Online Stock Span

Online Stock Span is a Medium Data Structures and Algorithms interview problem you can solve, run and submit on Thita.ai. It belongs to the Stack Patterns pattern, in the Monotonic Stack subpattern.

Problem statement

Design an algorithm that collects daily price quotes for some stock and returns the span of that stock's price for the current day.

The span of the stock's price in one day is the maximum number of consecutive days (starting from that day and going backward) for which the stock price was less than or equal to the price of that day.

- For example, if the prices of the stock in the last four days is [7,2,1,2] and the price of the stock today is 2, then the span of today is 4 because starting from today, the price of the stock was less than or equal 2 for 4 consecutive days.

- Also, if the prices of the stock in the last four days is [7,34,1,2] and the price of the stock today is 8, then the span of today is 3 because starting from today, the price of the stock was less than or equal 8 for 3 consecutive days.

Implement the StockSpanner class:

- StockSpanner() Initializes the object of the class.

- int next(int price) Returns the span of the stock's price given that today's price is price.

Example 1:

Input ["StockSpanner", "next", "next", "next", "next", "next", "next", "next"] [[], [100], [80], [60], [70], [60], [75], [85]] Output [null, 1, 1, 1, 2, 1, 4, 6]

Explanation StockSpanner stockSpanner = new StockSpanner(); stockSpanner.next(100); // return 1 stockSpanner.next(80); // return 1 stockSpanner.next(60); // return 1 stockSpanner.next(70); // return 2 stockSpanner.next(60); // return 1 stockSpanner.next(75); // return 4, because the last 4 prices (including today's price of 75) were less than or equal to today's price. stockSpanner.next(85); // return 6

Constraints:

- 1 <= price <= 105

- At most 104 calls will be made to next.

Topics and companies

Topics: Stack, Design, Monotonic Stack, Data Stream.

Reported in interviews at Amazon.

How to practise Online Stock Span on Thita.ai

Starter code is provided in C, C#, C++, Go, Java, JavaScript and Python. Your solution runs against 5 test cases for this problem, with the AI coach available for a hint when you are stuck rather than a finished answer. The reference solution runs in O(1) amortized per next() call. Each price is pushed and popped at most once from the stack, so over N calls, total work is O(N). time and O(N), where N is the number of calls to next(), since in the worst case (strictly decreasing prices), all prices are stored in the stack. space.

Open Online Stock Span in the code editor, or read the Online Stock Span editorial for a worked solution with its approach and complexity analysis.

Where Online Stock Span sits in the DSA pattern sheet

Problems related to Online Stock Span

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