Как найти сумму элементов столбца питон

How do I add up all of the values of a column in a python array? Ideally I want to do this without importing any additional libraries.

input_val = [[1, 2, 3, 4, 5],
             [1, 2, 3, 4, 5],
             [1, 2, 3, 4, 5]]

output_val = [3, 6, 9, 12, 15]

I know I this can be done in a nested for loop, wondering if there was a better way (like a list comprehension)?

You may also use sum with zip within the map function:

# In Python 3.x 
>>> list(map(sum, zip(*input_val)))
[3, 6, 9, 12, 15]
# explicitly type-cast it to list as map returns generator expression

# In Python 2.x, explicit type-casting to list is not needed as `map` returns list
>>> map(sum, zip(*input_val))
[3, 6, 9, 12, 15]

answered Apr 17, 2017 at 21:10

Try this:

input_val = [[1, 2, 3, 4, 5],
         [1, 2, 3, 4, 5],
         [1, 2, 3, 4, 5]]

output_val = [sum([i[b] for i in input_val]) for b in range(len(input_val[0]))]

print output_val

answered Apr 17, 2017 at 21:12

Please construct your array using the NumPy library:

import numpy as np

create the array using the array( ) function and save it in a variable:

 arr = np.array(([1, 2, 3, 4, 5],[1, 2, 3, 4, 5],[1, 2, 3, 4, 5]))

apply sum( ) function to the array specifying it for the columns by setting the axis parameter to zero:

arr.sum(axis = 0)

answered Aug 1, 2020 at 22:15

This should work:

[sum(i) for i in zip(*input_val)]

answered Apr 17, 2017 at 21:09

I guess you can use:

import numpy as np
new_list = sum(map(np.array, input_val))

answered Apr 17, 2017 at 21:11

I think this is the most pythonic way of doing this

map(sum, [x for x in zip(*input_val)])

answered Apr 17, 2017 at 21:14

One-liner using list comprehensions: for each column (length of one row), make a list of all the entries in that column, and sum that list.

output_val = [sum([input_val[i][j] for i in range(len(input_val))]) 
                 for j in range(len(input_val[0]))]

answered Apr 17, 2017 at 21:10

Try this code. This will make output_val end up as [3, 6, 9, 12, 15] given your input_val:

input_val = [[1, 2, 3, 4, 5],
             [1, 2, 3, 4, 5],
             [1, 2, 3, 4, 5]]

vals_length = len(input_val[0])
output_val = [0] * vals_length # init empty output array with 0's
for i in range(vals_length): # iterate for each index in the inputs
    for vals in input_val:
        output_val[i] += vals[i] # add to the same index

print(output_val) # [3, 6, 9, 12, 15]

Using Numpy you can easily solve this issue in one line:

1: Input

input_val = [[1, 2, 3, 4, 5],
             [1, 2, 3, 4, 5],
             [1, 2, 3, 4, 5]]

2: Numpy does the math for you

np.sum(input_val,axis=0)

3: Then finally the results

array([ 3,  6,  9, 12, 15])

answered Nov 22, 2018 at 7:30

You can use the sum function instead of np.sum simply.

input_val = np.array([[1, 2, 3, 4, 5],
         [1, 2, 3, 4, 5],
         [1, 2, 3, 4, 5]])
sum(input_val)

output: array([ 3,  6,  9, 12, 15])

answered Jun 21, 2022 at 7:40

asked Apr 18, 2014 at 0:40

Here is your code changed to return the sum of whatever column you specify:

def sumColumn(m, column):
    total = 0
    for row in range(len(m)):
        total += m[row][column]
    return total

column = 1
print("Sum of the elements in column", column, "is", sumColumn(matrix, column))

answered Apr 18, 2014 at 1:08

import numpy as np
np.sum(M,axis=1)

where M is the matrix

This can be made easier if you represent the matrix as a flat array:

m = [
    1,2,3,4,
    10,11,12,13,
    100,101,102,103,
    1001,1002,1003,1004
]

def sum_column(m, n):
    return sum(m[i] for i in range(n, 4 * 4, 4))

answered Apr 18, 2014 at 0:50