Pandas Practice Set-1: Calculate the mean of price for each cut of diamonds DataFrame
28. Calculate Mean of Price for Each Cut
Write a Pandas program to calculate the mean of price for each cut 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("\nCalculate the mean of price for each cut:")
print(diamonds.groupby('cut').price.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 Calculate the mean of price for each cut: cut Fair 4358.757764 Good 3928.864452 Ideal 3457.541970 Premium 4584.257704 Very Good 3981.759891 Name: price, dtype: float64
For more Practice: Solve these Related Problems:
- Write a Pandas program to group the diamonds DataFrame by 'cut' and compute the mean price for each group.
- Write a Pandas program to calculate the average price for each diamond cut and sort the results in descending order.
- Write a Pandas program to group by 'cut', calculate the mean price, and plot a bar chart of the mean prices.
- Write a Pandas program to group diamonds by 'cut' and compare the mean price with the median price for each group.
Python Code Editor:
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