None
For more Practice: Solve these Related Problems:
- Write a Pandas program to calculate and display the true memory usage of the diamonds DataFrame using memory_usage(deep=True).
- Write a Pandas program to compute the memory footprint of each column in the diamonds DataFrame and sum them up.
- Write a Pandas program to print the memory usage details for each series in the diamonds DataFrame and then the total memory usage.
- Write a Pandas program to display deep memory usage statistics of the diamonds dataset and export the information to a CSV file.
Python Code Editor:
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Next: Write a Pandas program to calculate the memory usage for each Series (in bytes) of diamonds DataFrame.
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