numpy transpose matrix code example

Example 1: transpose matrix numpy

>>> a = np.array([[1, 2], [3, 4]])
>>> a
array([[1, 2],
       [3, 4]])
>>> a.transpose()
array([[1, 3],
       [2, 4]])
>>> a.transpose((1, 0))
array([[1, 3],
       [2, 4]])
>>> a.transpose(1, 0)
array([[1, 3],
       [2, 4]])

Example 2: numpy transpose

>>> np.transpose(x)
array([[0, 2],
       [1, 3]])

Example 3: transpose matrices numpy

import numpy as np

A = [1, 2, 3, 4]
np.array(A).T # .T is used to transpose matrix

Example 4: transpose matrix in python without numpy

def transpose(matrix):
    rows = len(matrix)
    columns = len(matrix[0])

    matrix_T = []
    for j in range(columns):
        row = []
        for i in range(rows):
           row.append(matrix[i][j])
        matrix_T.append(row)

    return matrix_T

Example 5: transpose of a matrix using numpy

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

M.transpose()

Example 6: what is the transpose of a matrix

The transpose of a matrix is just a flipped version of 
the original matrix. We can transpose a matrix by switching 
its rows with its columns. The original rows become the new columns
and the original columns become the new rows.
We denote the transpose of matrix A by AT. 

For example:
	1 2 3                      1 4 7
A = 4 5 6       then      AT = 2 5 8
    7 8 9                      3 6 9
    
Similarly if 

B = 1 2 3       then      BT = 1 4
    4 5 6                      2 5 
                               3 6