Merge two matrix in python.

To merge two matrices in Python, you can concatenate them either row-wise or column-wise based on your requirements. Here’s how you can do it with both methods, along with example code and output:

import numpy as np

# Function to merge matrices row-wise
def merge_matrices_row_wise(matrix1, matrix2):
    return np.concatenate((matrix1, matrix2), axis=0)

# Example matrices
matrix1 = np.array([[1, 2, 3],
                    [4, 5, 6]])

matrix2 = np.array([[7, 8, 9],
                    [10, 11, 12]])

# Merge matrices row-wise
merged_matrix = merge_matrices_row_wise(matrix1, matrix2)

# Output
print("Matrix 1:")
print(matrix1)

print("\nMatrix 2:")
print(matrix2)

print("\nMerged Matrix (Row-Wise):")
print(merged_matrix)

OUTPUT:

Matrix 1:
[[1 2 3]
[4 5 6]]

Matrix 2:
[[ 7 8 9]
[10 11 12]]

Merged Matrix (Row-Wise):
[[ 1 2 3]
[ 4 5 6]
[ 7 8 9]
[10 11 12]]

KEYPOINTS:

1.Row-Wise Concatenation (np.concatenate((matrix1, matrix2), axis=0)):

This method stacks matrix2 below matrix1, combining them row-wise.
axis=0 specifies the axis along which the matrices are concatenated (0 for rows).
Column-Wise Concatenation (np.concatenate((matrix1, matrix2), axis=1)):

2.This method concatenates matrix2 to the right of matrix1, combining them column-wise.
axis=1 specifies the axis along which the matrices are concatenated (1 for columns).
Notes:
1.Both methods use numpy for array manipulation and concatenation, which is efficient for handling matrix operations in Python.
2.Ensure that the dimensions of the matrices match appropriately for concatenation along the chosen axis.
3.These examples assume you are working with numpy arrays. If you are using nested lists (standard Python lists), you would need to implement concatenation manually using list comprehension or loops.