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Matrices are used extensively in mathematics and statistics for data representation and solving multiple linear equations. In programming, two-dimensional arrays are considered as matrices.

In Python, we have many functions and classes that can be used to perform different operations on matrices. In this tutorial, we will learn how to print a matrix in Python.

We demonstrate in the following code how to print a two-dimensional array in Python using all square brackets and without proper spacing.

import numpy as np

a = np.array([[1, 2, 3], [3, 4, 5], [7, 8, 9]])

print(a)

Output:

[[1 2 3]
 [3 4 5]
 [7 8 9]]

In the method discussed below, we will print the array in a clean matrix type format.

forPrinting matrices in Python using loop

This method will forloop through the matrix using and print each row one by one after formatting it correctly. The following code shows how to do it.

import numpy as np

a = np.array([[1, 2, 3], [3, 4, 5], [7, 8, 9]])

for line in a:
    print("  ".join(map(str, line)))

Output:

1  2  3
3  4  5
7  8  9

We use mapthe function to convert the entire line into a string, and then apply jointhe function to the entire line to convert it all into a single string with the elements separated by the specified delimiter.

Printing a Matrix in Python Using List Comprehension

List comprehensions provide a concise and elegant way to use lists in a single line of code.

This method also uses fora loop, but is considered to be slightly faster than using it before, just like the previous method.

Take the following code as an example.

import numpy as np

a = np.array([[1, 2, 3], [3, 4, 5], [7, 8, 9]])

print("\n".join(["".join(["{:4}".format(item) for item in row]) for row in a]))

Output:

   1   2   3
   3   4   5
   7   8   9

Although the code above uses almost the same function as the previous method, this is much more efficient and can be done in one line. The other major difference is that format()the function is used here to provide the necessary spacing between string elements.

Another way to use this method is shown below. Here, we split the code into several lines separately and try to make the matrix similar to a table-like structure.

import numpy as np

a = np.array([[1, 2, 3], [3, 4, 5], [7, 8, 9]])

s = [[str(e) for e in row] for row in a]
lens = [max(map(len, col)) for col in zip(*s)]
fmt = "\t".join("{{:{}}}".format(x) for x in lens)
table = [fmt.format(*row) for row in s]
print("\n".join(table))

Output:

1	2	3
3	4	5
7	8	9