#0009

Find Revenue By Category

EasyPandas15 min10 XP

Problem

Given a DataFrame with category, price, and quantity columns, return total revenue per category sorted from highest to lowest.

Why This Matters

This is one of the most common data analysis moves: choose the grain, group rows, and aggregate a metric.

Function Signature

def revenue_by_category(df):

Examples

Example 1

Inputcategory: ["book", "pen", "book"], price: [100, 10, 150], quantity: [2, 5, 1]

Outputbook revenue = 350, pen revenue = 50

Book revenue is 100*2 + 150*1. Pen revenue is 10*5.

Constraints

Do not modify the original DataFrame in place.
Return columns category and revenue.
Sort by revenue descending.

CodePython

def revenue_by_category(df):
    """
    Input example: category: ["book", "pen", "book"], price: [100, 10, 150], quantity: [2, 5, 1]
    Return: book revenue = 350, pen revenue = 50
    Return the value from the function so the tests can compare it. Do not print unless the prompt asks.
    """
    # df has columns: category, price, quantity
    # write your code here
    return df

def revenue_by_category(df):
    """
    Input example: category: ["book", "pen", "book"], price: [100, 10, 150], quantity: [2, 5, 1]
    Return: book revenue = 350, pen revenue = 50
    Return the value from the function so the tests can compare it. Do not print unless the prompt asks.
    """
    # df has columns: category, price, quantity
    # write your code here
    return df

Visible browser tests run here when available.

Testcases1 visible / 4 hidden categories

Two categories

Inputbook/pen rows with price and quantity

Expectedbook first, then pen

Book has the larger total revenue.

Hidden Test Categories

Single categoryCategories already sorted incorrectlyZero quantity rowsDecimal prices