Pandas Practice Set-1: Calculate the mean of each numeric column of diamonds DataFrame
Pandas Practice Set-1: Exercise-26 with Solution
Write a Pandas program to calculate the mean of each numeric column 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("\nMean of each numeric column of diamonds DataFrame:")
print(diamonds.mean())
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 Mean of each numeric column of diamonds DataFrame: carat 0.797940 depth 61.749405 table 57.457184 price 3932.799722 x 5.731157 y 5.734526 z 3.538734 dtype: float64
Python Code Editor:
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Previous: Write a Pandas program to pass a list of data types to only describe certain types of diamonds DataFrame.
Next: Write a Pandas program to calculate the mean of each row of diamonds DataFrame.
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https://w3resource.com/python-exercises/pandas/practice-set1/pandas-practice-set1-exercise-26.php
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