NumPy ndarray.transpose() Method | Find Transpose of the NumPy Array

The ndarray.transpose() function returns a view of the array with axes transposed.

• For a 1-D array, this has no effect, as a transposed vector is simply the same vector.
• For a 2-D array, this is a standard matrix transpose.
• For an n-D array, if axes are given, their order indicates how the axes are permuted. If axes are not provided and arr.shape = (i[0], i[1], ... i[n-2], i[n-1]), then arr.transpose().shape = (i[n-1], i[n-2], ... i[1], i[0]).

Example

import numpy as np
arr = np.array([[5, 6], [7, 8]])
transposed_arr = arr.transpose()
print(transposed_arr)

Output:

[[5 7]
 [6 8]]

Syntax

Syntax : numpy.ndarray.transpose(*axes) 

Parameters : 

• axes : [None, tuple of ints, or n ints] None or no argument: reverses the order of the axes. tuple of ints: i in the j-th place in the tuple means arr’s i-th axis becomes arr.transpose()’s j-th axis. n ints: same as an n-tuple of the same ints (this form is intended simply as a “convenience” alternative to the tuple form)

Return : [ndarray] View of arr, with axes suitably permuted.

Examples

Let's look at some examples to of transpose() method of the NumPy library to find transpose of a ndarray:

Example 1 :

# Python program explaining
# numpy.ndarray.transpose() function

# importing numpy as np 
import numpy as np

arr = np.array([[5, 6], [7, 8]])

gfg = arr.transpose()

print( gfg )

Output :

[[5 7]
 [6 8]]

Example 2 :

# Python program explaining
# numpy.ndarray.transpose() function

# importing numpy as np
import numpy as np

arr = np.array([[5, 6], [7, 8]])

gfg = arr.transpose((1, 0))

print( gfg )

Output :

[[5 7]
 [6 8]]