from itertools import permutations

from math import sqrt, pow, factorial



n = int(eval(input()))

xy = [list(map(int, input().split())) for _ in range(n)]



def calc(a,b):

    [x1, y1] = a

    [x2, y2] = b

    return sqrt(pow(x1 - x2, 2) + pow(y1 - y2, 2))



sum = 0

for i in permutations(list(range(n))):

    distance = 0

    for j in range(1, n):

        distance = calc(xy[i[j]], xy[i[j-1]])

        sum += distance

print((sum/factorial(n)))









import numpy as np

from itertools import combinations

from itertools import permutations

from math import factorial





N = int(eval(input()))

xy = np.array([list(map(int, input().split())) for _ in range(N)])

cnt = 0



for i in xy:

    for j in xy:

        cnt += np.linalg.norm(i - j)

print((cnt / N))
from itertools import permutations
from math import sqrt, pow, factorial

n = int(eval(input()))
xy = [list(map(int, input().split())) for _ in range(n)]


def calc(a, b):
    [x1, y1] = a
    [x2, y2] = b
    return sqrt(pow(x1 - x2, 2) + pow(y1 - y2, 2))


sum = 0
for i in permutations(list(range(n))):
    distance = 0
    for j in range(1, n):
        distance = calc(xy[i[j]], xy[i[j - 1]])
        sum += distance
print((sum / factorial(n)))

import numpy as np
from itertools import combinations
from itertools import permutations
from math import factorial

N = int(eval(input()))
xy = np.array([list(map(int, input().split())) for _ in range(N)])
cnt = 0
for i in xy:
    for j in xy:
        cnt += np.linalg.norm(i - j)
print((cnt / N))

+import numpy as np +from itertools import combinations -from math import sqrt, pow, factorial +from math import factorial -n = int(eval(input())) -xy = [list(map(int, input().split())) for _ in range(n)] - - -def calc(a, b): -    [x1, y1] = a -    [x2, y2] = b -    return sqrt(pow(x1 - x2, 2) + pow(y1 - y2, 2)) - - -sum = 0 -for i in permutations(list(range(n))): -    distance = 0 -    for j in range(1, n): -        distance = calc(xy[i[j]], xy[i[j - 1]]) -        sum += distance -print((sum / factorial(n))) +N = int(eval(input())) +xy = np.array([list(map(int, input().split())) for _ in range(N)]) +cnt = 0 +for i in xy: +    for j in xy: +        cnt += np.linalg.norm(i - j) +print((cnt / N))