You can use the following methods to sum the rows and columns of a 2D NumPy array:

Method 1: Sum Rows of NumPy Array

arr.sum(axis=1)

Method 2: Sum Columns of NumPy Array

arr.sum(axis=0) 

The following examples show how to use each method in practice with the following 2D NumPy array:

import numpy as np

#create NumPy array
arr = np.arange(18).reshape(6,3)

#view NumPy array
print(arr)

[[ 0  1  2]
 [ 3  4  5]
 [ 6  7  8]
 [ 9 10 11]
 [12 13 14]
 [15 16 17]]

Example 1: Sum Rows of NumPy Array

We can use the following syntax to sum the rows of a NumPy array:

import numpy as np

#calculate sum of rows in NumPy array
arr.sum(axis=1)

array([ 3, 12, 21, 30, 39, 48])

The resulting array shows the sum of each row in the 2D NumPy array.

For example:

• The sum of values in the first row is 0 + 1 + 2 = 3.
• The sum of values in the first row is 3 + 4 + 5 = 12.
• The sum of values in the first row is 6 + 7 + 8 = 21.

And so on.

Example 2: Sum Columns of NumPy Array

We can use the following syntax to sum the columns of a NumPy array:

import numpy as np

#calculate sum of columns in NumPy array
arr.sum(axis=0)

array([45, 51, 57])

For example:

• The sum of values in the first column is 0+3+6+9+12+15 = 45.
• The sum of values in the first row is 1+4+7+10+13+16 = 51.
• The sum of values in the first row is 2+5+8+11+14+17 = 57.

Note: You can find the complete documentation for the NumPy sum() function .

The following tutorials explain how to perform other common operations in NumPy: