739. Daily Temperatures

Problem Description

The problem provides an array named temperatures, which represents the daily temperatures recorded. The goal is to find out how many days one would have to wait for a warmer temperature than the current day. To solve this problem, we need to construct an array called answer where answer[i] represents the number of days you would have to wait after the i-th day to experience a warmer temperature. If there is no such day in the future where the temperature is warmer, then answer[i] should be set to 0.

For example, given temperatures = [73, 74, 75, 71, 69, 72, 76, 73], the output should be [1, 1, 4, 2, 1, 1, 0, 0]. This means that on day 0 with a temperature of 73, you have to wait 1 day to get a temperature higher than 73, which occurs on day 1 with a temperature of 74. By the end of the array, the temperatures are not followed by any warmer temperatures, hence the 0s.

Intuition

The intuition behind the solution is to use a stack that helps to track the temperatures and indexes. We traverse the temperatures from left to right, and for each day's temperature, we check whether it is higher than the temperature at the indexes recorded on the stack. If so, this means we have found a day with a warmer temperature for the days corresponding to those indexes. Therefore, for each such index, j, we can update answer[j] to the current day's index minus j, indicating the number of days that had to be waited.

The stack keeps track of indexes with temperatures that we haven't yet found a warmer day for. This is an effective approach because the temperatures are processed in order and the stack ensures we only compare temperatures where the future warmer temperature hasn't been found yet. When a warmer temperature is encountered, it is the immediate next warmer temperature for all temperatures currently in the stack. Once updated, we no longer need to consider those days because their next warmer temperature has been determined.

In cases where there are no warmer temperatures in the future, the answer will remain 0 by default, as established at the start of the solution.

Overall, the idea is to push the index of the current temperature to the stack if it cannot find a higher temperature immediately. Subsequently, with each new day's temperature, we compare it against the peak temperatures on the stack until we find one that is lower or until the stack is empty. This process efficiently calculates the number of days to wait for each day, leading to the final answer array when we have processed all temperatures.

Learn more about Stack and Monotonic Stack patterns.

Solution Approach

The implementation of the solution uses a stack data structure to keep track of the indices of days that have not yet found a warmer future temperature. The stack will help us maintain the order in which we need to find the next warmer temperature while iterating through the temperatures only once, which achieves a time complexity of O(n), where n is the number of days.

Here is a step-wise breakdown of the algorithm used in the solution:

Initialize an answer array ans with the same length as the temperatures array, filled with zeros. This array will hold the final number of days one has to wait for a warmer temperature.
Create an empty stack stk that will store indices of the temperatures array.
Iterate through the temperatures array using an index i and temperature t.
- While there are indices on the stack and the current temperature t is greater than the temperature at the top index of the stack (i.e., temperatures[stk[-1]] < t), pop the index j from the top of the stack. This indicates that we have found a warmer day for the day at index j.
- Calculate the number of days waited for index j by subtracting j from the current index i (i.e., ans[j] = i - j). This gives us the number of days that had to pass to reach a warmer temperature.
- Continue popping from the stack and updating the ans array until the stack is empty or a day with a lower temperature is found.
If the current day's temperature isn't higher than the temperature at the top index of the stack, or if the stack is empty, push the current index i onto the stack. This signifies that we are still looking for a future warmer temperature for this day.
Once we exit the loop, we have filled out the ans array with the number of days to wait for a warmer temperature after each day. In cases where we do not find a warmer temperature, the default value of 0 remains.

This approach utilizes a monotonic stack in which, instead of storing the values, we store indices and ensure that the temperatures related to these indices are in ascending order. A monotonic stack is helpful when dealing with problems where we need to know the next greater or smaller element in an array.

The beauty of this algorithm lies in its efficient use of the stack to find the next greater element and its ability to accomplish this in a single pass through the temperatures array, hence having a linear time complexity relative to the input size.

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Example Walkthrough

Let's follow the solution approach using a small example with the temperatures array [71, 72, 70, 76, 69].

We start by initializing an answer array, ans, of the same length as temperatures, filled with zeros: [0, 0, 0, 0, 0].
We also create an empty stack stk to keep track of indices where we haven't found a warmer temperature yet.
Now let's iterate through the temperatures array:
- Day 0: t = 71
  - The stack stk is empty, so we push the index 0 onto stk.
- Day 1: t = 72
  - The top index on stk is 0 and temperatures[0] < 72, so we pop 0 from stk and update ans[0] = 1 - 0 = 1. We then push the index 1 onto stk.
- Day 2: t = 70
  - The top index on stk is 1 and temperatures[1] > 70, so we don't pop anything from stk. Push the index 2 onto stk.
- Day 3: t = 76
  - The top index on stk is 2 and temperatures[2] < 76, so we pop 2 from stk and update ans[2] = 3 - 2 = 1.
  - Next, we check the new top index which is 1. Since temperatures[1] < 76, we pop 1 from stk and update ans[1] = 3 - 1 = 2. There are no more indices on stk, so we push the current index 3 onto stk.
- Day 4: t = 69
  - The top index on stk is 3 and temperatures[3] > 69, so we don't pop anything from stk. Push the index 4 onto stk.
After the iteration, we have the ans array updated as [1, 2, 1, 0, 0], which means:
- On Day 0, you have to wait 1 day to get a higher temperature on Day 1 (71 to 72).
- On Day 1, you have to wait 2 days to get a higher temperature on Day 3 (72 to 76).
- On Day 2, you have to wait 1 day to get a higher temperature on Day 3 (70 to 76).
- Day 3 and Day 4 are followed by no warmer temperatures, so their values remain 0.

This walkthrough has provided a step-by-step execution of the solution approach, showcasing how we use a stack to efficiently calculate the number of days one would have to wait for a warmer temperature.

