Daily Temperatures
Given an array of daily temperatures, return an array where each element is the number of days you have to wait until a warmer day. If there's no future warmer day, the answer for that day is 0.
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Problem
Given an array of integers temperatures representing the daily temperatures, return an array answer such that answer[i] is the number of days you have to wait after the ith day to get a warmer temperature. If there is no future day for which this is possible, keep answer[i] == 0 instead.
Input
An integer array `temperatures`.
Output
An array `answer` where `answer[i]` is the number of days after day i until a warmer temperature. 0 if there is no such day.
Examples
Input: temperatures = [73,74,75,71,69,72,76,73]
Output: [1,1,4,2,1,1,0,0]
Day 0 (73): day 1 is warmer (74), so 1. Day 2 (75): next warmer is day 6 (76), so 4.
Input: temperatures = [30,40,50,60]
Output: [1,1,1,0]
Each day the next day is warmer, except the last.
Input: temperatures = [30,60,90]
Output: [1,1,0]
Same pattern: each day is warmer than the last.
The brute-force approach
For each day, scan forward until you find a day with a higher temperature. Record the distance.
answer = [0] * len(temperatures)
for i in range(len(temperatures)):
for j in range(i + 1, len(temperatures)): # scan forward
if temperatures[j] > temperatures[i]:
answer[i] = j - i
break
return answerFor each of the n days, you might scan up to n more days, making it O(n²). A monotonic stack lets you process each day exactly once: when you find a warmer day, resolve all the colder days waiting in the stack.
Spotting the pattern
This is a Stack problem. The key question to ask yourself:
For each day, how do I find the next warmer one without comparing it to every future day?
Answering that is where it clicks, and it's exactly what the guided walkthrough below builds with you: the pattern reasoning, a progressive hint ladder that never spoils the answer, a row-by-row dry run, the optimized solution, and an in-browser editor to run your code against real test cases.
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