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Car Shopping Problem

After accidentally leaving an ice chest of fish and shrimp in your car for a week while you were on vacation, you’re now in the market for a new vehicle 🚗. Your insurance didn’t cover the loss, so you want to make sure you get a good deal on your new car.

Given a Series of car asking_prices and another Series of car fair_prices, determine which cars for sale are a good deal. In other words, identify cars whose asking price is less than their fair price.

import numpy as np
import pandas as pd

asking_prices = pd.Series([5000, 7600, 9000, 8500, 7000], index=['civic', 'civic', 'camry', 'mustang', 'mustang'])
fair_prices = pd.Series([5500, 7500, 7500], index=['civic', 'mustang', 'camry'])

# civic      5000
# civic      7600
# camry      9000
# mustang    8500
# mustang    7000
# dtype: int64

# civic      5500
# mustang    7500
# camry      7500
# dtype: int64

The result should be a list of integer indices corresponding to the good deals in asking_prices.

Try with Google Colab See the solution