finding the element in a list closest to the mean of elements in python?

IIUC, use numpy.argmin to find the the index of the value closest to the mean by computing the absolute difference to the mean:

a = np.array([5, 25, 50, 100, 250, 500])

out = a[np.argmin(np.abs(a-a.mean()))]

output: 100

If you want to keep it pure python, you can use a custom key for sorted to find the lowest difference element:

a= [5, 25, 50, 100, 250, 500]
a_mean = sum(a)/len(a)
out = sorted(a, key=lambda val:abs(val-a_mean))[0]
# 100

If we want to go with pure python, I would write a function like this:

from typing import List
numb_list = [1, 4, 10, 20, 55, 102, 77, 89]


def find_closest_to_mean(num_list: List[int])->int:
    mean = sum(numb_list)/len(num_list)
    distance_list = [abs(mean - num) for num in numb_list]
    return num_list[distance_list.index(min(distance_list))]


print(find_closest_to_mean(numb_list))  

[Out]

mean = 44.75
closest number = 55

here I create a function called find_closest_to_mean that expects a num_list argument that is a list of integers. It then first calculates the mean of the list, creates a distance_list in which each element corresponds to the distance of the num_list in that position with the mean (as an absolute value). lastly it returns an integer from the num_list that has the least distance to the mean.