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Transpose a matrix in Single line in Python

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Transpose of a matrix is a task we all can perform very easily in Python (Using a nested loop). But there are some interesting ways to do the same in a single line. In Python, we can implement a matrix as a nested list (a list inside a list). Each element is treated as a row of the matrix. For example m = [[1, 2], [4, 5], [3, 6]] represents a matrix of 3 rows and 2 columns. The first element of the list – m[0] and the element in the first row, first column – m[0][0].

Example

Input: [[1,2],[3,4],[5,6]]
Output: [[1,3,5],[2,4,6]]
Explanation: Suppose we are given a matrix
[[1, 2],
[3, 4],
[5, 6]]
Then the transpose of the given matrix will be,
[[1, 3, 5],
[2, 4, 6]]

Python Programs to Transpose a Matrix in Single Line

There are various approaches to find the Transpose of a matrix in a single line in Python. In this article, we will discuss all the approaches which are specific to transposing a matrix in a single line in Python.

Transpose Matrix In Single Line using List Comprehension

List comprehension is used to iterate through each element in the matrix. In the given example, we iterate through each element of matrix (m) in a column-major manner and assign the result to the rez matrix which is the transpose of m.

Python3

m = [[1, 2], [3, 4], [5, 6]]
for row in m:
    print(row)
rez = [[m[j][i] for j in range(len(m))] for i in range(len(m[0]))]
print("\n")
for row in rez:
    print(row)

                    

Output:

[1, 2]
[3, 4]
[5, 6]
[1, 3, 5]
[2, 4, 6]

Transpose a matrix in Single line in Python using zip

Python Zip returns an iterator of tuples, where the i-th tuple contains the i-th element from each of the argument sequences or iterables. In this example we unzip our array using * and then zip it to get the transpose.

Python3

matrix = [(1, 2, 3), (4, 5, 6),
                  (7, 8, 9), (10, 11, 12)]
for row in matrix:
    print(row)
print("\n")
t_matrix = zip(*matrix)
for row in t_matrix:
    print(row)

                    

Output:

Note :- If you want your result in the form [[1,4,7,10][2,5,8,11][3,6,9,12]] , you can use t_matrix=map(list, zip(*matrix)).

(1, 2, 3)
(4, 5, 6)
(7, 8, 9)
(10, 11, 12)
(1, 4, 7, 10)
(2, 5, 8, 11)
(3, 6, 9, 12)

Python Programs to Transpose a matrix using NumPy

Python NumPy is a general-purpose array-processing package designed to efficiently manipulate large multi-dimensional arrays.

Example 1: The transpose method returns a transposed view of the passed multi-dimensional matrix.

Python3

import numpy
matrix = [[1, 2, 3], [4, 5, 6]]
print(matrix)
print("\n")
print(numpy.transpose(matrix))

                    

Output:

[[1, 2, 3], [4, 5, 6]]
[[1 4]
[2 5]
[3 6]]

Example 2: Using “.T” after the variable

Python3

import numpy as np
matrix = np.array([[1, 2, 3], [4, 5, 6]])
print(matrix)
print("\n")
print(matrix.T)

                    

Output:

As you can see that both the output are same.

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

Fastest way to Transpose a Matrix using Itertools

Python itertools is a module that provides various functions that work on iterators to produce complex iterators. chain() is a function that takes a series of iterables and returns one iterable.

In this example, we are using chain() function to convert all the values inside the matrix into a single list and then transpose the matrix. This method is way faster then other methods.

Python3

from itertools import chain
import time
import numpy as np
 
def transpose2(M):
    n = len(M[0])
    L = list(chain(*M))
    return [L[i::n] for i in range(n)]
 
start = time.time_ns()
matrix = np.array([[1, 2, 3], [4, 5, 6]])
end = time.time_ns()
print(transpose2(matrix))
print("Time taken", end-start, "ns")

                    

Output

[[1, 4], [2, 5], [3, 6]]
Time taken 108570 ns


Last Updated : 16 Aug, 2023
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