import java.util.*;

public class Solution { public static void main(String[] args) { Scanner scanner = new Scanner(System.in);

    // Read the size of the array
    int n = scanner.nextInt();
    int[] numbers = new int[n];
    double sum = 0;

    // Read array elements and compute sum for mean
    for (int i = 0; i < n; i++) {
        numbers[i] = scanner.nextInt();
        sum += numbers[i];
    }

    // Sort the array for median and mode
    Arrays.sort(numbers);

    // Calculate mean
    double mean = sum / n;

    // Calculate median
    double median;
    if (n % 2 == 0) {
        median = (numbers[n / 2 - 1] + numbers[n / 2]) / 2.0;
    } else {
        median = numbers[n / 2];
    }

    // Calculate mode
    int mode = numbers[0];
    int maxCount = 1;
    int currentCount = 1;

    for (int i = 1; i < n; i++) {
        if (numbers[i] == numbers[i - 1]) {
            currentCount++;
        } else {
            currentCount = 1;
        }

java code: if (currentCount > maxCount || (currentCount == maxCount && numbers[i] < mode)) { maxCount = currentCount; mode = numbers[i]; } }

    // Output the results rounded to 1 decimal place
    System.out.printf("%.1f\n", mean);
    System.out.printf("%.1f\n", median);
    System.out.println(mode);
}

}

This is my algoritmic solution in python. I just use math library to round floor for counting the median:

import math`

n = int(input())

x = input().split(" ")

for i in range(len(x)): x[i] = int(x[i])

x.sort()

print(sum(x)/n)

if(n%2==0): print((x[int(n/2)-1]+x[int(n/2)])/2) else: print(x[math.floor(n/2)])

occur = 0 high = 0 modus = x[0]
for i in range(1, n): if (x[i] == x[i-1]): occur += 1 if occur > high: modus = x[i] high = occur else: occur = 0

print(modus)

`

**simple and sweet python solution **

from collections import Counter as c
n = int(input())
x = list(map(int,input().split()))
print(s.mean(x))
print(s.median(x))
a = c(x)
m = 0
for i,j in a.items():
if m < j:
m = j
if m==1:
print(min(x))
else:
print(min(s.multimode(x)))

python

import numpy as np

from collections import Counter

array_size = int(input())

array_numbers = list(map(int, input().split()))

mean = np.mean(array_numbers)

median = np.median(array_numbers)

counts= Counter(array_numbers)

max_count= max(counts.values())

modes= [number for number, count in counts.items() if count == max_count]

mode = min(modes)

print(mean) print(median) print(mode)

from collections import Counter

n=int(input())
arr=list(map(int,input().split()))

mean=sum(arr)/n

freq=Counter(arr)
sorted_dict = {
    k: v for k, v in sorted(freq.items(), key=lambda item: (-item[1], item[0]))
}
mode,*_=sorted_dict

arr=sorted(arr)
if n%2==0:
    median=(arr[n//2]+arr[(n//2)-1])/2
else:
    median=arr[(n//2)-1]

print(mean)
print(median)
print(mode)

or

import statistics
from collections import Counter
n = int(input())
arr = list(map(int, input().split()))
mean = statistics.mean(arr)
median = statistics.median(arr)
freq=Counter(arr)
mode = max(freq.items(), key=lambda item: (item[1], -item[0]))[0]

print(f"{mean:.1f}")
print(f"{median:.1f}")
print(mode)