Question

This is an offshoot of a previous question which started to snowball. If I have a matrix A and I want to use the mean/average of each row [1:] values to create another matrix B, but keep the row headings intact, how would I do this? I’ve included matrix A, my attempt at cobbling together a list comprehension, and the expected result.

from operator import sum,len

# matrix A with row headings and values
A = [('Apple',0.95,0.99,0.89,0.87,0.93),
('Bear',0.33,0.25.0.85,0.44,0.33),
('Crab',0.55,0.55,0.10,0.43,0.22)]

#List Comprehension
B = [(A[0],sum,A[1:]/len,A[1:]) for A in A]

Expected outcome

B = [('Apple', 0.926), ('Bear', 0.44), ('Crab', 0.37)]

Answer 1

Your list comprehension looks a little weird. You are using the same variable for the iterable and the item.

This approach seems to work:

def average(lst):
    return sum(lst) / len(lst)

B = [(a[0], average(a[1:])) for a in A]

I’ve created a function average for readability. It matches your expected values, so I think that’s what you want, although your use of mul suggests that I may be missing something.