Python | Numpy matrix.transpose() (original) (raw)

Last Updated : 09 Jan, 2024

With the help of Numpy matrix.transpose() method, we can find the transpose of the matrix by using the matrix.transpose()method in Python.

Numpy matrix.transpose() Syntax

**Syntax : matrix.transpose()

**Parameter: No parameters; transposes the matrix it is called on.

**Return : Return transposed matrix

What is Numpy matrix.transpose()?

`numpy.matrix.transpose()` is a function in the NumPy library that computes the transpose of a matrix. It swaps the rows and columns of the matrix, effectively reflecting it along its main diagonal. The function is called on a NumPy matrix object, and it does not take any parameters. The result is a new matrix representing the transposed version of the original matrix.

NumPy Matrix transpose() – Transpose of an Array in Python

There are numerous examples of `numpy.matrix.transpose()`. Here, we illustrate commonly used instances of `numpy.matrix.transpose()` for clarity.

NumPy Matrix Transformation

**Example 1: In this example, the code uses the NumPy library to create a 2×3 matrix. It then calculates the transpose of the original matrix using the `transpose()` function. Finally, it prints both the original and transposed matrices to the console.

Python3

import numpy as np

original_matrix = np.matrix([[ 1 , 2 , 3 ], [ 4 , 5 , 6 ]])

transposed_matrix = original_matrix.transpose()

print ( "Original Matrix:" )

print (original_matrix)

print ( "\nTransposed Matrix:" )

print (transposed_matrix)

**Output:

**Original Matrix: [[1 2 3] [4 5 6]] **Transposed Matrix: [[1 4] [2 5] [3 6]]

**Example 2: In this example This Python code uses the NumPy library to create a 3×3 matrix named ‘gfg’. It then applies the transpose() method to the matrix and assigns the result to ‘geek’. Finally, it prints the transposed matrix ‘geek’.

Python3

import numpy as np

gfg = np.matrix( '[4, 1, 9; 12, 3, 1; 4, 5, 6]' )

geek = gfg.transpose()

print (geek)

**Output:

[[ 4 12 4] [ 1 3 5] [ 9 1 6]]

Transpose of an Array Like Object

In this example code uses NumPy to create two 2×2 matrices, `matrix_a` and `matrix_b`. It then transposes `matrix_b` using the `transpose()` function and performs matrix multiplication between `matrix_a` and the transposed `matrix_b`. The result is printed to the console.

Python3

import numpy as np

matrix_a = np.matrix([[ 1 , 2 ], [ 3 , 4 ]])

matrix_b = np.matrix([[ 5 , 6 ], [ 7 , 8 ]])

result = matrix_a * matrix_b.transpose()

print ( "Result of Matrix Multiplication:" )

print (result)

**Output:

**Result of Matrix Multiplication: [[17 23] [39 53]]