How to reverse column order in a matrix with Python?

In this article, we will see how to reverse the column order of a matrix in Python.

Examples:

Input: 
arr = [[10,20,30],
       [40,50,60],
       [70,80,90]]
Output:
30 20 10 
60 50 40
90 80 70 

Input:
arr = [[15,30],
       [45,60],
       [75,90],
       [105,120]]
Output:
30 15
60 45
90 75
120 105

Matrices are created in python by using nested lists/arrays. However, a more efficient way to handle arrays in python is the NumPy library. To create arrays using NumPy use this or matrix in python once go through this.

Method 1:

1. Iterate through each row
2. For every row, use list comprehension to reverse the row (i.e. a[::-1])
3. Append the reversed rows into a new matrix
4. Print the matrix

Example:

# creating a 3X4 matrix using nested lists
matrix_1 = [['c1', 'c2', 'c3'],
            [10, 20, 30],
            [40, 50, 60],
            [70, 80, 90]]

# creating an empty array to store the reversed column matrix
matrix_2 = []

# looping through matrix_1 and appending matrix_2
for i in range(len(matrix_1)):
    matrix_2.append(matrix_1[i][::-1])

print('Matrix before changing column order:\n')
for rows in matrix_1:
    print(rows)
print('\nMatrix after changing column order:\n')
for rows in matrix_2:
    print(rows)

Output:

Method 2:

An array object in NumPy is called ndarray, which is created using the array() function. To reverse column order in a matrix, we make use of the numpy.fliplr() method. The method flips the entries in each row in the left/right direction. Column data is preserved but appears in a different order than before.

Syntax:  numpy.fliplr(m)

Parameters: m (array_like) - Input array must be at least 2-D.

Returned Value: ndarray - A view of m is returned with the columns reversed, and this operation's time complexity is O(1).

Example:

import numpy as np

# creating a numpy array(matrix) with 3-columns and 4-rows
arr = np.array([
    ['c1', 'c2', 'c3'],
    [10, 20, 30],
    [40, 50, 60],
    [70, 80, 90]])

# reversing column order in matrix
flipped_arr = np.fliplr(arr)

print('Array before changing column order:\n', arr)
print('\nArray after changing column order:\n', flipped_arr)

Output:

Flipped_arr contains a reversed column order matrix where the column order has changed from c1,c2,c3 to c3,c2,c1, and the elements of each column remain intact under their respective headers (c1,c2,c3).