Is Maximum Average Subarray I easy or hard?

Maximum Average Subarray I is classified as an Easy problem on LeetCode. The challenge mainly tests understanding of the sliding window pattern and recognizing that overlapping subarray sums can be updated incrementally instead of recomputed.

How to solve Maximum Average Subarray I in O(n)?

Use a sliding window of size k. First compute the sum of the first k elements. Then iterate from index k to the end of the array, updating the window sum by subtracting nums[i-k] and adding nums[i]. Track the maximum sum during traversal and divide by k to get the maximum average.

Maximum Average Subarray I Python or Java solution?

Both Python and Java implementations follow the same sliding window logic. Compute the first window sum of k elements, then update the sum while moving the window forward. This ensures O(n) time complexity and constant extra space regardless of the language.

What is the best approach for Maximum Average Subarray I?

The sliding window approach is the best solution. Compute the sum of the first k elements, then slide the window across the array by subtracting the element leaving the window and adding the new element entering it. This reduces the time complexity to O(n) with O(1) extra space.

What data structure is used in Maximum Average Subarray I?

The problem primarily uses arrays along with the sliding window technique. No additional data structures are required because the algorithm maintains only a running sum and a maximum value while iterating through the array.

What is the time complexity of Maximum Average Subarray I?

The optimal sliding window solution runs in O(n) time because each element is processed once as the window moves across the array. The brute force method requires O(n*k) time since it recalculates the sum of k elements for every starting index.

Is Maximum Average Subarray I asked at Google, Amazon, or Meta?

Maximum Average Subarray I is a common entry-level array and sliding window problem frequently used in coding interviews and online assessments. Variations of fixed-size window problems appear in interviews at companies like Amazon, Google, and Meta to test array traversal and optimization skills.

Description Solution Video 13:22

643. Maximum Average Subarray I

Easy49.2% acceptance12 companies

You are given an integer array nums consisting of n elements, and an integer k.

Find a contiguous subarray whose length is equal to k that has the maximum average value and return this value. Any answer with a calculation error less than 10^-5 will be accepted.

Example 1:

Input: nums = [1,12,-5,-6,50,3], k = 4
Output: 12.75000
Explanation: Maximum average is (12 - 5 - 6 + 50) / 4 = 51 / 4 = 12.75

Example 2:

Input: nums = [5], k = 1
Output: 5.00000

Constraints:

n == nums.length
1 <= k <= n <= 10⁵
-10⁴ <= nums[i] <= 10⁴

Asked at 12 companies

Oppo

TCS

Google Microsoft Meta Amazon Bloomberg

Infosys JPMorgan Chase Uber Goldman Sachs Yandex

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Array Sliding Window

13:22

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643. Maximum Average Subarray I

Asked at 12 companies

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