Transpose of a matrix using numpy.ndarray with example

Overview:

Transpose of a matrix is achieved by flipping the matrix over its main diagonal.
Transpose of a matrix is formed in two steps. In the new matrix,
- copy the columns of the original matrix as rows.
- copy the rows of the original matrix as columns.
By repeating the transpose operation on the already transposed matrix yields the original matrix.
Using the transpose() method of the numpy.ndarray transpose of a matrix can be obtained.

import numpy as np

import random

# Populate Array

def FillMatrix(matrix_in):

for x in range(0, matrix_in.shape[0]):

for y in range(0, matrix_in.shape[1]):

matrix_in[x][y] = random.randrange(1, 5)

# Create a matrix1

matrix1 = np.ndarray((3, 3))

# Populate the matrix

FillMatrix(matrix1)

# Create the transpose of the matrix

transposed = matrix1.transpose()

# Print the Matrices

print("Original Matrix:")

print(matrix1)

print("Transpose of Matrix:")

print(transposed)

Original Matrix:

[[ 2. 1. 4.]

[ 4. 4. 2.]

[ 2. 2. 3.]]

Transpose of Matrix:

[[ 2. 4. 2.]

[ 1. 4. 2.]

[ 4. 2. 3.]]