Weighted Mean

Given a discrete set of numbers, $X$, and a corresponding set of weights, $W$, the weighted mean is calculated as follows: $m_w = \frac{\sum_{i=1}^n (x_i * w_i)}{\sum_{i=1}^n w_i}$, where $x_i$ and $w_i$ are the respective $i^{th}$ corresponding elements of $X$ and $W$.

For example, if $X = \{1, 3, 5\}$and $W=\{2, 4, 6\}$, our weighted mean would be:

$m_w = \frac{(1*2)+(3*4)+(5*6)}{2 + 4 + 6}=\frac{2+12+30}{12}=3.\bar{66}$

If we wanted to round this to a scale of decimal place, our result would be .

num = int(input())
values = list(map(int, input().split()))
weights = list(map(int, input().split()))

v = list(map(lambda x, y: x*y, values, weights))
wmean= sum(v)/sum(weights)

print('%.1f' % wmean)