HACKERRANK - 10 DAYS OF STATISTICS SOLUTIONS IN PYTHON

DAY 0 - MEAN MEDIAN MODE

Learn - Numpy, Scipy, stats library

import numpy as np
from scipy import stats

size = int(input())
numbers = list(map(int, input().split())) #Take input
print(np.mean(numbers))
print(np.median(numbers))
print(int(stats.mode(numbers)[0]))

DAY 0 - WEIGHTED MEAN

def weightedMean(X, W):
    weighted_sum = 0
    weight_sum = 0
    for i in range(len(X)):
        weighted_sum += (X[i]*W[i])
        weight_sum += W[i]
           
    print("%0.1f"%(weighted_sum/ weight_sum));

* Full Program-

#!/bin/python3

import math
import os
import random
import re
import sys

#
# Complete the 'weightedMean' function below.
#
# The function accepts following parameters:
#  1. INTEGER_ARRAY X
#  2. INTEGER_ARRAY W
#

def weightedMean(X, W):
    weighted_sum = 0
    weight_sum = 0
    for i in range(len(X)):
        weighted_sum += (X[i]*W[i])
        weight_sum += W[i]
           
    print("%0.1f"%(weighted_sum/ weight_sum));

if __name__ == '__main__':
    n = int(input().strip())

    vals = list(map(int, input().rstrip().split()))

    weights = list(map(int, input().rstrip().split()))

    weightedMean(vals, weights)

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DAY 5
DAY 6
DAY 7
DAY 8
DAY 9
DAY 10