README_EN.md

1619. Mean of Array After Removing Some Elements

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Description

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

Solutions

Python3

class Solution:
    def trimMean(self, arr: List[int]) -> float:
        n = len(arr)
        start, end = int(n * 0.05), int(n * 0.95)
        arr.sort()
        t = arr[start:end]
        return round(sum(t) / len(t), 5)

Java

class Solution {
    public double trimMean(int[] arr) {
        Arrays.sort(arr);
        int n = arr.length;
        double s = 0;
        for (int start = (int) (n * 0.05), i = start; i < n - start; ++i) {
            s += arr[i];
        }
        return s / (n * 0.9);
    }
}

TypeScript

function trimMean(arr: number[]): number {
    arr.sort((a, b) => a - b);
    let n = arr.length,
        rmLen = n * 0.05;
    let sum = 0;
    for (let i = rmLen; i < n - rmLen; i++) {
        sum += arr[i];
    }
    return sum / (n * 0.9);
}

C++

class Solution {
public:
    double trimMean(vector<int>& arr) {
        sort(arr.begin(), arr.end());
        int n = arr.size();
        double s = 0;
        for (int start = (int)(n * 0.05), i = start; i < n - start; ++i)
            s += arr[i];
        return s / (n * 0.9);
    }
};

Go

func trimMean(arr []int) float64 {
	sort.Ints(arr)
	n := len(arr)
	sum := 0.0
	for i := n / 20; i < n-n/20; i++ {
		sum += float64(arr[i])
	}
	return sum / (float64(n) * 0.9)
}

Rust

impl Solution {
    pub fn trim_mean(mut arr: Vec<i32>) -> f64 {
        arr.sort();
        let n = arr.len();
        let count = (n as f64 * 0.05).floor() as usize;
        let mut sum = 0;
        for i in count..n - count {
            sum += arr[i];
        }
        sum as f64 / (n as f64 * 0.9)
    }
}

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