Introduction

In this blog post, we will explore how to solve the LeetCode problem "1619" using AI. LeetCode is a popular platform for preparing for coding interviews, and with the help of AI tools like Chatmagic, we can generate solutions quickly and efficiently - helping you pass the interviews and get the job offer without having to study for months.

Problem Statement

Given an integer array arr, return the mean of the remaining integers after removing the smallest 5% and the largest 5% of the elements. Answers within 10-5 of the actual answer will be considered accepted. Example 1: Input: arr = [1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3] Output: 2.00000 Explanation: After erasing the minimum and the maximum values of this array, all elements are equal to 2, so the mean is 2. Example 2: Input: arr = [6,2,7,5,1,2,0,3,10,2,5,0,5,5,0,8,7,6,8,0] Output: 4.00000 Example 3: Input: arr = [6,0,7,0,7,5,7,8,3,4,0,7,8,1,6,8,1,1,2,4,8,1,9,5,4,3,8,5,10,8,6,6,1,0,6,10,8,2,3,4] Output: 4.77778 Constraints: 20 <= arr.length <= 1000 arr.length is a multiple of 20. 0 <= arr[i] <= 105

Explanation

Here's the solution:

• Sort the array: Sorting allows us to easily identify and exclude the smallest and largest 5% of elements.
• Calculate trim indices: Determine the indices corresponding to the 5th and 95th percentiles of the sorted array.

• Calculate the mean: Sum the elements between the trim indices and divide by the number of elements included in the sum.

• Runtime Complexity: O(n log n), where n is the length of the array (due to sorting). Storage Complexity: O(1) (in-place sort can be used, otherwise O(n) for creating a sorted copy)

Code

    def trim_mean(arr: list[int]) -> float:
    """
    Calculates the mean of the remaining integers after removing the smallest 5%
    and the largest 5% of the elements in an integer array.

    Args:
        arr (list[int]): The input integer array.

    Returns:
        float: The mean of the remaining integers after trimming.
    """

    n = len(arr)
    trim_percent = 0.05
    trim_count = int(n * trim_percent)

    arr.sort()  # Sort the array in ascending order

    trimmed_arr = arr[trim_count:n - trim_count]

    if not trimmed_arr:
        return 0.0  # Handle edge case where the array is too small after trimming

    return sum(trimmed_arr) / len(trimmed_arr)