In this article, you will learn how to transpose numpy array in python using transpose() function.

you need to learn syntax, parameters before using this function.

**Syntax:** ndarray.transpose(*axes)

Returns a view of the array with axes transposed.

For a 1-D array, this has no effect. (To change between column and row vectors, first cast the 1-D array into a matrix object.) For a 2-D array, this is the usual matrix transpose. For an n-D array, if axes are given, their order indicates how the axes are permuted (see Examples). If axes are not provided and a.shape = (i[0], i[1], … i[n-2], i[n-1]), then a.transpose().shape = (i[n-1], i[n-2], … i[1], i[0]).

**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 a’s i-th axis becomes a.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)

**Returns:**

out : ndarray

View of a, with axes suitably permuted.

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```
import numpy as np
a = np.array([[1, 2, 3], [4,5,6]])
b= a.transpose()
print("Transpose Array",b)
b= a.transpose(1,0)
print("Transpose Array",b)
b= a.transpose(0,1)
print("Transpose Array",b)
```

` `

` `

Output:

Transpose Array [[1 4]

[2 5]

[3 6]]

Transpose Array [[1 4]

[2 5]

[3 6]]

Transpose Array [[1 2 3]

[4 5 6]]