🐍 Python Scenario-Based Interview Question: Find Maximum Profit from Stock Prices

If you are preparing for Python coding interviews or working on data analysis projects, this is a very common and important problem. It tests your understanding of loops, variables, and optimization.

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 Problem Statement

You are given stock prices with timestamps. Your task is to find the maximum profit by buying at one price and selling at a later higher price.

Input Data

prices = [
    ("2026-03-29 09:30:00", 150.25),
    ("2026-03-29 09:31:00", 152.10),
    ("2026-03-29 09:32:00", 151.80),
    ("2026-03-29 09:33:00", 154.50)
]

Expected Output

4.25
Buy at 150.25 (09:30)
Sell at 154.50 (09:33)

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 Python Code Solution

prices = [
    ("2026-03-29 09:30:00", 150.25),
    ("2026-03-29 09:31:00", 152.10),
    ("2026-03-29 09:32:00", 151.80),
    ("2026-03-29 09:33:00", 154.50)
]

max_profit = 0
min_price = prices[0][1]

buy_time = prices[0][0]
sell_time = prices[0][0]

for time, price in prices[1:]:

    if price - min_price > max_profit:
        max_profit = price - min_price
        sell_time = time

    if price < min_price:
        min_price = price
        buy_time = time

print("Maximum Profit:", round(max_profit, 2))
print("Buy Time:", buy_time)
print("Sell Time:", sell_time)

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 Explanation (Step-by-Step)

• We start by assuming the first price is the minimum price.
• We loop through each stock price one by one.
• For each price, we calculate the possible profit.
• If the profit is greater than the previous maximum profit, we update it.
• If the current price is lower than the minimum price, we update the minimum price.
• This ensures we always buy before selling.

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 Time and Space Complexity

• Time Complexity: O(n)
• Space Complexity: O(1)
• This is an optimized single-pass algorithm.

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 Why This Question is Important in Interviews

• Very common Python coding interview problem
• Tests logical thinking and optimization
• Used in real-world stock and financial applications
• Frequently asked in Data Analyst and Software Developer interviews
• Also known as: Best Time to Buy and Sell Stock Problem

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 Alternative Python Solution Using Function

def max_stock_profit(prices):

    max_profit = 0
    min_price = prices[0][1]

    for _, price in prices[1:]:

        profit = price - min_price
        max_profit = max(max_profit, profit)
        min_price = min(min_price, price)

    return round(max_profit, 2)

print(max_stock_profit(prices))

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 Real-World Use Cases

• Stock market analysis
• Crypto trading bots
• Financial data analytics
• Business profit optimization
• Algorithmic trading systems

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Practice Interview Question

Modify the program to:

• Return the buy and sell timestamps
• Handle negative profits
• Work with large datasets
• Read prices from a CSV file

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Conclusion

This is a classic Python interview question that demonstrates how to optimize performance using a single loop. Understanding this problem will help you perform better in coding interviews and real-world data analysis projects.