Adding/Subtracting With Matrices

Adding and subtracting matrices is a fundamental part of linear algebra and a lot of data science techniques.

Let’s take a look at how to add/subtract with numpy arrays and matrices.

First, let’s import numpy and create some matrices to practice our operations with.

import numpy as np

a = np.array([[1,2,3,4],[5,6,7,8],[9,10,11,12],[13,14,15,16]])
b = np.array([[1,2,3,4],[5,6,7,8],[9,10,11,12],[13,14,15,16]])

Now that we have matrices to play with, it only takes a single operation, with the help of numpy, to add or subtract our a and b matrices.

np.add(a,b)
# array([[ 2,  4,  6,  8],
#       [10, 12, 14, 16],
#       [18, 20, 22, 24],
#       [26, 28, 30, 32]])

np.subtract(a,b)
#array([[0, 0, 0, 0],
#       [0, 0, 0, 0],
#       [0, 0, 0, 0],
#       [0, 0, 0, 0]])

Adding and subtracting wasn’t so bad was it?

Check out the full code sample below.

import numpy as np

a = np.array([[1,2,3,4],[5,6,7,8],[9,10,11,12],[13,14,15,16]])
b = np.array([[1,2,3,4],[5,6,7,8],[9,10,11,12],[13,14,15,16]])

np.add(a,b)
# array([[ 2,  4,  6,  8],
#       [10, 12, 14, 16],
#       [18, 20, 22, 24],
#       [26, 28, 30, 32]])

np.subtract(a,b)
#array([[0, 0, 0, 0],
#       [0, 0, 0, 0],
#       [0, 0, 0, 0],
#       [0, 0, 0, 0]])