w3resource

Pandas Practice Set-1: Calculate count, minimum, maximum price for each cut of diamonds DataFrame

Pandas Practice Set-1: Exercise-29 with Solution

Write a Pandas program to calculate count, minimum, maximum 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("\nCount, minimum, maximum  price for each cut of diamonds DataFrame:")
print(diamonds.groupby('cut').price.agg(['count', 'min', 'max']))

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

Count, minimum, maximum  price for each cut of diamonds DataFrame:
           count  min    max
cut                         
Fair        1610  337  18574
Good        4906  327  18788
Ideal      21551  326  18806
Premium    13791  326  18823
Very Good  12082  336  18818

Python Code Editor:


Have another way to solve this solution? Contribute your code (and comments) through Disqus.

Previous: Write a Pandas program to calculate the mean of price for each cut of diamonds DataFrame.
Next: Write a Pandas program to create a side-by-side bar plot of the diamonds DataFrame.

What is the difficulty level of this exercise?



Python: Tips of the Day

Python: Cache results with decorators

There is a great way to cache functions with decorators in Python. Caching will help save time and precious resources when there is an expensive function at hand.

Implementation is easy, just import lru_cache from functools library and decorate your function using @lru_cache.

from functools import lru_cache

@lru_cache(maxsize=None)
def fibo(a):
    if a <= 1:
        return a
    else:
        return fibo(a-1) + fibo(a-2)

for i in range(20):
    print(fibo(i), end="|")

print("\n\n", fibo.cache_info())

Output:

0|1|1|2|3|5|8|13|21|34|55|89|144|233|377|610|987|1597|2584|4181|

 CacheInfo(hits=36, misses=20, maxsize=None, currsize=20)