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])

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

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 here.

**Additional Resources**

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

How to Find Index of Value in NumPy Array

How to Get Specific Column from NumPy Array

How to Add a Column to a NumPy Array