Python: Find the weighted average of two or more numbers

Python List: Exercise - 254 with Solution

Write a Python program to get the weighted average of two or more numbers.

A weighted average is an average in which some of the items to be averaged are 'more important' or 'less important' than some of the others. The weights are (non-negative) numbers which measure the relative importance

For example, the weighted average of a list of numbers x₁,…,x_n with corresponding weights w₁,…,w_n is

• Use sum() to sum the products of the numbers by their weight and to sum the weights.
• Use zip() and a list comprehension to iterate over the pairs of values and weights.

Sample Solution:

Python Code:

# Define a function 'weighted_average' that takes two lists 'nums' and 'weights'.
# The function calculates the weighted average by summing the product of corresponding elements in 'nums' and 'weights'
# and dividing it by the sum of 'weights'.
def weighted_average(nums, weights):
    return sum(x * y for x, y in zip(nums, weights)) / sum(weights)
	
# Example 1: Create two lists 'nums1' and 'nums2' with elements.
nums1 = [10, 50, 40]
nums2 = [2, 5, 3]
print("Original list elements:")
print(nums1)
print(nums2)
# Call 'weighted_average' to compute the weighted average of 'nums1' and 'nums2'.
print("\nWeighted average of the said two lists of numbers:")
print(weighted_average(nums1, nums2))

# Example 2: Create two lists 'nums1' and 'nums2' with elements.
nums1 = [82, 90, 76, 83]
nums2 = [.2, .35, .45, 32]
print("\nOriginal list elements:")
print(nums1)
print(nums2)
# Call 'weighted_average' to compute the weighted average of 'nums1' and 'nums2'.
print("\nWeighted average of the said two lists of numbers:")
print(weighted_average(nums1, nums2)) 

Sample Output:

Original list elements:
[10, 50, 40]
[2, 5, 3]

Weighted average of the said two list of numbers:
39.0

Original list elements:
[82, 90, 76, 83]
[0.2, 0.35, 0.45, 32]

Weighted average of the said two list of numbers:
82.97272727272727

Flowchart:

Python Code Editor:

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