Solution Implementation

1class Solution:
2    def dailyTemperatures(self, temperatures: List[int]) -> List[int]:
3        # Initialize a list of zeros for the answer with the same length as the input list
4        answer = [0] * len(temperatures)
5        # Initialize an empty list to be used as a stack to keep track of temperatures indices
6        stack = []
7      
8        # Enumerate over the list of temperatures
9        for index, current_temp in enumerate(temperatures):
10            # Loop through the stack as long as it's not empty and the current temperature
11            # is greater than the temperature at the index of the last element in the stack
12            while stack and temperatures[stack[-1]] < current_temp:
13                # Pop the index of the temperature that is less than the current temperature
14                previous_index = stack.pop()
15                # Calculate the number of days between the previous and current temperature
16                # and update the answer list
17                answer[previous_index] = index - previous_index
18          
19            # Append the current index to the stack
20            stack.append(index)
21      
22        # Return the answer list which contains the number of days to wait until a warmer temperature
23        return answer
24

1class Solution {
2    // This method returns an array that contains the number of days you would 
3    // have to wait until a warmer temperature for each day represented in 'temperatures'.
4    public int[] dailyTemperatures(int[] temperatures) {
5        int n = temperatures.length; // Total number of days
6        int[] result = new int[n]; // Initialize the result array with the same length as temperatures
7        Deque<Integer> stack = new ArrayDeque<>(); // Use a stack to keep track of indices
8      
9        // Iterate through each day in temperatures
10        for (int currentIndex = 0; currentIndex < n; ++currentIndex) {
11            // While the stack is not empty and the current temperature is greater 
12            // than the temperature at the top index of the stack
13            while (!stack.isEmpty() && temperatures[stack.peek()] < temperatures[currentIndex]) {
14                int prevIndex = stack.pop(); // Get the index from the top of the stack
15                result[prevIndex] = currentIndex - prevIndex; // Calculate the number of days and update result
16            }
17            // Push current index onto the stack
18            stack.push(currentIndex);
19        }
20        // At the end, result array contains the answer
21        return result;
22    }
23}
24

1#include <vector>
2#include <stack>
3using namespace std;
4
5class Solution {
6public:
7    // Function to find the number of days to wait for a warmer temperature for each day
8    vector<int> dailyTemperatures(vector<int>& temperatures) {
9        int n = temperatures.size(); // Number of days based on the temperature list
10        vector<int> daysToWait(n); // Initialize the answer array with the same size as temperatures
11        stack<int> indexStack; // Stack to keep track of temperatures indices
12
13        // Iterate over each day in temperatures
14        for (int i = 0; i < n; ++i) {
15            // Check if the current day's temperature is higher than the temperature at the 
16            // top of the stack (which represents the last unprocessed day's temperature)
17            while (!indexStack.empty() && temperatures[indexStack.top()] < temperatures[i]) {
18                int previousDayIndex = indexStack.top(); // Get the index of the day with the lower temperature
19                daysToWait[previousDayIndex] = i - previousDayIndex; // Calculate the days to wait
20                indexStack.pop(); // Remove that day from the stack since it's now processed
21            }
22          
23            // Always push the current day's index to the stack to process later
24            indexStack.push(i);
25        }
26      
27        // The stack will automatically contain 0s where there is no warmer temperature in the future
28        return daysToWait;
29    }
30};
31

1// Function to calculate the number of days until a warmer temperature for each day.
2function dailyTemperatures(temperatures: number[]): number[] {
3    // Determine the total number of days in the temperatures array.
4    const totalDays = temperatures.length;
5    // Initialize an array to store the number of days to wait for a warmer temperature.
6    const daysUntilWarmer = new Array(totalDays).fill(0);
7    // Stack to keep track of indices of days which temperatures haven't been processed yet.
8    const indexStack: number[] = [];
9  
10    // Iterate through the temperatures array in reverse order.
11    for (let currentIndex = totalDays - 1; currentIndex >= 0; --currentIndex) {
12        // While the stack is not empty and the current temperature is greater than or equal to
13        // the temperature at the top index of the stack, pop the stack.
14        while (indexStack.length && temperatures[indexStack[indexStack.length - 1]] <= temperatures[currentIndex]) {
15            indexStack.pop();
16        }
17        // If the stack is not empty after the popping elements, compute the days to wait
18        // for a warmer temperature by subtracting the current index from the top index in the stack.
19        if (indexStack.length) {
20            daysUntilWarmer[currentIndex] = indexStack[indexStack.length - 1] - currentIndex;
21        }
22        // Push the current index onto the stack.
23        indexStack.push(currentIndex);
24    }
25    // Return the array of days to wait.
26    return daysUntilWarmer;
27}
28

Time and Space Complexity

Time Complexity

The time complexity of the given code is O(N), where N is the number of days in the temperatures list. The reason for this is that each element is processed as it's pushed into the stack stk and then processed again when it's popped from the stack. Each element can be pushed and popped at most once which gives us a linear time complexity over the number of elements in the temperatures list.

Space Complexity

The space complexity of the given code is O(N) as well, where N is the number of days in the temperatures list. This is because we have an auxiliary stack stk that, in the worst case, might contain all temperature indices (N) at some point in time. Additionally, we have an array ans to store the answer for each day, which also contains N elements.

Learn more about how to find time and space complexity quickly using problem constraints.

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Question 1 out of 10

You are given an array of intervals where intervals[i] = [start_i, end_i] represent the start and end of the ith interval. You need to merge all overlapping intervals and return an array of the non-overlapping intervals that cover all the intervals in the input.

Sort the intervals by their start time, then iterate through the sorted intervals, merging any overlapping intervals.

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