numpy.rot90() in Python

numpy.rot90() in Python

Last Updated : 08 Mar, 2024

The numpy.rot90() method performs rotation of an array by 90 degrees in the plane specified by axis(0 or 1). Syntax:

numpy.rot90(array, k = 1, axes = (0, 1))

Parameters :

array : [array_like]i.e. array having two or more dimensions.
k     : [optional , int]No. of times we wish to rotate array by 90 degrees.
axes  : [array_like]Plane, along which we wish to rotate array.

Returns :

rotated copy of array

Python

# Python Program illustrating
# numpy.rot90() method

import numpy as geek

array = geek.arange(12).reshape(3, 4)
print("Original array : \n", array)

# Rotating array 4 times : Returns same original array
print("\nArray being rotated 4 times : \n", geek.rot90(array, 4))

# Rotating once
print("\nRotated array : \n", geek.rot90(array))

# Rotating twice
print("\nRotated array : \n", geek.rot90(array, 2))

Output :

Original array : 
 [[ 0  1  2  3]
 [ 4  5  6  7]
 [ 8  9 10 11]]

Array being rotated 4 times : 
 [[ 0  1  2  3]
 [ 4  5  6  7]
 [ 8  9 10 11]]

Rotated array : 
 [[ 3  7 11]
 [ 2  6 10]
 [ 1  5  9]
 [ 0  4  8]]

Rotated array : 
 [[11 10  9  8]
 [ 7  6  5  4]
 [ 3  2  1  0]]

Note : These codes won’t run on online IDE's. Please run them on your systems to explore the working

numpy.rot90() in Python

M

Mohit Gupta_OMG

Improve

Article Tags :

Practice Tags :

python

Similar Reads

numpy.roll() in Python

The numpy.roll() function rolls array elements along the specified axis. Basically what happens is that elements of the input array are being shifted. If an element is being rolled first to the last position, it is rolled back to the first position. Syntax : numpy.roll(array, shift, axis = None) Par

numpy.rint() in Python

The numpy.rint() is a mathematical function that rounds elements of the array to the nearest integer. Syntax : numpy.rint(x[, out]) = ufunc â€˜rintâ€™) Parameters : array : [array_like] Input array. Return : An array with all array elements being rounded off, having same type and shape as input. Code #1

numpy.repeat() in Python

The numpy.repeat() function repeats elements of the array - arr. Syntax :Â numpy.repeat(arr, repetitions, axis = None) Parameters :Â array : [array_like]Input array. repetitions : No. of repetitions of each array elements along the given axis. axis : Axis along which we want to repeat values. By def

numpy.take() in Python

The numpy.take() function returns elements from array along the mentioned axis and indices. Syntax: numpy.take(array, indices, axis = None, out = None, mode ='raise') Parameters : array : array_like, input array indices : index of the values to be fetched axis : [int, optional] axis over which we ne

numpy.unwrap() in Python

numpy.unwrap(p, discount=3.141592653589793, axis=-1) function helps user to unwrap a given array by changing deltas to values of 2*pi complement. It unwraps radian phase p by changing absolute jumps greater than discount to their 2*pi complement along the given axis. Result is an unwrapped array. Pa

numpy.reshape() in Python

In Python, numpy.reshape() function is used to give a new shape to an existing NumPy array without changing its data. It is important for manipulating array structures in Python. Let's understand with an example:Pythonimport numpy as np # Creating a 1D NumPy array arr = np.array([1, 2, 3, 4, 5, 6])

numpy.right_shift() in Python

numpy.right_shift() function is used to Shift the bits of an integer to the right. Because the internal representation of numbers is in binary format, this operation is equivalent to dividing arr1 by 2**arr2. For example, if the number is 20 and we want to 2-bit right shift then after right shift 2-

numpy.mod() in Python

numpy.mod() is another function for doing mathematical operations in numpy.It returns element-wise remainder of division between two array arr1 and arr2 i.e. arr1 % arr2 .It returns 0 when arr2 is 0 and both arr1 and arr2 are (arrays of) integers. Syntax : numpy.mod(arr1, arr2, /, out=None, *, where

numpy.base_repr() in Python

numpy.base_repr(number, base=2, padding=0) function is used to return a string representation of a number in the given base system. For example, decimal number 10 is represented as 1010 in binary whereas it is represented as 12 in octal. Syntax : numpy.base_repr(number, base=2, padding=0) Parameters

numpy.flip() in Python

The numpy.flip() function reverses the order of array elements along the specified axis, preserving the shape of the array.Â Syntax: numpy.flip(array, axis) Parameters :Â array : [array_like]Array to be input axis : [integer]axis along which array is reversed. Returns :Â reversed array with shape pr