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:
Have another way to solve this solution? Contribute your code (and comments) through Disqus.
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.
What is the difficulty level of this exercise?
It will be nice if you may share this link in any developer community or anywhere else, from where other developers may find this content. Thanks.
https://198.211.115.131/python-exercises/pandas/practice-set1/pandas-practice-set1-exercise-26.php
- Weekly Trends and Language Statistics
- Weekly Trends and Language Statistics