Python Augmented Matrix
import numpy as np Example 1
# Define coefficient matrix A and constant vector b A = np.array([[1, 3], [4, 5]]) print(A) 
B = np.array([[2], [7]]) # Augmented matrix augmented_matrix = np.column_stack((A, B)) print(augmented_matrix) 
Example 2
A = np.array([[2, 2, -1], [5, 9, 1], [-6, 1, -2]]) B = np.array([[8], [11], [4]]) augmented_matrix = np.column_stack((A, B)) print(augmented_matrix) 
row operations
# Swapping two rows augmented_matrix[[0, 1]] = augmented_matrix[[1, 0]] print(augmented_matrix) 
Multiply the first row by 3
augmented_matrix[0] = augmented_matrix[0] * 3 print(augmented_matrix) 
add: 2nd row to the first
augmented_matrix[0] = augmented_matrix[0] + augmented_matrix[1] print(augmented_matrix) 
subtract 2nd row from the 3rd
augmented_matrix[2] = augmented_matrix[2] - augmented_matrix[1] print(augmented_matrix) df.loc[idx] 
