Python Augmented Matrix

Table of Contents 

				
					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]

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Ryan Nolan

Ryan is a Data Scientist at a fintech company, where he focuses on fraud prevention in underwriting and risk. Before that, he worked as a Data Analyst at a tax software company. He holds a degree in Electrical Engineering from UCF.

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