Create a revenue column

pandaseasyassign

Write add_revenue(df) that returns a copy of df with a new column `revenue` = units * price. Do not mutate the input.

preloaded fixtures

import pandas as pd
import numpy as np

sales = pd.DataFrame({
    "order_id": [1, 2, 3, 4, 5, 6, 7, 8],
    "customer": ["ada", "grace", "ada", "alan", "grace", "marie", "alan", "ada"],
    "country": ["UK", "USA", "UK", "UK", "USA", "France", "UK", "UK"],
    "category": ["hardware", "audio", "audio", "furniture", "hardware", "audio", "hardware", "furniture"],
    "units": [1, 2, 1, 3, 1, 2, 4, 1],
    "price": [129.0, 249.99, 199.0, 420.0, 329.5, 249.99, 59.0, 540.0],
    "rating": [4.5, np.nan, 3.0, 5.0, np.nan, 4.0, 4.5, 2.5],
})

customers = pd.DataFrame({
    "customer": ["ada", "grace", "alan", "hedy"],
    "segment": ["pro", "pro", "starter", "starter"],
})

hint ladder

sql ↔ pandas

solution.py

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output

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Reference solution

The shape we check against. Any implementation that passes the assertions is valid — this one favours clarity.

def add_revenue(df):
    return df.assign(revenue=df['units'] * df['price'])

Code is blurred until you solve this problem — the reasoning stays readable.