Python | Numpy numpy.transpose()

The numpy.transpose() function is used to reverse or permute the axes of an array. For 2D arrays, it simply flips rows and columns. For 1D arrays, transpose has no effect because they have only one axis. This function is commonly used in matrix operations and data transformations where orientation matters.

Example: Here is a example showing how a 2D array is transposed

import numpy as np
a = np.array([[1, 2], [3, 4]])
print(np.transpose(a))

[[1 3]
 [2 4]]

Syntax

numpy.transpose(a, axes=None)

Parameters:

• a: Input array to transpose
• axes (Optional): tuple that defines the new axis order (e.g., (1, 0) for swapping rows and columns)

Examples

Example 1: In this example, we transpose a 3×3 matrix using the default behavior of numpy.transpose(), which swaps row and column indices.

import numpy as np

a = np.array([[1, 2, 3],
              [4, 5, 6],
              [7, 8, 9]])

print(np.transpose(a))

[[1 4 7]
 [2 5 8]
 [3 6 9]]

Explanation: np.transpose(a) swaps axes (0, 1) -> rows become columns.

Example 2: Here, we use the axes parameter to manually specify the new axis order, explicitly swapping the two axes of a 3×2 array.

import numpy as np

a = np.array([[1, 2],
              [3, 4],
              [5, 6]])

print(np.transpose(a, (1, 0)))

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

Explanation: np.transpose(a, (1, 0)) forces column axis to come first and row axis to come second.

Example 3: This example demonstrates using the shorthand .T attribute, which provides the same result as numpy.transpose() for 2D arrays.

import numpy as np

a = np.array([[10, 20, 30],
              [40, 50, 60]])

print(a.T)

[[10 40]
 [20 50]
 [30 60]]

Explanation: a.T directly returns the transpose of the array by swapping axes (0, 1).