How to make a matrix in Python

Make a matrix in Python with an example: learn how to create a matrix, access elements & print a matrix in Python.

Creating a Matrix in Python

Matrices are an important concept in linear algebra and are used to represent data in many different ways. They are also used in many programming languages such as Python. In this tutorial, we will learn how to create and manipulate matrices in Python.

The most basic way to create a matrix in Python is to use the built-in

list
data type. A list can be used to represent a matrix by using a nested structure. For example, the following code creates a matrix with 3 rows and 4 columns:

matrix = [[0, 1, 2, 3],
          [4, 5, 6, 7],
          [8, 9, 10, 11],]

The matrix is represented by a list of lists. Each row is represented by a list, and each column is represented by an element in that list. We can access elements of the matrix by using the indices of the list.

For example, we can access the second element in the first row of the matrix with the following code:

matrix[0][1]

This code would return the value

1
, which is the second element in the first row of the matrix.

We can also use the

numpy
library to create matrices in Python. The
numpy
library provides a powerful
matrix
object that can be used to represent matrices. For example, the following code creates a matrix with 3 rows and 4 columns:

import numpy as np

matrix = np.matrix([[0, 1, 2, 3],
                    [4, 5, 6, 7],
                    [8, 9, 10, 11],])

We can access elements of the matrix in the same way as with a list of lists. For example, we can access the second element in the first row of the matrix with the following code:

matrix[0, 1]

This code would return the value

1
, which is the second element in the first row of the matrix.

In this tutorial, we have learned how to create and manipulate matrices in Python. Matrices are an important concept in linear algebra and are used to represent data in many different ways. They can be represented using lists of lists or using the

numpy
library.

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