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:
- Iterate through each row
- For every row, use list comprehension to reverse the row (i.e. a[::-1])
- Append the reversed rows into a new matrix
- Print the matrix
Example:
Python3
# creating a 3X4 matrix using nested listsmatrix_1 = [['c1', 'c2', 'c3'], [10, 20, 30], [40, 50, 60], [70, 80, 90]]# creating an empty array to store the reversed column matrixmatrix_2 = []# looping through matrix_1 and appending matrix_2for 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:
Python3
import numpy as np# creating a numpy array(matrix) with 3-columns and 4-rowsarr = np.array([ ['c1', 'c2', 'c3'], [10, 20, 30], [40, 50, 60], [70, 80, 90]])# reversing column order in matrixflipped_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).
